Agenda packet — Ontario City Council, June 16, 2026 (part 18 of 28)

Start age:45
End age:54
Baseline functional form:Incidence*POP*A
Incidence dataset:Other Incidence (2014)
Beta:0.00225
Beta distribution:Normal
P1Beta:0.000591837
P2Beta:0
A:0.971812
NameA:% of hospMI surviving 28 days
B:0
NameB:

C:0
NameC:

Percentile:0
Weight:0
</Health.impact.function>
<Health.impact.function>
Health impact function dataset:EPA Standard Health Functions Endpoint group:Acute Myocardial Infarction
Endpoint:Acute Myocardial Infarction, Nonfatal
Pollutant:PM2.5
Metric:D24HourMean
Metric statistic:None
Author:Zanobetti et al
Qualifier:All Seasons
Function:(1-(1/EXP(Beta*DELTAQ)))*Incidence*POP*A
Year:2009
3971
file:///C/Users/lmoel/Downloads/BenMAP%20Audit%20Trails/BenMAP%20Audit%20Trails/pm25.2020.pmit.txt[5/5/2021 9:32:06 AM] Geographic area:Everywhere
Other pollutants:

Reference:Zanobetti, A., M. Franklin and J. Schwartz. 2009. Fine particulate air pollution and its components in association with cause-specific emergency admissions. Environmental Health Vol. 8: 58-60.

Start age:55
End age:64
Baseline functional form:Incidence*POP*A
Incidence dataset:Other Incidence (2014)
Beta:0.00225
Beta distribution:Normal
P1Beta:0.000591837
P2Beta:0
A:0.971812
NameA:% of hospMI surviving 28 days
B:0
NameB:

C:0
NameC:

Start age:25
End age:44
Baseline functional form:Incidence*POP*A
Incidence dataset:Other Incidence (2014)
Beta:0.00225
Beta distribution:Normal
P1Beta:0.000591837
P2Beta:0
A:0.98148
NameA:% of hospMI surviving 28 days
B:0
NameB:

C:0
NameC:

Percentile:0
Weight:0
</Health.impact.function>
<Health.impact.function>
Health impact function dataset:EPA Standard Health Functions Endpoint group:Acute Myocardial Infarction
Endpoint:Acute Myocardial Infarction, Nonfatal
3972
file:///C/Users/lmoel/Downloads/BenMAP%20Audit%20Trails/BenMAP%20Audit%20Trails/pm25.2020.pmit.txt[5/5/2021 9:32:06 AM] Pollutant:PM2.5
Metric:D24HourMean
Metric statistic:None
Author:Zanobetti et al
Qualifier:All Seasons
Function:(1-(1/EXP(Beta*DELTAQ)))*Incidence*POP*A
Year:2009
Geographic area:Everywhere
Other pollutants:

Start age:65
End age:99
Baseline functional form:Incidence*POP*A
Incidence dataset:Other Incidence (2014)
Beta:0.00225
Beta distribution:Normal
P1Beta:0.000591837
P2Beta:0
A:0.925661
NameA:% of hospMI surviving 28 days
B:0
NameB:

C:0
NameC:

Percentile:0
Weight:0
</Health.impact.function>
</Incidence.Pooling.And.Aggregation.>
<Valuation.Pooling.Window.Name.Acute.Myocardial.Infarction> Acute Myocardial Infarction
Zanobetti:Pooling Method Type:None
Zanobetti:Pooling Method Type:None
Zanobetti:Pooling Method Type:None
Zanobetti:Pooling Method Type:None
Zanobetti:Pooling Method Type:None
</Valuation.Pooling.Window.Name.Acute.Myocardial.Infarction> <Incidence.Pooling.And.Aggregation.>
<Health.impact.function>
Health impact function dataset:EPA Standard Health Functions Endpoint group:Hospital Admissions, Cardiovascular
Endpoint:HA, All Cardiovascular (less Myocardial Infarctions) Pollutant:PM2.5
Metric:D24HourMean
Metric statistic:None
Author:Bell
Qualifier:National; Yearly
Function:(1-EXP(-Beta*DELTAQ))*Incidence*POP
Year:2012
Geographic area:Everywhere
Other pollutants:

Reference:Bell, M.L. 2012. Assessment of the Health Impacts of Particulate Matter Characteristics. Research Report 161. Health Effects Institute. Research Report 161: 1-59.

Start age:65
End age:99
Baseline functional form:Incidence*POP
Incidence dataset:Other Incidence (2014)
3973
file:///C/Users/lmoel/Downloads/BenMAP%20Audit%20Trails/BenMAP%20Audit%20Trails/pm25.2020.pmit.txt[5/5/2021 9:32:06 AM] Beta:0.0008
Beta distribution:Normal
P1Beta:0.000107143
P2Beta:0
A:0
NameA:

B:0
NameB:

C:0
NameC:

Percentile:0
Weight:0
</Health.impact.function>
</Incidence.Pooling.And.Aggregation.>
<Valuation.Pooling.Window.Name.Hospital.Admissions.Cardiovascular> Hospital Admissions, Cardiovascular
</Valuation.Pooling.Window.Name.Hospital.Admissions.Cardiovascular> <Incidence.Pooling.And.Aggregation.>
<Hospital.Admissions.RespiratoryPooling.Method.TypeNone> <Health.impact.function>
Health impact function dataset:EPA Standard Health Functions Endpoint group:Hospital Admissions, Respiratory
Endpoint:HA, All Respiratory
Pollutant:PM2.5
Metric:D24HourMean
Metric statistic:None
Author:Zanobetti et al
Year:2009
Location:26 U.S. Communities
Other pollutants:

Geographic area:Everywhere
Reference:Zanobetti, A., M. Franklin and J. Schwartz. 2009. Fine particulate air pollution and its components in association with cause-specific emergency admissions. Environmental Health Vol. 8: 58-60.

Start age:65
End age:99
Baseline functional form:

Incidence dataset:Other Incidence (2014)
Beta:0.00207
Beta distribution:Normal
P1Beta:0.000446429
P2Beta:0
A:0
NameA:

B:0
NameB:

C:0
NameC:

Percentile:0
Weight:0
</Health.impact.function>
<Health.impact.function>
Health impact function dataset:EPA Standard Health Functions Endpoint group:Hospital Admissions, Respiratory
Endpoint:HA, Asthma
Pollutant:PM2.5
Metric:D24HourMean
Metric statistic:None
3974
file:///C/Users/lmoel/Downloads/BenMAP%20Audit%20Trails/BenMAP%20Audit%20Trails/pm25.2020.pmit.txt[5/5/2021 9:32:06 AM] Author:Sheppard
Year:2003
Location:Seattle, WA
Other pollutants:

Geographic area:Everywhere
Reference:Sheppard, L. Ambient Air Pollution and Nonelderly Asthma Hospital Admissions in Seattle, Washington, 1987-1994. In: Revised Analyses of Time-Series Studies of Air Pollution and Health. 2003, Health Effects Institute: Boston, MA. p. 227-230.

Start age:0
End age:64
Baseline functional form:

Incidence dataset:Other Incidence (2014)
Beta:0.003323789
Beta distribution:Normal
P1Beta:0.00104459
P2Beta:0
A:0
NameA:

B:0
NameB:

C:0
NameC:

Percentile:0
Weight:0
</Health.impact.function>
</Hospital.Admissions.RespiratoryPooling.Method.TypeNone> <Health.impact.function>
Health impact function dataset:EPA Standard Health Functions Endpoint group:Hospital Admissions, Respiratory
Endpoint:HA, All Respiratory
Pollutant:PM2.5
Metric:D24HourMean
Metric statistic:None
Author:Zanobetti et al
Qualifier:All Seasons
Function:(1-EXP(-Beta*DELTAQ))*Incidence*POP
Year:2009
Geographic area:Everywhere
Other pollutants:

Start age:65
End age:99
Baseline functional form:Incidence*POP
Incidence dataset:Other Incidence (2014)
Beta:0.00207
Beta distribution:Normal
P1Beta:0.000446429
P2Beta:0
A:0
NameA:

B:0
NameB:

C:0
NameC:

Percentile:0
Weight:0
3975
file:///C/Users/lmoel/Downloads/BenMAP%20Audit%20Trails/BenMAP%20Audit%20Trails/pm25.2020.pmit.txt[5/5/2021 9:32:06 AM] </Health.impact.function>
<Health.impact.function>
Health impact function dataset:EPA Standard Health Functions Endpoint group:Hospital Admissions, Respiratory
Endpoint:HA, Asthma
Pollutant:PM2.5
Metric:D24HourMean
Metric statistic:None
Author:Sheppard
Qualifier:

Function:(1-(1/EXP(Beta*DELTAQ)))*Incidence*POP
Year:2003
Geographic area:Everywhere
Other pollutants:

Reference:Sheppard, L. Ambient Air Pollution and Nonelderly Asthma Hospital Admissions in Seattle, Washington, 1987-1994. In: Revised Analyses of Time-Series Studies of Air Pollution and Health. 2003, Health Effects Institute: Boston, MA. p. 227-230.

Start age:0
End age:64
Baseline functional form:Incidence*POP
Incidence dataset:Other Incidence (2014)
Beta:0.003323789
Beta distribution:Normal
P1Beta:0.00104459
P2Beta:0
A:0
NameA:

B:0
NameB:

C:0
NameC:

Percentile:0
Weight:0
</Health.impact.function>
</Incidence.Pooling.And.Aggregation.>
<Valuation.Pooling.Window.Name.Hospital.Admissions.Respiratory> Hospital Admissions, Respiratory
Zanobetti:Pooling Method Type:None
Sheppard:Pooling Method Type:None
</Valuation.Pooling.Window.Name.Hospital.Admissions.Respiratory> <Incidence.Pooling.And.Aggregation.>
<Health.impact.function>
Health impact function dataset:EPA Standard Health Functions Endpoint group:Emergency Room Visits, Respiratory
Endpoint:Emergency Room Visits, Asthma
Pollutant:PM2.5
Metric:D24HourMean
Metric statistic:None
Author:Mar et al.

Qualifier:Entire study period (January 3, 1999 - May 30, 2002) Function:(1-EXP(-Beta*DELTAQ))*Incidence*POP
Year:2010
Geographic area:Everywhere
Other pollutants:

Reference:Mar, T. F., J. Q. Koenig and J. Primomo. 2010. Associations between asthma emergency visits and particulate matter sources, including diesel emissions from stationary generators in Tacoma, Washington.

Inhal Toxicol. Vol. 22 (6): 445-8. http://www.ncbi.nlm
3976
file:///C/Users/lmoel/Downloads/BenMAP%20Audit%20Trails/BenMAP%20Audit%20Trails/pm25.2020.pmit.txt[5/5/2021 9:32:06 AM] Start age:0
End age:99
Baseline functional form:Incidence*POP
Incidence dataset:Other Incidence (2014)
Beta:0.005602959
Beta distribution:Normal
P1Beta:0.002103073
P2Beta:0
A:0
NameA:

B:0
NameB:

C:0
NameC:

Percentile:0
Weight:0
</Health.impact.function>
</Incidence.Pooling.And.Aggregation.>
<Valuation.Pooling.Window.Name.Emergency.Room.Visits.Respiratory> Emergency Room Visits, Respiratory
</Valuation.Pooling.Window.Name.Emergency.Room.Visits.Respiratory> Processing complete. Valuation processing time: 0 hours 0 minutes 0 seconds. </Aggregate, Pool & Value>
3977
ATTACHMENT B-7

BENMAP-CE AUDIT TRAIL REPORT
PM25.2031.PROJ.TXT
3978
file:///C/Users/lmoel/Downloads/BenMAP%20Audit%20Trails/BenMAP%20Audit%20Trails/pm25.2031.proj.txt[5/5/2021 9:32:09 AM] BenMAP-CE 1.5.0
<Aggregate, Pool & Value>
Create Datetime:2021-04-19 13:08:39
IsRunInPointMode:False
Latin Hypercube Points:20
Population Dataset:PopFriantUpdated-Friant
Year:2031
Threshold:0
Incidence averaging:All
<Baseline.And.Control.Group0>
<Pollutant>
Name:PM2.5
Observation Type:Daily
Season0:January 1-March 31
Season1:April 1-June 30
Season2:July 1-September 30
Season3:October 1-December 31
Metric0:D24HourMean
Seasonal Metric0:QuarterlyMean
</Pollutant>
<Baseline.Air.Quality.Surfaces>
Create Datetime:2021-04-19 10:17:45
Pollutant:PM2.5
Model Database File:C:\Users\Frank\Documents\My BenMAP-CE Files\Friant\Data\pm25.2031.proj.benmap.csv
<Grid.Definition>
Name:Friant
ID:33
Columns:87
Rows:103
Grid Type:Shapefile
Shapefile Name:CEQA_FRanch_lc_87_103_4000_4000_-108_-256_WGS1984 </Grid.Definition>
<Pollutant>
Name:PM2.5
Observation Type:Daily
Season0:January 1-March 31
Season1:April 1-June 30
Season2:July 1-September 30
Season3:October 1-December 31
Metric0:D24HourMean
Seasonal Metric0:QuarterlyMean
</Pollutant>
</Baseline.Air.Quality.Surfaces>
<Control.Air.Quality.Surfaces>
Create Datetime:2021-04-19 10:17:21
Pollutant:PM2.5
Model Database File:C:\Users\Frank\Documents\My BenMAP-CE Files\Friant\Data\pm25.2031.base.benmap.csv
<Grid.Definition>
Name:Friant
ID:33
Columns:87
Rows:103
Grid Type:Shapefile
Shapefile Name:CEQA_FRanch_lc_87_103_4000_4000_-108_-256_WGS1984 3979
file:///C/Users/lmoel/Downloads/BenMAP%20Audit%20Trails/BenMAP%20Audit%20Trails/pm25.2031.proj.txt[5/5/2021 9:32:09 AM] </Grid.Definition>
<Pollutant>
Name:PM2.5
Observation Type:Daily
Season0:January 1-March 31
Season1:April 1-June 30
Season2:July 1-September 30
Season3:October 1-December 31
Metric0:D24HourMean
Seasonal Metric0:QuarterlyMean
</Pollutant>
</Control.Air.Quality.Surfaces>
</Baseline.And.Control.Group0>
<Selected.health.impact.functions>
<Health.impact.function.0>
Health impact function dataset:EPA Standard Health Functions Endpoint group:Mortality
Endpoint:Mortality, All Cause
Start age:30
End age:99
Race:

Ethnicity:

Gender:

Pollutant:PM2.5
Metric:D24HourMean
Metric statistic:Mean
Seasonal metric:QuarterlyMean
Author:Krewski et al.

Qualifier:Random effects cox; 44 individual and 7 ecologic co-variates; 1999--2000 follow-up (Commentary table 4)
Function:(1-(1/EXP(Beta*DELTAQ)))*Incidence*POP
Year:2009
Geographic area:Everywhere
Other pollutants:TSP, O3, SO4, SO2
Reference:Krewski D, Jerrett M, Burnett R, et al. 2009. Extended Follow-Up and Spatial analysis of the American Cancer Society Linking Particulate Air Pollution and Mortality. Health Effects Institute, Cambridge MA
Baseline functional form:Incidence*POP
Incidence dataset:Mortality Incidence (2000)
Prevalence dataset:

Variable dataset:

Beta:0.005826891
Beta distribution:Normal
P1Beta:0.000962763
P2Beta:0
A:0
NameA:

B:0
NameB:

C:0
NameC:

Percentile:0
</Health.impact.function.0>
<Health.impact.function.1>
Health impact function dataset:EPA Standard Health Functions Endpoint group:Acute Myocardial Infarction
Endpoint:Acute Myocardial Infarction, Nonfatal
3980
file:///C/Users/lmoel/Downloads/BenMAP%20Audit%20Trails/BenMAP%20Audit%20Trails/pm25.2031.proj.txt[5/5/2021 9:32:09 AM] Start age:18
End age:24
Race:

Ethnicity:

Gender:

Pollutant:PM2.5
Metric:D24HourMean
Metric statistic:None
Author:Zanobetti et al
Qualifier:All Seasons
Function:(1-(1/EXP(Beta*DELTAQ)))*Incidence*POP*A
Year:2009
Geographic area:Everywhere
Other pollutants:

Baseline functional form:Incidence*POP*A
Incidence dataset:Other Incidence (2014)
Prevalence dataset:

Variable dataset:

Beta:0.00225
Beta distribution:Normal
P1Beta:0.000591837
P2Beta:0
A:0.98148
NameA:% of hospMI surviving 28 days
B:0
NameB:

C:0
NameC:

Percentile:0
</Health.impact.function.1>
<Health.impact.function.2>
Health impact function dataset:EPA Standard Health Functions Endpoint group:Acute Myocardial Infarction
Endpoint:Acute Myocardial Infarction, Nonfatal
Start age:45
End age:54
Race:

Ethnicity:

Gender:

Baseline functional form:Incidence*POP*A
Incidence dataset:Other Incidence (2014)
Prevalence dataset:

Variable dataset:

Beta:0.00225
3981
file:///C/Users/lmoel/Downloads/BenMAP%20Audit%20Trails/BenMAP%20Audit%20Trails/pm25.2031.proj.txt[5/5/2021 9:32:09 AM] Beta distribution:Normal
P1Beta:0.000591837
P2Beta:0
A:0.971812
NameA:% of hospMI surviving 28 days
B:0
NameB:

C:0
NameC:

Percentile:0
</Health.impact.function.2>
<Health.impact.function.3>
Health impact function dataset:EPA Standard Health Functions Endpoint group:Acute Myocardial Infarction
Endpoint:Acute Myocardial Infarction, Nonfatal
Start age:55
End age:64
Race:

Ethnicity:

Gender:

Baseline functional form:Incidence*POP*A
Incidence dataset:Other Incidence (2014)
Prevalence dataset:

Variable dataset:

Beta:0.00225
Beta distribution:Normal
P1Beta:0.000591837
P2Beta:0
A:0.971812
NameA:% of hospMI surviving 28 days
B:0
NameB:

C:0
NameC:

Percentile:0
</Health.impact.function.3>
<Health.impact.function.4>
Health impact function dataset:EPA Standard Health Functions Endpoint group:Hospital Admissions, Respiratory
Endpoint:HA, All Respiratory
Start age:65
End age:99
Race:

Ethnicity:

Gender:

Pollutant:PM2.5
3982
file:///C/Users/lmoel/Downloads/BenMAP%20Audit%20Trails/BenMAP%20Audit%20Trails/pm25.2031.proj.txt[5/5/2021 9:32:09 AM] Metric:D24HourMean
Metric statistic:None
Author:Zanobetti et al
Qualifier:All Seasons
Function:(1-EXP(-Beta*DELTAQ))*Incidence*POP
Year:2009
Geographic area:Everywhere
Other pollutants:

Baseline functional form:Incidence*POP
Incidence dataset:Other Incidence (2014)
Prevalence dataset:

Variable dataset:

Beta:0.00207
Beta distribution:Normal
P1Beta:0.000446429
P2Beta:0
A:0
NameA:

B:0
NameB:

C:0
NameC:

Percentile:0
</Health.impact.function.4>
<Health.impact.function.5>
Health impact function dataset:EPA Standard Health Functions Endpoint group:Acute Myocardial Infarction
Endpoint:Acute Myocardial Infarction, Nonfatal
Start age:25
End age:44
Race:

Ethnicity:

Gender:

Baseline functional form:Incidence*POP*A
Incidence dataset:Other Incidence (2014)
Prevalence dataset:

Variable dataset:

Beta:0.00225
Beta distribution:Normal
P1Beta:0.000591837
P2Beta:0
A:0.98148
NameA:% of hospMI surviving 28 days
B:0
3983
file:///C/Users/lmoel/Downloads/BenMAP%20Audit%20Trails/BenMAP%20Audit%20Trails/pm25.2031.proj.txt[5/5/2021 9:32:09 AM] NameB:

C:0
NameC:

Percentile:0
</Health.impact.function.5>
<Health.impact.function.6>
Health impact function dataset:EPA Standard Health Functions Endpoint group:Acute Myocardial Infarction
Endpoint:Acute Myocardial Infarction, Nonfatal
Start age:65
End age:99
Race:

Ethnicity:

Gender:

Baseline functional form:Incidence*POP*A
Incidence dataset:Other Incidence (2014)
Prevalence dataset:

Variable dataset:

Beta:0.00225
Beta distribution:Normal
P1Beta:0.000591837
P2Beta:0
A:0.925661
NameA:% of hospMI surviving 28 days
B:0
NameB:

C:0
NameC:

Percentile:0
</Health.impact.function.6>
<Health.impact.function.7>
Health impact function dataset:EPA Standard Health Functions Endpoint group:Hospital Admissions, Cardiovascular
Endpoint:HA, All Cardiovascular (less Myocardial Infarctions) Start age:65
End age:99
Race:

Ethnicity:

Gender:

Pollutant:PM2.5
Metric:D24HourMean
Metric statistic:None
Author:Bell
Qualifier:National; Yearly
Function:(1-EXP(-Beta*DELTAQ))*Incidence*POP
Year:2012
3984
file:///C/Users/lmoel/Downloads/BenMAP%20Audit%20Trails/BenMAP%20Audit%20Trails/pm25.2031.proj.txt[5/5/2021 9:32:09 AM] Geographic area:Everywhere
Other pollutants:

Reference:Bell, M.L. 2012. Assessment of the Health Impacts of Particulate Matter Characteristics. Research Report 161. Health Effects Institute. Research Report 161: 1-59.

Baseline functional form:Incidence*POP
Incidence dataset:Other Incidence (2014)
Prevalence dataset:

Variable dataset:

Beta:0.0008
Beta distribution:Normal
P1Beta:0.000107143
P2Beta:0
A:0
NameA:

B:0
NameB:

C:0
NameC:

Percentile:0
</Health.impact.function.7>
<Health.impact.function.8>
Health impact function dataset:EPA Standard Health Functions Endpoint group:Hospital Admissions, Respiratory
Endpoint:HA, Asthma
Start age:0
End age:64
Race:

Ethnicity:

Gender:

Pollutant:PM2.5
Metric:D24HourMean
Metric statistic:None
Author:Sheppard
Qualifier:

Function:(1-(1/EXP(Beta*DELTAQ)))*Incidence*POP
Year:2003
Geographic area:Everywhere
Other pollutants:

Baseline functional form:Incidence*POP
Incidence dataset:Other Incidence (2014)
Prevalence dataset:

Variable dataset:

Beta:0.003323789
Beta distribution:Normal
P1Beta:0.00104459
P2Beta:0
A:0
NameA:

B:0
NameB:

C:0
NameC:

Percentile:0
</Health.impact.function.8>
3985
file:///C/Users/lmoel/Downloads/BenMAP%20Audit%20Trails/BenMAP%20Audit%20Trails/pm25.2031.proj.txt[5/5/2021 9:32:09 AM] <Health.impact.function.9>
Health impact function dataset:EPA Standard Health Functions Endpoint group:Emergency Room Visits, Respiratory
Endpoint:Emergency Room Visits, Asthma
Start age:0
End age:99
Race:

Ethnicity:

Gender:

Pollutant:PM2.5
Metric:D24HourMean
Metric statistic:None
Author:Mar et al.

Qualifier:Entire study period (January 3, 1999 - May 30, 2002) Function:(1-EXP(-Beta*DELTAQ))*Incidence*POP
Year:2010
Geographic area:Everywhere
Other pollutants:

Inhal Toxicol. Vol. 22 (6): 445-8. http://www.ncbi.nlm
Baseline functional form:Incidence*POP
Incidence dataset:Other Incidence (2014)
Prevalence dataset:

Variable dataset:

Beta:0.005602959
Beta distribution:Normal
P1Beta:0.002103073
P2Beta:0
A:0
NameA:

B:0
NameB:

C:0
NameC:

Percentile:0
</Health.impact.function.9>
</Selected.health.impact.functions>
<Log.And.Message>
Processing complete. HIF processing time: 0 hours 15 minutes 49 seconds. </Log.And.Message>
Sort Incidence LHPs:False
Default Advanced Pooling Method:Roundweightstotwodigits Default Monte Carlo Iterations:5000
Random Seed:1
<Inflation.Adjustment>
Dataset:

Year:-1
</Inflation.Adjustment>
<Income.Growth.Adjustment>
Dataset:

Year : -1
</Income.Growth.Adjustment>
<Incidence.Aggregation>
Name:Friant
ID:33
Columns:87
3986
file:///C/Users/lmoel/Downloads/BenMAP%20Audit%20Trails/BenMAP%20Audit%20Trails/pm25.2031.proj.txt[5/5/2021 9:32:09 AM] Rows:103
Grid Type:Shapefile
Shapefile Name:CEQA_FRanch_lc_87_103_4000_4000_-108_-256_WGS1984 </Incidence.Aggregation>
<Valuation.Aggregation>
Name:Friant
ID:33
Columns:87
Rows:103
Grid Type:Shapefile
Shapefile Name:CEQA_FRanch_lc_87_103_4000_4000_-108_-256_WGS1984 </Valuation.Aggregation>
<Incidence.Pooling.And.Aggregation.>
<Health.impact.function>
Health impact function dataset:EPA Standard Health Functions Endpoint group:Mortality
Endpoint:Mortality, All Cause
Pollutant:PM2.5
Metric:D24HourMean
Metric statistic:Mean
Seasonal metric:QuarterlyMean
Author:Krewski et al.

Qualifier:Random effects cox; 44 individual and 7 ecologic co-variates; 1999--2000 follow-up (Commentary table 4)
Function:(1-(1/EXP(Beta*DELTAQ)))*Incidence*POP
Year:2009
Geographic area:Everywhere
Other pollutants:TSP, O3, SO4, SO2
Reference:Krewski D, Jerrett M, Burnett R, et al. 2009. Extended Follow-Up and Spatial analysis of the American Cancer Society Linking Particulate Air Pollution and Mortality. Health Effects Institute, Cambridge MA
Start age:30
End age:99
Baseline functional form:Incidence*POP
Incidence dataset:Mortality Incidence (2000)
Beta:0.005826891
Beta distribution:Normal
P1Beta:0.000962763
P2Beta:0
A:0
NameA:

B:0
NameB:

C:0
NameC:

Percentile:0
Weight:0
</Health.impact.function>
</Incidence.Pooling.And.Aggregation.>
<Valuation.Pooling.Window.Name.Mortality>
Mortality
</Valuation.Pooling.Window.Name.Mortality>
<Incidence.Pooling.And.Aggregation.>
<Acute.Myocardial.InfarctionPooling.Method.TypeNone>
<Health.impact.function>
Health impact function dataset:EPA Standard Health Functions Endpoint group:Acute Myocardial Infarction
3987
file:///C/Users/lmoel/Downloads/BenMAP%20Audit%20Trails/BenMAP%20Audit%20Trails/pm25.2031.proj.txt[5/5/2021 9:32:09 AM] Endpoint:Acute Myocardial Infarction, Nonfatal
Pollutant:PM2.5
Metric:D24HourMean
Metric statistic:None
Author:Zanobetti et al
Year:2009
Location:26 U.S. Communities
Other pollutants:

Start age:18
End age:24
Baseline functional form:

Incidence dataset:Other Incidence (2014)
Beta:0.00225
Beta distribution:Normal
P1Beta:0.000591837
P2Beta:0
A:0.98148
NameA:% of hospMI surviving 28 days
B:0
NameB:

C:0
NameC:

Start age:45
End age:54
Baseline functional form:

Incidence dataset:Other Incidence (2014)
Beta:0.00225
Beta distribution:Normal
P1Beta:0.000591837
P2Beta:0
A:0.971812
NameA:% of hospMI surviving 28 days
B:0
NameB:

C:0
NameC:

Percentile:0
3988
file:///C/Users/lmoel/Downloads/BenMAP%20Audit%20Trails/BenMAP%20Audit%20Trails/pm25.2031.proj.txt[5/5/2021 9:32:09 AM] Weight:0
</Health.impact.function>
<Health.impact.function>
Health impact function dataset:EPA Standard Health Functions Endpoint group:Acute Myocardial Infarction
Endpoint:Acute Myocardial Infarction, Nonfatal
Pollutant:PM2.5
Metric:D24HourMean
Metric statistic:None
Author:Zanobetti et al
Year:2009
Location:26 U.S. Communities
Other pollutants:

Start age:55
End age:64
Baseline functional form:

Incidence dataset:Other Incidence (2014)
Beta:0.00225
Beta distribution:Normal
P1Beta:0.000591837
P2Beta:0
A:0.971812
NameA:% of hospMI surviving 28 days
B:0
NameB:

C:0
NameC:

Start age:25
End age:44
Baseline functional form:

Incidence dataset:Other Incidence (2014)
Beta:0.00225
Beta distribution:Normal
P1Beta:0.000591837
P2Beta:0
A:0.98148
NameA:% of hospMI surviving 28 days
3989
file:///C/Users/lmoel/Downloads/BenMAP%20Audit%20Trails/BenMAP%20Audit%20Trails/pm25.2031.proj.txt[5/5/2021 9:32:09 AM] B:0
NameB:

C:0
NameC:

Start age:65
End age:99
Baseline functional form:

Incidence dataset:Other Incidence (2014)
Beta:0.00225
Beta distribution:Normal
P1Beta:0.000591837
P2Beta:0
A:0.925661
NameA:% of hospMI surviving 28 days
B:0
NameB:

C:0
NameC:

Percentile:0
Weight:0
</Health.impact.function>
</Acute.Myocardial.InfarctionPooling.Method.TypeNone>
<Health.impact.function>
Health impact function dataset:EPA Standard Health Functions Endpoint group:Acute Myocardial Infarction
Endpoint:Acute Myocardial Infarction, Nonfatal
Pollutant:PM2.5
Metric:D24HourMean
Metric statistic:None
Author:Zanobetti et al
Qualifier:All Seasons
Function:(1-(1/EXP(Beta*DELTAQ)))*Incidence*POP*A
Year:2009
Geographic area:Everywhere
Other pollutants:

Start age:18
End age:24
Baseline functional form:Incidence*POP*A
3990
file:///C/Users/lmoel/Downloads/BenMAP%20Audit%20Trails/BenMAP%20Audit%20Trails/pm25.2031.proj.txt[5/5/2021 9:32:09 AM] Incidence dataset:Other Incidence (2014)
Beta:0.00225
Beta distribution:Normal
P1Beta:0.000591837
P2Beta:0
A:0.98148
NameA:% of hospMI surviving 28 days
B:0
NameB:

C:0
NameC:

Percentile:0
Weight:0
</Health.impact.function>
<Health.impact.function>
Health impact function dataset:EPA Standard Health Functions Endpoint group:Acute Myocardial Infarction
Endpoint:Acute Myocardial Infarction, Nonfatal
Pollutant:PM2.5
Metric:D24HourMean
Metric statistic:None
Author:Zanobetti et al
Qualifier:All Seasons
Function:(1-(1/EXP(Beta*DELTAQ)))*Incidence*POP*A
Year:2009
3991
file:///C/Users/lmoel/Downloads/BenMAP%20Audit%20Trails/BenMAP%20Audit%20Trails/pm25.2031.proj.txt[5/5/2021 9:32:09 AM] Geographic area:Everywhere
Other pollutants:

C:0
NameC:

Percentile:0
Weight:0
</Health.impact.function>
<Health.impact.function>
Health impact function dataset:EPA Standard Health Functions Endpoint group:Acute Myocardial Infarction
Endpoint:Acute Myocardial Infarction, Nonfatal
3992
file:///C/Users/lmoel/Downloads/BenMAP%20Audit%20Trails/BenMAP%20Audit%20Trails/pm25.2031.proj.txt[5/5/2021 9:32:09 AM] Pollutant:PM2.5
Metric:D24HourMean
Metric statistic:None
Author:Zanobetti et al
Qualifier:All Seasons
Function:(1-(1/EXP(Beta*DELTAQ)))*Incidence*POP*A
Year:2009
Geographic area:Everywhere
Other pollutants:

C:0
NameC:

Reference:Bell, M.L. 2012. Assessment of the Health Impacts of Particulate Matter Characteristics. Research Report 161. Health Effects Institute. Research Report 161: 1-59.

Start age:65
End age:99
Baseline functional form:Incidence*POP
Incidence dataset:Other Incidence (2014)
3993
file:///C/Users/lmoel/Downloads/BenMAP%20Audit%20Trails/BenMAP%20Audit%20Trails/pm25.2031.proj.txt[5/5/2021 9:32:09 AM] Beta:0.0008
Beta distribution:Normal
P1Beta:0.000107143
P2Beta:0
A:0
NameA:

B:0
NameB:

C:0
NameC:

Start age:65
End age:99
Baseline functional form:

Incidence dataset:Other Incidence (2014)
Beta:0.00207
Beta distribution:Normal
P1Beta:0.000446429
P2Beta:0
A:0
NameA:

B:0
NameB:

C:0
NameC:

Percentile:0
Weight:0
</Health.impact.function>
<Health.impact.function>
Health impact function dataset:EPA Standard Health Functions Endpoint group:Hospital Admissions, Respiratory
Endpoint:HA, Asthma
Pollutant:PM2.5
Metric:D24HourMean
Metric statistic:None
3994
file:///C/Users/lmoel/Downloads/BenMAP%20Audit%20Trails/BenMAP%20Audit%20Trails/pm25.2031.proj.txt[5/5/2021 9:32:09 AM] Author:Sheppard
Year:2003
Location:Seattle, WA
Other pollutants:

Start age:0
End age:64
Baseline functional form:

Incidence dataset:Other Incidence (2014)
Beta:0.003323789
Beta distribution:Normal
P1Beta:0.00104459
P2Beta:0
A:0
NameA:

B:0
NameB:

C:0
NameC:

Start age:65
End age:99
Baseline functional form:Incidence*POP
Incidence dataset:Other Incidence (2014)
Beta:0.00207
Beta distribution:Normal
P1Beta:0.000446429
P2Beta:0
A:0
NameA:

B:0
NameB:

C:0
NameC:

Percentile:0
Weight:0
3995
file:///C/Users/lmoel/Downloads/BenMAP%20Audit%20Trails/BenMAP%20Audit%20Trails/pm25.2031.proj.txt[5/5/2021 9:32:09 AM] </Health.impact.function>
<Health.impact.function>
Health impact function dataset:EPA Standard Health Functions Endpoint group:Hospital Admissions, Respiratory
Endpoint:HA, Asthma
Pollutant:PM2.5
Metric:D24HourMean
Metric statistic:None
Author:Sheppard
Qualifier:

Function:(1-(1/EXP(Beta*DELTAQ)))*Incidence*POP
Year:2003
Geographic area:Everywhere
Other pollutants:

Start age:0
End age:64
Baseline functional form:Incidence*POP
Incidence dataset:Other Incidence (2014)
Beta:0.003323789
Beta distribution:Normal
P1Beta:0.00104459
P2Beta:0
A:0
NameA:

B:0
NameB:

C:0
NameC:

Qualifier:Entire study period (January 3, 1999 - May 30, 2002) Function:(1-EXP(-Beta*DELTAQ))*Incidence*POP
Year:2010
Geographic area:Everywhere
Other pollutants:

Inhal Toxicol. Vol. 22 (6): 445-8. http://www.ncbi.nlm
3996
file:///C/Users/lmoel/Downloads/BenMAP%20Audit%20Trails/BenMAP%20Audit%20Trails/pm25.2031.proj.txt[5/5/2021 9:32:09 AM] Start age:0
End age:99
Baseline functional form:Incidence*POP
Incidence dataset:Other Incidence (2014)
Beta:0.005602959
Beta distribution:Normal
P1Beta:0.002103073
P2Beta:0
A:0
NameA:

B:0
NameB:

C:0
NameC:

BENMAP-CE AUDIT TRAIL REPORT
PM25.2031.PMIT.TXT
3998
file:///C/Users/lmoel/Downloads/BenMAP%20Audit%20Trails/BenMAP%20Audit%20Trails/pm25.2031.pmit.txt[5/5/2021 9:32:08 AM] BenMAP-CE 1.5.0
<Aggregate, Pool & Value>
Create Datetime:2021-04-19 12:22:02
IsRunInPointMode:False
Latin Hypercube Points:20
Population Dataset:PopFriantUpdated-Friant
Year:2031
Threshold:0
Incidence averaging:All
<Baseline.And.Control.Group0>
<Pollutant>
Name:PM2.5
Observation Type:Daily
Season0:January 1-March 31
Season1:April 1-June 30
Season2:July 1-September 30
Season3:October 1-December 31
Metric0:D24HourMean
Seasonal Metric0:QuarterlyMean
</Pollutant>
<Baseline.Air.Quality.Surfaces>
Create Datetime:2021-04-19 12:05:19
Pollutant:PM2.5
Model Database File:C:\Users\Frank\Documents\My BenMAP-CE Files\Friant\Data\pm25.2031.pmit.benmap.csv
<Grid.Definition>
Name:Friant
ID:33
Columns:87
Rows:103
Grid Type:Shapefile
Shapefile Name:CEQA_FRanch_lc_87_103_4000_4000_-108_-256_WGS1984 </Grid.Definition>
<Pollutant>
Name:PM2.5
Observation Type:Daily
Season0:January 1-March 31
Season1:April 1-June 30
Season2:July 1-September 30
Season3:October 1-December 31
Metric0:D24HourMean
Seasonal Metric0:QuarterlyMean
</Pollutant>
</Baseline.Air.Quality.Surfaces>
<Control.Air.Quality.Surfaces>
Create Datetime:2021-04-19 10:17:21
Pollutant:PM2.5
Model Database File:C:\Users\Frank\Documents\My BenMAP-CE Files\Friant\Data\pm25.2031.base.benmap.csv
<Grid.Definition>
Name:Friant
ID:33
Columns:87
Rows:103
Grid Type:Shapefile
Shapefile Name:CEQA_FRanch_lc_87_103_4000_4000_-108_-256_WGS1984 3999
file:///C/Users/lmoel/Downloads/BenMAP%20Audit%20Trails/BenMAP%20Audit%20Trails/pm25.2031.pmit.txt[5/5/2021 9:32:08 AM] </Grid.Definition>
<Pollutant>
Name:PM2.5
Observation Type:Daily
Season0:January 1-March 31
Season1:April 1-June 30
Season2:July 1-September 30
Season3:October 1-December 31
Metric0:D24HourMean
Seasonal Metric0:QuarterlyMean
</Pollutant>
</Control.Air.Quality.Surfaces>
</Baseline.And.Control.Group0>
<Selected.health.impact.functions>
<Health.impact.function.0>
Health impact function dataset:EPA Standard Health Functions Endpoint group:Mortality
Endpoint:Mortality, All Cause
Start age:30
End age:99
Race:

Ethnicity:

Gender:

Pollutant:PM2.5
Metric:D24HourMean
Metric statistic:Mean
Seasonal metric:QuarterlyMean
Author:Krewski et al.

Variable dataset:

Beta:0.005826891
Beta distribution:Normal
P1Beta:0.000962763
P2Beta:0
A:0
NameA:

B:0
NameB:

C:0
NameC:

Percentile:0
</Health.impact.function.0>
<Health.impact.function.1>
Health impact function dataset:EPA Standard Health Functions Endpoint group:Acute Myocardial Infarction
Endpoint:Acute Myocardial Infarction, Nonfatal
4000
file:///C/Users/lmoel/Downloads/BenMAP%20Audit%20Trails/BenMAP%20Audit%20Trails/pm25.2031.pmit.txt[5/5/2021 9:32:08 AM] Start age:18
End age:24
Race:

Ethnicity:

Gender:

Baseline functional form:Incidence*POP*A
Incidence dataset:Other Incidence (2014)
Prevalence dataset:

Variable dataset:

Beta:0.00225
Beta distribution:Normal
P1Beta:0.000591837
P2Beta:0
A:0.98148
NameA:% of hospMI surviving 28 days
B:0
NameB:

C:0
NameC:

Ethnicity:

Gender:

Baseline functional form:Incidence*POP*A
Incidence dataset:Other Incidence (2014)
Prevalence dataset:

Variable dataset:

Beta:0.00225
4001
file:///C/Users/lmoel/Downloads/BenMAP%20Audit%20Trails/BenMAP%20Audit%20Trails/pm25.2031.pmit.txt[5/5/2021 9:32:08 AM] Beta distribution:Normal
P1Beta:0.000591837
P2Beta:0
A:0.971812
NameA:% of hospMI surviving 28 days
B:0
NameB:

C:0
NameC:

Ethnicity:

Gender:

Baseline functional form:Incidence*POP*A
Incidence dataset:Other Incidence (2014)
Prevalence dataset:

Variable dataset:

Beta:0.00225
Beta distribution:Normal
P1Beta:0.000591837
P2Beta:0
A:0.971812
NameA:% of hospMI surviving 28 days
B:0
NameB:

C:0
NameC:

Percentile:0
</Health.impact.function.3>
<Health.impact.function.4>
Health impact function dataset:EPA Standard Health Functions Endpoint group:Acute Myocardial Infarction
Endpoint:Acute Myocardial Infarction, Nonfatal
Start age:25
End age:44
Race:

Ethnicity:

Gender:

Pollutant:PM2.5
4002
file:///C/Users/lmoel/Downloads/BenMAP%20Audit%20Trails/BenMAP%20Audit%20Trails/pm25.2031.pmit.txt[5/5/2021 9:32:08 AM] Metric:D24HourMean
Metric statistic:None
Author:Zanobetti et al
Qualifier:All Seasons
Function:(1-(1/EXP(Beta*DELTAQ)))*Incidence*POP*A
Year:2009
Geographic area:Everywhere
Other pollutants:

Baseline functional form:Incidence*POP*A
Incidence dataset:Other Incidence (2014)
Prevalence dataset:

Variable dataset:

Beta:0.00225
Beta distribution:Normal
P1Beta:0.000591837
P2Beta:0
A:0.98148
NameA:% of hospMI surviving 28 days
B:0
NameB:

C:0
NameC:

Ethnicity:

Gender:

Baseline functional form:Incidence*POP*A
Incidence dataset:Other Incidence (2014)
Prevalence dataset:

Variable dataset:

Beta:0.00225
Beta distribution:Normal
P1Beta:0.000591837
P2Beta:0
A:0.925661
NameA:% of hospMI surviving 28 days
B:0
4003
file:///C/Users/lmoel/Downloads/BenMAP%20Audit%20Trails/BenMAP%20Audit%20Trails/pm25.2031.pmit.txt[5/5/2021 9:32:08 AM] NameB:

C:0
NameC:

Percentile:0
</Health.impact.function.5>
<Health.impact.function.6>
Health impact function dataset:EPA Standard Health Functions Endpoint group:Hospital Admissions, Respiratory
Endpoint:HA, All Respiratory
Start age:65
End age:99
Race:

Ethnicity:

Gender:

Pollutant:PM2.5
Metric:D24HourMean
Metric statistic:None
Author:Zanobetti et al
Qualifier:All Seasons
Function:(1-EXP(-Beta*DELTAQ))*Incidence*POP
Year:2009
Geographic area:Everywhere
Other pollutants:

Baseline functional form:Incidence*POP
Incidence dataset:Other Incidence (2014)
Prevalence dataset:

Variable dataset:

Beta:0.00207
Beta distribution:Normal
P1Beta:0.000446429
P2Beta:0
A:0
NameA:

B:0
NameB:

C:0
NameC:

Ethnicity:

Gender:

Pollutant:PM2.5
Metric:D24HourMean
Metric statistic:None
Author:Bell
Qualifier:National; Yearly
Function:(1-EXP(-Beta*DELTAQ))*Incidence*POP
Year:2012
4004
file:///C/Users/lmoel/Downloads/BenMAP%20Audit%20Trails/BenMAP%20Audit%20Trails/pm25.2031.pmit.txt[5/5/2021 9:32:08 AM] Geographic area:Everywhere
Other pollutants:

Reference:Bell, M.L. 2012. Assessment of the Health Impacts of Particulate Matter Characteristics. Research Report 161. Health Effects Institute. Research Report 161: 1-59.

Baseline functional form:Incidence*POP
Incidence dataset:Other Incidence (2014)
Prevalence dataset:

Variable dataset:

Beta:0.0008
Beta distribution:Normal
P1Beta:0.000107143
P2Beta:0
A:0
NameA:

B:0
NameB:

C:0
NameC:

Ethnicity:

Gender:

Pollutant:PM2.5
Metric:D24HourMean
Metric statistic:None
Author:Sheppard
Qualifier:

Function:(1-(1/EXP(Beta*DELTAQ)))*Incidence*POP
Year:2003
Geographic area:Everywhere
Other pollutants:

Baseline functional form:Incidence*POP
Incidence dataset:Other Incidence (2014)
Prevalence dataset:

Variable dataset:

Beta:0.003323789
Beta distribution:Normal
P1Beta:0.00104459
P2Beta:0
A:0
NameA:

B:0
NameB:

C:0
NameC:

Percentile:0
</Health.impact.function.8>
4005
file:///C/Users/lmoel/Downloads/BenMAP%20Audit%20Trails/BenMAP%20Audit%20Trails/pm25.2031.pmit.txt[5/5/2021 9:32:08 AM] <Health.impact.function.9>
Health impact function dataset:EPA Standard Health Functions Endpoint group:Emergency Room Visits, Respiratory
Endpoint:Emergency Room Visits, Asthma
Start age:0
End age:99
Race:

Ethnicity:

Gender:

Pollutant:PM2.5
Metric:D24HourMean
Metric statistic:None
Author:Mar et al.

Qualifier:Entire study period (January 3, 1999 - May 30, 2002) Function:(1-EXP(-Beta*DELTAQ))*Incidence*POP
Year:2010
Geographic area:Everywhere
Other pollutants:

Inhal Toxicol. Vol. 22 (6): 445-8. http://www.ncbi.nlm
Baseline functional form:Incidence*POP
Incidence dataset:Other Incidence (2014)
Prevalence dataset:

Variable dataset:

Beta:0.005602959
Beta distribution:Normal
P1Beta:0.002103073
P2Beta:0
A:0
NameA:

B:0
NameB:

C:0
NameC:

Percentile:0
</Health.impact.function.9>
</Selected.health.impact.functions>
<Log.And.Message>
Processing complete. HIF processing time: 0 hours 16 minutes 8 seconds. </Log.And.Message>
Sort Incidence LHPs:False
Default Advanced Pooling Method:Roundweightstotwodigits Default Monte Carlo Iterations:5000
Random Seed:1
<Inflation.Adjustment>
Dataset:

Year:-1
</Inflation.Adjustment>
<Income.Growth.Adjustment>
Dataset:

Year : -1
</Income.Growth.Adjustment>
<Incidence.Aggregation>
Name:Friant
ID:33
Columns:87
4006
file:///C/Users/lmoel/Downloads/BenMAP%20Audit%20Trails/BenMAP%20Audit%20Trails/pm25.2031.pmit.txt[5/5/2021 9:32:08 AM] Rows:103
Grid Type:Shapefile
Shapefile Name:CEQA_FRanch_lc_87_103_4000_4000_-108_-256_WGS1984 </Incidence.Aggregation>
<Valuation.Aggregation>
Name:Friant
ID:33
Columns:87
Rows:103
Grid Type:Shapefile
Shapefile Name:CEQA_FRanch_lc_87_103_4000_4000_-108_-256_WGS1984 </Valuation.Aggregation>
<Incidence.Pooling.And.Aggregation.>
<Health.impact.function>
Health impact function dataset:EPA Standard Health Functions Endpoint group:Mortality
Endpoint:Mortality, All Cause
Pollutant:PM2.5
Metric:D24HourMean
Metric statistic:Mean
Seasonal metric:QuarterlyMean
Author:Krewski et al.

Qualifier:Random effects cox; 44 individual and 7 ecologic co-variates; 1999--2000 follow-up (Commentary table 4)
Function:(1-(1/EXP(Beta*DELTAQ)))*Incidence*POP
Year:2009
Geographic area:Everywhere
Other pollutants:TSP, O3, SO4, SO2
Reference:Krewski D, Jerrett M, Burnett R, et al. 2009. Extended Follow-Up and Spatial analysis of the American Cancer Society Linking Particulate Air Pollution and Mortality. Health Effects Institute, Cambridge MA
Start age:30
End age:99
Baseline functional form:Incidence*POP
Incidence dataset:Mortality Incidence (2000)
Beta:0.005826891
Beta distribution:Normal
P1Beta:0.000962763
P2Beta:0
A:0
NameA:

B:0
NameB:

C:0
NameC:

Percentile:0
Weight:0
</Health.impact.function>
</Incidence.Pooling.And.Aggregation.>
<Valuation.Pooling.Window.Name.Mortality>
Mortality
</Valuation.Pooling.Window.Name.Mortality>
<Incidence.Pooling.And.Aggregation.>
<Acute.Myocardial.InfarctionPooling.Method.TypeNone>
<Health.impact.function>
Health impact function dataset:EPA Standard Health Functions Endpoint group:Acute Myocardial Infarction
4007
file:///C/Users/lmoel/Downloads/BenMAP%20Audit%20Trails/BenMAP%20Audit%20Trails/pm25.2031.pmit.txt[5/5/2021 9:32:08 AM] Endpoint:Acute Myocardial Infarction, Nonfatal
Pollutant:PM2.5
Metric:D24HourMean
Metric statistic:None
Author:Zanobetti et al
Year:2009
Location:26 U.S. Communities
Other pollutants:

Start age:18
End age:24
Baseline functional form:

Incidence dataset:Other Incidence (2014)
Beta:0.00225
Beta distribution:Normal
P1Beta:0.000591837
P2Beta:0
A:0.98148
NameA:% of hospMI surviving 28 days
B:0
NameB:

C:0
NameC:

Start age:45
End age:54
Baseline functional form:

Incidence dataset:Other Incidence (2014)
Beta:0.00225
Beta distribution:Normal
P1Beta:0.000591837
P2Beta:0
A:0.971812
NameA:% of hospMI surviving 28 days
B:0
NameB:

C:0
NameC:

Percentile:0
4008
file:///C/Users/lmoel/Downloads/BenMAP%20Audit%20Trails/BenMAP%20Audit%20Trails/pm25.2031.pmit.txt[5/5/2021 9:32:08 AM] Weight:0
</Health.impact.function>
<Health.impact.function>
Health impact function dataset:EPA Standard Health Functions Endpoint group:Acute Myocardial Infarction
Endpoint:Acute Myocardial Infarction, Nonfatal
Pollutant:PM2.5
Metric:D24HourMean
Metric statistic:None
Author:Zanobetti et al
Year:2009
Location:26 U.S. Communities
Other pollutants:

Start age:55
End age:64
Baseline functional form:

Incidence dataset:Other Incidence (2014)
Beta:0.00225
Beta distribution:Normal
P1Beta:0.000591837
P2Beta:0
A:0.971812
NameA:% of hospMI surviving 28 days
B:0
NameB:

C:0
NameC:

Start age:25
End age:44
Baseline functional form:

Incidence dataset:Other Incidence (2014)
Beta:0.00225
Beta distribution:Normal
P1Beta:0.000591837
P2Beta:0
A:0.98148
NameA:% of hospMI surviving 28 days
4009
file:///C/Users/lmoel/Downloads/BenMAP%20Audit%20Trails/BenMAP%20Audit%20Trails/pm25.2031.pmit.txt[5/5/2021 9:32:08 AM] B:0
NameB:

C:0
NameC:

Start age:65
End age:99
Baseline functional form:

Incidence dataset:Other Incidence (2014)
Beta:0.00225
Beta distribution:Normal
P1Beta:0.000591837
P2Beta:0
A:0.925661
NameA:% of hospMI surviving 28 days
B:0
NameB:

C:0
NameC:

Start age:18
End age:24
Baseline functional form:Incidence*POP*A
4010
file:///C/Users/lmoel/Downloads/BenMAP%20Audit%20Trails/BenMAP%20Audit%20Trails/pm25.2031.pmit.txt[5/5/2021 9:32:08 AM] Incidence dataset:Other Incidence (2014)
Beta:0.00225
Beta distribution:Normal
P1Beta:0.000591837
P2Beta:0
A:0.98148
NameA:% of hospMI surviving 28 days
B:0
NameB:

C:0
NameC:

Percentile:0
Weight:0
</Health.impact.function>
<Health.impact.function>
Health impact function dataset:EPA Standard Health Functions Endpoint group:Acute Myocardial Infarction
Endpoint:Acute Myocardial Infarction, Nonfatal
Pollutant:PM2.5
Metric:D24HourMean
Metric statistic:None
Author:Zanobetti et al
Qualifier:All Seasons
Function:(1-(1/EXP(Beta*DELTAQ)))*Incidence*POP*A
Year:2009
4011
file:///C/Users/lmoel/Downloads/BenMAP%20Audit%20Trails/BenMAP%20Audit%20Trails/pm25.2031.pmit.txt[5/5/2021 9:32:08 AM] Geographic area:Everywhere
Other pollutants:

C:0
NameC:

Percentile:0
Weight:0
</Health.impact.function>
<Health.impact.function>
Health impact function dataset:EPA Standard Health Functions Endpoint group:Acute Myocardial Infarction
Endpoint:Acute Myocardial Infarction, Nonfatal
4012
file:///C/Users/lmoel/Downloads/BenMAP%20Audit%20Trails/BenMAP%20Audit%20Trails/pm25.2031.pmit.txt[5/5/2021 9:32:08 AM] Pollutant:PM2.5
Metric:D24HourMean
Metric statistic:None
Author:Zanobetti et al
Qualifier:All Seasons
Function:(1-(1/EXP(Beta*DELTAQ)))*Incidence*POP*A
Year:2009
Geographic area:Everywhere
Other pollutants:

C:0
NameC:

Reference:Bell, M.L. 2012. Assessment of the Health Impacts of Particulate Matter Characteristics. Research Report 161. Health Effects Institute. Research Report 161: 1-59.

Start age:65
End age:99
Baseline functional form:Incidence*POP
Incidence dataset:Other Incidence (2014)
4013
file:///C/Users/lmoel/Downloads/BenMAP%20Audit%20Trails/BenMAP%20Audit%20Trails/pm25.2031.pmit.txt[5/5/2021 9:32:08 AM] Beta:0.0008
Beta distribution:Normal
P1Beta:0.000107143
P2Beta:0
A:0
NameA:

B:0
NameB:

C:0
NameC:

Start age:65
End age:99
Baseline functional form:

Incidence dataset:Other Incidence (2014)
Beta:0.00207
Beta distribution:Normal
P1Beta:0.000446429
P2Beta:0
A:0
NameA:

B:0
NameB:

C:0
NameC:

Percentile:0
Weight:0
</Health.impact.function>
<Health.impact.function>
Health impact function dataset:EPA Standard Health Functions Endpoint group:Hospital Admissions, Respiratory
Endpoint:HA, Asthma
Pollutant:PM2.5
Metric:D24HourMean
Metric statistic:None
4014
file:///C/Users/lmoel/Downloads/BenMAP%20Audit%20Trails/BenMAP%20Audit%20Trails/pm25.2031.pmit.txt[5/5/2021 9:32:08 AM] Author:Sheppard
Year:2003
Location:Seattle, WA
Other pollutants:

Start age:0
End age:64
Baseline functional form:

Incidence dataset:Other Incidence (2014)
Beta:0.003323789
Beta distribution:Normal
P1Beta:0.00104459
P2Beta:0
A:0
NameA:

B:0
NameB:

C:0
NameC:

Start age:65
End age:99
Baseline functional form:Incidence*POP
Incidence dataset:Other Incidence (2014)
Beta:0.00207
Beta distribution:Normal
P1Beta:0.000446429
P2Beta:0
A:0
NameA:

B:0
NameB:

C:0
NameC:

Percentile:0
Weight:0
4015
file:///C/Users/lmoel/Downloads/BenMAP%20Audit%20Trails/BenMAP%20Audit%20Trails/pm25.2031.pmit.txt[5/5/2021 9:32:08 AM] </Health.impact.function>
<Health.impact.function>
Health impact function dataset:EPA Standard Health Functions Endpoint group:Hospital Admissions, Respiratory
Endpoint:HA, Asthma
Pollutant:PM2.5
Metric:D24HourMean
Metric statistic:None
Author:Sheppard
Qualifier:

Function:(1-(1/EXP(Beta*DELTAQ)))*Incidence*POP
Year:2003
Geographic area:Everywhere
Other pollutants:

Start age:0
End age:64
Baseline functional form:Incidence*POP
Incidence dataset:Other Incidence (2014)
Beta:0.003323789
Beta distribution:Normal
P1Beta:0.00104459
P2Beta:0
A:0
NameA:

B:0
NameB:

C:0
NameC:

Qualifier:Entire study period (January 3, 1999 - May 30, 2002) Function:(1-EXP(-Beta*DELTAQ))*Incidence*POP
Year:2010
Geographic area:Everywhere
Other pollutants:

Inhal Toxicol. Vol. 22 (6): 445-8. http://www.ncbi.nlm
4016
file:///C/Users/lmoel/Downloads/BenMAP%20Audit%20Trails/BenMAP%20Audit%20Trails/pm25.2031.pmit.txt[5/5/2021 9:32:08 AM] Start age:0
End age:99
Baseline functional form:Incidence*POP
Incidence dataset:Other Incidence (2014)
Beta:0.005602959
Beta distribution:Normal
P1Beta:0.002103073
P2Beta:0
A:0
NameA:

B:0
NameB:

C:0
NameC:

APPENDIX C
Resumes
4018
16870 West Bernardo Drive, Suite 400, San Diego, CA 92127 | 858.695.9200 | www.bluescapeinc.com Expertise
Air Quality Permitting & Compliance
Litigation Support
Strategic Business and Project Management
Mitigation Programs
Greenhouse Gas Management
Air Dispersion Modeling
CEQA Air Quality Impact Analysis
Chemical Spill Risk Management
Health Risk Assessment
Air Emissions Inventories
Emissions Credit Banking
Industry Focus
Power Generation
Refineries and Chemical Plants
Oil and Gas Production
LNG Facilities
Aggregate and Asphalt Production
Coating Operations
Pharmaceuticals
Building Materials Manufacturing
Aerospace Industry
Metal Plating Operations
General Manufacturing
Education
MS, Environmental Science, Indiana Univ.

BS, Atmospheric Sciences, UCLA
Certifications
Certified Consulting Meteorologist (CCM)
Certified Permitting Professional (CPP)
Associations / Memberships
American Meteorological Society
Air & Waste Management Association
California Alliance for Distributed Energy
Resources (CADER)
LA Bar Association
CA Climate Action Registry
Company Background
BlueScape
Kleinfelder
ENVIRON Corporation
Engineering-Science, Inc.

Summary of Experience
In 1997, James A. Westbrook, founded BlueScape Environmental (BlueScape) to help businesses achieve practical, cost-effective air quality compliance solutions. Since then, he has independently grown BlueScape by way of exceptional skills in strategic business planning, marketing, and project management. BlueScape currently serves businesses with annual revenues in excess of one billion dollars, including power generation and manufacturing companies, developers and consulting firms.

Mr. Westbrook helps clients to obtain air permits and achieve strategic business goals by drawing upon his expert skills in regulatory analysis & negotiation, air emissions calculations, greenhouse gas emissions management, dispersion modeling, and human health risk and exposure assessment. Mr. Westbrook serves as an expert witness in litigation cases involving air emissions estimates, dispersion modeling, and health risk assessment. To provide superior customer service, he has assembled a team of engineers and scientists with a wide range of experience and knowledge with industrial equipment, emission control technologies, computer emissions and dispersion modeling tools, and agency contacts throughout the U.S.

Mr. Westbrook actively speaks to industry trade groups regarding air quality compliance issues. He is the co-instructor for the only publicly available training course on the Hotspots Analysis and Reporting Program (HARP) risk assessment software. His work background includes experience obtained at Kleinfelder in Pleasanton, CA, ENVIRON Corporation in Emeryville, CA, and Parsons Engineering-Science in Pasadena, California.

His formal education includes an M.S. in Environmental Science from Indiana University, Bloomington and a B.S. in Atmospheric Sciences from UCLA. He is a Certified Consulting Meteorologist (CCM) and is recognized as a Certified Permitting Professional (CPP) by the South Coast Air Quality Management District. Mr. Westbrook is listed as a CEQA Consultant for Air Quality by the County of San Diego, Planning Department.

James A. Westbrook
President
Principal Air Quality Scientist
BL U
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James A. Westbrook
President
Principal Air Quality Scientist
BlueScape Environmental
Select Project Experience:

Human Health Risk and Exposure Assessment
 Diesel Health Risk Assessment, Boeing Corporation, Long Beach. Project Manager for completion of a health risk assessment for diesel PM emissions from 18 emergency and portable generators at Boeing’s facilities in Long Beach. The work was completed using the HARP software. The purpose of the study was to evaluate the potential impacts from the engines, if included in a proposed South Coast Air Quality Management District air toxics rule. The results from the study were used to determine the location and time needed to operate the engines and be in compliance with the proposed rule.  Comprehensive Proposition 65 Audits, Confidential Power Producer, California. For a confidential independent power producer, completed comprehensive Prop 65 audits for six facilities. The facilities combust petroleum coke, a byproduct of refining.

Potential exposure areas covered included occupational and visitor, water discharges, air discharges, and exposure to a co-product from the electricity generation process. A report was prepared stating conclusions and whether there was a need to warn the community.
 Duwamish Regional Health Risk Assessment, Seattle, Washington. Teamed with Dillingham Software Engineering (DSE), the developer of California Air Resources Board Hotspots Analysis and Reporting Program (HARP), to complete a regional health risk assessment for the Duwamish River Valley just to the south of downtown Seattle. The modeling and health risk study included onroad diesel emissions sources, wood stoves, and criteria pollutant and air toxic emissions from more than 200 industrial facilities.

BlueScape was responsible for developing the industrial facility air toxics emissions inventory, and completing a report utilizing modeling output provided by DSE. The study was sponsored by the Washington Department of Health.  AB2588 Health Risk Assessments, Multiple California Facilities. Project Manager or Technical Lead for more than 20 AB2588 health risk assessment projects for industrial facilities located in Southern California. These included 10 Southern California Edison power plants, a fiberglass manufacturing facility, a spice processing plant, a plumbing supplies plant, the Kwikset manufacturing facility in Anaheim, two petroleum processing/refining facilities, two small parts coatings facilities (hexavalent chromium-based pigments), a resin manufacturer, a specialty resistor manufacturer and two aerospace part manufacturers. Used the SCREEN3 and ISCST3 dispersion models and the ACE2588 and HRA health risk assessment models to calculate and report health risks.  New Source Review Air Permitting Health Risk Assessments, Multiple California Facilities. Project Manager or Technical Lead for completing health risk assessments to obtain air permits for a wide range of industrial emission sources located in California, for example, three separate air strippers, a can manufacturing facility, a landfill gas flare, two wood cabinet manufacturing facilities, a fiberglass manufacturing facility, a major refinery, and a power generation company. In the process of obtaining air permits, BLUESCAPE has used techniques ranging from consulting look-up tables and screening dispersion modeling, to full refined dispersion modeling and risk calculations.  Benzene Exposure Analysis, Confidential Refinery, Appalachian Region. Lead dispersion modeler for an analysis of potential human exposure to benzene emitted from wastewater processing operations at a medium-sized petroleum refinery. Used the ISCST and COMPLEXI models to estimate ground-level impacts due to fugitive sources such as tanks, pipes, and ponds, as well as point sources such as cooling towers. Estimated potential excess cancer risk under various exposure scenarios, accounting for population mobility, indoor concentrations relative to outdoor concentrations, and movement of population between various microenvironments.
 Evaluation of U.S. EPA’s use of the HAPEM Exposure Model to Estimate Benzene Emissions from Mobile Sources, Confidential Client. Lead modeler for evaluating U.S. EPA’s application of the HAPEM exposure model to mobile source pollutants, especially benzene. Downloaded CO monitoring data from the Aerometric Information Retrieval System. Using statistical and graphical methods, analyzed the relationship between ambient measurements of CO and tailpipe benzene emissions to critically evaluate U.S. EPA’s methodology.

Air Permitting: Minor New Source Review, PSD and Title V Air Permitting  Refinery Integration and PSD Review, Annual Emissions Reporting, Confidential Midwest Refineries. Project Manager for securing air permits and avoiding major PSD permitting for integration of two refineries located in the Midwest, separated by one mile. Conducted PSD Review of such issues as stationary source definition and common control, project aggregation, projected 4020

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President
Principal Air Quality Scientist
BlueScape Environmental
actual emissions, and capable of accommodating. In addition to integration of refinery operations, future projects included physical modifications and new units. Because the state determined that integration of both refineries was a change in method of operation, any future emissions increases above baseline would trigger major PSD permitting. BlueScape developed a method to use Projected Actual Emissions for integration plus aggregated projects to help the refineries avoid PSD. In addition to PSD review, the refineries hired BlueScape to develop a consistent Annual Emissions Reporting framework for both refineries and create a GHG emissions reporting plan under EPA’s MRR program.
 Hydrogen Plant Permits, Chevron Refinery, El Segundo, California. Project Manager for securing installation permits for a new hydrogen plant, including a 780 MMBtu/hr heater, SCR system, process vents and components. The project was required to replace an old, existing plant under an Order for Abatement. Successfully negotiated installation of the project without requiring scarce and expensive emission credits (PM10, 176 lb/day) that would have rendered the project impossible. Functionally identical replacement and concurrent modification offset exemptions were proposed and accepted by the South Coast AQMD. Negotiated permit conditions to provide operational flexibility during commissioning and startup conditions. Completed dispersion modeling using SCREEN3 and ISCST3 to show that short-term and long term operations will not cause or contribute to an exceedance of the health standards. Completed emission calculations and assembled all supporting documentation required as part of the rule review. Permits were issued in only six months, much less than the typical 1-2 years for similar projects, allowing the plant to be built and started as scheduled. BlueScape was a subcontractor to the Denali Group.  CEC Licensing and Air Quality Permits, Eastshore Energy Facility, Hayward, California. Air Quality Project Manager for CEC licensing and air quality permitting for a 115.5 MW peaking power plant consisting of 14 natural gas-fired lean-burn engines. CEC application work supported the Air Quality and Public Health sections of the AFC, including construction emissions and modeling and the health risk assessment. Developed a CEQA PM10 mitigation plan provided to CEC. Participated in workshops and public meetings to resolve issues. Developed air permit conditions for the BAAQMD Final Determination of Compliance (PDOC).  PSD Permit, Confidential Fiberglass Manufacturer, Northern California. Project Manager for completion of a PSD air permit application for a fiberglass manufacturing facility located in Northern California. Work included an air quality modeling analysis for PM10 and CO emissions. The facility’s compliance with federal ambient air quality standards and with allowable PSD increment consumption was assessed. Mr. Westbrook assisted with preparation of a PM10 pre-construction monitoring and QA/QC plan, addressing monitor siting issues.
 Expedited Distributed Generation Air Permits, RealEnergy Inc., California. Managed Phase I & II installation of clean gas-fired internal combustion engines in 10 sites located in the South Coast Region and San Diego County of California. Worked with team members Resource Catalysts and Environmental Compliance Solutions under a very aggressive schedule to successfully obtain permits. Providing RealEnergy with ongoing permitting and compliance management support.  CEC Siting Application for a 62 MW Peaker Turbine Facility, RAMCO Inc. & PG&E, California. Project leader with team member Resource Catalysts and other consultants; developed and submitted the licensing application for a peaking generation plant under the California Energy Commission 21-day expedited review process.  Backup Diesel Engine Air Permits, EDS Corporation and the U.S. Navy. As subcontractor to Rancho Santa Fe Technologies, prepared air permit applications for five 1 MW diesel-fired engines as part of the U.S. Naval global military intranet system called "SPAWARS.”
 Title V Permits, Peaking Power Plant, Chowchilla, California. BlueScape is prepared Title V permit applications for a peaking power plant consisting of 16 lean-burn gas engines, located in Chowchilla in the Valley Air District. The facility recently entered the program due to lowering of the Title V thresholds of NOx and VOC.  SIP Permit, Confidential Fiberglass Manufacturer, West Virginia. Project Manager for completion of air dispersion modeling services for a fiberglass manufacturing facility located in West Virginia. The work was performed to assess the effect of changing the West Virginia State Implementation Plan on attainment of area PM10 NAAQS. On-site meteorological data was processed for multiple tower levels. The SCREEN3 model was used to reduce the number of nearby sources to be included in the NAAQS modeling analyses. The IGM model with ISCST and RTDM was used to model impacts from facility sources. ISCST and COMPLEX I were used to model impacts from nearby sources.  Synthetic Minor Air Permits, Three Prestolite Wire Corporation Facilities in the Midwest and Eastern US. Project Manager for completion of synthetic minor air permit applications for telecommunication and automotive wire manufacturing facilities located 4021

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James A. Westbrook
President
Principal Air Quality Scientist
BlueScape Environmental
in Nebraska and Arkansas. Assisted facilities in preparing up-to-date emission inventories and avoiding Title V permitting requirements. For a third facility located in Georgia, negotiated with air pollution control agency staff to obtain an exemption from State air permitting requirements.
 PSD Permit, Confidential Fiberglass Manufacturer, Georgia. Managed and completed the modeling study to support a PSD application submittal for a fiberglass manufacturing facility located near Atlanta. The facility proposed to add sodium nitrate to raw batch materials to reduce odor-causing emissions of hydrogen sulfide from a melter. As a result, PSD for NO2 was triggered. The project involved estimating process emissions of criteria pollutants, assessing compliance with NAAQS and increment thresholds for NO2, and completing other required PSD analyses, including a visibility screening analysis.  Synthetic Minor Air Permit, Fisher-Hamilton Scientific, Two Rivers, Wisconsin. Project Manager for completion of a Federally Enforceable State Operating Permit (FESOP) application for a wood furniture manufacturer. Our staff assisted the facility in implementing strategic measures to reduce VOC emissions and avoid Title V permit requirements. Calculations were performed for both actual and potential emissions based on future production scenarios, and drafted permit limits.  Title V Permits, Three California Facilities. Assisted with completion of Title V permit applications for the Owens-Brockway glass facility in Tracy, California, the Lodi Metal Tech Facility in Lodi, California, and the Sony Electronics facility in San Diego, California.

Lists of Title V-applicable regulations were developed for the facilities, and application forms were completed using client-supplied information.
 Air Permits, Confidential Fiberglass Facility, Southern California. Assisted a fiberglass facility in obtaining a modified air permit for an increase in production capacity on a highly restricted line. Although no net increase in emissions was expected following regulatory definitions, the permitting agency wanted air emission increases to be calculated using a restrictive methodology. This methodology triggered a Rule 1401 health risk assessment and led to delays in the permitting process.

Assisted the facility throughout the process by analyzing the effect of agency requirements and presented ways to express production limits in a manner that would move the project forward. Ultimately, BlueScape succeeded in showing that the facility could expand production without causing significant health risk impacts or requiring emissions offsets. The facility received the modified air permit.

Air Dispersion Modeling Analyses
 AERMOD Modeling, Bradwood Landing LNG Terminal, Oregon. As a subcontractor to SRA, used the AERMOD model to assess impacts from a proposed Bradwood Landing LNG carrier vessel offloading terminal on the Columbia River. Developed an air dispersion modeling protocol in consultation with the Oregon Department of Environmental Quality. Analyzed impacts of emissions from submerged combustion vaporizers at rugged terrain along the banks of the river. Assisted the design team with exhaust design to optimize engineering design and satisfy applicable air quality thresholds.  OCD Modeling, Clearwater Port LNG Terminal, Ventura, California. As a subcontractor to SRA, used the Offshore and Coastal Dispersion Model to assess overwater and onshore impacts from a proposed LNG offloading terminal and regasification platform 13 miles off Ventura County. Developed an air dispersion modeling protocol and completed modeling in consultation with the US EPA and the US Coast Guard.
 LAX Construction Equipment Modeling Study, Los Angeles, California. As a subcontractor to ECS, completed a dispersion modeling analysis for the proposed expansion of the Los Angeles International Airport. The majority of emissions resulted from diesel-fueled construction equipment. In order to show compliance with the Federal and State ambient air quality standards, completed ISCST3 air dispersion modeling using the ozone limiting technique for NOx emissions.  PSD Modeling Study, Columbia Ridge Landfill, Arlington, Oregon. As a subcontractor to SCS Engineers, managed completion of a dispersion modeling study to assess impacts from increased fugitive PM10 emissions from a landfill. Impacts modeled using AERMOD were compared to the Oregon state ambient standards and increment levels. The project was particularly challenging given the amount of emissions from ground-level sources. Worked closely with the prime contractor to refine the modeling study emissions and source parameter inputs so that future operations will be in compliance with the standards.  Odor Modeling, San Diego Metropolitan Wastewater District (SDMWD), San Diego, California. Completed dispersion modeling study using the ISCST3 model to assess potential odor impacts and health risks. The San Diego MWD planned construction of a Wet Weather Storage Facility (WWSF), consisting of two 7 million gallon underground storage tanks, to handle future peak wastewater flows during storm events. Required analysis of potential nuisance odors and health risk impacts as 4022

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James A. Westbrook
President
Principal Air Quality Scientist
BlueScape Environmental
compared to thresholds established by the San Diego APCD under Rule 1200 for surrounding businesses. Developed engineering design data, such as stack height, air flows, and scrubber control efficiency that would be required to meet City's odor design standards of 5 odor units (OU). Used conservative modeling and exposure assumptions, to show that odor impacts and health risks from the Wet Weather Storage Facility would meet design requirements.  Air Dispersion Modeling & Health Risk Assessment, THUMS, Inc., Long Beach, California. Owner of natural gas and petroleum production fields, planned to site a 44 MW simple-cycle turbine facility in Long Beach harbor to provide onsite electricity for well pumping. Needed modeling and HRA to show that operation was in compliance with South Coast Air District Rules 1303 and 1401. Modeled impacts from criteria pollutants (NOx, PM10, etc.), ammonia slip, and air toxics found at three candidate site locations. Examined the effect of different stack heights, and the effect of building downwash on air quality impacts. For each candidate site, determined a stack configuration that would result in compliance with the district rules.  Ambient Air Quality Analysis, Motorola 52nd Street, Phoenix, Arizona. Lead dispersion modeler for an ambient air quality analyses performed for a semiconductor manufacturing facility. Estimated off-site air quality impacts using the ISCST and SHORTZ dispersion models. From estimates of off-site concentrations and emissions data, compared modeling results to state ambient air quality guidelines. Completed feasibility studies to evaluate the impact of modifying facilities.  Stack Increase Study, Confidential Metal Container Manufacturer, Southern California. Entrainment of sulfuric acid emissions released from three stacks into building ventilation intakes was apparently resulting in poor product finish quality for some can batches. As a subcontractor to Kleinfelder, made visual observations at the site and confirmed a potential problem during strong northeast winds. Using the ISCST3 model and ASHRAE guidance, stack height increases needed to avoid intake contamination were estimated. Reconstruction of the stacks was commenced based upon study recommendations.  Indoor Contamination Study, Confidential Hospital, Nevada. A hospital in Nevada was evaluating reports of health effects possibly caused by indoor pollutant contamination. An investigation of rooftop stacks revealed that emissions from two boilers were potentially entrained into building ventilation intakes on the lee side (cavity area) of a downwind structure. The ASHRAE ventilation guidance was used to estimate boiler stack height increases recommended to avoid the building cavity zone.  Third-Party Modeling Review; Instantaneous and Short-Term Releases from Multiple Federal Munitions Disposal Facilities, Eastern United States. Health risk assessments were performed by the facilities following the USEPA Human Health Risk Assessment Procedures (HHRAP) guidance document. Models proposed for use included OBODM, ISCST3, INPUFF, and TRPUF. Resulting documentation required third-party review by an independent source. The review focused primarily on the appropriateness of modeling input data assumptions, including emissions, source release parameters, and meteorological data.

Comments were provided to Booz-Allen, and submitted along with other comments to USEPA and state air pollution agency staff.  Monitoring/Meteorological Data Validation Study, Confidential Municipal Waste Landfill, Southern California. Compared vinyl chloride monitoring data to concurrently obtain meteorological measurements. Used on-site meteorological measurements as well as synoptic observations to validate monitoring data.

Mitigation Programs
 Air Quality Mitigation and Monitoring Support, Confidential California Utility Transmission Project. With ZMassociates, Project Director providing air quality mitigation support to a major utility. At the outset of the project the utility was required to mitigate more than 200 tons/year of NOx emissions. Refined project emissions estimates for updated route alignment and construction equipment forecasts. The outcome NOx mitigation requirements were removed. Calculated construction and operational GHG emissions and developed a plan for providing mitigation using carbon credits. Led team development of a Construction Emissions Monitoring Plan to track actual usage of construction equipment.  PM10 Mitigation Plan, Escondido, California. Sempra Energy developed a 500 MW power generation facility in Escondido, California. Sempra was required to fund up to $1.9 million for local PM10 mitigation, with a preference for diesel exhaust mitigation.

Under contract to City of Escondido, developed a PM10 mitigation plan identifying potential sources of local diesel mitigation. The mitigation plan considered the cost-effectiveness of diesel mitigation, as well as reducing emissions from other source types.

Helped City of Escondido to apply for up to $500,000 in funding for particulate filters for several on-road and off-road diesel vehicles, and new school buses.
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James A. Westbrook
President
Principal Air Quality Scientist
BlueScape Environmental
 PM10 Mitigation Plan, Eastshore Energy Facility, Hayward, California. Project Manager for developing a PM10 mitigation plan under California CEQA requirements. The Eastshore Energy facility is not required to mitigate PM10 under BAAQMD regulations.

However, CEC requires that PM10 emissions be mitigated, especially during potential non-attainment periods. Developed a twoprong plan that proposes using BAAQMD-banked emission reduction credits, or a wood stove and fireplace replacement program.

The mitigation is currently being negotiated with CEC.
 LAX PM10 Mitigation Study, Los Angeles, California. Completed research of PM10 mitigation options for the LAX expansion project. Focus of the research work was on air filtration in air conditioning systems in area schools.  Rule 1309.1 Priority Reserve Rule Review, Southern California. For a confidential client, applying PM10 offsets, closely followed Rule 1309.1 Priority Reserve developments. Challenges to Rule 1309.1 placed many restrictions on facilities needing access to the Priority reserve. This will have a significant impact on the market for PM10 Emission Reduction Credits within the SCAQMD.

Greenhouse Gas Management
 Johns Manville Corporation, Corporate Greenhouse Gas Inventory Management. Johns Manville is a Berkshire Hathaway Company that manufactures residential and commercial insulation and roofing products (www.jm.com). The company has 50 manufacturing facilities worldwide. BlueScape conducted baseline emissions inventory work focusing on two California facilities that may be subject to AB32 reporting requirements. The 2006 emissions inventory data were be supplied to the California Climate Action Registry, and successfully verified by a third party. On a corporate level, BlueScape is working with Johns Manville to develop corporate strategies to address climate change issues, considering energy efficiency and credit development opportunities, national Climate Registry participation, and insulation product sales.  Greenhouse Gas Footprint Life Cycle Analysis, Confidential LNG Project, Western US. BlueScape partnered with WorleyParsons Komex to prepare a GHG footprint life cycle analysis for a proposed liquefied natural gas project. The project will obtain natural gas from fields in Asia or Australia, clean and liquefy the gas and transport LNG across the Pacific Ocean to the US West Coast. Regasification and compression of natural gas will be accomplished utilizing four gas turbines. The project is being completed for submittal to the Coastal Commission, US Coast Guard and other agencies as part of a NEPA review. The life cycle GHG impact with and without the project (no action alternative) will be compared. The no action alternative considers forecasted Western US power industry fuel and generation technology mix, including coal, natural gas, renewable, nuclear and hydroelectric, from 2012 to 2050. To complete the work, BlueScape obtained and analyzed utility, CEC and PUC reports.  Confidential Independent Power Producer, Greenhouse Gas Emissions Inventory and Solutions, California. BlueScape completed a baseline greenhouse gas emissions inventory for an independent power producer operating nine plants with 500 MW of total power production capacity. At six plants, the company combusts petroleum coke, a fuel with CO2 emissions similar to coal.

The company is facing contract renewal with PG&E, and is concerned that the facilities will not be competitive to natural gas-fired plants. BlueScape is working with the company to analyze possible solutions to reduce GHG emissions ahead of impending AB32 compliance requirements and PG&E contract renegotiation. Options identified to date include boiler oxy-firing, fuel switching, carbon sequestration, load shifting to re-permitted gas-fired power plants, and plant shutdown. The company is also considering investing in renewable energy projects to offset GHG emissions from fossil fuels. The project goal will be to help the company to remain competitive in the rapidly changing California power generation market.  Greenhouse Gas Emissions Inventory Verification, California Climate Action Registry. BlueScape has completed verification work on three greenhouse gas emission inventories. The work was completed as a subcontractor to ICF Consulting, for 2006 inventories submitted to the California Climate Action Registry. The companies include Los Angeles County, Driftwood Dairy, and Termo Oil and Gas., all located in the Los Angeles area. The verification work included initial meetings, site visits, auditing of records and calculations, and filing a verification opinion.  Oil Production CO2 Life Cycle Analysis, Client: Confidential Refinery, California. Managed a project to complete a life cycle analysis to compare the CO2 emissions from extraction and delivery of Los Angeles heavy crude oil to a Los Angeles refinery versus extraction, marine shipping, and delivery of Alaskan or Middle East light crude oil to a Los Angeles refinery. CO2 emissions for extraction of Los Angeles heavy crude oil were based on an oil production lease’s certified California Climate Action Registry emissions. CO2 emissions for extraction of Canadian light crude oil were based on average natural gas combustion and production 4024

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James A. Westbrook
President
Principal Air Quality Scientist
BlueScape Environmental
data published by the Alaska Oil and Gas Conservation Commission. CO2 emissions for extraction of Middle East light crude oil were estimated from Los Angeles/Canada data and a reduced water/oil ratio. CO2 emissions from transportation considered heavy fuel oil combustion in main and auxiliary engines throughout the tanker travel distance, as well as marine diesel combustion by tugs and during maneuvering and hotelling. Results were compiled as a production carbon intensity to show that the higher CO2 emissions from heavy crude oil production in Los Angeles were offset by the reduced transportation emissions.

Accidental Release Offsite Consequence Analyses
 RMP Offsite Consequence Analysis, Multi-Chem, New Iberia, Louisiana and Denver City, Texas. As a subcontractor to Denali, Inc., BlueScape completed an offsite consequence analysis for a chemical storage and distribution facility. The facility distributes acrolein, a highly toxic substances used in oil and gas fields in the petroleum industry. The worst-case and alternative release scenarios were assessed, including breach of a storage tank and a PRV release involving a fire. Modeling was completed using RMPComp and Aloha.
 RMP Offsite Consequence Analysis, Hill Brothers Chemical Company and Modern Ice and Cold Storage, San Jose, California. As a subcontractor to Denali, Inc., completed a CalARP (RMP) modeling study for a chemical company that stores and redistributes for sale anhydrous and aqueous ammonia, and a food cold storage facility. For each facility, assessed the worst-case and alternative release scenarios for each process utilizing ammonia, then calculated the source term (ammonia release rates) for each process. The worst-case and alternative case impacts were determined using the DEGADIS and/or other appropriate models or guidance.
 Offsite Consequence Analysis, Microchip, Tempe, Arizona. A semiconductor manufacturer needed to update its accidental release management plan for compressed gases, hydrochloric acid, and sulfuric acid. The ISCST3 model with one year of meteorological data was used to model compressed gas releases. DEGADIS was used to model acid spills. The radii of impact, based upon the distance to IDLH values, were found to be within the facility boundary. A report presenting the results of the analysis and showing the onsite radii of impact was completed.  Risk Management and Prevention Plan, Komag, Fremont, California. For development of an RMPP, analyzed meteorological data to determine typical conditions that could occur during an accidental release. Developed a report section describing typical meteorological conditions in the RMPP.
 Accidental Release Models Evaluation, Pure-Etch, Salinas, California. As part of a CEQA study, an etching solution reclaim facility was required to conduct a “customized” accidental release analysis for a mitigated negative declaration. The chemicals at issue were sulfuric acid, hydrochloric acid, and ammonia. Assisted in the project by locating and evaluating candidate dispersion models for completing offsite consequence analyses.

Air Emissions Inventories
 Air Emissions Fee Reports, Johns Manville Corporation, Corona, California. Assisted a fiberglass company in Southern California in response to SCAQMD’s request for revised Rule 301 emissions inventories for the period 1994-1997 and completed the 1997-1998 report. A full air compliance audit initiated the project to verify permit status and emissions source inclusion.

Emission factors were updated to reflect recent source tests and a Title V emissions inventory.  Clean Air Act Emissions Inventory for Two ABEX/NWL Control Systems Facilities. Managed the completion of facility-wide emissions inventories for two aerospace component manufacturing facilities located in Michigan and Georgia. The emission inventories were submitted to State agencies and became the basis for determining applicable Clean Air Act requirements, including Title V permitting.
 Due Diligence Emissions Inventory, Confidential Golf Club Manufacturer, San Diego, California. A golf club manufacturer was interested in estimating air toxic emissions from one of two facilities. Emissions had not been tracked closely in the past. The project proved to be challenging, since many different paint and solvent products were used, usage logs differed between different production areas, and materials were often transferred from another facility. Data gaps were filled to complete the inventory.

Results of the due diligence inventory were compared to local air district regulations to assess compliance. 4025

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James A. Westbrook
President
Principal Air Quality Scientist
BlueScape Environmental
 Dehydration Unit Emissions, Confidential Natural Gas Producer, Western U.S. Using natural gas composition information supplied by the client, estimated VOC and hazardous air pollutant emissions from triethylene glycol dehydration units at three facilities. The purpose of the project was to determine if Title V permit applicability thresholds were exceeded. The GlyCalc 3.0 model was used to complete emissions estimates.
 AB2588 Emissions Inventory, Johns Manville, Willows, California. A fiberglass manufacturing facility was required to update its original AB2588 emissions report. Several new source test results had been completed. Using the source test data and other information sources, a comprehensive air toxics inventory was completed and submitted to the Glenn County Air Pollution Control District using FATES. From the results of the analysis, risk prioritization scores were estimated and the facility was counseled on potential updated risk assessment requirements.
 AB2588 Emissions Inventory Plans, Calmat, Southern California. Completed Air Toxics Inventory Plans for more than 10 sand and aggregate, batch concrete, and batch asphalt plants. Provided detailed information to agencies on processes and emission quantification methods. The plans were the basis for later completion of emissions inventory reports.

Clean Air Regulatory Analyses and Compliance Audits
 Confidential Coatings Manufacturing Company, Air Permitting and Compliance – South Coast AQMD – A coatings manufacturing facility in Los Angeles required help with emission calculations to avoid Title V major source permitting requirements.

BlueScape avoided Title V, by completing alternative emission calculations for more than 20 vessels using EPA’s TANKS equations and specific chemical mixture properties. Subsequently, when auditing facility permits, BlueScape found that the facility had not properly permitted several mixing vessels. BlueScape completed permits under SCAQMD’s amnesty self-disclosure program, thus avoiding violations. BlueScape is currently working with the facility to triple the amount of throughput in a solvent recovery process. The project will require installation of a vapor condenser to reduce VOC and air toxic emissions increases.  Regulatory Analysis for the Petroleum Industry, Western States Petroleum Association. Conducted a comparative analysis of over 150 environmental regulations affecting petroleum companies in five key areas: air toxics, new source review, endangered species, hazardous materials, and oil spills. Determined reporting requirements, and assessed inefficiencies and overlaps between regulations.
 Clean Air Act Compliance Audits, Confidential National Client. Task Manager for analyzing the impact of the 1990 Clean Air Act Amendments on over 30 facilities located in 11 states and engaged in a variety of manufacturing activities. Reviewed emissions and process information to determine the applicability of, and compliance with, Federal, State and local air quality regulations. Prioritized issues and gave recommendations for action.  General Motors Environmental Audit, Flint, Michigan. As a team member with Golden Environmental, completed the air quality audit portion of the environmental for the maintenance services at “Buick City” located in Flint Michigan.  Environmental Compliance Audit, Triptych CD, Stockton, California. Completed the environmental compliance audit for a company located in Stockton, California, which produces compact discs. Evaluated the facility’s compliance with applicable air, solid waste, hazardous waste, and water discharge regulations.  Clean Air Act Compliance Audit, Confidential Aluminum Production Facility, South Carolina. Completed a review of Clean Air Act regulations that might apply to the facility as part of an environmental audit. Assessed the applicability of NSPS, NESHAP, MACT, CAA Section 112(r) and other requirements.

Environmental Impact Air Quality Analysis
 Air Quality Impact Analysis, Homestead Village, San Ramon, California. Project Manager for completion of an air quality impact analysis for a hotel development, as part of a CEQA environmental impact report. The analysis was completed efficiently using BAAQMD guidance and a study previously completed for a shopping center. Using traffic information supplied by another consultant, insignificant project impacts were estimated.  Environmental and Air Quality Impact Review, City of Antioch and Pittsburg District Energy Facility. Project Manager retained by The City of Antioch, and Intervener, to review the California Energy Commission’s (CEC) Preliminary Staff Assessment 4026

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James A. Westbrook
President
Principal Air Quality Scientist
BlueScape Environmental
for the Pittsburg District Energy Facility. Worked with team members to developed written testimony regarding potential impacts to air quality, water quality, and infrastructure. Attended workshops and hearings to obtain information and present City of Anitoch’s concerns to CEC staff.
 Air Quality Modeling Analysis, Alta Ski Resort Draft EIR, Utah. Revised the air quality impact section of a draft EIR for the Alta Ski Resort. The section was expanded to address lead agency comments regarding potential impacts on ambient air quality, visibility, and PSD increments. The SCREEN3 model and CALINE4 model were used to estimate impacts from direct and indirect sources. A formal response satisfying the comments was submitted.  Traffic and Air Emissions Study, Reno, Nevada. As part of the environmental impact report for the Southern Pacific-Union Pacific railroad merger, estimated automobile air emissions due to increased traffic delays caused by train trips in downtown Reno.

Estimated emissions using MOBILE5. Train emissions were estimated using emission factors supplied by the Washoe County Air Agency.
 Air Quality Impact Analysis, Vintage Faire Mall, Modesto, California. The Vintage Faire Mall was planning to expand to include additional services with added parking spaces. An analysis was completed to determine air quality impacts from increased automobile trips. The EMFAC7F model was run to obtain vehicle emission factors. Impacts from CO and other emissions were estimated using the CALINE4 model and CEQA guidance.

Litigation Support
 Litigation Support, SLOAPCD Rule 1001, Oceano Dunes, California. On behalf of Friends of Oceano Dunes, reviewed the South County Phase 2 Particulate Study for Oceano Dunes and the proposed San Luis Obispo County APCD Rule 1001 to permit and control dust emissions within the State Vehicular Recreation Area (SVRA). BlueScape’s report, among other things, challenged a direct connection between monitored PM concentrations and dust generated from within the SVRA, and also the practical enforceability of Rule 1001. The report was presented to the San Luis Obispo County Board of Directors, and used in subsequent litigation.
 Confidential Litigation, CO Poisoning Case, New Mexico. Project Manager and Expert Witness for a litigation case involving a CO exposure and poisoning case at a hotel in New Mexico. Performed site investigation and analysis of meteorological data as a preliminary step to indoor CO exposure modeling. Developed procedures to conduct modeling, considering placement of CO monitors and air flow into and out of emission source and exposure areas. The case was settled.  Confidential Odor Litigation Case, Southern California. Project Manager and Expert Witness for a litigation case involving a pet food manufacturing plant and reports of odors in the community. Reviewed the previous emission calculations and modeling approach completed by a consultant using ISCST3, and updated air quality modeling using AERMOD, the current EPA-required dispersion model for offsite impacts. Meteorological data were updated to nearby wind monitors and using MM5 prognostic upper air data. Peaking factors were developed to extrapolate one-hour average model impacts to 3-minute average impacts. The case is pending trial.
 Litigation Case for a Residential Housing Developer, San Diego. Project Manager and Expert Witness to support a residential housing developer as Defendant. A resident that lived on the road to a new housing developing sued the developer for dust and diesel emissions entering the property, claiming severe asthma and other health impacts. Developed an analysis of ambient ozone and particulate matter concentrations, and pollen data. Reviewed local wind data and proximity of roadways to the plaintiff’s house.

The case is pending trial.
 Confidential Air Toxics Litigation Case, Southern California. Project Manager and Expert Witness for a toxic tort litigation case in Southern California. The case involved transport of emissions from open burning and open detonation of waste munitions into a residential community. Developed meteorological data for air dispersion modeling using the CALMET system. Dispersion modeling was completed using ISCST3, OBODM, and CALPUFF to assess various historical operational scenarios. Deposed regarding modeling results. Case was settled out of court.  Litigation Support for an Accidental Chemical Release, Confidential Pesticide Manufacturing Company. Served as an Expert Witness on behalf of the Defendant, a pesticide manufacturing company, that had released chlorosulfonic acid from a tank. 4027

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James A. Westbrook
President
Principal Air Quality Scientist
BlueScape Environmental
The Plaintiff claimed injury from exposure to hydrochloric acid (HCL) generated from the release. Work involved meteorological data analysis to show that the Plaintiff could not have been in contact with an acid cloud, and SLAB dispersion modeling to predict downwind concentrations of HCL. Deposed regarding modeling results. The case ended in a settlement favorable to the Defendant.
 Proposition 65 Litigation, Confidential California Facility. Prepared a Proposition 65 health risk assessment for a metal polishing and plating facility that uses perchloroethylene in a vapor degreasing operation. A citizen’s group contended that the facility failed to warn off-site receptors of perchloroethylene levels above the no significant risk level (NSRL). BlueScape used refined analysis methods to show that, given very conservative exposure assumptions that overstate actual risk, exposure values above the NSRL were confined to locations very near the emissions source.  Proposition 65 Litigation and Evaluation Services, Nine Confidential California Companies. Project Manager or Technical Lead in Proposition 65 services ranging from due diligence audits to litigation support. Industries served include battery manufacturers, a glass container manufacturer, a golf club manufacturer, two metal plating facilities, an electronics manufacturing firm, and an airplane parts manufacturing company. Completed community exposure assessments using the SCREEN3 and ISCST models. Evaluated representativeness of assumptions used in litigant’s and plaintiff’s modeling analyses, including meteorological data inputs, monitoring and emissions data referenced, equipment operating schedules, estimates of indoor concentrations of lead relative to outdoor concentrations, and mobility of worker populations.  Litigation Assistance for a Consortium of Confidential Petroleum Refineries, Texas. Assisted several petroleum refineries located in Texas in class action litigation involving fugitive benzene emissions from piping and tanks, and chromium emissions from cooling towers. Performed dispersion modeling for benzene impacts using plaintiff’s input files and ISCST, but revised benzene emissions estimates reflecting more realistic assumptions. Also, used plaintiffs ISCST and FDM input files to evaluate chromium impacts for various particle sizes and surface roughness lengths.  Air Toxics Litigation, Confidential Chemical Manufacturer, Texas. A chemical company in Texas was being sued by nearby residents alleging exposure to benzene and other chemicals was causing various health ailments. Depositions from over 30 litigants were reviewed to develop an exposure parameters database. Used a visual basic-driven system to estimate benzene exposure under various scenarios. The scenarios accounted for population mobility, indoor concentrations relative to outdoor concentrations, and movement of population between various micro-environments.

Papers and Presentations:
 Westbrook, J.A. 2007. How to Calculate and Reduce Fleet Carbon Emissions. Presented at the National Alternative Fuels & Vehicles Conference, Anaheim, California, April.
 Westbrook, J.A. and Sullivan, P.S. 2006. Fugitive Dust Modeling for PM10 Emissions from a Municipal Waste Landfill. Presented at the “Guideline on Air Quality Models: Applications and FLAG Developments — An A&WMA Specialty Conference”, Denver, Colorado, April.
 Westbrook, J.A. and Dillingham, J. 2005. Rule 1401 Health Risk Assessment Course. One-day course presented in Anaheim, California.
 Westbrook, J.A. and Dillingham J. 2005. Air Toxics Health Risk Assessment Featuring HARP Software. Two-day course presented in Anaheim and San Francisco, California.
 Westbrook J.A. 2004. Environmental Justice & DER. Presented at the 2004 California Alliance for Distributed Energy Resources Conference, San Diego, California.
 Tarde J.A. and Westbrook J.A. 2003. Air Quality Modeling in a Highly Industrialized Valley Regime: A Comparison of AERMOD– PRIME to ISCST–PRIME and ISCST3 Results for PM10 Emissions. Presented at the “Guideline on Air Quality Models; the Path Forward” Conference, Mystic, Connecticut, October.
 Westbrook, J.A. 1998. Regional Risk Analysis and CALPUFF: A Review of the Tri-State Initiative. Presented at the 10th Joint Conference on the Applications of Air Pollution Meteorology with the AW&MA, Phoenix, Arizona. 4028

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James A. Westbrook
President
Principal Air Quality Scientist
BlueScape Environmental
 Westbrook, J.A. 1998. Facilitating the Air Permitting Process: Strategic Planning Makes a Difference. Presented at the 1998 Johns Manville Environmental Coordinator’s Conference, Denver, Colorado.  Westbrook, J.A. 1998. Air Dispersion Models: Tools to Assess Impacts from Air Pollution Sources. Natural Resources & Environment New Science and Technology Issue. ABA Section of Natural Resources, Energy, and Environmental Law, Chicago, Illinois, Spring.
 Westbrook J.A., and Tarde J.A., 1995. Dispersion Modeling Techniques for Horizontal, Titled or Capped Emission Sources.

Presented at the 88th Meeting of the Air & Waste Management Association, San Antonio, Texas.  Hayes S.R., and Westbrook J.A. 1992. Analysis of Regulatory Requirements for Petroleum Companies in California. Presented at the DOE California Petroleum Industry Environmental Workshop, Bakersfield, California. 4029
16870 West Bernardo Drive, Suite 400, San Diego, CA 92127 | 858.695.9200 | www.bluescapeinc.com Expertise
Air Quality & Photochemical Models

CALPUFF

CALGRID
CMAQ
CAMx

SCIPUFF

SCICHEM
AERMOD
Business Solutions
Databases
MySQL 5
SQL Server 2005-2014
PostGREQL 9.0
Environmental Engineering
Meteorological Models
WRF
CALMET
RAMS
Software Development
Visual Studio .NET (C# .NET 4.6)
Delphi 7 – BDS 2007
Java (J2SE, J2EE)
Fortran 77/90
C/C+
PHP 5.0
JavaScript, HTML & CSS
JQuery / Bootstrap
Tracer Studies
Industry Focus
Landfill
Lumber Industry
Mining Industry
VisualCheck
Education
Civil Eng, Computer Science
Universidad de Chile
Certifications
MBS, Great Plains Report Writer
Company Background
EnviroModeling Ltda
Lakes Environmental, Inc. Canada
NetCAS Ltda
AeroVironment, Inc. USA
Summary of Experience
Twenty-four (24) years of experience in air quality modeling and in the development of software solutions for environmental engineering companies and the mining industry. Has participated in dozens of environmental engineering projects worldwide, leading modeling teams in every stage of the consulting process. Has designed and developed software for the visualization and analysis of air quality modeling data, emissions inventories and other environmental data sets.

Has extensive experience with air dispersion models, including mastery of the CALPUFF modeling system, SCIPUFF and AERMOD.

Has ample experience with complex photochemical models, including CMAQ, CAMx and SCICHEM. Has designed and developed
software for the visualization and analysis of air dispersion and photochemical models (CALPUFF, SCIPUFF, CAMx),
commercialized and sold all over the world.

Has implemented the Weather Research and Forecast
meteorological model WRF (versions 3.5 and newer) and setup dynamic execution clusters in both Lakes Environmental and EnviroModeling. Extensive knowledge of the execution, processing and visualization of WRF, implementing the model in projects worldwide.

Has led development teams in the implementation of intelligent realtime systems for air pollution management (FETS-RT Web), with deployments in Canada, Mexico, and Australia.

Innate problem solver, able to visualize and solve complex tasks.

Can perform proper design abstraction and the practical implementation of a solution. Understands and utilizes agile development methodologies, in particular cyclical development with prototypes. Practices domain driven design.

Excellent grasp of most high level development languages, including C/C++/C#, Delphi, Java (J2EE), Fortran, amongst others.

Extensive experience with the .NET platform, up to and including .NET 4.6. Comprehensive knowledge of database management and design, having ample experience with SQL Server 2005-2014 and MySQL.

Francisco J. Matamala
Photochemical Modeler, Software Engineer
4030

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Francisco J. Matamala
Photochemical Modeler, Software Engineer
BlueScape Environmental
Select Project Experience:

Select Dispersion Modeling and Tracer Studies
 ARAMCO Saudi Arabia. SF6 tracer studies 2001 – 2002. Validation of the CALPUFF System.  Enami, Chile. SF6 tracer studies at Ventana and Paipote cooper smelters. 2006 – 2007. Validation of CALPUFF system.
 EnviroModeling Ltda., IT Manager and Senior Partner, Chile. Main IT support for all air quality consulting projects, such as lead engineer and project manager for WRF execution cluster. Lead developer of CAMx modeling engineer and CalDESK and other software products. Provided main IT support for all air quality consulting projects.
 Lakes Environmental, Inc., Senior Developer, Canada. Implemented a distributed graphical rendering engine. Lead team member built to support air quality software packages, such as FETS-RT that was a three (3) year project. Lead developer and project manager for WRF distributed execution cluster. Team member for Kuwait AQMIS project for UNDP. Provided developer support for CALPUFF View.  WoodTech S.A., Independent Consultant, Las Condes, Las Condes. Developed main infrastructure and core components of the Logmeter 4000 system.
 PROTAB S.A., Independent Consultant, Spain. Developed multiple business solutions modules.  NetCAS Ltda, IT Manager, Designed and implemented business solutions projects for ERPs for Great Plains, Solomon, J.D. Edwards and PeopleSoft). Course Instructor (Crystal Reports and Report Writer of Microsoft Dynamics)
Software Products
 CALPUFF Online Modeling System. Development of a CALPUFF Online Modeling System (COS) to evaluate in real time the air quality due to odor emission from land fields and similar process. The COS software runs using local meteorology as well as meteorology generated from WRF runs.  CalDESK. Software for the visualization and analysis of the CALPUFF Modeling System (CALMET/CALPUFF/CALGRID). Sold internationally since 1997, with hundreds of licenses in over 20 countries. Currently at version 2.98. CalDESK has multiple features, including:
o CALMET, CALPUFF, and CALGRID data visualization with multiple views. Surface views, vertical XZ and YZ slices, vertical profile at a specific point, time series, and a dual slice view provide complete visualization capabilities. Multiple variables can be displayed within a single view, and views can be linked for paired viewing.
o Visualization of CALMET meteorological data and CALPUFF concentrations at the same time.

Wind fields, contours, box fills, streamlines and line graphs are available. o Puff visualization in surface and vertical views, using detailed display options that include specific colors per emission source, transparency based on puff concentrations, and color fills based on puff age.
o Advanced trajectory analysis module, which allows the users to perform complex trajectory analysis, calculating the trajectories for an entire period and allowing the user to visualize specific trajectories with varied display options. Trajectories can be saved for future analysis, independent of the CALMET data file.
 FETS-RT Web (Participated as Lead Developer). Real-time web-based program which can demonstrate the correlation between pollutant emissions from industrial processes and their impact concentrations. FETS-RT Web performs continuous air dispersion modeling runs to project the most 4031

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Francisco J. Matamala
Photochemical Modeler, Software Engineer
BlueScape Environmental
probable outcomes for a collection of user-defined operating scenarios. This involves using forecast meteorology data and real-time data from monitoring stations as input to an air dispersion model which calculates the expected concentrations of a pollutant based on source parameters and emission properties. FETS-RT Web has been implemented in several industrial sites within Canada, Mexico, and Australia.
 Kuwait AQMIS (Participated as Developer): Developed for KEPA under a UNDP contract, the Kuwait AQMIS is web-based platform that uses a Geographic Information System (GIS) style user interface to show where sources as they are physically located in relationship to other features. It also includes meteorology data to run five (5) years of AERMOD air modeling in order to identify all possible dispersion options. The AQMIS provides KEPA with a nation-wide tool to manage all elements of air quality. The major functions of the AQMIS are to:
o Serve as a National Emissions Inventory Repository and prepare periodical reports on hazardous air pollutants and greenhouse gas emissions.
o Provide air dispersion modeling for all sources and receptors in the country and conduct human health risk assessments based on population exposure. o Establish an emission source permitting and tracking program to issue Permits to Construct and Permits to Operate.
o Collect atmospheric data from mobile and fixed site air monitoring stations, as well as point source data from emissions monitoring systems at major sources. o Track site visits to emission sources and manage outstanding violations.  SisDCA: Air Quality Diagnostics System - Management system for the analysis of the results of air quality simulations. Used to generate meteorological input data for the CALPUFF modeling system and to provide analysis tools for the visualization of air quality data.  CAMxDESK: Visualization and analysis platform for the photochemical model CAMx, versions 3.0 to

5.0. Based on CalDESK development platform.
 GradsDESK: Visualization and analysis platform for GrADS synoptic data files. Based on CalDESK development platform.
 ECOSOFT: Environmental legislation visual database, in a web based platform.  SIMPCA: Air dispersion prediction system, implemented for the copper smelter Fundicion Hernan Videla Lira (ENAMI) in Copiapo, Chile.
 Radomiro Tomic mine of CODELCO Chile.
 RIPIO-Gaby. Similar to RIPIO-RT, developed for the Gaby mine.  MODEEM. Estimation model for metallurgical extraction, developed for the South Mine GeoMetallurgical Plan, CODELCO Chile.  MCA-Teniente. Graphical implementation of the water quality model developed for the El Teniente division of CODELCO Chile. Developed working under engineers of CIMM.  MCA-Andina. Similar to MCA-Teniente, developed for the Andina division of CODELCO Chile. 4032
1 Resumé JAMES WILKINSON
Education
PhD, Engineering and
Public Policy, Carnegie
Mellon University,
Pittsburgh, Pennsylvania,
2004
BS (with honors), Petroleum
Engineering, Montana
College of Mineral Science
and Technology, Butte,
Montana, 1985
AA, Computer Science,
Montana College of Mineral
Science and Technology,
Butte, Montana, 1983
Quotes
“You may not remember, but
during my freshman year
and your junior year (as I
was struggling with Physics
1 {mechanics} from Jack
Youngblood) you were
gracious enough to give me
a 30 minute lesson on
dimensional analysis which
helped me better
understand alternative
methods for checking my
work and applicable to
almost all of my engineering
classes. I have never
forgotten what you did for
me...thank you. I've done
the same thing for many
other engineering students
over the years.”
Ron Layton
11-Jan-2016
“Jim is an excellent balance
of engineer and scientist
with a seemingly unlimited
capacity for solving
complicated problems. He is
fearless and dependable,
and a real pleasure to work
with.”
Stephen Andersen
26-Jan-2016
IT Manager,
Senior Consulting Engineer,
Senior Software Developer,
Dr. Wilkinson possesses knowledge and experience in applied research and directly related technical experience in disciplines spanning the physical sciences, geophysical sciences, mathematics, and computational sciences. His experience includes but is not limited to managing large scale, multidisciplinary applied research projects with multiple stakeholders and sponsors, such as urban- to continental-scale air quality (CAMx, CMAQ) and meteorological (WRF, MM5) modeling studies. Jim also has experience in emissions modeling system design, development, and application (e.g., SMOKE, CONCEPT, and EMS-95); micro- to global-scale environmental data base management system design and deployment; design, development, and application of computational mathematical models of the environment (e.g., URM and BIOME).

Dr. Wilkinson has experience in the application of Failure Mode and Effects Analysis (FMEA), Threat and Hazard Identification and Risk Analysis (THIRA), and Hazard Consequence Modeling and Risk Assessment. He has applied the Process Hazard Analysis Software Tool (PHAST) to assess hazards and risks associated with gaseous and liquid hydrocarbon pipelines, carbon dioxide pipelines, and hazardous chemicals storage tanks. He has used these techniques to prepare siting plans for Liquefied Natural Gas (LNG) facilities and acrylonitrile production facilities.

Dr. Wilkinson is an experienced software developer having designed, developed, tested, deployed, and maintained systems across Windows and Linux platforms.

He has expertise across the LAMP and WAMP environments working in frameworks such as LINQ, .NET, and Entity Framework with the C#, PHP, and ReactJS languages.

Jim has formulated public policy perspectives associated with the technical and scientific findings of basic and applied research, and taught at the university level.

Employment History
Organic Materials Review Institute (OMRI) – Eugene, Oregon IT Manager (Mar-2020 to Present)
Senior Software Developer (Jul-2016 to Mar-2020)
Staff mentoring and project supervision. Business development, cost modelling, personal resource deployment and load balancing, project management, technical leader for air quality modeling and meteorological modeling.

Terra-Technologies. – Eugene, Oregon
Senior Consultant (Nov-2015 to Present)
Staff mentoring and project supervision. Business development, cost modelling, personal resource deployment and load balancing, project management, technical leader for air quality modeling and meteorological modeling. 4033
2 Resumé JAMES WILKINSON
Golder Associates Inc. – Portland, Oregon
Senior Consultant (Aug-2013 to Nov-2015)
Staff mentoring and project supervision. Business development, cost modelling, personal resource deployment and load balancing, project management, technical leader for air quality modeling, process safety management, risk assessment, and hazard consequence studies.

Alpine Geophysics, LLC – Eugene, Oregon
Senior Engineer and Managing Partner (1993 to 2013)
Business development, project management, and technical leader providing guidance on air quality modeling studies. Cost modelling and personal resource deployment.

Radian Corporation – Sacramento, California
Senior Engineer (1992 to 1993)
Project and technical leader who provided guidance on air quality modeling studies.

Radian Corporation – Sacramento, California
Staff Engineer and Computer Scientist/Engineer (1988 to 1992) Project technical leader who provided environmental engineering and air quality modeling services. Provided database and systems development services for environmental engineers.

ARCO Alaska, Inc. – Anchorage, Alaska
Petroleum Engineer (1985 to 1986)
Drilling engineer and operations engineer supporting production drilling and facilities operations in Prudhoe Bay, Kuparuk River, and Cook Inlet fields.

Montana Tech Computer Services – Butte, Montana
Programmer II (1984 to 1985)
Provided support for campus-wide computer services.

ARCO Alaska, Inc. – Anchorage, Alaska
Petroleum Engineer (1984)
Provided reservoir modeling support on Cray supercomputer.

Montana Tech, Environmental Engineering Department – Butte, Montana
Teaching Assistant (1982 to 1984)
Provided necessary support to a professor to teach environmental engineering to undergraduates. Ran computer laboratory for various classes. 4034
3 Resumé JAMES WILKINSON
PROJECT EXPERIENCE – METEOROLOGICAL & AIR QUALITY MODELLING

WRF, SMOKE, CMAQ
Modelling for the City
of Hamilton
Hamilton, Ontario
Dr. Wilkinson developed model inputs for WRF, SMOKE, and CMAQ to support comprehensive air quality modelling over Hamilton for 2012. He prepared data sets for nested 36-12-4-1.33 km domains centered over Hamilton with 30 vertical levels extending to 100 mb. Dr. Wilkinson conducted model performance evaluations for WRF and CMAQ to determine their skill at reproducing historical conditions. Pollutants considered in this assessment included B(a)P, formaldehyde, cadmium, ammonia, mercury, and chromium among others.

Steamboat Springs
Colorado
Estimated the impacts that planned improvements to the Steamboat Resort will have on air quality. Using MOVES2014a and NONROAD2008 to estimate the emissions (volatile organic compounds [VOCs], nitrogen oxides [NOx], sulfur dioxide [SO2], particulate matter [PM], and greenhouse gases [GHG]) from diesel and gasoline-fueled vehicles used during construction and operation.

Impacts were estimated based on activities occurring during the summer of 2017.

Acid Mist Modelling
with AERMOD
Glencore --Mopani
Copper Mines;
Zambia, Africa
Dr. Wilkinson prepared analyzed observational data for sulfuric acid concentrations and meteorology in order to prepare inputs to the MAKEMET and AERMOD models. MAKMET was used to estimate meteorological parameters necessary to drive AERMOD in its screening mode. AERMOD was used in screening mode to predict acid concentrations from an acid mist system used at the copper heap leach pad. The purpose of the modelling was to determine if acid concentrations are predicted to exceed established WHO levels at any time during the year. The team discovered that the proposed location of the heap leach pad was such that acid concentrations were likely to exceed regulatory levels near established neighborhoods. Based on our efforts, we offered alternative nearby locations for the proposed heap leach pad such that during its operation, there were predicted to be no exceedances of the WHO levels.

WRF Modelling for the
City of Toronto
Toronto, Ontario
Dr. Wilkinson developed WRF model inputs for the initialization, 3D analysis nudging, and observational nudging fields based on data from the NCEP North American Regional Reanalysis data sets maintained at UCAR and routine monitoring data maintained at NOAA National Climatic Data Centre. He prepared WRF data sets for nested 36-12-4 km domains centered over Toronto with 30 vertical levels extending to 50 mb. WRF was run for each hour of 2012 to predict two- and three-dimensional prognostic meteorological fields including wind speed, wind direction, temperature, solar radiation, and mixing ratio. Dr.

Wilkinson conducted a model performance evaluation to determine WRF’s skill at reproducing historical meteorological conditions. Finally, he converted WRF outputs for use in CALPUFF simulations.
4035
4 Resumé JAMES WILKINSON
WRF Modelling over
the Chukchi Sea;
ConocoPhillips
Chukchi Sea
Using the Weather Research and Forecasting (WRF) system, prognostic meteorological simulations for period July through November, 2007, 2008, and 2009 were constructed and run for a 36-12-04 km nested domain structure, with a 37 layer vertical structure extending to 50 mb, for the Chukchi Sea off the coast of northwest Alaska. NCEP GFS 0.5 degree model data was used for WRF initialization and analysis nudging. NCEP GFS data were also used for sea ice and sea surface temperatures updated every six hours. Model performance evaluation (MPE) was conducted with MAPS and METSTAT at both the surface and aloft using available observations from routine monitoring. Model performance for mixing ratio, temperature, wind speed, and wind direction met or exceeded performance metrics. Finally, WRF outputs were converted for use in CALPUFF.

Eldora Mountain
Resort Expansion
Colorado
Examined the impacts that a planned expansion to the Eldora Mountain Ski Resort will have on air quality. Using MOVES2010b and NONROAD2008 to estimate the emissions (VOCs, NOx, SO2, PM, and GHG) from diesel and gasoline-fueled vehicles used in the construction and operation phases of the project. The planned expansion is for the period 2015 through 2019, with peak operation impacts occurring in 2023.

Houston 8-Hour Dual
Ozone Phenomena
Texas
Currently involved in research efforts focused on determining the conditions that led to the 8-hour dual-ozone formation phenomena in the Houston-GalvestonBrazoria (HGB) region of Texas. Developing and applying ensemble air quality modeling techniques that can further bound the range of modeled 8-hour ozone.

Developing and applying 8-hour modeled ozone bias correction techniques.

Ethanol Fuels Study;
CRC
Illinois, Michigan, and
Georgia
Constructing a turn-key system that integrates the SMOKE emissions modeling platform with the CAMx air quality modeling for the Coordinating Research Council (CRC) to support its study of the impacts of alternative ethanol-blended fuels on air quality in multiple urban regions in the United States. Leading the effort to ingest multiple link-based on-road mobile source networks into SMOKE and apply on-road mobile source emissions factors from the MOVES2010b motor vehicle emissions simulator that have been adjusted to account for effects on emissions factors due to alternative ethanol-blended fuels. An additional component to this effort is likely to be an assessment of the effects of meteorology that is “flexi-nested” from 12 kilometers to 4 kilometers in CAMx, contrasted to a meteorology derived from first principles at 4-kilometer resolution using MM5.
4036
5 Resumé JAMES WILKINSON
San Joaquin Valley
WOE
California
Developed methods that can be used in weight of evidence (WOE) analyses to support State Implementation Plans (SIPs). One method developed concerns determining the plausible range of future year design values for 8-hour ozone in the Central California Ozone Study (CCOS). Analyzed air quality model outputs to determine the range of ozone outcomes in both the base year and future year.

Also examined the outputs to determine if grid cells selected for use in the relative response factor (RRF) are inappropriate for more than one monitor.

Another method examined concerns the longitudinal trends that are being observed between ambient measurements of ozone and its precursors. Further, this trends analysis was extended to determine how the trends in the planning inventories are tracking with precursor trends.

Agricultural Emissions
Tool (AgTool)
California
Developed a geographic information systems (GIS)-based platform in PostgreSQL-PostGIS to store and manipulate agricultural emissions. Developed methods to ingest agricultural surrogate data that can be used to spatially allocate emissions to grid cells. Further, provided a means to better temporalize agricultural emissions. This system was developed in tandem with an agricultural emissions forecasting system.

United States On-road
Mobile Source
Emissions Estimates
United States
Used MOVES2010a to develop hourly on-road mobile source emissions estimates for the years 2008, 2009, 2010, and 2020 for each county in the United States for each month of the years and for representative weekends and weekdays. Used the MOVES/SMOKE Interface Tool to facilitate the process of using MOVES to create on-road mobile source emissions estimates for use in air quality modeling. The MOVES/SMOKE Interface Tool is comprised of scripts that automate the proper use of the Emission Rate calculations. The SMOKEMOVES tool provides three major functions: (1) Meteorological data preprocessor; (2) MOVES2010 model processor; and (3) SMOKE model processor. Modified the meteorological data preprocessor (MET4MOVES) to prepare month-specific, hourly profiles of temperature and humidity that are suitable for direct input to MOVES. Built custom SQL scripts to better facilitate the loading of data directly into the MOVES databases.

Areas of Influence;
Various Clients
Various
Conducts research in the areas of emissions uncertainty and economic-based incentives (e.g., market trading programs) to control regional emissions. Current primary research project is concerned with determining the geographic extent of areas whose sources may contribute to air quality exceedances. These areas are known as Areas of Influence (AOI). Also interested in elucidating the impacts that uncertainty in biogenic emissions estimates have on urban- and regionalscale emissions control strategies. 4037
6 Resumé JAMES WILKINSON
Modeling On-Road
Mobile Source
Emissions Estimates
for SESARM
Georgia
Used MOVES2010a to develop on-road mobile source emissions factors that can be used to estimate emissions for 10 states that cover the southeast United States. Modeled the year 2007 for winter and summer fuels for 40 representative counties in the 10 southeast states. Used the MOVES/SMOKE Interface Tool to facilitate the process of using MOVES to create on-road mobile source emissions estimates for use in air quality modeling. The MOVES/SMOKE Interface Tool is comprised of scripts that automate the proper use of the Emission Rate calculations. The SMOKE-MOVES tool provides three major functions: (1) Meteorological data preprocessor; (2) MOVES2010 model processor; and (3) SMOKE model processor. The Meteorological data preprocessor (MET4MOVES) prepares spatially and temporally averaged temperatures and relative humidity data to set up the meteorological input conditions for MOVES2010 and SMOKE using the Meteorology-Chemistry Interface Processor (MCIP) output files. The MOVES2010 model processor creates data input files (i.e., runspec) for use in MOVES2010 that specifies the characteristics of the particular scenario to be modeled, and it reformats the resulting MOVES2010 emission rates lookup tables that are suitable for input to SMOKE. The SMOKE postprocessor (MOVESMRG) estimates emissions from on-road mobile sources based on MOVES2010-based emission rate lookup tables and meteorology data from MET4MOVES.

Review of the Houston
8-hour Ozone SIP;
TCEQ
Texas
Provided in-depth analyses of emissions, meteorological, and air quality modeling results developed by the Texas Commission on Environmental Quality (TCEQ) for use in preparing the 8-hour ozone State Implementation Plan (SIP).

Six multi-day episodes in 2005, 2006, and 2018 were modeled. Conducted CAMx model performance evaluation of the Houston region to further understand the meteorological phenomena that led to elevated ozone levels. Conducted independent CAMx modeling and sensitivity analyses through the use of OSAT to elucidate the emissions source sectors and source regions that contribute to high ozone in the Houston region. Developed independent sets of stationary, area, non-road, on-road, and biogenic source emissions files suitable for use in SMOKE to provide parallel, corroborative, and alternative base case and future year episodic emissions development capabilities for use by the 8-hour Coalition and the US Environmental Protection Agency (EPA). Produced alternative analyses for the ozone modeled attainment demonstration based on the flexibility that is afforded in EPA’s guidance. Performed extensive analysis of the ambient air quality record to examine trends in the regulatory design values (DV) at all monitors in the Houston region. Studied and evaluated the performance of the monitor-specific baseline design values (DVb), relative response factors (RRFs), and future year design values (DVf) with multiple tools including MATS. Models that are being used in this effort include CAMx, CMAQ, MM5, SMOKE, EPS3, MEGAN, BEIS3, GloBEIS, NONROAD, MOBILE6, and MOVES2010a. 4038
7 Resumé JAMES WILKINSON
Sacramento Air Quality
Modeling Study
California
Provided emissions, air quality, and meteorological modeling capabilities to determine impacts to the Sacramento urban heat island, biogenic emissions, and air quality as a result of alternative tree planting scenarios in the Sacramento urban area. The goal of this effort was to quantify the State Implementation Plan (SIP) credit that can be taken for planting new urban forests in Sacramento or exchanging lower-emitting tree species for existing high-emitting tree species.

Used urbanized-MM5 (uMM5) to quantify localized meteorological changes that may occur due to landuse/landcover changes as the results of tree planting scenarios. Propagated the meteorological predictions through BEIS3 and MEGAN to estimate changes in biogenic emissions. Finally, used CAMx to determine the outcome on air quality, in particular ozone, due to changes as a result of various tree planting scenarios.

CAMx Google Earth
Illinois
Developed a software tool to display Comprehensive Air Quality Model with extensions (CAMx) predictions in Google Earth. The software tool allows a user to select the time period and chemicals to display from a CAMx output file, and prepares a KMZ file containing PNG graphics and a KML file. The tool is based on Open Source and freeware tools PostgreSQL, PostGIS, and perl. Recently extended the tool to display stationary source daily emissions as estimated by SMOKE. Currently extending the tool to display air quality observations.

Enhancements to the
California ITN
California
Developed version three of the Integrated Transportation Network (ITN) for the California Air Resource Board. The ITN was constructed using Open Source and freeware tools PostgerSQL, PostGIS, and perl. The ITN was based on the travel demand modeling results from more than 20 metropolitan planning organizations (MPOs). The ITN was constructed to function within the CONCEPT framework, but can also operate as a stand-alone system. The ITN utilized on-road mobile source emissions factors that were extracted from EMFAC2007. The extraction of emissions factors from EMFAC2007 was automated with the Windows-based tool AutoIt. The goal of this effort was to construct a unified travel demand modeling link-based network with associated travel analysis zone (TAZ) data for the state of California that can be used for such purposes as environmental justice litigation, conformity planning, development of on-road mobile source emissions estimates, and State Implementation Plan (SIP)-level air quality modeling.
4039
8 Resumé JAMES WILKINSON
Columbia River Gorge
Air Quality Modeling
Study
Oregon
Worked on a study of historical regional haze in the Columbia River Gorge. The study focused on assigning source culpability to haze and visibility degradation in the Columbia River Gorge. Developed CAMx-ready emissions estimates using SMOKE for winter and summer episodes in 2005 and 2018. Used SMOKE to develop CAMx-ready emissions estimates for such sources as confined animal feeding operations, commercial marine vessels, railroad operations, dairy operations, pulping operations, lumber mills, and electric generating units (EGUs)]. Prepared hourly estimates of sulphur dioxide (SO2) emissions from Mt.

St. Helens. Estimated hourly emissions of carbon monoxide (CO), nitrogen oxides (NOx), volatile organic compounds (VOC), particulate matter (PM) 2.5, PM-coarse, and ammonia (NH3) from controlled burns and wildfires. Prepared hourly estimates of emissions from EGUs and pulping facilities based on data extracted from the US Environmental Protection Agency (EPA) continuous emissions monitoring (CEM) archive. The emissions estimates were aggregated into multiple categories for use in the Particulate Matter Source Apportionment Technology (PSAT) tool of the CAMx air quality model. Developed an Excel workbook with associated Visual Basic macros that allows a user to investigate emissions by source category and source region (further extending the Ozone and Particulate Source Apportionment Technology (OSAT/PSAT) capabilities of CAMx. The Excel workbook with Visual Basic macros takes output from the SMOKE/SMKREPORT tool as input to the spreadsheet. Further, the Excel workbook has macros that allow the user to prepare summary graphics of the emissions estimates. Finally, modeled air quality using CAMx for 2018 to determine if air quality objectives for regional haze and visibility can be met.

Control Strategy Tool
(CoST); EPA
North Carolina
Worked with the US Environmental Protection Agency (EPA) to develop the Control Strategy Tool (CoST). CoST is EPA’s vision to replace AirControlNET.

CoST is used to develop overall program costs associated with the selection of control measures and control programs that may be implemented to control emissions to achieve future year air quality objectives. Collected control measure and control program data and costs for criteria pollutants, air toxics, and greenhouse gases (GHGs). Provided analyses to determine the applicability of these data to sources in the US, as some of these data are being derived from programs outside the US.

Integration of the
Model of Emissions
and Gases from Nature
(MEGAN) into
ConCEPT
Illinois
Worked with the Lake Michigan Air Directors Consortium (LADCo) to update the Consolidated Community Emissions Processing Tool (ConCEPT) to include the biogenic emissions estimates model MEGAN. MEGAN (the Model for the Emissions of Gases and Aerosols from Nature) is the state-of-the-science model to estimate biogenic emissions. MEGAN is currently designed in MS-Access VBA and MS-Excel VBA. Lead analyst and programmer converting MEGAN to run under the PostgreSQL database. Performed the tasks to improve throughput of MEGAN under the SQL framework, as well as the throughput of the CONCEPT meteorological data processor. Also guided the effort to verify the MEGAN emissions estimates against the BEIS3 emissions estimates. 4040
9 Resumé JAMES WILKINSON
Retrospective Analysis
of Trending Air Quality
and Emissions
Inventories in
California
California
Prepared spatially and temporally resolved emissions estimates from stationary, area, and on-road mobile sources for a period spanning 1990 through 2004.

These emissions estimates were compared to air quality measurements made over the same period to determine if trends in the air quality matched trends in the emissions inventory. One goal of this effort was to determine where deficiencies existed in the emissions inventory. Currently working with the California Air Resources Board (ARB) to determine trends of nitrogen oxides (NOx) and volatile organic compound (VOC) emissions versus ozone in Central California from 1990 through 2004. Comparisons of emission trends with ambient air quality trends at an air-basin level of aggregation may obscure important local changes, but the large-scale comparisons serve to illustrate why the rates of progress in improving ozone levels may be of concern in some areas. For example, in both the San Joaquin Valley (SJV) and South Coast Air Basin (SoCAB) areas, emissions of carbon monoxide (CO) declined by approximately 60 percent between 1990 and the present, and maximum ambient concentrations of CO declined by about the same amount (60 percent) in the two areas. In both areas, substantial (albeit somewhat different) decreases occurred in the emissions of both nitrogen oxides (NOx) and reactive organic gases (ROG). In both areas, ambient nitrogen dioxide (NO2) levels declined by approximately the same magnitude as did NOx emissions (35 to 40 percent).

Yet, maximum 1-hour and 8-hour ozone levels declined appreciably in the SoCAB while remaining virtually unchanged in the SJV. Providing emissions support for this study, preparing emissions data for use in regression and trends analyses.

Central Regional Air
Planning Area of
Influence; CENRAP
Oklahoma
Prepared Area of Influence (AOI) diagrams and estimated emissions reductions needed to attain visibility objectives by 2018 for 10 Central Regional Air Planning Association (CENRAP) Class I areas and 12 near-CENRAP Class I areas.

Developed AOIs for the 22 Class I areas by synthesizing the following data:

Residence Time Difference plots; Probability of Regional Source Contribution to Haze (PORSCH) plots; and Tagged Species Source Apportionment (TSSA) results. The results of this effort were converted to geocoded coverages and maps using ARC/Info. Estimated sensitivity coefficients (for example, a sulphur dioxide [SO2] reduced value of -0.001 µg/m3 of sulfate per ton per day means that for each ton of SO2 reduced within an AOI, the Class I area will exhibit a decrease of 0.001 µg/m3 in sulfate concentration) by synthesizing the results of numerous brute force and DDM-3D air quality model runs. These data were in turn used to estimate the annualized costs to achieve emissions reductions necessary to meet future year air quality objectives in each of the Class I areas.

Consolidated
Community Emissions
Processing Tool
(ConCEPT)
Illinois
Helped design and implement the open source emissions modeling system Consolidated Community Emissions Processing Tool (CONCEPT). CONCEPT is a PostgreSQL-based system whose goal is to house all data related to the emissions modeling process under a single database. Geographic information systems (GIS)-related functions are managed within the same PostgreSQL database using the PostGIS plugin.
4041
10 Resumé JAMES WILKINSON
California ITN;
California ARB
California
Commissioned by the California Air Resources Board (ARB) to develop version two of the California Integrated Transportation Network (ITN). Recently completed the first version of the ITN using data from transportation demand models (TDMs) from 15 California metropolitan planning organizations (MPOs).

In version two of the ITN, TDM data from approximately 20 MPOs were used.

The ITN is a seamless representation of the on-road mobile source transportation network for all of California. On behalf of the ARB, used the ITN, in conjunction with the on-road emissions factors model EMFAC2002 and the Direct Travel Impact Model (DTIM), to estimate on-road mobile source emissions for a variety of multi-day air quality modeling episodes spanning the years 2000 through 2010. An interesting component of this effort was the development of a transportation gravity model in Excel VBA that can be used to estimate commercial truck trips and their distribution on the ITN. 1997 Southern
California Ozone Study
California
In collaborative research with Dr. Robert Bornstein at San Jose State University, used MM5 to develop meteorological fields for the 1997 Southern California Ozone Study (SCOS-97). Developed the initialization fields and the fourdimensional data assimilation (FDDA) fields for use in MM5 for the 4-7 August 1997 modeling period. Developed alternative inputs to MM5 for this period (e.g., updated landuse) in an effort to garner better performance. Responsible for all aspects of model performance evaluation. Ultimately, used the MM5 outputs to prepare meteorological inputs to the CAMx air quality model.

Texas Biogenic
Emissions Estimates
Texas
Completed work to estimate emissions for four ozone episodes in the Houston, Texas area using GloBEIS. Estimated emissions for 36-kilometer, 12-kilometer, and 4-kilometer grid structures. Prepared all meteorological inputs (base temperatures, antecedent temperatures, Palmer Drought Index, phased array radar [PAR], wind speed, and mixing ratio) based on predictions from MM5. The episodes ran from 8 to 15 days in duration. GloBEIS outputs were speciated using CB4 and reformatted for use in the CAMx and CMAQ chemical transport models.

Biogenic Emissions in
Missouri and Kansas;
Missouri DNR
Missouri
Prepared estimates of biogenic emissions for the Missouri Department of Natural Resources (DNR) for 36-kilometer, 12-kilometer, and 4-kilometer grid structures that center on St Louis, Missouri. Used SMOKE/BEIS to model the emissions for three multi-day episodes. Prepared all input files to SMOKE/BEIS. The landuse data were derived from version three of the Biogenic Emissions Landuse Database (BELD3). Temperature and phased array radar [PAR] data were based on MM5 predictions.
4042
11 Resumé JAMES WILKINSON
San Francisco Bay
Area Air Quality
Modeling Study;
BAAQMD
California
Completed an emissions modeling study for the Bay Area Air Quality Management District (BAAQMD). Estimated emissions for multi-day ozone episodes for base case years in July 1999 and July 2000. Estimated emissions for future years 2002, 2005, 2007, and 2010. Estimated emissions for area sources, stationary sources, non-road mobile sources, on-road mobile source, commercial marine shipping, and biogenics for an airshed that encompassed most of California. The emissions estimates developed by him were used to model base year air quality levels over California with particular emphasis on model performance over the San Francisco Bay Area. Further, the future year emissions estimates will be used in on-going air quality modeling efforts to develop emissions control strategies for mitigation of the 1-hour and 8-hour ozone National Ambient Air Quality Standards. In an effort to understand where potential deficiencies in the emissions inventory exists, also completed an indepth, comparative analysis of emissions estimates among common source categories between the Central California Ozone Study (CCOS) emissions database and the VISTAS emissions database.

Southern Appalachian
Mountains Initiative
Georgia
Lead emissions and air quality modeler for the Southern Appalachian Mountains Initiative (SAMI) project. The SAMI was a multi-episodic, integrated (i.e., acid deposition, ozone, and visibility/particulate matter), regional-scale air quality modeling study over the eastern United States with particular focus on the southern Appalachian Mountains. The selected episodes were 7 to 15 days in length and span 1990 through 1995, with future years of 2010 and 2040. In the SAMI project, responsible for the preparation of all aspects of the air quality model ready inputs including, but not limited to, emissions estimates (e.g., area source spatial surrogates, mobile source emissions estimates, biogenic emissions estimates, emissions estimates speciation, and data management of the emissions data); conversion of prognostic meteorological modeling results from RAMS and MM5 to URM-ready meteorological fields (including interpolation of the fields from the meteorological grid structure to the air quality modeling grid structure); and diagnosis of boundary and initial air quality conditions. In the SAMI study, designed, implemented, and maintained the geographic information system (GIS)-based components of the emissions and air quality modeling system. As part of the GIS for the SAMI project, maintained coverages of population, housing, urban areas, water, political boundaries (i.e., states, counties, national boundaries, and airsheds), forests, biogenic land cover, railroads, major roadways, water ports, airports, major stationary sources of air pollution, and air quality monitoring stations. The GIS-based data were used to disaggregate county-wide estimates of emissions from minor emissions sources into sub-county areas for the purposes of air quality modeling. Used the GISbased data to link and display emissions estimates to sources, air quality observations, and air quality model predictions. Further, responsible for developing inputs to URM so air quality model performance goals for ozone, particulates, and wet/dry acid deposition were met.
4043
12 Resumé JAMES WILKINSON
Peninsula Florida
Ozone Study
Florida
Prepared point source, area source, on-road mobile source, and biogenic emissions estimates for multiple ozone episodes over peninsular Florida.

Developed a wildfire emissions estimates model that could estimate temporally and spatially varying wildfire emissions based on fuel types and fuel loads.

Collected day-specific emissions for all electric generating utilities in the air quality modeling domain. Prepared alternative emissions estimates for commercial marine shipping. Point and area source emissions were based on the 1996 NEI, supplemented with emissions data and estimates from the Florida Department of Environmental Protection (DEP). Biogenic emissions were estimated using BEIS, BEIS2, and GloBEIS. Future year inventories were grown using E-GAS derived growth and control factors, supplemented with growth and control factors developed for specific source categories as determined by the Florida Department of Environmental Protection (DEP).

Biogenic Emissions
from Mexico
Mexico
Performed a study to develop the first biogenic emissions inventory for northern Mexico. The new biogenic emissions inventory was integrated with existing anthropogenic emissions in an effort to better understand transboundary air pollution along the Mexico-United States border. The biogenic emissions inventory was developed from Mexican-supplied ground-truthed agricultural and forest coverage data, as well as satellite-based land use data. The data were compiled for use in BEIS2.

Breton Island Air
Monitoring Program
Louisiana
Helped to complete a design of an air quality and meteorological monitoring network for the Breton Island National Wildlife Refuge Class I Area, located in the Gulf of Mexico just east of New Orleans, Louisiana. Designed the geographic information system (GIS) emissions, air quality, and meteorological database management system that will be used to house these data when the Breton Island Air Monitoring Program (BAMP) field program is implemented.

NH3 from
Concentrated Animal
Feeding Operations
(CAFOs) in San
Joaquin Valley
California
Completed a study to evaluate and improve existing ammonia emissions estimate techniques for use in the San Joaquin Valley of California. This study included a comprehensive literature review that focused on the following:
methods that were used to estimate ammonia emissions; the development of a new ammonia emissions inventory for the study domain; the implementation of a pilot field study to improve upon methods to estimate ammonia emissions from dairy livestock, soils, and wastewater treatment plants; and the development of methods to estimate quantitative values of uncertainty about the ammonia emissions estimates. Developed a statistical model to estimate ammonia emissions from dairies.

Pittsburgh-Beaver
Valley 1-hour Ozone
SIP
Pennsylvania
Helped to complete the technical analysis for the State Implementation Plan (SIP) for the Pittsburgh-Beaver Valley 1-hour ozone non-attainment area. The technical analysis included the emissions modeling, air quality modeling, and attainment demonstration work needed for the SIP.
4044
13 Resumé JAMES WILKINSON
Study of Particulates
and Health in Atlanta
Georgia
Completed work to determine the association of airborne pollutants to increased visits of children with respiratory problems to Atlanta-area emergency rooms.

Using the geospatial statistical method known as kreiging, prepared maps of temporally and spatially disaggregated air quality measurements over greater Atlanta, Georgia. Coupled these data with information derived from emergency room visits to Atlanta-area hospitals to determine that there was a statistically significant increase in respiratory-associated visits to the emergency room in the presence of elevated ozone levels.

Horizontal Advection
Solver
Pennsylvania
Involved in examining the impacts of the horizontal advection solver in threedimensional air quality models on emissions control strategies. In that study, responsible for running the UAM-IV and CIT models for established air quality modeling studies, and statistical analysis of the air quality modeling outputs. The statistical analyses were conducted to isolate and quantify the numerical interference due to various horizontal advection solvers that were introduced into the UAM and CIT air quality models.

OTAG
NE United States
Involved in the Ozone Transport and Assessment Group's (OTAG) efforts to examine regional-scale air quality in the eastern United States. Primary engineer tasked with preparing emissions modeling inputs (e.g., area source spatial surrogates, on-road mobile source transportation network, and geographic information systems [GIS]-based EMS-95 foundation data) for the Emissions Modeling System version 1995 (EMS-95). Provided technical support to the OTAG participants in the application of EMS-95 to the eastern United States and southern Canada.

GEMAP
California
Instrumental in the design and development of the Geocoded Emissions Modeling and Projections System (GEMAP) which was the predecessor of EMS95. Prepared design documents for the overall architecture of the system, as well as for the point and area source models. Developed both SAS and ARC/Info code for the point source, area source, and on-road mobile source models. Applied GEMAP to develop emissions estimates for the SARMAP and LMOS air quality modeling studies.

Houston 8-hour Ozone
Coalition
Texas
Currently involved in research efforts focused on determining the conditions that led to the 8-hour dual-ozone formation phenomena in the Houston-GalvestonBrazoria (HGB) region of Texas. Developing and applying ensemble air quality modeling techniques that can further bound the range of modeled 8-hour ozone.

Developing and applying 8-hour modeled ozone bias correction techniques.

These methods and techniques, which are based on applied research that are taken from such forecasting efforts as hurricane and tsunami tracking, are directed at developing control scenarios that better address the unique dual ozone formation conditions that arise in the HGB 8-hour ozone non-attainment region.
4045
14 Resumé JAMES WILKINSON
PROJECT EXPERIENCE – HAZARD CONSEQUENCE ASSESSMENT
UEO DTI;
Momentum, LLC
Leesville, Ohio
15 MMscfd of natural gas is conveyed along a 4 mile long, 15 inch diameter underground pipeline operating at 525 psi and 38°F. The purpose of the study was to determine if high consequence areas (HCAs) (i.e., sensitive ecosystems, drinking water supply, or populated areas) were impacted due various leak and rupture scenarios that result in natural gas being released. Using PHAST, models of hazardous events were constructed. Consequences that were modelled include pooling-evaporation and 10% lower explosive level assessment that might result in an explosion or fire. Model results were overlaid on a geo-referenced aerial photograph to graphical show the areal extent of impacts to HCAs.

Facility Hazard
Assessment Review;
National Renewable
Energy Laboratory
Golden, Colorado
Conducted hazard consequence modelling for scenarios involving accidental releases of arsine, silane, ammonia, dodecane, and hydrogen. Using PHAST, estimated hazard distances to IDLH-AEGL-ERPG toxic thresholds, overpressure threshold (1 psi) from explosions, and thermal threshold (4 kW·m-2) from fires.

Estimated thermal intensity for grassland wildfire to determine if ethanol storage facility was at risk. Determined likely impacts to worker and general public health and safety. Conducted asphyxiation assessment due to liquid nitrogen spill.

Conducted asphyxiation assessment due to carbon monoxide release. Conducted dropped load risk assessment due to excessive crane load.

Aqueous NH3 Storage
Tank Consequence &
Risk Assessment;
TransAlta Canada
Edmonton, Alberta
Aqueous ammonia is transported, stored, and utilized at a gas-fired power plant.

Accidental release scenarios were developed including the rupture of the delivery line, the rupture of the transfer pipe, and a ten minute release. Five years of meteorological data were analyzed to determine the joint probability of the occurrences of wind speed, wind direction, and atmospheric stability. The Process Hazard Analysis Software Tool (PHAST) was used to estimate the hazard distance for each hazard scenario. Maximum concentration plume footprints were estimated based on IDLH, ERPG-1, ERPG-2, ERPG-3, AEGL-1, AEGL-2, and AEGL-3 values. The likelihood of these events was estimated based on historical accidental release data. The 1-in-1,000,000 individual risk of fatality was estimated should an event occur. The number of residences was estimated to be impacted by a hazardous event. The information was used to develop a Risk Management Plan, including shelter-in-place and emergency evacuation procedures, for mitigation and communication.

Anhydrous NH3
Storage Tank
Consequence & Risk
Assessment;
TransAlta Canada
Edmonton, Alberta
Liquid anhydrous ammonia is transported, stored, and utilized at a gas-fired power plant. Accidental release scenarios were developed including the rupture of the delivery line, the rupture of the transfer pipe, activation of the relief valve, and a ten minute release. Five years of meteorological data were analyzed to determine the joint probability of the occurrences of wind speed, wind direction, and atmospheric stability, which impact the transport and dispersion of ammonia released to the atmosphere. The consequences of these hazard events were modelled using PHAST, and the hazard distance estimated for each hazard scenario. The likelihood of these events was estimated based on historical hazard events.

Overall risk was estimated as number of chances in one million that event would occur. Maximum concentration plume footprints were estimated based on IDLH and ERPG-2 values, and the number of residences was estimated to be impacted by the hazardous event. The information was used to develop a Risk Management Plan for mitigation and communication purposes.
4046
15 Resumé JAMES WILKINSON
Diesel & Bitumen
Pipelines Emergency
Release and Odour
Analyses;
TransCanada Pipelines
Limited (TransCanada)
Ft. McKay, Alberta
Conducted an air quality modelling assessment using PHAST of odour effects resulting from a potential accidental leak from the proposed pipelines near the Hamlet of Fort MacKay, Alberta. The project included two buried pipelines (a Diluent Pipeline and a Bitumen Pipeline) that are located together on the same right-of-way. The goal of the air quality modelling assessment was to address concerns over possible odour effects and exceedances of Alberta Ambient Air Quality Objectives for H2S, BTX, and mercaptans from an accidental release of product. Accidental release events considered were three sizes of corrosion leaks, and a full rupture of a pipeline by an impact such as a backhoe strike. Leak sizes assumed were 20 mm, 50 mm, and 80 mm in diameter. A full rupture was assumed to last for 10 minutes before the line fully emptied and was shut down.

These events are considered worst case, and possible leaks or ruptures may not be as large or continue for as long as the hypothetical scenarios.

UEO M3 HCA;
M3 Midstream, LLC
Scio, Ohio
LNG, ethane, and propane are being transported via three separate pipelines (both above and below ground). The purpose of the study is to determine the consequences of a pipeline rupture due to a strike from a backhoe during uncovering and to determine if there adverse impacts to populated areas. Using PHAST, a model of the hazardous event has been constructed. Consequences that have been modelled include the following: pooling and evaporation; toxic endpoint (IDLH) assessment; jet-fire assessment; and explosion assessment.

Model results have been overlaid on a geo-referenced aerial photograph to graphical show the areal extent of impacts to populated areas.

Propane-Air Plant &
Storage Facility FMEA;
Puget Sound Energy
Renton, WA
Conducted a failure mode effects analysis (FMEA) of a Propane-Air Plant and Storage facility. The purpose of the FMEA was to determine if any of the identified potential failure modes could result in significant adverse safety consequences (e.g., bodily injury, death). Each potential failure mode was evaluated based on a qualitative assessment of the probability of failure, the severity of effects, and the likelihood of detection. The scales assigned to the probability of failure, the severity of effects, and the likelihood of detection ranged from one to five with the higher value indicating a more detrimental effect. The product of these three values provided a qualitative means to rate the potential failure modes. Based on the FMEA results, it was determined that no additional quantitative risk analysis would be required for the facility.
4047
16 Resumé JAMES WILKINSON
CO2 Pipeline Rupture
Consequence Analysis;
Anadarko Petroleum
Company
Casper, WY
CO2 is transported via pipeline to wellheads for use in enhanced oil recovery (i.e., injection). Two PHAST modelling scenarios were considered: breach of a 20" pipe operating at approximately 1400 psi; and breach of a 30" pipe at approximately 300 psi (both operating at 40 F). Ambient meteorological conditions modelled included wind speed of 5 mph, D atmospheric stability class, temperature of 14 F, and atmospheric pressure of 11.5 psia. The total weighted average permissible limit (TWA) for CO2 is 5,000 ppm, and the short term exposure limit (STEL) is 30,000 ppm based on NIOSH and OSHA standards. Steady state was achieved almost instantly for both cases when concerning the 30,000 ppm STEL boundary. The higher pressure 20" pipe spread to a distance of approximately 90' and the lower pressure release achieved a distance of 14'. Both scenarios showed high elevations (>60') at this concentration. The 5,000 ppm cloud from the high pressure 20" pipe rupture did not descend to the ground until approximately 135' from the source. Final diffusion to concentrations lower than 5,000 ppm occurred at 522' from the source (at steady-state). The lower pressure 30" pipe rupture reached steady state almost instantly and did not reach ground level before diffusion reduced concentrations below 5,000 ppm. The cloud did reach a distance of approximately 112' (at an elevation of 102') from the source before diffusion.

PROJECT EXPERIENCE – EXPERT TESTIMONY
Garfield County,
Colorado Oil and Gas
Commission
Denver, Colorado
Dr. Wilkinson provided testimony to the Colorado Oil and Gas Commission on behalf of Garfield County who represented the Energy Producing Attainment Counties of Colorado in their efforts to challenge expansion of new emissions controls on oil and gas exploration/production operations outside the Denver 8-hr ozone non-attainment area. Dr. Wilkinson prepared and delivered evidence refuting claims by Environmental Defense Fund (EDF) that expansion of emissions controls state-wide would be beneficial to society. He demonstrated that air quality modelling results were incorrectly interpreted by the EDF, and that an alternative explanation of the modelling results showed virtually no predicted improvement in air quality would occur with the state-wide expansion of changes to Regulation 7; however, the cost to implement such state-wide changes would be large..

Columbia Pacific BioRefinery (CPBR),
Oregon Department of
Environmental Quality
(DEQ)
Portland, Oregon
Dr. Wilkinson conducted research into claims made by plaintiffs that accused CPBR of using incorrect data to determine its facility-wide emissions, which kept the facility under PSD permitting requirements. CPBR is a facility that transloads Bakken crude oil from trains to barges on the Columbia River. He specifically focused on chemical analyses of the crude oil and its vapor, which the plaintiffs claimed were grossly underestimated by CPBR. Based on his research, Dr.

Wilkinson determined that the data used by CPBR to estimate its facility-wide emissions were appropriate.

MOVES2014 Modelling
for Chicago,
Minneapolis, and
Kansas City;
Urban Air Initiative
Dr. Wilkinson prepared inputs to and ran the Motor Vehicle Emissions Simulator (MOVES2014) for the subject cities for 2017 based on default data. Based on new fuel parameter data supplied by the sponsor, he adjusted the MOVES2014 inputs to reflect the alternate fuel parameters that were indicative of real-world fuels. A comparison of the on-road emissions estimates based on the default data and those based on the real-world fuel parameters showed that MOVES2014 may incorrectly account for changes in fuel parameters specifically associated with ethanol-blended fuels above E10.
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17 Resumé JAMES WILKINSON
TransAlta Sundance 7,
Alberta Utilities
Commission
Edmonton, Alberta
Dr. Wilkinson provided testimony on behalf of TransAlta and its application to install an 856 MW natural gas-fired electricity generating facility in the Lake Wabamun area west of Edmonton, Alberta. He delivered testimony to the Alberta Utilities Commission, which is the provincial licensing agency in Alberta.

As approximately 15 to 40 metric tons of ammonia need be stored on site for use in the selective catalytic reduction system, Dr. Wilkinson spoke specifically to the consequences of an accidental release of anhydrous and aqueous ammonia. He spoke specifically to the modelling methods and tools used to estimate the consequences of an accidental release and the probability of such events occurring. He explained the differences in the toxic endpoints (i.e., AEGL, ERPG, and IDLH) that were used to determine hazard distances.

Western Energy
Operators,
Colorado Oil and Gas
Commission
Denver, Colorado
Dr. Wilkinson provided testimony on behalf of Davis, Graham and Stubbs, LLP, who represented the Western Energy Operators, in its efforts to challenge new emissions controls on oil and gas exploration/production operations proposed under Regulation 7. He delivered testimony to the Colorado Oil and Gas Commission. Dr. Wilkinson prepared and delivered evidence refuting claims by the Colorado Department of Public Health and the Environment (CDPHE) that air quality modelling showed that the proposed emissions controls would be beneficial to society. He demonstrated that air quality modelling results were incorrectly interpreted by the CDPHE, and that an alternative explanation of the modelling results showed virtually no predicted improvement in air quality would occur with the implementation of changes to Regulation 7.

Houston 8-hour Ozone
SIP Coalition,
Texas Commission on
Environmental Quality
Austin, Texas
Dr. Wilkinson provided testimony on behalf of the Houston 8-hour Ozone SIP Coalition in its efforts to modify emissions control rules for industrial facilities in the Houston-region. He delivered testimony indicating that some elevated ozone days in Houston were due to fires occurring in the Pacific Northwest, Alberta, and British Columbia. He also demonstrated the contribution of flaring emissions to overall predicted air quality.

Bay Area Air Quality
Management District
(BAAQMD)
San Francisco,
California
Dr. Wilkinson provided testimony to support BAAQMD in its efforts to defend the adequacy of its comprehensive air quality modelling studies. Plaintiffs claimed that BAAQMD made inappropriate assumptions in its modelling analyses, which led to the construction of emissions control strategies that were far less stringent than needed to be in order to attain the ozone NAAQS for the greater San Francisco Bay Area. Dr. Wilkinson’s analyses showed that for each assumption made by the BAAQMD, the modelling assumption was appropriate and in some cases more conservative than needed to be.

PROFESSIONAL AFFILIATIONS
Air and Waste Management Association (AWMA)
Institute of Electrical and Electronics Engineers (IEEE)

PUBLICATIONS
Refereed Journal
Articles
Taha, H., J. Wilkinson, R. Bornstein, Q. Xiao, G. McPherson, J. Simpson, C.

Anderson, S. Lau, J. Lam, C. Blain: An urban-forest control measure for ozone in the Sacramento Federal Non-Attainment Area (SFNA). Atmospheric Environment, in press (2015).
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18 Resumé JAMES WILKINSON
Bergin, M. S., JS Shih, J. Krupnick, J. W. Boylan, J. G. Wilkinson, M. T. Odman and A. G. Russell. Regional Air Quality: Local and Interstate Impacts of NOx and SO2 Emissions on Ozone and Fine Particulate Matter in the Eastern United States. Environmental Science & Technology, 41 (2007), 4677-4689.

Boylan, J. W., M. T. Odman, J. G. Wilkinson, A. G. Russell, K. G. Doty, W. B.

Norris and R. T. McNider. Integrated assessment modeling of atmospheric pollutants in the Southern Appalachian Mountains. Part I: Hourly and seasonal ozone. Journal of the Air and Waste Management Association, 55 (2005), 1019- 1030.

Boylan, J. W., M. T. Odman, J. G. Wilkinson and A. G. Russell. Integrated assessment modeling of atmospheric pollutants in the Southern Appalachian Mountains: Part II. Fine particulate matter and visibility. Journal of the Air and Waste Management Association, 56 (2006), 12-22.

Hanna, S. R., A. G. Russell, J. G. Wilkinson, J. Vukovich and D. A. Hansen.

Monte Carlo estimation of uncertainties in BEIS3 emission outputs and their effects on uncertainties in chemical transport model predictions. Journal of Geophysical Research, 110 (2005)
Boucouvala, D., R. Bornstein, J. Wilkinson and D. Miller. MM5 simulations of a SCOS97-NARSTO episode. MM5 simulations of a SCOS97-NARSTO episode, 37 (2003), S95-S117.

Boylan, J. B., M. T. Odman, J. G. Wilkinson, A. G. Russell, K. G. Doty, W. B.

Norris and R. T. McNider. Development of a comprehensive, multiscale ‘oneatmosphere’ modeling system: application to the Southern Appalachian Mountains. Atmospheric Environment, 36 (2002), 3721-3734.

Fiore, A. M., D. J. Jacob, I. Bey, R. M. Yantosca, B. D. Field and J. G. Wilkinson.

Background Ozone over the United States in summer: origin and contribution to pollution episodes. Journal of Geophysical Research, 107 (2001) Mendoza, A., J. G. Wilkinson and A. G. Russell. Source Impact Quantification of Anthropogenic and Biogenic Emissions on Regional Ozone in the Mexico-U.S.

Border Area using Direct Sensitivity Analysis. Journal of the Air and Waste Management Association, 50 (2000)
Yang, Y. J., J. G. Wilkinson and A. G. Russell. Fast, Direct Sensitivity Analysis of Multidimensional Photochemical Models. Environmental Science & Technology, 33 (1999), 1116-1126.

Mullholland, J. A., A. J. Butler, J. G. Wilkinson, A. G. Russell, P. E. Tolbert et al.

Temporal and Spatial Distributions of Ozone in Atlanta: Regulatory and Epidemiologic Implications. Journal of the Air and Waste Management Association, 48 (1998), 418-426.

Chapters Uncertainty Assessment of Biogenic Emissions Estimates and Its Impact on Ozone Attainment Control Strategy Selection, Air Pollution in the Ural Mountains:
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19 Resumé JAMES WILKINSON
Environmental, Health, and Policy Aspects (2. Environment Volume 40), edited by I. Linkov and R. Wilson, Kluwer Academic Publishers, Boston, 1997.

Fast Sensitivity Analysis of Three-Dimensional Photochemical Models, Air Pollution Modeling and Its Application XII (Volume 22), edited by S. E. Gryning and N. Chaumerliac, Plenum Press, New York, 1997.

Conference
Proceedings
Yang, Y. J., J. G. Wilkinson, M. T. Odman and A. G. Russell. 1998. Ozone Sensitivity and Uncertainty Analysis Using DDM-3D in a Photochemical Air Quality Model. Twenty-third NATO/CCMS International Technical Meeting On Air Pollution Modeling And Its Application, September. Varna, Bulgaria.

Wilkinson, J. G. and Y. J. Yang. 1998. Area Of Influence: Identifying Regions Whose Sources Potenitally Impact Downwind Air Quality. Twenty-third NATO/CCMS International Technical Meeting On Air Pollution Modeling And Its Application, September. Varna, Bulgaria.

Tolbert, P. E., J. A. Mulholland, J. G. Wilkinson, A. G. Russell, A. Butler and K.

M. Hall. 1997. Spatio-Temporal Analysis Of Air Qality And Pediatric Asthma Emergency Room Visits. Proceedings of the Annual Joint Statistical Meetings of the American Statistical Association, August. Anaheim, California.

Wilkinson, J. G., T. W. Tesche, D. E. McNally and C. F. Loomis. 1997. Nested Regional Photochemical Modeling In Support Of The Pittsburgh-Beaver Valley Ozone SIP. 10th Conference on Applications of Air Pollution Meteorology with the Air & Waste Management Association, American Meteorological Society, January. Phoenix, Arizona.

Wilkinson, J. G., T. W. Tesche and D. E. McNally. 1997. Application Of EPA’s Flexible Attainment Demonstration Guidance To The Pittsburgh-Beaver Valley Ozone Nonattainment Area. 10th Conference on Applications of Air Pollution Meteorology with the Air & Waste Management Association, American Meteorological Society, January. Phoenix, Arizona.

Wilkinson, J. G., A. Beidler and R. A. Wayland. 1996. The Emissions Modeling System (EMS-95) and the Flexible Regional Emissions Data System (FREDS): A Comparison of Emissions Modeling Tools. The Emission Inventory: Key to Planning, Permits, Compliance and Reporting. Proceedings of a Specialty Conference, September. New Orleans, Louisiana.

Wilkinson, J. G., C. F. Loomis, R. A. Emigh, T. W. Tesche and S. Tanrikulu. 1996. Application Of The Emissions Modeling System EMS-95 To The Southern California SCAQS-97 Do. Ninth Joint Conference on the Applications of Air Pollution Meteorology, January. Atlanta, Georgia.

Wilkinson, J. G., T. E. Pierce and R. A. Emigh. 1995. An Intercomparison of Biogenic Emissions Estimates from BEIS2 and BIOME: Reconciling the Differences. AWMA and EPA Emissions Inventory Conference , October. 4051
20 Resumé JAMES WILKINSON
Wilkinson, J. G. and C. F. Loomis. 1993. Evaluation Protocols for Emissions Modeling Systems. International Regional Photochemical Measurements & Modeling Studies Specialty Conference, August. San Diego, California.

Wilkinson, J. G. and C. F. Loomis. 1993. An Independent Evaluation of the Geocoded Emissions Modeling and Projections System. International Regional Photochemical Measurements & Modeling Studies Specialty Conference , August. San Diego, California.

Wilkinson, J. G., R. J. Dickson, V. M. Sadeghi, P. K. Brooks and S. J. Strasset. 1992. Development of a New Emissions Modeling System. International Specialty Conference sponsored by the Air & Waste Management Association, October. Durham, North Carolina.

Wilkinson, J. G. and S. J. Strasser. 1993. Regional Air Quality: Local and Interstate Impacts of NOx and SO2 Emissions on Ozone and Fine Particulate Matter in the Eastern United States. SUGI 18, May. New York, New York.

Reports “MOVES2014a Emissions Estimates Due to Steamboat Ski Area Project.” Prepared for Ms. Larissa Read, Associate Planner, SE Group, PO Box 2729, Frisco, CO 80443. Prepared by James G. Wilkinson, PhD, Senior Engineer, 2076 Westwood Lane, Eugene, OR 97401. 18-Mar-2017.
“MOVES2014a Emissions Estimates Due to Snowmass Multi-Season Recreation Project.” Prepared for Ms. Gabby Voeller, Associate Planner, SE Group, PO Box 2729, Frisco, CO 80443. Prepared by James G. Wilkinson, PhD, Senior Engineer, 2076 Westwood Lane, Eugene, OR 97401. 01-October-2016. “Hazard Consequence Modeling of a Natural Gas Pipeline from the Leesville Cryogenic Processing Plant to the DTI Interconnect.” Prepared for Utica East Ohio Midstream, LLC, 10 East Main Street, Salineville, OH 43945. Prepared by Golder Associates Inc., 9 Monroe Parkway, Suite 270, Lake Oswego, OR 97035.

Report Number 140766_CO1a_RevB. July 31, 2015
“Consequence Analysis for NREL Solar Energy Research Facility (SERF).” Prepared for the National Renewable Energy Laboratory, 15013 Denver West Parkway, Golden, CO 80401. Prepared by Golder Associates Inc., 9 Monroe Parkway, Suite 270, Lake Oswego, OR 97035. July 30, 2015. “Declaration of James G. Wilkinson, PhD.” REQUEST FOR CORRECTION OF INFORMATION submitted on behalf of THE STATE OF KANSAS, THE STATE OF NEBRASKA, THE ENERGY FUTURE COALITION, and URBAN AIR INITIATIVE Concerning the U.S. Environmental Protection Agency’s EPAct/V2/E-89 FUEL EFFECTS STUDY and MOTOR VEHICLE EMISSIONS SIMULATOR MODEL (MOVES2014). Docket ID Nos. EPA–420-R-13-002, FRL9917-26-OAR. March 16, 2015. “Hazard Consequence Modeling of a Natural Gas Liquids Pipeline from the Leesville Cryogenic Processing Plant to the Harrison Hub Complex.” Prepared for Mr. Jim Roberts, Utica East Ohio Midstream, LLC, 11543 SR 644, 4052
21 Resumé JAMES WILKINSON
Kensington, OH 44427. Prepared by Golder Associates Inc., 9 Monroe Parkway, Suite 270, Lake Oswego, OR 97035. Report Number 1407666_RG1_r0.

February 13, 2015.
“Air Dispersion Modeling Study of the Mulfulira Heap Leach Pad Extension.” Prepared for Nyundo Armitage, Project Engineer, Golder Associates Zambia Ltd., ZEC Flats, Unit 15, Plot 5C, Cnr Martin Luther King & Roan Road, Kabulanga, Lusaka, Africa. Prepared by Golder Associates Inc., 9 Monroe Parkway, Suite 270, Lake Oswego, OR 97035. Project Number: 1415632.

December 10, 2014.
“Safety-Based Qualitative Risk Assessment of the Puget Sound Energy D.W.

Swarr Propane-Air Plant.” Prepared for Mr. Dave Jenness, PMP, Senior Project Manager, Puget Sound Energy Inc., 10885 N.E. 4th Street, Bellevue, Washington 98004. Prepared by Golder Associates Inc., 18300 NE Union Hill Road, Suite 200, Redmond, WA 98052 USA. Project Number: 14-01901.

November 18, 2014.
“Pipeline Spill Scenario Odour Modelling Study Report.” Prepared for Northern Courier Pipeline GP Ltd., A Wholly Owned Subsidiary of TransCanada Pipelines Limited, 450 - 1st Street SW, Calgary, AB T2P 4K5. Prepared by Golder Associates Ltd.,102, 2535 - 3rd Avenue S.E., Calgary, Alberta, T2A 7W5.

Report Number: 1213340008-3000-3001. September 30, 2014. “Hazard Consequence Modeling of a Natural Gas Liquids Pipeline, and Ethane Pipeline, and a Propane Pipeline – Final Findings.” Prepared for Mr. Jim Roberts, Utica East Ohio Midstream, LLC, 11543 SR 644, Kensington, OH 44427. Prepared by Golder Associates Inc., 9 Monroe Parkway, Suite 270, Lake Oswego, OR 97035. Report Number 1402217_TM_F_r0. September 2, 2014. “MOVES2010b and NONROAD2008 Emissions Estimates Due to Proposed Eldora Mountain Resort Expansion.” Prepared for Mr. Travis Beck, Senior Project Manager, SE Group, PO Box 2729, Frisco, CO 80443. Prepared by James G. Wilkinson, PhD, Senior Engineer, Alpine Geophysics, LLC, 2076 Westwood Lane, Eugene, OR 97401. 29-July-2013.
“CO2 Hazard Consequence Modeling.” Prepared for Mr. Keith Pipkin, Senior Engineer, Anadarko Petroleum Corporation, 1099 18th Street, Denver, CO 80202-1908. Prepared by Goler Associates Inc., 9 Monroe Parkway, Suite 270, Lake Oswego, OR 97035. Project Number: 140971. August 6, 2014. “Agricultural Emissions Temporal and Spatial Allocation Tool (AgTool): Software Requirements Specification &
System Documentation.” Prepared by James G. Wilkinson, PhD, Alpine Geophysics, LLC, 2076 Westwood Lane
Eugene, OR 97401 and Tom Carlson, Sierra Research, Inc., 1801 J Street, Sacramento, CA 95811. December 31, 2012.
“Modeling Protocol for the 2013 Houston, TX Air Quality Model Study: Ensemble Modeling and Probabilistic Attainment Demonstration for the New 8-hour Ozone National Ambient Air Quality Standard.” Prepared for Ms. Liz Hendler, 8-hr 4053
22 Resumé JAMES WILKINSON
Ozone SIP Coalition Project Manager, 10715 Fountainbleu Circle, Austin, TX 78750 and Mr. Rohit Sharma, Lyondell Chemical Company, 1515 Miller Cut-Off Road, La Porte, TX 77571. Prepared by T. W. Tesche, CARA, 85 Falcon Drive, Boise, ID 83716 and James G. Wilkinson, Gregory M. Stella, Dennis E. McNally, Cynthia F. Loomis, Alpine Geophysics, LLC, 2076 Westwood Lane, Eugene, OR 97401. December 8, 2010.
“HARC Project H97: Multi-Model, Multi-Episode Process Analysis to Investigate Ozone Formation and Control Sensitivity in the 2000/2005/2006 Houston SIP Episode Models”. Vizuete, W., H. Jeffries, A. Valencia, E. Couzo, E. Christoph, J. Wilkinson, B. Henderson, H. Parikh, J. Kolling. September 29, 2009. files.harc.edu/Projects/AirQuality/Projects/H097/H097FinalReport.pdf “User’s Guide and Standards & Design: California Integrated Transportation Network (ITN).” Prepared for Ms. Cheryl Taylor, Atmospheric Modeling and Support Section, CalEPA - Air Resources Board, Planning and Technical Support Division, 1001 I Street, Sacramento, CA. Prepared by James G.

Wilkinson, Alpine Geophysics, LLC, Eugene, OR. September 30, 2009. “8-Hour Ozone SIP Coalition Comments on the Proposed Houston-GalvestonBrazoria Attainment Demonstration SIP Revision for the 1997 Eight-Hour Ozone Standard Rule Project Number 2009-017-SIP-NR.” Prepared for Ms. Lola Brown, Texas Commission on Environmental Quality, Austin, Texas 78711-3087.

Prepared by BASF Corporation, Enterprise Products Operating LLC, Exxon Mobil Corporation, Lyondell Chemical Company, NRG Texas Power LLC, Shell Oil Company, Valero Refining-Texas, L.P. with support from James G. Wilkinson, Alpine Geophysics, and T. W. Tesche, Climate and Atmospheric Research Associates.
“Factors Contributing to the Simultaneous Decline in Measured Design Values (DVbs), Modeled Relative Response Factors (RRFs), and Calculated Future Design Values (DVfs) in Houston as the Result of Advancing to the More Recent TexAQSII 2006 Baseline.” Prepared for Baker-Botts, LLP, 910 Louisiana, Houston, TX 77002. Prepared by James G. Wilkinson, Alpine Geophysics, LLC, Eugene, OR and Thomas W. Tesche, Climate & Atmospheric Research Associates, LLC, Ft. Wright, KY. February 6, 2009.
“Flexibility in EPA’s 8-hr Ozone Attainment Test.” Prepared for Baker-Botts, LLP, 910 Louisiana, Houston, TX 77002. Prepared by James G. Wilkinson, Alpine Geophysics, LLC, Eugene, OR and Thomas W. Tesche, Climate & Atmospheric Research Associates, LLC, Ft. Wright, KY. January 16, 2009. “Evaluation of 36/12 km MM5 and WRF for February and August 2005 over the Continental and Western United States.” Prepared for the U.S. Environmental Protection Agency, Office of Air Quality Planning and Standards, RTP, NC 27711 and UNC Institute for the Environment, Chapel Hill, NC 27599. Prepared under contract: Modeling Support for Source Sector Projects, Contract Number EP-D-07-102, Work Assignment 1-08. Prepared by James G. Wilkinson and Dennis McNally, Alpine Geophysics, LLC, Arvada, CO 80007. September 30, 2008.
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23 Resumé JAMES WILKINSON
“Evaluation of 36/12/4 km MM5 for Calendar Year 2005 over the Continental and Western United States with Emphasis in Southwestern Wyoming.” Prepared for ARCADIS-US, Inc., Highlands Ranch, CO 80129. Prepared by Dennis McNally and James G. Wilkinson, Alpine Geophysics, LLC, Arvada, CO 80007.

December 2008.
“Final Report: Modeling Analyses Conducted for the Columbia River Gorge National Scenic Area Air Quality Study.” Prepared for The Southwest Clean Air Agency, 11815 NE 99th Street, Vancouver, Washington 98682. Prepared by Chris Emery, Edward Tai, Uarporn Nopmongcol, Jeremiah Johnson, and Ralph Morris, ENVIRON International Corporation, 101 Rowland Way, Novato, California 94945 and Jim Wilkinson and Dennis McNally, Alpine Geophysics, LLC, 2076 Westwood Lane, Eugene, OR 97401. August 28, 2007. www.swcleanair.org/gorgereports.html
“Implementation of the Model of Emissions of Gases ad Aerosols from Nature (MEGAN) into the CONCEPT Modeling Framework.” Prepared for Mr. Mark Janssen, Lake Michigan Air Directors’ Consortium, 2250 East Devon Ave. Suite 250, Des Plaines IL, 60018. Prepared by J. G. Wilkinson, Alpine Geophysics, LLC, 2076 Westwood Lane, Eugene, OR 97401. June 16, 2006. www.conceptmodel.org/Documents/megan/Final_CONCEPT_MEGAN_Report.p df
<http://www.conceptmodel.org/Documents/megan/Final_CONCEPT_MEGAN_R eport.pdf>
“Development Of The California Integrated Transportation Network (ITN).” Prepared for Mr. Vernon Hughes, Manager, Control Strategy Modeling Section, CalEPA- Air Resources Board, Planning and Technical Support Division, 1001 I Street, Sacramento, CA. Prepared by Alpine Geophysics, LLC, 7691 Alpine Road, La Honda, CA 94020. AG-TS-90/155. June 7, 2004.
“Scientific Peer-Review of the Hg-CAMx Atmospheric Mercury Model and Its Application to the 2002 Annual Cycle,” prepared for Wisconsin Department of Natural Resources, Mercury Modeling Team, prepared by Alpine Geophysics, LLC, Arvada, CO, April 2004 (with Stella, G.M., T.W. Tesche, D. McNally). “Review of BEIS3 Formulation and Consequences Relative to Air Quality Standards: Estimation of Uncertainties in BEIS3 Emissions Outputs.” EPRI Technical Report 1005159, EPRI, 3412 Hillview Ave., Palo Alto, CA 94304 (with Hanna, S.R., Russell, A.G., and Vukovich, J). 2002.
“Review of BEIS3 Formulation and Consequences Relative to Air Quality Standards: Estimation of Effects of Uncertainties in BEIS3 Emissions on Uncertainties in Ozone Predictions by Chemical Transport Models.” EPRI Technical Report, EPRI, 3412 Hillview Ave., Palo Alto, CA 94304 (with Hanna, S.R., Russell, A.G., and Vukovich, J). 2003.
“SAMI Air Quality Modeling Final Report. Prepared for the Southern Appalachian Mountains Initiative (SAMI).” Prepared by School of Civil and Environmental 4055
24 Resumé JAMES WILKINSON
Engineering, Georgia Institute of Technology, 200 Bobby Dodd Way, Atlanta GA 30332-0512. July 2002. (with Odman, M. T., J. W. Boylan, A. G. Russell, S. F.

Mueller, R. E. Imhoff, K. G. Doty, W. B. Norris and R. T. McNider). environmental.gatech.edu/SAMI/Documents/Reports/final_report.pdf “Meteorological, Emissions and Air Quality Modeling for an Integrated Assessment Framework in Support of the Southern Appalachians Mountain Initiative: Emissions Modeling Protocol.” Prepared by the Georgia Institute of Technology. 1998 (with Russell, A.G., J. G. Wilkinson, M. T. Odman, and R.

McNider). environmental.gatech.edu/SAMI/downloads.htm
<http://environmental.gatech.edu/SAMI/downloads.htm>.
“Meteorological, Emissions and Air Quality Modeling for an Integrated Assessment Framework in Support of the Southern Appalachians Mountain Initiative: Air Quality Modeling Protocol.” Prepared by the Georgia Institute of Technology. environmental.gatech.edu/SAMI/downloads.htm <http://environmental.gatech.edu/SAMI/downloads.htm>. 1998 (with Russell, A.G., M. T. Odman, and R. McNider).
“Technical Support Study 15: Evaluation And Improvement Of Methods For Determining Ammonia Emissions In The San Joaquin Valley.” Prepared for the California Air Resources Board, Sacramento, CA. Prepared by Sonoma Technology, Inc., Santa Rosa, CA. STI-95310-1759-DFR. 1997 (with S. Coe, L. Chinkin, C. Loomis, J. Zwicker, D. Fitz, D. Pankratz, and E. Ringler). “Comparison of the CAL-MoVEM and DTIM2 Motor Vehicle Emissions Estimate Models”, prepared for the California Air Resources Board (Sacramento, CA), February, 1997.
“Photochemical Modeling Analysis of the Pittsburgh-Beaver Valley Ozone Nonattainment Area”, (with others) prepared for the Southwestern Pennsylvania Clean Air Stakeholders Group, February 21, 1997.
“Uncertainty Assessment of Biogenic Emissions Estimates And Its Impact On Ozone Attainment Control Strategy Selection,” PhD qualifying examination, Carnegie Mellon University, Department of Engineering and Public Policy, Pittsburgh, PA, January 1997.
“Horizontal Advection Solver Uncertainty in the Urban Airshed Model,” prepared for the California Air Resources Board (Contract Number 93-722) (with M. Talat Odman, L. A. McNair, A. G. Russell and others).
“Estimates of UAM-IV Model Sensitivities to Emissions Changes in the Pittsburgh-Beaver Valley Ozone Non- Attainment Area”, (with others) prepared for the Southwestern Pennsylvania Clean Air Stakeholders Group, September 15, 1996.
“PM10 Air Quality Models for Application in the San Joaquin Valley PM10 SIP”, (with others) prepared for the California Air Resources Board (Sacramento, CA), September 1996.
4056
25 Resumé JAMES WILKINSON
“Pittsburgh Regional Ozone Attainment Study: Emissions Modeling Results”, (with James G. Wilkinson) prepared for the Southwestern Pennsylvania Clean Air Stakeholders Group, July 1996.
“Review of Current Methodologies for Estimating Ammonia Emissions”, (with others) prepared for the California Air Resources Board (Sacramento, CA), May 1996.
“EMS-95: Technical Formulation Document,” prepared for the Lake Michigan Air Directors Consortium (Des Plaines, IL) and the Valley Air Pollution Study Agency (Fresno, CA), October 22, 1994 (with Cyndi F. Loomis).
www.ladco.org/emis/guide/ems95.html
<http://www.ladco.org/emis/guide/ems95.html>
“The Geocoded Emissions Modeling and Projections System (GEMAP) Advanced Training Workshop,” prepared for the US EPA, AREAL, Research Triangle Park, NC, August 29, 1994 (with Robert A. Emigh). 4057
Appendix F
Health Risk Assessment
4058

HEALTH RISK ASSESSMENT
for the
Friant Ranch Community Development Project
Prepared for:

Friant Ranch LP
Fresno, California
Prepared by:

BlueScape Environmental
16870 West Bernardo Drive, Suite 400
San Diego, California 92127
March 4, 2021

BL U E SCAPE

ENVIRONM EN TAL
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Friant Ranch Community Development Project Health Risk Assessment Report BlueScape Environmental i March 4, 2021

TABLE OF CONTENTS

1.0 INTRODUCTION........................................................................ 1

1.1 Site Setting and Project Description ..................................... 2

1.2 Objective ......................................................................... 3

1.2.1 Construction Emissions Health Risk Screening............. 3

1.2.2 Off-Site and On-Site Traffic Emissions ....................... 5

1.2.3 Unmitigated vs. Mitigated Traffic Emissions ................ 5

1.3 Methodology ..................................................................... 5

1.3.1 Project Sources – Operation at Project Build-Out (2031)6

1.3.2 Cumulative Sources at Project Build-Out (2031).......... 6

2.0 OPERATIONAL EMISSIONS ESTIMATES .................................... 6

2.1 Calculation Methodologies for Stationary Sources................... 7

2.2 Calculation Methodologies for Mobile Sources ........................ 7

3.0 AIR CONCENTRATION ESTIMATES............................................ 9

3.1 Chemical Selection ............................................................ 9

3.2 Model Selection and Parameters .........................................10

4.0 RISK CHARACTERIZATION METHODS ..................................... 12

4.1 Sources Evaluated............................................................12

4.2 Cancer Risk Exposure Assessment ......................................12

4.3 Cancer Risk Toxicity Assessment ........................................13

4.4 Estimation of Cancer Risks.................................................14

4.5 Estimation of Chronic Non-cancer Hazard Quotients / Indices . 14

4.6 Estimation of Acute Non-cancer Hazard Quotients / Indices ....15

5.0 RESULTS FROM PROJECT ANALYIS ......................................... 15

6.0 RESULTS FROM CUMULATIVE ANALYSIS ................................ 16

6.1 Methodology ....................................................................16

6.2 Cumulative Risk Results ....................................................16

7.0 REFERENCES ........................................................................... 18 4060
Friant Ranch Community Development Project Health Risk Assessment Report BlueScape Environmental ii March 4, 2021
TABLES
Table 1: Emergency Generator Emissions for AERMOD Modeling Table 2: Traffic Volumes for AERMOD Modeling
Table 3a: Traffic Emission Factors for AERMOD Modeling
Table 3b: Exposure Weighted Traffic Emission Factors for Annual AERMOD Modeling
Table 4: Diesel and Gasoline Split for Traffic Emissions Calcuations Table 5: Roadway Source Parameters for AERMOD Modeling
Table 6a: Traffic Emission Rates for Acute Impact AERMOD Modeling Table 6b: Exposure Weighted Traffic Emission Rates for Annual AERMOD Modeling
Table 7: Hourly Scalars for AERMOD Modeling
Table 8: Residential Receptor Exposure Parameters
Table 9: Toxicity Values
Table 10: Vehicle Exhaust TOG Weight Fractions
Table 11: Modeled Excess Lifetime Cancer Risk and Acute Hazard Indices - Project
Table 12: Excess Lifetime Cancer Risk and Acute Hazard Indices - Cumulative

FIGURES
Figure 1: AERMOD Model Set-Up Parameters

APPENDICES
Appendix A: AERMOD Output Files
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GLOSSARY OF TERMS AND ACRONYMS
Acronym Description
AADT Annual average daily traffic
AERMOD AMS/EPA Regulatory Model
AM Morning (ante meridiem)
aREL Acute Reference Exposure Level
ASF Age sensitivity factor
AT Averaging time
BAAQMD Bay Area Air Quality Management District
C Annual Average or Maximum Hourly Air Concentration
CalEEMod California Emissions Estimator Model
Cal/EPA California Environmental Protection Agency
Caltrans California Department of Transportation
CAPCOA California Air Pollution Control Officers Association CARB California Air Resources Board
CAS # Chemical Abstracts Service Registry Number
CEQA California Environmental Quality Act
CF Conversion factor
CPF Cancer potency factor
cREL Chronic Reference Exposure Level
DBR Daily breathing rate
DPM Diesel particulate matter
ED Exposure duration
EF Exposure frequency
EIR Environmental Impact Report
EMFAC2017 California Air Resources Board’s Mobile Source Emissions Factor Inventory
ET Exposure Time
FAH Fraction time at home
g/sec Grams per second
HI Hazard index
HIA Health Impact Analysis
HQ Hazard quotient
HRA Health risk assessment
IFinh Intake Factor for Inhalation
K Kelvin
kg Kilograms
kW Kilowatt
L Liters
LP Limited Partnership
m Meters
m2 Square meters
m3 Cubic meters
MEI Maximally Exposed Individual
mg Milligrams
m/s Meters per second
NED National Elevation Dataset
OEHHA Office of Environmental Health Hazard Assessment
PM Afternoon (Post Meridiem)
PM10 Particulate Matter 10 Micrometers or less in aerodynamic 4062
Friant Ranch Community Development Project Health Risk Assessment Report BlueScape Environmental iv March 4, 2021

GLOSSARY OF TERMS AND ACRONYMS
Acronym Description
diameter
SAFE Safer Affordable Fuel-Efficient factor
SJVAPCD San Joaquin Valley Air Pollution Control District TAC Toxic air contaminant
TOGD Total Organic Gases in Diesel Exhaust
TOGG Total Organic Gases in Gasoline Exhaust
TRU Transport refrigeration unit
USEPA US Environmental Protection Agency
USGS United States Geological Survey
µg/m3 Microgram per Cubic Meter
UTM Universal Transverse Mercator
WWTP Wastewater treatment plant
yd3 Cubic yards
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1.0 INTRODUCTION
At the request of the County of Fresno (County) and the San Joaquin Valley Air Pollution Control District (SJVAPCD), BlueScape Environmental (BlueScape) prepared this Health Risk Assessment (HRA), which describes local health impacts due to emissions of toxic air contaminants (TACs) associated with the proposed Friant Ranch Community Development Project (Project) in Friant, California. The HRA was prepared to support the Project’s California Environmental Quality Act (CEQA) documentation.1 The Project consists of the Friant Ranch Specific Plan, the update to the Friant Ranch Community Plan, a new wastewater treatment facility, and improvements at such locations as the Depot Parcel.

The California Air Resources Board (CARB) maintains a list of TACs, defined as an “air pollutant which may cause or contribute to an increase in mortality or in serious illness, or which may pose a present or potential hazard to human health” (CARB 2007). A TAC HRA, utilizing dispersion modeling to determine atmospheric concentrations, is the type of study typically requested by SJVAPCD for CEQA analyses to determine localized health impacts of a Project.

The Project site is located nearly twenty (20) miles to the north of Downtown Fresno, California in a largely rural setting within the jurisdiction of the SJVAPCD. A few scattered residential neighborhoods are located to the east, northeast, and west of the Project site.

Construction of the Project is assumed to begin in 2022 and is scheduled to occur in five phases over an approximate ten-year period, starting with Phase 1 in the northern-most area of the Project site. Impacts from construction emissions over the ten-year period are considered in this analysis. However, as discussed in this report, a screening analysis using SJVAPCD’s risk prioritization score calculator demonstrates that health risk impacts on on-site and off-site residents from construction activities will not exceed thresholds that, if exceeded, would indicate a need for further evaluation of health risk impacts. Therefore, Project construction emissions-related impacts are considered to be insignificant and only Project operational impacts are analyzed for this HRA.

Full Project operation is projected to begin in 2031. The HRA considered potential impacts from traffic due to the Project, as well as from cumulative traffic that is not related to the Project in 2031, using traffic volume data from the year 2030, which is the closest year to 2031 for which projected traffic data was available. These two scenarios (called Project-only and Cumulative, respectively) analyze potential impacts from diesel and gasoline exhaust from traffic on roads adjacent to the Project site, as well as from diesel-powered generators proposed to be installed nearby at a new wastewater treatment

1 A Project HRA was discussed with the SJVAPCD in a 9/13/2014 meeting. 4064
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plant (WWTP). Diesel exhaust includes diesel particulate matter (DPM) and speciated components including benzene, formaldehyde, and other TAC compounds. Gasoline exhaust includes speciated components such as acrolein, naphthalene, and other TAC compounds. Air emissions were calculated using emission factors obtained from the CARB’s Mobile Source Emissions Factor Inventory, EMFAC2017 (CARB 2017) and from the California Department of Transportation (or Caltrans) peak hour volume data for No-Project conditions in 2030 and for With-Project conditions in 2030 provided in the Friant Ranch Draft Environmental Impact Report (County of Fresno 2009).

The HRA was completed by referencing the SJVAPCD Update to District’s Risk Management Policy to Address OEHHA’s Revised Risk Assessment Guidance Document (SJVAPCD 2015b), the SJVAPCD Framework for Performing Health Risk Assessments (SJVAPCD 2018), the SJVAPCD Draft Guidance for Air Dispersion Modeling (SJVAPCD 2007), and the Office of Environmental Health Hazard Assessment Risk Assessment Guidelines (OEHHA 2015). This report provides a brief description of diesel and gasoline exhaust emission sources from Project operations, traffic that is not related to the Project, and the WWTP diesel generators. The TAC emission calculations, calculation of TAC concentrations from air dispersion modeling, and estimation of health risk impacts are provided in the report attachments.

As stated in the HRA report conclusions, the Project-only localized health risk impacts on off-site and on-site residential receptors from Project operational emissions are not expected to exceed a 20 in one million excess cancer risk CEQA significance threshold. The Project-only non-cancer chronic and acute localized health risk impacts will not exceed a 1.0 hazard index (HI) CEQA significance threshold. The Cumulative localized health risk impacts on off-site and on-site residential receptors are not expected to exceed a 100 in one million excess cancer risk CEQA significance threshold. The Cumulative noncancer chronic and acute health risk impacts will not exceed a 10 HI CEQA significance threshold. Therefore, the Project is not expected to expose off-site or on-site residences to substantial amounts of TAC emissions that would cause a significant health impact and require further mitigation.

1.1 Site Setting and Project Description
The proposed Project is a mixed-use development proposed by Friant Ranch LP (Project sponsor). The Project would develop retail, residential, and open space uses on a 942-acre site in Friant, California as shown in Figure 1. The Project will be primarily residential, with up to 2,270 dwelling units age restricted to over 55, and up to 230 dwelling units without age restriction.

The site is in a mostly rural area, with scattered neighborhoods and houses to the northwest, northeast, and southwest of the Project site. Off-site roads near the Project site include North Friant Road, which runs in a northwest/southwest direction directly along the eastern property line of the Project. North Friant Road becomes Millerton Road at the northern tip of the Project site where the 4065
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direction changes to mostly an east/west direction. North Fork Road / Road 206 branches off at the N. Friant Rd. / Millerton Rd. transition, and runs in an east/west direction. These off-site roads are included in the HRA.

A wastewater treatment facility will be developed to support the Project and other expected growth in the Friant Community at a different site (the Beck Property) on the west side of Friant Road. The wastewater treatment facility will require two diesel emergency generators at full build-out, and for the analysis presented in this report, are considered to be a part of the Project.

1.2 Objective
The purpose of the air quality analysis was to assess potential health impacts that would result from emission of TACs from the operation of the Project consistent with guidelines and methodologies from SJVAPCD, CARB, the Office of Environmental Health Hazard Assessment (OEHHA), and the US Environmental Protection Agency (USEPA). Consistent with the methods recommended in those guidelines, the HRA evaluated the estimated excess lifetime cancer risk associated with TACs that would be emitted by the Project’s operational stationary source emissions (e.g., diesel generators) as well as from Project-related diesel and gasoline vehicles. The Cumulative analysis estimates excess lifetime cumulative cancer risks from TACs that are attributable to existing and projected future mobile sources within the Project vicinity, and a gasoline dispensing facility, in addition to impacts from the Project. Chronic and acute non-cancer impacts are also estimated for the Project during operation, and for the Cumulative analysis.

As requested in discussion with SJVAPCD, the HRA evaluated excess lifetime cancer risks and chronic and acute hazard indices from Project operational emissions to existing sensitive receptor populations.

Following CARB recommendations and using guidance from the Bay Area Quality Management District (BAAQMD) for an approximate 1,000-foot zone of influence surrounding the site, cumulative excess lifetime cancer risks and non-cancer chronic and acute hazard indices resulting from major roadway mobile source TAC emissions, as well as stationary source TAC emissions, were evaluated.

1.2.1 Construction Emissions Health Risk Screening
The construction emissions associated with the ten years and five phases of Project construction were considered for the HRA. Because TAC emissions from other sources such as gasoline exhaust will be negligible during construction, and only diesel exhaust will drive the health impacts, only diesel exhaust from construction equipment was included in risk screening. SJVAPCD guidance (SJVAPCD 2015a) states that construction emissions shall be analyzed separately from operational emissions. To determine whether or not emissions from Project construction need to be included in the HRA, the SJVAPCD Prioritization Risk Screening Tool was used to screen cancer, chronic, and acute 4066
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risk impacts due to the maximum diesel particulate matter (DPM) emissions from construction activities over the approximate 10-year construction period (CAPCOA 2016). If a cancer prioritization score exceeds a value of 10 at the nearest residential receptor, then the health risk impact from the construction operations must be included in the HRA. Additionally, if a chronic and/or acute non-cancer prioritization score exceeds a value of 10, then SJVAPCD recommends that further review of construction health risk impacts be conducted (SJVAPCD 2018).

The California Emissions Estimator Model (CalEEMod), v.2016.3.2, was used to model emissions for each year of construction, starting in 2022 and ending in 2031. The average unmitigated DPM construction emissions for that tenyear period were estimated by CalEEMod to be 0.204 tons/year or 1.57 lb/day, and a maximum of 4.94 lbs/day. A receptor proximity of 250 meters was chosen for screening purposes, which is the minimum distance from the middle of construction Phase 1 and from the middle of construction Phase 2 to the nearest resident, either off-site or on-site.

To screen for cancer risk impacts, the average annual DPM emissions of 0.204 tons/year were annualized over a 70-year lifetime cancer risk time period, by multiplying by 10 years/70 years. This annualized DPM emissions number was then entered into the prioritization screening tool with the DPM Chemical Abstracts Service Registry Number (CAS #) 9901. The resulting cancer score for a receptor that is between 250 meters and 500 meters from a source is

5.39, which does not exceed the cancer prioritization score of 10.

To screen for chronic risk impacts, the average annual DPM emissions of 0.204 tons/year were entered into the prioritization screening tool with the DPM CAS #9901. The resulting chronic score for a receptor that is between 250 meters and 500 meters from a source is 0.056, which does not exceed the chronic prioritization score of 10.

To screen for acute risk impacts, the maximum daily DPM emissions of 4.94 lbs/day were divided by the assumed 8 hrs/day workday to give 0.62 lbs/hr.

Then, the resulting 0.62 lbs/hr were apportioned to each of the speciated components in diesel exhaust using the weight fractions of compounds in diesel exhaust shown in Table 10. Each of the seven Total Organic Gases in Diesel Exhaust (TOGD) components that have acute risk Reference Exposure Levels (aRELs) were entered into the prioritization screening tool with their corresponding CAS numbers. The resulting acute score for a receptor that is between 250 meters and 500 meters from a source is 0.12, which does not exceed the acute prioritization score of 10.

Since none of the screening prioritization scores exceed their limits, impacts on residents from Project construction were not included in this HRA. 4067
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1.2.2 Off-Site and On-Site Traffic Emissions
In addition to traffic emissions from off-site roads, emissions from on-site roads were considered. Cal/EPA’s 2005 Land Use Handbook (Cal/EPA 2005) recommends that health protective distances (500 feet at minimum) be implemented to separate sensitive uses from freeways, urban roads with 100,000 vehicles/day, or rural roads with 50,000 vehicles/day. Traffic on the main off-site access roads into the Friant Ranch Community such as Friant Road is not expected to exceed 3,000 vehicles/day, but has been included at SJVAPCD’s request. As recommended by BAAQMD Guidance, the off-site traffic emissions within 1,000 feet from the Project site were considered for the HRA.

The on-site roads in the Friant Ranch retirement community will have much lower daily vehicle traffic volumes spread over a large area as compared to the main access roads located within 1,000 feet of the Project site. Impacts from the on-site roads would be inconsequential compared to impacts from the offsite roads that were included in the HRA. Therefore, impacts from Project onsite roads were not analyzed in this HRA.

1.2.3 Unmitigated vs. Mitigated Traffic Emissions
A detailed study of unmitigated and mitigated emissions due to traffic exhaust was conducted using CalEEMod in the Health Impact Analysis (HIA) report that addresses regional air quality and health impacts (BlueScape 2021). For this localized HRA, vehicle exhaust emissions were calculated using a calculation method similar to the one used in the HIA, except that, to obtain necessary TAC emissions details, CalEEMod was not used to quantify these emissions.

Both CalEEMod and the HRA calculations shown in the report tables use EMFAC2017 and the “Safer Affordable Fuel-Efficient” (SAFE) factors (CARB 2019), and the emissions calculated using these two methods resulted in very similar emissions numbers between the two studies. Because there are no additional feasible mitigation methods for vehicle exhaust due to traffic on these off-site roads, the DPM, Total Organic Gases from Gasoline Exhaust (TOGG), and TOGD emissions calculated are considered mitigated emissions in this HRA.

1.3 Methodology
Due to the Project, there will be traffic-related operational TAC emissions as well as TAC emissions from two stationary standby emergency generators located at the proposed wastewater treatment facility. Cancer risks and noncancer chronic and acute hazard indices from total organic gases from gasoline and diesel exhaust (TOGG and TOGD) and diesel particulate matter (DPM) from traffic at the site and the standby emergency generators were evaluated.

To meet these objectives, the HRA was conducted consistent with the following guidance:
• Air Toxics Hot Spots Program Risk Assessment Guidelines, Office of 4068
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Environmental Health Hazard Assessment (OEHHA) and California Environmental Protection Agency (OEHHA 2015);
• Update to District’s Risk Management Policy to Address OEHHA’s Revised Risk Assessment Guidance Document, San Joaquin Valley APCD (SJVAPCD 2015b);
• Framework for Performing Health Risk Assessments, San Joaquin Valley APCD (SJVAPCD 2018); and
• Draft Guidance for Air Dispersion Modeling, San Joaquin Valley APCD (SJVAPCD 2007).

Excess lifetime cancer risks and non-cancer chronic and acute hazard indices were evaluated based on the emissions estimation methods described in the following sections.

1.3.1 Project Sources – Operation at Project Build-Out (2031) According to the Project sponsor, the Project will be developed in phases over multiple years. Project emissions at full build-out in 2031, the first year when the Project site can be fully occupied, were analyzed. However, the HRA was performed using traffic volumes assuming full Project operation in the year 2030, which was the year analyzed in the EIR’s traffic study (County of Fresno 2009). This is a conservative approach, given that improvements in vehicle technology and turnover within the vehicle fleets are expected as time goes by. Emissions in 2030 are expected to be slightly higher than emissions in 2031.

1.3.2 Cumulative Sources at Project Build-Out (2031)
Emissions were based on Project Build-out conditions and 2030 cumulative traffic volumes2, but the HRA was performed for year 2031 which is consistent with the Project-only analysis.

2.0 OPERATIONAL EMISSIONS ESTIMATES
For each source of operational emissions, the most conservative (i.e., with the greatest potential impact) options were evaluated. While both the Friant Ranch Community and the wastewater treatment facility will be developed in stages, this analysis assumes that the Project is at full build-out in 2031, and it is understood that this year also corresponds with the first year that the Project site could be fully occupied. The operational emissions discussed here include gasoline and diesel exhaust from mobile and stationary sources due to the Project and due to non-Project traffic and operations. Mobile and stationary source diesel exhaust was analyzed in this HRA as both DPM and the TACs in

2 2030 traffic estimates were the closest year available to the build-out date from the EIR (County of Fresno 2009).
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that exhaust, known as total organic gases (TOGD). Mobile source gasoline exhaust was analyzed in this HRA as the TACs in that exhaust, known as total organic gases (TOGG).

2.1 Calculation Methodologies for Stationary Sources
The Project includes two new diesel emergency generators to support a small,

0.8 million gallon per day wastewater treatment facility. The wastewater treatment facility, which will run on electricity, will only require one 500- kilowatt (kW) backup generator for many years, until demand necessitates the use of another 300-kW backup generator. However, it is conservatively assumed that the entire complement of emergency generators (800 kW) would be in use in 2031. This conservative approach also ensures that the analysis includes the highest possible exposure scenario for the nearby receptors. The backup generators will be used infrequently up to 50 hours/year for testing and during any emergencies. Emissions from both generators were calculated for an engine with the Tier 3 emissions standards using the methodology presented in Table 1.

Stationary sources that are not a part of the Project include a gas station that dispenses around 1.6 million gallons per year within 600 feet of the Project site. This source, which is located adjacent to the northern portion of the Project site at the intersection of N. Fork Road and Millerton Road/N. Friant Road, is included in the Cumulative analysis.

2.2 Calculation Methodologies for Mobile Sources
The analysis included emissions from vehicle trips, based on estimated 2030 PM peak hourly traffic volumes provided by the traffic engineer in the Draft EIR (the highest estimated traffic year from the Draft EIR) (County of Fresno 2009). Project traffic emissions were estimated assuming full Project build-out in 2031 with the understanding that 2031 would also be the first year that residents could fully occupy Friant Ranch. Note that the traffic volumes provided in the Draft EIR were for a land use plan with more proposed homes than the version of Project approved by the County of Fresno in 2011 (Alternative 3 from the Draft EIR) and being considered again by the County.

This assumption of a larger number of homes than are currently being considered adds an additional layer of conservatism. Traffic volumes for the Project-only analysis were obtained by subtracting the 2030 No-Project Conditions from the 2030 With-Project Conditions estimated PM peak hourly traffic volumes. The Cumulative analysis relied on the traffic volumes provided as the 2030 With-Project Conditions as a conservative measure. Afternoon (PM) peak hourly traffic volumes were converted to annual average daily traffic (AADT) volumes by applying the 75th percentile “K” factor (7.88%) from CalTrans 2017 data for Fresno County3, as many traffic studies only estimate

3 A “K” factor represents the percentage of the AADT in both directions during the peak hour. Data for this analysis gathered from the following source: CalTrans 2017. Peak Hour Volume Data. 4070
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AM and PM peak hourly traffic. The PM peak hourly and AADT volumes for the Project at the relevant traffic segments are shown in Table 2.

Mobile emission factors were calculated for each individual year over a 70-year period (beginning in calendar year 2031 as described above) for DPM, diesel TOG, and gasoline TOG. Mobile emissions over a time period of 70 years are required for the HRA, as exposure to pollutants over a 70-year period is consistent with SJVAPCD guidance for calculating lifetime cancer risk impacts (SJVAPCD 2018) and includes children in utero in their mothers’ third trimester of pregnancy, rounded from 70.25 to 70 years. While the same traffic volumes are assumed for each year, vehicle emission factors are reduced every year due to automobile turnover and increasingly stringent emissions regulations.

Table 3a shows the emission factors used for the analysis. The emission factors were developed on a gram per mile basis using EMFAC2017, assuming that DPM and diesel TOG are emitted via running exhaust vehicle emission pathways, and that gasoline TOG is emitted via running exhaust and evaporative running loss pathways. These gram per mile emission factors were used to develop emissions estimates for each roadway analyzed in the HRA and were also used to develop residential receptor exposure weighted emission factors (presented in Table 3b) for use in the HRA dispersion modeling for cancer risk analysis. Exposure assumptions and dispersion modeling methods are discussed in further detail in the following report sections. To develop these exposure weighted emissions, the gram per mile emission factors from Table 3a were weighted on a year-by-year basis by the product of a residential receptor’s Daily Breathing Rate (DBR), Fraction of time at Home (FAH), and Age Sensitivity Factor (ASF) exposure parameters consistent with 2015 OEHHA guidance. The 70-year average exposure-weighted emission factor is used in the HRA dispersion modeling.

Table 4 shows the percentage split of diesel and gasoline vehicles in 2031 in Fresno County (CARB 2017). This county-wide breakdown is used for both the Project-only and Cumulative analysis. The breakdown of gasoline and diesel vehicles is required to estimate emissions from the traffic.

In addition to the roadway vehicle trips discussed above, Friant Ranch will have six to twelve businesses that may require deliveries, resulting in truck idling and transport refrigeration unit (TRU) operation at local business loading docks. Most of the businesses would only require deliveries on a sporadic basis, likely one truck per day or less. The loading docks at the Friant Ranch businesses will be equipped with 110/208-volt power outlets in order that any TRU can be plugged in for deliveries. Localized risks from diesel traffic and TRU idling at retail or dining establishments are not typically estimated for projects due to the minimal risk expected due to the small level of diesel traffic. CARB’s Air Quality and Land Use Handbook (Cal/EPA 2005) describes potential risks from distribution centers, which have significantly higher diesel traffic, and thus risks, and sets the threshold for special consideration of distribution centers at 100 trucks per day, more than 40 trucks with operating TRUs per day, or where TRU unit operations exceed 300 hours per week. Since the 4071
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operations at Friant Ranch are much lower than this threshold in the aggregate, the risk due to diesel and TRU idling from off-site sources is expected to be minimal and well below significance thresholds. Accordingly, they do not warrant quantitative emission estimation or modeling.

3.0 AIR CONCENTRATION ESTIMATES
For the Project analysis, TAC concentrations due to Project traffic and the two emergency generators at the proposed wastewater treatment facility are quantified. For the Cumulative analysis, TACs from the estimated total traffic and Project emergency generators are quantified; other potential contributors to risk are discussed qualitatively.

3.1 Chemical Selection
The excess lifetime cancer and chronic risk analyses in the HRA were based on DPM emissions and TOGs from on-road gasoline vehicles. Diesel exhaust, a complex mixture that includes hundreds of individual constituents, is identified by the State of California as a known carcinogen (CARB 1998). Under California regulatory guidelines, DPM is used as a surrogate measure of carcinogen exposure for the mixture of chemicals that make up diesel exhaust as a whole (OEHHA 2015). OEHHA and other proponents of using the surrogate approach to quantifying excess lifetime cancer risks associated with the diesel mixture indicate that this method is preferable to use of a component-based approach because it provides a protective approach to estimating health risks. A component-based approach involves estimating risks for each of the individual components of a mixture. Critics of the component-based approach believe it will underestimate the risks associated with diesel as a whole mixture because the identity of all chemicals in the mixture may not be known and/or exposure and health effects information for all chemicals identified within the mixture may not be available. Furthermore, OEHHA has concluded that “potential cancer risk from inhalation exposure to whole diesel exhaust will exceed the multi-pathway cancer risk from the speciated components.” (OEHHA 2015).

These analyses were based on the surrogate approach, as recommended by OEHHA. DPM also has a chronic non-cancer toxicity value associated with it, so the chronic risk analysis was based on this surrogate approach, as well.

Speciated components of gasoline (TOGG) are also included as carcinogens and/or contributors to chronic risk.

There is currently no acute non-cancer toxicity value available for DPM. Thus, speciated components of diesel total organic gases (TOGD) with acute toxicity values were included in the acute non-cancer hazard analysis. Speciated components of gasoline TOGG are similarly included in the acute non-cancer hazard analysis. Toxicity values for DPM as well as for the individual components speciated from diesel and gasoline TOGs are included in Table 9. 4072
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3.2 Model Selection and Parameters
Consistent with SJVAPCD guidance, near-field air dispersion modeling of DPM, TOGD, and TOGG was conducted using the USEPA’s AERMOD model version 19191 (USEPA 2019). For each receptor location, the model generated average air concentrations that result from emissions from multiple sources.

Air dispersion models such as AERMOD require a variety of inputs such as source parameters, meteorological parameters, topography information, and receptor parameters. When site-specific information was unknown, default parameter sets that are designed to produce conservative (i.e., overestimates of) air concentrations were used.

The AERMOD output files are included in Appendix A.

Meteorological data: Air dispersion modeling applications require the use of meteorological data that ideally are spatially and temporally representative of conditions in the immediate vicinity of the site under consideration. For this HRA, SJVAPCD’s Fresno meteorological data for years 2013 through 2017 (v. 18081) was used. According to SJVAPCD, the v. 19191 version of this data is not available, and the v. 18081 version is suitable for use.4 Terrain considerations: Elevation and land use data was imported from the National Elevation Dataset (NED) maintained by the United States Geological Survey (USGS). An important consideration in an air dispersion modeling analysis is the selection of rural or urban dispersion coefficients. Based on the rural area in which the Project site is located, rural dispersion coefficients were used.

Source parameters: Source location and parameters are necessary to model the dispersion of air emissions. Elevated line-volume sources are used to represent the roadway traffic sources, and the line-volume sources extend over 1,000 feet beyond the Project boundary to capture the sources relevant to the Project receptors. The roadways modeled are presented in Figure 1. A release height of 3.05 meters (10 feet) with an initial vertical dimension (sigma z) of 1.42 m (4.65 feet) was used for the roadway sources, which is a conservative estimate of initial exhaust plume lift from multiple types of vehicles on the roadways. The source parameters used in the AERMOD input files for each roadway line-volume source are presented in Table 5.

The location of the diesel emergency generators was determined by the Project sponsor. Figure 1 shows the modeled location of the proposed generators.

Refined modeling of the operational emissions was performed for the two emergency generators. The two generators were modeled as a single point source, with a stack exit temperature of 739.8 Kelvin (K), a stack exit velocity of 45.3 meters per second (m/s), and a stack diameter of 0.183 meters (m).

Building downwash caused by the Project buildings, as well as neighboring

4 Email communication from Kyle Melching of SJVAPCD, dated Jan. 11, 2021. 4073
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buildings, was not accounted for.

Emission rates: The emission rates associated with each roadway source are shown in Tables 6a and 6b for both the Project and Cumulative HRAs. These emission rates were entered into AERMOD for each roadway line-volume source. For traffic, exhaust-emitting activities were modeled to reflect the distribution of traffic throughout the day. As discussed in Section 2.1.2, daily emissions can be estimated from the data provided by the traffic engineer, but hourly emission rates are needed as input to the dispersion model used to calculate concentrations. Hourly emission rate scalars are necessary to correlate emissions with the appropriate meteorological conditions if long-term concentrations are required. Table 7 shows the hourly scalar values used in the AERMOD input files to distribute emissions throughout the day. These hourly scalar values were entered into AERMOD as variable emission factors so that the annualized roadway emissions are distributed throughout the day, matching estimated traffic patterns (e.g. less traffic in the middle of the night, more traffic in the daytime hours). The variable emission factors were used only for annual, long-term model runs. The acute, short-term model runs assumed even traffic throughout the 24-hr day so that maximum hourly emissions were not adjusted within the model. The hourly variable emission factors were calculated from data obtained through the EMFAC2017 model, a model designed to provide emission factors for automobile traffic in California, run in the “burden mode” for Fresno County in 2031 (CARB 2017).

The maximum time allowed by maintenance and testing of emergency generators, 50 hours per year, were considered for this analysis.5 Annual total DPM emissions from the maintenance and testing of the emergency generators were assumed to be spread over each year, since long-term cancer and chronic risks are based on long-term daily average dose. Emission factors were based on Tier 3 standards from the CARB and USEPA Off-Road Compression-Ignition (Diesel) Engine Standards (CARB 2013). Emission factors for DPM are conservatively based on the PM emission standard. Emission factors for TOGD are calculated using proportions of TOG to non-methane hydrocarbons as provided by USEPA's "Conversion Factors for Hydrocarbon Emission Components" (USEPA 2005).

Receptors: In order to evaluate health impacts, receptors were placed on the Project site with 20-meter spacing and a 185-foot setback from Friant Road (as per Project design). Receptors were also placed on off-site residential communities. Receptors were modeled at a height of 1.8 meters above terrain height, a default breathing height for ground-level receptors (CAPCOA 2005).

Modeled receptors are shown in Figure 1.

5 Maximum hours determined as per CARB Stationary Diesel Engine ATCM. Available at:
https://ww3.arb.ca.gov/diesel/documents/finalreg2011.pdf 4074
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4.0 RISK CHARACTERIZATION METHODS
The following sections discuss in detail the various components required to conduct the HRA.

4.1 Sources Evaluated
As discussed in Section 1.2, excess lifetime cancer risks, and chronic and acute non-cancer hazards were evaluated for the following scenarios:
• Project traffic and stationary source emissions reflective of traffic at Project build-out of 2031 (2030 in traffic study) and full emergency generator use at the wastewater treatment facility. 70-year average traffic emission factors weighted by exposure parameters were used.
• Cumulative emissions, including traffic emissions reflective of Project build-out year of 2031 (2030 in traffic study). Cumulative traffic emissions consist of the Project traffic and other future anticipated growth, also with conservative 70-year average traffic emission factors weighted by exposure parameters. Cumulative emissions also include the emergency generators and a nearby gasoline dispensing facility as described in Section 2.1.1.

4.2 Cancer Risk Exposure Assessment
Potentially Exposed Populations: The following receptor populations were evaluated:
• On-site and off-site 70-year lifetime residents for the Project scenario. • On-site and off-site 70-year lifetime residents for the Cumulative scenario.

Residential exposure assumptions are more conservative than those for other sensitive receptor types as residential uses have the longest exposure time and exposure duration and highest exposure frequency. No other sensitive receptors (such as schools or daycare centers) were identified in the area that would have higher risk impacts than for residential receptors.

Exposure Assumptions: The exposure parameters used to estimate excess lifetime cancer risks for potentially exposed populations for the Project and Cumulative scenarios were obtained using risk assessment guidelines from OEHHA (OEHHA 2015) and SJVAPCD (SJVAPCD 2018), unless otherwise noted, and are presented in Table 8.

Calculation of Intake: The dose estimated for each exposure pathway is a function of the concentration of a chemical and the intake of that chemical.

The intake factor for inhalation, IFinh, can be calculated as follows:
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𝐼𝐼𝐼𝐼𝑖𝑖𝑖𝑖ℎ =
𝐷𝐷𝐷𝐷𝐷𝐷 × 𝐸𝐸𝐸𝐸 × 𝐸𝐸 × 𝐸𝐸 × 𝐴𝐴𝐴𝐴 × 𝐹𝐹 × 𝐶𝐶
𝐴𝐴
Where:

IFinh = Intake Factor for Inhalation (m3/kg-day)
DBR = Daily Breathing Rate (L/kg-day)
ET = Exposure Time (hours/24 hours)
EF = Exposure Frequency (days/year)
ED = Exposure Duration (years)
ASF = Age Sensitivity Factor (unitless)
FAH = Fraction at Home (unitless)
CF = Conversion Factor, 0.001 (m3/L)
AT = Averaging Time (days)
The estimated excess lifetime cancer risks for residents were adjusted using the age sensitivity factors (ASFs) recommended in the OEHHA Hot Spots Guidance (OEHHA 2015). This approach accounts for an “anticipated special sensitivity to carcinogens” of infants and children. Cancer risk estimates are weighted by a factor of 10 for exposure of the age group that includes the third trimester fetus up to two years of age and by a factor of three for exposures that occur from two years through 15 years of age. No weighting factor (i.e., an ASF of one, which is equivalent to no adjustment) is applied to ages 16 and above.

Typically, the chemical intake or dose is estimated by multiplying the inhalation intake factor, IFinh, by the chemical concentration in air, Ci. When coupled with the chemical concentration, this calculation is mathematically equivalent to the dose algorithm given in OEHHA Hot Spots guidance (OEHHA 2015). For this Project, since traffic emission factors decrease by year, these emission factors were weighted by a product of DBR, ASF, and FAH and averaged for the 70- year exposure duration for the AERMOD modelling. The AERMOD outputs were then processed by incorporating other terms in the above equation (see Section 4.4).

4.3 Cancer Risk Toxicity Assessment
The toxicity assessment characterizes the relationship between the magnitude of exposure and the nature and magnitude of adverse health effects that may result from such exposure. For purposes of calculating exposure criteria to be used in risk assessments, adverse health effects are classified into two broad categories – cancer and non-cancer endpoints. Toxicity values used to estimate the likelihood of adverse effects occurring in humans at different exposure levels are identified as part of the toxicity assessment component of a risk assessment.

The carcinogenic toxicity for DPM and additional organic gases from on-road 4076
Friant Ranch Community Development Project Health Risk Assessment Report BlueScape Environmental 14 March 4, 2021
gasoline-powered vehicles are included. Toxicity values are summarized in Table 9.

4.4 Estimation of Cancer Risks
The equation used to calculate the potential excess lifetime cancer risk for the inhalation pathway is as follows:

𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑖𝑖𝑖𝑖ℎ = 𝐶𝐶𝑖𝑖 × 𝐶𝐶𝐶𝐶 × 𝐼𝐼 𝑖𝑖𝑖𝑖ℎ × 𝐶𝐶𝐶𝐶𝐶𝐶𝑖𝑖
Where:

Riskinh = Cancer Risk; the incremental probability of an individual developing cancer as a result of inhalation exposure to a particular potential carcinogen (unitless)
Ci = Annual Average Air Concentration for chemical i (µg/m3) CF = Conversion Factor, 0.001 mg/µg
IFinh = Intake Factor for Inhalation (m3/kg-day)
CPFi = Cancer Potency Factor for chemical i (mg chemical/kg body weight-day)-1
Cancer risk estimations were determined using average concentrations from the period average concentration over all five years of meteorology modeled.

4.5 Estimation of Chronic Non-cancer Hazard Quotients / Indices The potential for exposure to result in adverse chronic effects is evaluated by comparing the estimated annual average air concentration of chemical to the chronic reference exposure level (cREL) for each chemical evaluated in this analysis. When calculated for a single chemical, the comparison yields a hazard quotient (HQ) for that chemical. To evaluate the potential for adverse chronic health effects from simultaneous exposure to multiple chemicals, the HQs for all chemicals are summed, yielding a hazard index (HI).

𝐻𝐻𝐻𝐻𝑖𝑖 = 𝐶𝐶
𝑐𝑐 𝑐𝑐𝑐𝑐𝑖𝑖 �
𝐻𝐻 = �𝐻𝐻𝐻𝐻𝑖𝑖
Where:

HQi = Chronic hazard quotient for chemical i
HI = Hazard index
Ci = Annual average concentration of chemical i (µg/m3) cRELi = Chronic reference exposure level for chemical i (µg/m³) 4077
Friant Ranch Community Development Project Health Risk Assessment Report BlueScape Environmental 15 March 4, 2021

4.6 Estimation of Acute Non-cancer Hazard Quotients / Indices The potential for exposure to result in adverse acute effects is evaluated by comparing the estimated one-hour maximum air concentration of chemical to the acute reference exposure level (aREL) for each chemical evaluated in this analysis. When calculated for a single chemical, the comparison yields a HQ.

To evaluate the potential for adverse acute health effects from simultaneous exposure to multiple chemicals, the HQs for all chemicals are summed, yielding a HI.

𝐻𝐻𝐻𝐻𝑖𝑖 = 𝐶𝐶
𝑎𝑎 𝑖𝑖 �
𝐻𝐻 = �𝐻𝐻𝐻𝐻𝑖𝑖
Where:

HQi = Acute hazard quotient for chemical i
HI = Hazard index
Ci = One-hour maximum concentration of chemical i (µg/m3) aRELi = Acute reference exposure level for chemical i (µg/m³)

5.0 RESULTS FROM PROJECT ANALYIS
This section presents the Project impact results for on-site and off-site residents.

The SJVAPCD CEQA air quality significance thresholds (SJVAPCD 2018) for health risks and hazards from a Project are:
• An excess lifetime cancer risk level of more than 20 in one million; and • A non-cancer (chronic or acute) HI greater than 1.0.

Table 11 shows the excess lifetime cancer risk and chronic/acute non-cancer HIs for the maximally exposed individual (MEI) receptor for potential on-site receptors and on off-site residential communities.

The lifetime cancer risk for the on-site MEI was estimated to be 10.5 in a million, which does not exceed a SJVAPCD CEQA significance threshold of 20 in a million. This conservatively assumes that the two generators at the wastewater treatment facility will both start to operate in 2031, and a 70-year resident scenario that will result in the highest exposure, including risks from childhood exposures. To the extent that this Project reflects age-restricted housing, consisting mostly of a population of older people who are less sensitive than children to health risk impacts, these risks are overestimated. 4078
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The actual lifetime cancer risk for on-site receptors will likely be much lower than 10.5 in a million.

The lifetime cancer risk for the off-site MEI was estimated to be 17.5 in a million, which also does not exceed a corresponding SJVAPCD threshold of 20 in a million. However, this receptor is located right next to N. Friant Rd., on a large, rural residential-zoned lot, and not where an actual residence is located (the nearest residence to this receptor location is 450 feet to the east). The actual lifetime cancer risk for the resident nearest to this MEI receptor would be much lower than 17.5 in one million.

The chronic and acute non-cancer HIs due to Project operation for on-site receptors are 0.002 and 0.006, respectively; and the chronic and acute noncancer HIs for off-site receptors are 0.004 and 0.010, respectively, which are well below the SJVAPCD significance threshold of 1.0.

6.0 RESULTS FROM CUMULATIVE ANALYSIS

6.1 Methodology
While SJVAPCD does not have specific guidance for a Cumulative health risk analysis, an analysis to determine the health risk from existing traffic on the proposed Project receptors and off-site resident receptors was requested by the SJVAPCD staff. 6 The CEQA air quality significance thresholds used to evaluate cumulative impacts on on-site and off-site residents are based on the Bay Area Air Quality Management District CEQA Guidelines (BAAQMD 2017).

The BAAQMD CEQA significance thresholds for cumulative cancer and noncancer risk are based on EPA guidance for conducting air toxics analyses and making risk management decisions at the community-scale level (USEPA 1989). BAAQMD CEQA significance thresholds for cumulative impacts are:
• An excess lifetime cancer risk level of more than 100 in one million; and • A non-cancer (chronic or acute) HI greater than 10.

Traffic information provided by the Project traffic engineer was used to estimate excess lifetime cancer risk and chronic and acute hazard indices due to traffic emissions within 1,000 feet surrounding the Project. Both the Project and non-Project traffic were considered, and the 2030 estimated traffic volumes were used.

6.2 Cumulative Risk Results
Besides the cumulative traffic, the emissions from the two generators at the WWTP, and that from a nearby gasoline dispensing facility were also considered. Table 12 shows a summary of the estimated excess lifetime cumulative cancer risks and non-cancer chronic and acute hazard indices from the total traffic and other sources at the MEI locations. Conservatively

6 Discussed with Leland Villavazo during a 9/4/2014 phone call. 4079
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calculated cumulative cancer risks were determined to be less than 44 in one million for on-site MEI and less than 55 in one million for off-site MEI, primarily due to the total traffic emitting DPM from the nearby highway. These cancer risk results do not exceed the BAAQMD CEQA significance threshold of 100 in a million.

The chronic and acute non-cancer HIs due to cumulative traffic for on-site receptors are 0.008 and 0.011, respectively; and the chronic and acute noncancer HIs for off-site receptors are 0.010 and 0.015, respectively, which are well below the BAAQMD CEQA significance threshold of 10. 4080
Friant Ranch Community Development Project Health Risk Assessment Report BlueScape Environmental 18 March 4, 2021

7.0 REFERENCES
BAAQMD 2017. California Environmental Quality Act Air Quality Guidelines, Bay Area Air Quality Management District (BAAQMD), May 2017. Available online at:
www.baaqmd.gov/~/media/files/planning-andresearch/ceqa/ceqa_guidelines_may2017-pdf.pdf?la=en BlueScape 2021. Regional Air Quality Modeling & Health Impact Analysis for the Friant Ranch Community Development Project, BlueScape Environmental, 2021.

Cal/EPA 2005. Air Quality and Land Use Handbook: A Community Health Perspective, California Environmental Protection Agency (Cal/EPA), California Air Resources Board (CARB), April 2005. Available online at:
www.arb.ca.gov/ch/handbook.pdf
Caltrans 2017. Peak Hour Volume Data, Fresno County, Caltrans, 2017.

Available online at: https://dot.ca.gov/programs/traffic-operations/census CAPCOA 2009. Health Risk Assessments for Proposed Land Use Projects, California Air Pollution Control Officers Association, July 2009. Available online at:
www.capcoa.org/wpcontent/uploads/2012/03/CAPCOA_HRA_LU_Guidelines_8-6-09.pdf CAPCOA 2016. SJVAPCD Prioritization Risk Screening Tool, California Air Pollution Control Officers Association, 2016. Accessible online at:
www.valleyair.org/busind/pto/Resources/resources_idx.htm CARB 1998. Findings of the Scientific Review Panel on the Report on Diesel Exhaust, as Adopted at the Panel’s April 22, 1998 Meeting, California Air Resources Board (CARB), Office of Environmental Health Hazard Assessment (OEHHA). Available online at:
www.arb.ca.gov/toxics/dieseltac/de-fnds.htm
CARB 2003. Recommended Interim Risk Management Policy for InhalationBased Residential Cancer Risk, California Air Resources Board (CARB), Office of Environmental Health Hazard Assessment (OEHHA), October 9, 2003.

Available online at:
ww3.arb.ca.gov/toxics/rmpolicy.pdf
CARB 2007. California Health and Safety Code Section 39655, California Air Resources Board, Last updated February 8, 2007. Available online at:
ww2.arb.ca.gov/resources/documents/carb-identified-toxic-aircontaminants#:~:text=According%20to%20section%2039655%20of,additio n%2C%20substances%20which%20have%20been
4081
Friant Ranch Community Development Project Health Risk Assessment Report BlueScape Environmental 19 March 4, 2021
CARB 2013. Non-road Diesel Engine Certification Tier Chart, California Air Resources Board (CARB), Available online at:
ww2.arb.ca.gov/resources/documents/non-road-diesel-engine-certificationtier-chart CARB 2017. Mobile Source Emission Factors for On-road Vehicles, California Air Resources Board (CARB), EMFAC2017. Available online at:
https://arb.ca.gov/emfac/
CARB 2019. EMFAC Off-Model Adjustment Factors to Account for the SAFE Vehicle Rule Part One, California Air Resources Board (CARB), November 20, 2019. Available online at:
ww3.arb.ca.gov/msei/emfac_off_model_adjustment_factors_final_draft.pdf CARB 2020. OEHHA/ARB Consolidated Table of Approved Risk Assessment Health Values, California Air Resources Board (CARB), Office of Environmental Health Hazard Assessment (OEHHA), October 2, 2020. Available online at:
www.arb.ca.gov/toxics/healthval/contable.pdf
County of Fresno 2009. Friant Community Plan Update and Friant Ranch Specific Plan, Draft Environmental Impact Report, County of Fresno, October 2009. Available online at:
www.co.fresno.ca.us/home/showpublisheddocument?id=14246 OEHHA 2015. Air Toxics Hot Spots Program, Risk Assessment Guidelines, Guidance Manual for Preparation of Health Risk Assessments, Office of Environmental Health Hazard Assessment (OEHHA), February 2015. Available online at: http://oehha.ca.gov/air/hot_spots/hotspots2015.html SJVAPCD 2007. Draft Guidance for Air Dispersion Modeling, San Joaquin Valley Air Pollution Control District (SJVAPCD), Rev. 2.0, January 2007. Available online at:
www.valleyair.org/busind/pto/tox_resources/Modeling%20Guidance.pdf SJVAPCD 2015a. Guidance for Assessing and Mitigating Air Quality Impacts, San Joaquin Valley Air Pollution Control District (SJVAPCD), March 19, 2015.

Available online at:
www.valleyair.org/transportation/GAMAQI_12-26-19.pdf
SJVAPCD 2015b. Final Staff Report: Update to District’s Risk Management Policy to Address OEHHA’s Revised Risk Assessment Guidance Document, San Joaquin Valley Air Pollution Control District (SJVAPCD), March 18, 2015.

Available online at:
www.valleyair.org/busind/pto/staff-report-5-28-15.pdf
SJVAPCD 2018. Framework for Performing Health Risk Assessments, San Joaquin Valley Air Pollution Control District (SJVAPCD), APR-1906, Revised July 1, 2018. Available online at:
www.valleyair.org/policies_per/Policies/APR-1906-7-1-18.pdf 4082
Friant Ranch Community Development Project Health Risk Assessment Report BlueScape Environmental 20 March 4, 2021
USEPA 1989. NESHAP 54 Federal Register 38044, September 14, 1989; CAA section 112(f). Available online at:
www.epa.gov/sites/production/files/2016-03/documents/54_fr_38044.pdf USEPA 2005. Conversion Factors for Hydrocarbon Emission Components, USEPA, EPA420-R-05-015, December 2005. Available online at:
https://19january2017snapshot.epa.gov/www3/otaq/models/nonrdmdl/nonr dmdl2005/420r05015.pdf
USEPA 2019. User's Guide for the AMS/EPA Regulatory Model - AERMOD.

Version 19191 released August 21, 2019. Available online at:
www.epa.gov/scram/air-quality-dispersion-modeling-preferred-andrecommended-models#aermod United States Geological Survey (USGS). National Elevation Dataset. Available online at:
https://catalog.data.gov/dataset/usgs-national-elevation-dataset-ned 4083
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Page 1 of 1 ends

Max. Emissions for
Short-Term (1-hr)
Modeling
Avg. Annual
Emissions for
Long-Term
Modeling
Exposure Weighted
AERMOD Emissions3

TOGD DPM TOGD DPM DPM
[kW] [hp] [g/s] [g/s] [(g/s)*(L/kg-day)]
WWTP at Beck Property 300 402 diesel 50 0.16 0.15 1.82E-02 9.6E-05 0.098 WWTP at Beck Property 500 671 diesel 50 0.16 0.15 3.04E-02 1.6E-04 0.164

4.86E-02 2.55E-04 0.2619
Notes:

References:

Reference Ramboll's draft HRA report, August 2019. Two emergency generators required at full build-out, 500 kW and 300 kW.

Abbreviations:

DPM: diesel particulate matter
TOGD: total organic gases in diesel exhaust
TOGG: total organic gases in gasoline exhaust
California Air Resources Board (ARB). 2011. Final Regulation Order, Amendments to the Airborne Toxic Control Measure for Stationary Compression Ignition Engines.

May. Available online at: https://ww3.arb.ca.gov/diesel/documents/finalreg2011.pdf.

California Air Resources Board (ARB) 2013. ARB and USEPA Off-Road Compression-Ignition (Diesel) Engine Standards. Available online at:
https://ww2.arb.ca.gov/resources/documents/non-road-diesel-engine-certification-tier-chart.

U.S. Environmental Protection Agency (USEPA) 2010. Conversion Factors for Hydrocarbon Emission Components, July 2010. Available online at:
http://www.epa.gov/otaq/models/nonrdmdl/nonrdmdl2010/420r10015.pdf.

Total Emissions:

3. Exposure weighted emission factors for AERMOD modeling calculated by averaging the annual DPM emissions over a full year, then weighting that g/s emission rate by the product of a residential receptor's Daily Breathing Rate (DBR), Fraction of Time at Home (FAH), and Age Sensitivity Factor (ASF) for each age group in a given year over 70 years (starting from third trimester in 2031) consistent with recommended values from 2015 OEHHA guidelines (presented in Table 8).

1. Operation is assumed to be 50 hours per year, consistent with the maximum hours of operation allowed under ARB's Stationary Diesel Engine ATCM (ARB 2011).

2. Emission factors based on Tier 3 standards from the ARB and USEPA Off-Road Compression-Ignition (Diesel) Engine Standards (ARB 2013). Emission factors for DPM are conservatively based on the PM emission standard. Emission factors for TOGD are calculated using proportions of TOG to Non-methane hydrocarbons as provided by EPA's "Conversion Factors for Hydrocarbon Emission Components" (EPA420-R-05-015, December 2005).

Table 1
Emergency Generator Emissions for AERMOD modeling
Friant Ranch Community
Friant, California
Location
Size Fuel
Type
Operation1
(hrs/yr)
Emission Factors2
[g/bhp-hr]
I
I
I
4085

Page 1 of 1 ends

PM Peak
Hourly
Traffic
AADT
estimate1
PM Peak
Hourly
Traffic
AADT
estimate1
PM Peak
Hourly
Traffic
AADT
estimate1
A Lost Lake to N Willow Ave 2,104 26,701 3,058 38,807 954 12,107 B Root Ave to Lost Lake 2,118 26,878 2,758 35,000 640 8,122 C Granite Ave to Root Ave 2,138 27,132 2,553 32,398 415 5,266 D Parker Ave to Granite Ave 2,145 27,221 2,566 32,563 421 5,343 E 206 to Parker 2,125 26,967 2,599 32,982 474 6,015
F Friant Road to Road 145 2,164 27,462 2,611 33,135 447 5,673 G 206 to Winchell Cove 1,733 21,992 1,839 23,338 106 1,345 Notes:

Abbreviations:

AADT: annual average daily traffic
References:

Environmental Impact Report. Appendix D: Traffic Impact Study. Tables 8.2 & 14.2 CalTrans 2017. Peak Hour Volume Data, Available online at: https://dot.ca.gov/programs/traffic-operations/census Draft Friant Community Plan Update & Friant Ranch Specific Plan, Fresno County, CA.

Road 206
Millerton Road
Friant Road (South to North)

1. AADT estimated by applying the 75th percentile "K" factor (the percentage of AADT during peak hour) from CalTrans 2017 data for Fresno County.

Table 2
Traffic Volumes for AERMOD modeling
Friant Ranch Community
Friant, California
2030 No-Project
Conditions
2030 With-Project
Conditions
Segment
Name
Segment Description
(Listed North to South)
2030 Project Trips
4086
DPM2 TOG:

Diesel3
TOG:

Gasoline4
2031 0.0199 0.0350 0.0654
2032 0.0197 0.0343 0.0630
2033 0.0195 0.0337 0.0606
2034 0.0193 0.0331 0.0581
2035 0.0191 0.0326 0.0558
2036 0.0189 0.0322 0.0542
2037 0.0188 0.0318 0.0528
2038 0.0187 0.0315 0.0515
2039 0.0186 0.0312 0.0503
2040 0.0185 0.0309 0.0491
2041 0.0185 0.0307 0.0482
2042 0.0184 0.0305 0.0474
2043 0.0184 0.0303 0.0470
2044 0.0184 0.0302 0.0465
2045 0.0184 0.0301 0.0461
2046 0.0184 0.0300 0.0458
2047 0.0184 0.0299 0.0455
2048 0.0183 0.0298 0.0452
2049 0.0183 0.0298 0.0450
2050 0.0183 0.0297 0.0448
2051 0.0183 0.0297 0.0448
2052 0.0183 0.0297 0.0448
2053 0.0183 0.0297 0.0448
2054 0.0183 0.0297 0.0448
2055 0.0183 0.0297 0.0448
2056 0.0183 0.0297 0.0448
2057 0.0183 0.0297 0.0448
2058 0.0183 0.0297 0.0448
2059 0.0183 0.0297 0.0448
2060 0.0183 0.0297 0.0448
2061 0.0183 0.0297 0.0448
2062 0.0183 0.0297 0.0448
2063 0.0183 0.0297 0.0448
2064 0.0183 0.0297 0.0448
2065 0.0183 0.0297 0.0448
2066 0.0183 0.0297 0.0448
2067 0.0183 0.0297 0.0448
2068 0.0183 0.0297 0.0448
2069 0.0183 0.0297 0.0448
2070 0.0183 0.0297 0.0448
Table 3a
Traffic Emission Factors for AERMOD modeling1
Friant Ranch Community
Friant, California
Year5
grams/mile
4087
DPM2 TOG:

Diesel3
TOG:

Gasoline4
2071 0.0183 0.0297 0.0448
2072 0.0183 0.0297 0.0448
2073 0.0183 0.0297 0.0448
2074 0.0183 0.0297 0.0448
2075 0.0183 0.0297 0.0448
2076 0.0183 0.0297 0.0448
2077 0.0183 0.0297 0.0448
2078 0.0183 0.0297 0.0448
2079 0.0183 0.0297 0.0448
2080 0.0183 0.0297 0.0448
2081 0.0183 0.0297 0.0448
2082 0.0183 0.0297 0.0448
2083 0.0183 0.0297 0.0448
2084 0.0183 0.0297 0.0448
2085 0.0183 0.0297 0.0448
2086 0.0183 0.0297 0.0448
2087 0.0183 0.0297 0.0448
2088 0.0183 0.0297 0.0448
2089 0.0183 0.0297 0.0448
2090 0.0183 0.0297 0.0448
2091 0.0183 0.0297 0.0448
2092 0.0183 0.0297 0.0448
2093 0.0183 0.0297 0.0448
2094 0.0183 0.0297 0.0448
2095 0.0183 0.0297 0.0448
2096 0.0183 0.0297 0.0448
2097 0.0183 0.0297 0.0448
2098 0.0183 0.0297 0.0448
2099 0.0183 0.0297 0.0448
2100 0.0183 0.0297 0.0448
Max EFs 0.0199 0.0350 0.0654
Notes:

Abbreviations:

DPM: diesel particulate matter
TOG: total organic gas
VMT: vehicle miles travelled
EMFAC: CA ARB's mobile source emission factors

5. Emission Factors in EMFAC are only projected to 2050.

To be conservative, it is assumed that vehicle emissions after this year will be the same as year 2050.

Table 3a (cont')
Traffic Emission Factors for AERMOD modeling1
Friant Ranch Community
Friant, California
Year5
grams/mile

1. Emission factors developed on a gram per mile basis by dividing EMFAC2017 Fresno County emissions by the VMT
for the relevant pollutants, emission factors, and vehicle fuel types as described in the following notes. SAFE factors (Off-Model Adjustment Factors for Gasoline Light Duty
Vehicle Emissions in EMFAC2017) have been applied to the EMFAC values.

2. DPM emission factors calculated based on PM10 running exhaust emissions from diesel fueled vehicles.

3.Diesel TOG emission factors calculated based on TOG
running exhaust emissions from diesel fueled vehicles

4. Gasoline TOG emission factors calculated based on TOG running exhaust and running loss emissions from gasoline fueled vehicles.
4088
DPM TOG: Diesel TOG:

Gasoline
2031 234.67 413.01 772.18
2032 214.31 373.82 686.62
2033 212.21 367.17 660.50
2034 43.08 74.08 129.95
2035 42.65 72.96 124.63
2036 42.31 72.00 121.15
2037 42.01 71.11 118.05
2038 41.76 70.34 115.12
2039 41.56 69.64 112.34
2040 41.41 69.07 109.76
2041 41.31 68.58 107.77
2042 41.22 68.15 106.04
2043 41.20 67.78 104.99
2044 41.11 67.54 104.01
2045 41.07 67.28 103.14
2046 41.04 67.03 102.34
2047 3.12 5.09 7.73
2048 3.12 5.07 7.68
2049 3.12 5.06 7.65
2050 3.12 5.05 7.62
2051 3.12 5.05 7.62
2052 3.12 5.05 7.62
2053 3.12 5.05 7.62
2054 3.12 5.05 7.62
2055 3.12 5.05 7.62
2056 3.12 5.05 7.62
2057 3.12 5.05 7.62
2058 3.12 5.05 7.62
2059 3.12 5.05 7.62
2060 3.12 5.05 7.62
2061 3.12 5.05 7.62
2062 3.12 5.05 7.62
2063 3.12 5.05 7.62
2064 3.12 5.05 7.62
2065 3.12 5.05 7.62
2066 3.12 5.05 7.62
2067 3.12 5.05 7.62
2068 3.12 5.05 7.62
2069 3.12 5.05 7.62
2070 3.12 5.05 7.62
2071 3.12 5.05 7.62
Year2,3
Table 3b
Exposure Weighted Traffic Emission Factors for Annual AERMOD Modeling1 Friant Ranch Community
Friant, California
[(grams/mile)*(L/kg-day)]
4089
DPM TOG: Diesel TOG:

Gasoline
2072 3.12 5.05 7.62
2073 3.12 5.05 7.62
2074 3.12 5.05 7.62
2075 3.12 5.05 7.62
2076 3.12 5.05 7.62
2077 3.12 5.05 7.62
2078 3.12 5.05 7.62
2079 3.12 5.05 7.62
2080 3.12 5.05 7.62
2081 3.12 5.05 7.62
2082 3.12 5.05 7.62
2083 3.12 5.05 7.62
2084 3.12 5.05 7.62
2085 3.12 5.05 7.62
2086 3.12 5.05 7.62
2087 3.12 5.05 7.62
2088 3.12 5.05 7.62
2089 3.12 5.05 7.62
2090 3.12 5.05 7.62
2091 3.12 5.05 7.62
2092 3.12 5.05 7.62
2093 3.12 5.05 7.62
2094 3.12 5.05 7.62
2095 3.12 5.05 7.62
2096 3.12 5.05 7.62
2097 3.12 5.05 7.62
2098 3.12 5.05 7.62
2099 3.12 5.05 7.62
2100 3.12 5.05 7.62
70-year
Weighted
Average

19.59 33.32 57.00
Notes:

Abbreviations:

DPM: diesel particulate matter
TOG: total organic gas
EMFAC: CA ARB's mobile source emission factors
70 Averaging Time (years)

2. Values have a large decrease in 2047 due to the assumed maximum exposed receptor reaching a daily breathing rate of age 16 (see Table 8).

3. Values flatten in 2050, as EMFAC data is only available through 2050; values after this date are therefore
conservative.

1. Exposure weighted emission factors calculated by
weighting the per mile emission factors from Table 3a by the product of a residential receptor's Daily Breathing Rate (DBR), Fraction of Time at Home (FAH), and Age Sensitivity Factor (ASF) for each age group in the given year (starting from third trimester in 2031) consistent with recommended values from 2015 OEHHA guidelines (presented in Table 8).

Year2,3
Table 3b (cont')
Exposure Weighted Traffic Emission Factors for Annual AERMOD Modeling1 Friant Ranch Community
Friant, California
[(grams/mile)*(L/kg-day)] I I
I I
I
4090
VMT Percentage
Diesel 4,254,968 13.3%
Gasoline 26,662,657 83.3%
Electric 1,084,129 3.4%
Natural Gas 16,457 0.1%
Total 32,018,211 100%
Notes:

Abbreviations:

VMT: vehicle miles travelled
Table 4
Diesel and Gasoline Split1 for Traffic Emissions
Calculations
Friant Ranch Community
Friant, California

1. Split based on EMFAC-2011 categories for year 2031 VMT in Fresno County.
4091
Elevation
(m)
Plume Width
(m)
Initial Sigma y
(m)
Length
(m)
Length
(mi)
ROAD_A N. Friant Rd. from Lost Lake to N. Willow Ave. Imported from AERMAP 30 13.95 1402.1 0.871 ROAD_B N. Friant Rd. from Root Ave. to Lost Lake Imported from AERMAP 30 13.95 1138.3 0.707 ROAD_C N. Friant Rd. from Granite Ave. to Root Ave Imported from AERMAP 30 13.95 185.9 0.116 ROAD_D N. Friant Rd. from Parker Ave. to Granite Ave. Imported from AERMAP 30 13.95 340.8 0.212 ROAD_E N. Friant Rd. from Road 206 to Parker Ave. Imported from AERMAP 30 13.95 361.5 0.225 ROAD_F Road 206 from Friant Rd. to Road 145 Imported from AERMAP 15 6.98 338.7 0.210 ROAD_G Millerton Rd. from Road 206 to Winchell Cove Imported from AERMAP 15 6.98 1055.5 0.656 Road Elevated LINE-VOLUME Sources
For all Road Sources:

Release Ht. = 3.05 m
Plume Height = 6.096 m
Initial Sigma z = 1.42 m
Abbreviations:

AERMAP: AERMOD's terrain processor
m: meters
mi: miles
Road
Roadway Line-Volume Source Parameters
Source ID
Table 5
Roadway Source Parameters for Traffic Emissions Calculations Friant Ranch Community
Friant, California
4092
Contaminant DPM2 TOGD TOGG DPM2 TOGD TOGG
EF1 (g/mile) 0.02 0.03 0.07 0.02 0.03 0.07
Percent Fleet 13% 13% 83% 13% 13% 83%
Roadway Link
ROAD_A N/A 1.07E-03 1.26E-02 N/A 3.44E-03 4.03E-02
ROAD_B N/A 5.85E-04 6.85E-03 N/A 2.52E-03 2.95E-02
ROAD_C N/A 6.19E-05 7.25E-04 N/A 3.81E-04 4.46E-03
ROAD_D N/A 1.15E-04 1.35E-03 N/A 7.02E-04 8.22E-03
ROAD_E N/A 1.38E-04 1.61E-03 N/A 7.54E-04 8.84E-03
ROAD_F N/A 1.22E-04 1.42E-03 N/A 7.10E-04 8.32E-03
ROAD_G N/A 8.98E-05 1.05E-03 N/A 1.56E-03 1.83E-02
Note:

2. DPM is not modeled for Acute risk. Instead, TOGs from diesel exhaust (TOGD) are evaluated.

Abbreviations:

DPM: diesel particulate matter
TOGD: total organic gas from diesel
TOGG: total organic gas from gasoline

1. Emission factors are the maximum year emission factors for TOGD and TOGG from Table 3a.

Table 6a
Traffic Emission Rates for Acute Impact AERMOD Modeling Friant Ranch Community
Friant, California
Project Emissions
(grams/sec)
Cumulative (2030 With-Project) Emissions
(grams/sec)
4093
Contaminant DPM TOGD2 TOGG DPM TOGD2 TOGG
EF
[(grams/mile)*(L/kg-day)]1 19.6 33.3 57.0 19.6 33.3 57.0 Percent Fleet 13% 13% 83% 13% 13% 83%
Chronic Risk Correction Factor3 0.0010 0.0011 0.0011 0.0010 0.0011 0.001 Roadway Link
ROAD_A 3.18E-01 N/A 5.79E+00 1.02E+00 N/A 1.86E+01
ROAD_B 1.73E-01 N/A 3.16E+00 7.46E-01 N/A 1.36E+01
ROAD_C 1.83E-02 N/A 3.34E-01 1.13E-01 N/A 2.06E+00
ROAD_D 3.41E-02 N/A 6.22E-01 2.08E-01 N/A 3.79E+00
ROAD_E 4.07E-02 N/A 7.42E-01 2.23E-01 N/A 4.07E+00
ROAD_F 3.60E-02 N/A 6.56E-01 2.10E-01 N/A 3.83E+00
ROAD_G 2.66E-02 N/A 4.85E-01 4.61E-01 N/A 8.41E+00
Note:

1.The emission factor is the weighted average as calculated in Table 3b.

2. TOGD (TOGs from diesel exhaust) are not analyzed for annual (long-term) impacts. Instead, DPM is analyzed for annual impacts.

Abbreviations:

DPM: diesel particulate matter
TOGD: total organic gas from diesel
TOGG: total organice gas from gasoline

3. The Chronic Risk Correction Factor is the maximum year emission factors for DPM, TOGD and TOGG from Table 3a, divided by the Exposure weighted chronic traffic emissions, in order to calculate chronic risk without including the Exposure Parameters.

Table 6b
Exposure Weighted Traffic Emission Rates for Annual AERMOD Modeling Friant Ranch Community
Friant, California
Project Emissions
(grams/sec*(L/kg-day))
Cumulative (2030 With-Project)
Emissions (grams/sec*(L/kg-day))
4094
Hour DPM2 TOG: Diesel3 TOG: Gasoline4
1 0.939 N/A 0.138
2 0.488 N/A 0.069
3 0.817 N/A 0.070
4 1.549 N/A 0.045
5 0.886 N/A 0.072
6 1.215 N/A 0.248
7 1.792 N/A 0.821
8 1.224 N/A 1.533
9 1.218 N/A 1.554
10 1.514 N/A 1.291
11 1.577 N/A 1.400
12 1.559 N/A 1.538
13 1.401 N/A 1.574
14 1.433 N/A 1.578
15 1.085 N/A 1.722
16 0.743 N/A 1.796
17 1.025 N/A 1.933
18 0.588 N/A 2.097
19 0.630 N/A 1.428
20 0.271 N/A 1.031
21 0.501 N/A 0.771
22 0.822 N/A 0.637
23 0.413 N/A 0.395
24 0.312 N/A 0.258
Notes:

Abbreviations:

DPM: diesel particulate matter
TOG: total organic gas

4. Gasoline TOG hourly scalars calculated based on TOG running exhaust and running loss emissions from gasoline fueled vehicles.

Table 7
Hourly Scalars for Annual (Long-Term) AERMOD modeling1
Friant Ranch Community
Friant, California

1. Calculated as a percentage of predicted total emissions per hour for Fresno County in 2031 from EMFAC-2017 (run in burden mode).

Hourly scalers used only in Annual (Long-Term) AERMOD modeling runs.

2. DPM hourly scalars estimated based on PM10 running exhaust emissions from diesel fueled vehicles.

3. Diesel TOG hourly scalers not required because TOGD is not analyzed in long-term modeling.
4095
Table 8
Residential Receptor Exposure Parameters
Friant Ranch Community
Friant, California
Daily Breathing
Rate (DBR)1
(L/kg-day)
Exposure
Duration (ED)2
(years)
Fraction of
Time at Home
(FAH)3
(unitless)
Exposure
Frequency
(EF)4
(days/year)
Averaging Time
(AT)
(days)
Age Sensitivity
Factor5
(ASF)
3rd Trimester Duration 361 0.25 1 350 25,550 10
Infant Exposure (0<2 Years ) 1090 2 1 350 25,550 10
Child Exposure (2<16 Years) 745 14 1 350 25,550 3
Adult Exposure (16-70 Years ) 233 54 0.73 350 25,550 1
Equation used:

IFinh = DBR * ET * EF * ED * ASF * FAH * CF / AT
CF: 0.001 (m3/L)
Notes:

Abbreviations:

DBR: daily breathing rates
ET: exposure time (hours/24 hours)
EF: exposure frequency
ED: exposure duration
ASF: age sensitivity factor
FAH: fraction at home
CF: conversion factor
AT: averaging time
OEHHA: Office of Environmental Health Hazard Assessment kg: kilogram
L: liter
m3: cubic meters
Reference:

5. Age sensitivity factors for each age group are consistent with OEHHA 2015 guidance. ASFs were incorporated into the exposure weighted AERMOD modeled emissions rates as presented in Table 3b.

OEHHA 2015. Air Toxics Hot Spots Program, Risk Assessment Guidelines, Guidance Manual for Preparation of Health Risk Assessments, Office of Environmental Health Hazard Assessment (OEHHA), February 2015. Available online at: http://oehha.ca.gov/air/hot_spots/hotspots2015.html.

Receptor Age Group
Exposure Parameter

1. Daily breathing rates reflect default breathing rates from OEHHA 2015 as follows: 95th percentile for children <16 years, and 80th percentile for adults 16- 70 years. For this cancer risk analysis, daily breathing rates were incorporated into the exposure weighted AERMOD modeled emissions rates as presented in Table 3b.

2. The total exposure duration for operation reflects the default residential exposure duration from OEHHA 2015.

3. Fraction of time at home was conservatively assumed to be 1 for age groups younger than 16 years old (100%). The FAH of 0.73 for age group 16 and above reflects the default value from OEHHA 2015. For this cancer risk analysis, FAH values were incorporated into the exposure weighted AERMOD modeled emissions rates as presented in Table 3b.

4. Exposure frequency (EF) reflects default exposure frequency for residents from OEHHA 2015. 4096
Table 9
Toxicity Values
Friant Ranch Community
Friant, California
Cancer Potency
Factor
Chronic Reference
Exposure Level
Acute Reference
Exposure Level
(mg/kg-day)-1 (µg/m3) (µg/m3)

1.10 5.0 --
1,3-Butadiene 0.60 2 -
Acetaldehyde 0.01 140 470
Acrolein - 0 3
Benzene 0.10 3 27
Ethylbenzene 0.01 2000 -
Formaldehyde 0.02 9 55
Hexane - 7000 -
Methanol - 4000 28000
Methyl ethyl ketone - - 13000
Naphthalene 0.12 9 -
Propylene - 3000 -
Styrene - 900 21000
Toluene - 420 5000
Xylenes - 700 22000
1,3-butadiene - - 660
Benzene - - 27
M-xylene - - 22000
O-xylene - - 22000
Toluene - - 5000
Acetaldehyde - - 470
Formaldehyde - - 55
Notes:

All toxicity values from Cal/EPA (2020).
-- not available
Abbreviations:
(mg/kg-day): milligram per kilogram-day
µg/m3: micrograms per cubic meter
ARB: California Air Resources Board
Cal/EPA: California Environmental Protection Agency
DPM: diesel particulate matter
HI: hazard index
OEHHA: Office of Environmental Health Hazard Assessment TAC: toxic air contaminant
TOG: total organic gas
Reference:

California Environmental Protection Agency (Cal/EPA). 2020. OEHHA/ARB Consolidated Table of Approved Risk Assessment Health Values. Updated Oct. 2, 2020. http://www.arb.ca.gov/toxics/healthval/contable.pdf Chemical
Diesel Particulate Matter (DPM)1

1. Diesel Particulate Matter (DPM) is used as a surrogate measure of carcinogen and chronic non-cancer exposure for the mixture of chemicals that make up diesel exhaust as a whole. There is currently no acute non-cancer toxicity value available for DPM. Accordingly, acute impacts from diesel combustion engines are typically not evaluated. As a conservative measure for traffic related emissions, speciated components of diesel total organic gas exhaust emissions (TOG) with acute toxicity values were included in the acute non-cancer hazard analysis.

2. Cancer potenty factors from TOG represent only the chemicals from the gasoline components (any diesel related emissions chemical potencies are incorporated as part of the DPM CPF).

TACS from
TOGG2
TACS from
TOGD
4097
Table 10
Vehicle Exhaust TOG Weight Fractions
Friant Ranch Community
Friant, California
1,3-Butadiene 106-99-0 0.0055
Acetaldehyde 75-07-0 0.0028
Acrolein 107-02-8 0.0013
Benzene 71-43-2 0.0247
Ethylbenzene 100-41-4 0.0105
Formaldehyde 50-00-0 0.0158
Hexane 110-54-3 0.0160
Methanol 67-56-1 0.0012
Methyl ethyl ketone 78-93-3 0.0002
Naphthalene 91-20-3 0.0005
Propylene 115-07-1 0.0306
Styrene 100-42-5 0.0012
Toluene 108-88-3 0.0576
Xylenes 1330-20-7 0.0480
1,3-butadiene 106-99-0 0.029
Benzene 71-43-2 0.044
M-xylene 108-38-3 0.029
O-xylene 95-47-6 0.018
Toluene 108-88-3 0.051
Acetaldehyde 75-07-0 0.0291
Formaldehyde 50-00-0 0.0861
TOGs from Diesel (TOGD) - Light Duty Vehicles2

1. Gasoline TOG Speciation from BAAQMD "Recommended
Methods for Screening and Modeling Local Risks and Hazards," Table 14.

2. Diesel TOG Speciation from EPA Speciation Profile 1201 (LDV) and 95227 (HDV). Only the chemicals with acute risk RELs are listed. Summing LDV and HDV weighted RELs to be conservative.

Chemical CAS Number Weight Fraction
TOGs from Gasoline (TOGG)1
TOGs from Diesel (TOGD) - Heavy Duty Vehicles2

I I I I
4098
(in one million)
Onsite MEI 10.5 0.002 0.0058
Offsite MEI 17.5 0.004 0.0098
20 1 1
No No No
Notes:

Abbreviations:
m: meter
µg/m3: micrograms per cubic meter
HI: hazard index
MEI: maximally exposed individual
Table 11
Modeled Excess Lifetime Cancer Risk, and Chronic and Acute Hazard Indices - Project Friant Ranch Community
Friant, California
Source Receptor Type
Cancer Risk1
Acute HI2 Chronic HI2
Project Operations (Traffic and Emergency
Generators)

2. The potential for exposure to result in adverse chronic and acute non-cancer effects is evaluated by comparing the estimated annual average and one-hour maximum air concentration to the non-cancer chronic and acute REL for each chemical, respectively. When calculated for a single chemical, the comparison yields a ratio termed a hazard quotient. To evaluate the potential for adverse chronic and acute noncancer health effects from simultaneous exposure to multiple chemicals, the hazard quotients for all chemicals are summed, yielding a hazard index. The chronic and acute hazard indices attributed to the emissions associated with operation of the Project and non-project traffic were calculated based on the modeled annual average and one-hour maximum air concentrations, respectively, and the chronic and acute reference exposure levels presented in Table 9.

SJVAPCD Project Significance Threshold

1. Excess lifetime cancer risks are estimated as the upper-bound incremental probability that an individual will develop cancer over a lifetime as a direct result of exposure to potential carcinogens. The estimated risk is expressed as a unitless probability. The cancer risks attributed to the emissions associated with operation of the Project were conservatively calculated based on the maximum modeled annual average air concentrations over the five modeled years, the intake factors presented in Table 8, and the CPFs presented in Table 9.

Exceed Threshold?
4099
(in one million)
Onsite MEI 34 0.008 0.011
Offsite MEI 45 0.010 0.015
Offsite Stationary Sources3 N/A <10 -- --
Cumulative Total Onsite MEI <44 0.008 0.011
Cumulative Total Offsite MEI <55 0.010 0.015
100 10 10
No No No
Notes:
-- not available
Abbreviations:

MEI: maximally exposed individual
HI: hazard index
Reference:

Table 12
Excess Lifetime Cancer Risk, and Chronic and Acute Hazard Indices - Cumulative Friant Ranch Community
Friant, California
Source Receptor Type
Cumulative
Cancer Risk1 Acute HI2 Chronic HI2

3. Offsite stationary sources included one gas station (that dispenses around one million gallons per day as per SJVAPCD staff) within 600 feet of the project. According to the California Environmental Protection Agency (Cal/EPA 2005), a cancer risk of less than 10 in a million is expected at the fenceline of a gas station dispensing less than 3.6 million gallons per day. Conservatively, in the cumulative health risk assessment it was assumed that a cancer risk impact of <10 in a million applied to both onsite and offsite receptors, regardless of their distance to the gas station.

Cal/EPA. 2005. Air Quality and Land Use Handbook: A Community Health Perspective. April. Available online at:
http://www.arb.ca.gov/ch/handbook.pdf.

Project Operations + Non-Project
Traffic

1. Excess lifetime cancer risks are estimated as the upper-bound incremental probability that an individual will develop cancer over a lifetime as a direct result of exposure to potential carcinogens. The estimated risk is expressed as a unitless probability. The cancer risks attributed to the cumulative emissions associated with operation of the Project and non-project traffic were calculated based on the modeled annual average air concentrations over the five modeled years, the intake factors presented in Table 8, and the cancer potency factors presented in Table 9.

When calculated for a single chemical, the comparison yields a ratio termed a hazard quotient. To evaluate the potential for adverse chronic and acute noncancer health effects from simultaneous exposure to multiple chemicals, the hazard quotients for all chemicals are summed, yielding a hazard index. The chronic and acute hazard indices attributed to the emissions associated with operation of the Project and non-project traffic were calculated based on the modeled annual average and one-hour maximum air concentrations, respectively, and the chronic and acute reference exposure levels presented in Table 9.

CEQA Cumulative Significance Threshold
Exceed Threshold?
4100
Friant Ranch Community Development Project Health Risk Assessment Report

FIGURES
4101
Friant Ranch Community Development Project Health Risk Assessment Report Figure 1: Friant Ranch Community AERMOD Model Set-Up
aff•Slte Rccepwrs
Specific Plan
- M(;J(lele(l ROOdways
4102

CALIFORNIA STATE UNIVERSITY, ENVIRONMENTAL IMPACT REPORT DOMINGUEZ HILLS CAMPUS MASTER PLAN 2018
B.4 Ramboll – Air Quality Impacts Analysis 2019
4103
Prepared by
Ramboll US Corporation
San Francisco
Project Number
1690013624
Date
July 2019
CALIFORNIA STATE UNIVERSITY–

DOMINGUEZ HILLS

AIR QUALITY IMPACTS ANALYSIS

CARSON, CALIFORNIA

RAMB LL
4104
California State University – Dominguez Hills
Contents i Ramboll

CONTENTS

1. INTRODUCTION 1

2. TECHNICAL APPROACH 3

3. RESULTS 5

APPENDICES
Appendix A: Emissions Inventory, Spatial Allocation, and SMOKE Setup Appendix B: PGM Inputs, Outputs, and Assumptions
Appendix C: BenMAP and Health Outcomes
Appendix D: Resumes of Technical Staff
4105
California State University – Dominguez Hills
Introduction 1 Ramboll

1. INTRODUCTION
This report presents an estimate of the potential health impact of the emissions of criteria pollutants that may result from the adoption and implementation of California State University Dominguez Hills (CSUDH)’s 2018 Campus Master Plan (the proposed Project). The proposed Project retains the existing campus enrollment cap of 20,000 full-time-equivalent students (FTES), while providing a framework for development of the University’s campus in a forward-looking manner that accommodates growth from the current enrollment of approximately 11,000 FTES to the maximum enrollment of 20,000 FTES over a planning horizon extending to 2035.

As background, Environmental Impact Reports (EIRs) prepared pursuant to the California Environmental Quality Act (CEQA) have long evaluated project-related health impacts of toxic air contaminants, such as diesel particulate matter, through quantitative and/or qualitative means relative to air district-issued thresholds of significance. However, EIRs historically have not evaluated the specific health impacts of project-related increases in criteria pollutants,1 other than to note and summarize scientific literature regarding the general effect of those pollutants on health. Instead, in accordance with air district-issued thresholds of significance and industry standard practice at the time, CEQA analysis historically and traditionally focused on estimating project-related mass emissions totals for criteria pollutants and, in certain cases, conducting dispersion modeling to assess impacts on local ambient air quality concentrations.

In response to comment on the proposed Project’s Draft EIR, and in light of a cited decision issued by the California Supreme Court issued in December 2018, this analysis estimates the health impacts of criteria pollutants and their precursors, specifically those that are evaluated by the U.S. Environmental Protection Agency (USEPA) in rulemaking setting the national ambient air quality standards: oxides of nitrogen (NOx), volatile organic compounds (VOC), carbon monoxide (CO), ozone (O3), sulfur dioxide (SO2), and particulate matter smaller than 2.5 microns in diameter2 (PM2.5). NOx and VOCs are not criteria air pollutants but, in the presence of sunlight, they form O3 and contribute to the formation of secondary PM2.5 and thus are analyzed here. As a conservative measure, SO2 and CO are evaluated due to their small contribution to the formation of secondary PM2.5 and ozone. The health impacts from O3 and PM2.5 are examined for this Project because the USEPA has determined that these criteria pollutants would have the greatest impact to human health. The emissions of other criteria pollutants, including VOC, NOx and SO2, are analyzed in their contribution in the formation of O3 and secondary PM2.5.

Notably, CEQA practitioners and other expert agencies (like air districts) are still developing tools and methodologies to provide the type of CEQA analysis described in the California Supreme Court’s decision. In this report, Ramboll presents one method that can be used to correlate project-related mass emissions totals for criteria pollutants to estimated health-based consequences. More specifically, in order to estimate the health impacts of the increases of criteria pollutants for the 1 Criteria pollutants are those pollutants with an air pollution standard or pollutants which are precursors to those with a standard. Pollutants with an air pollution standard include nitrogen dioxide, sulfur dioxide, ozone, carbon monoxide, particulate matter smaller than 2.5 microns and 10 microns and ozone. Precursor pollutants to criteria pollutants include oxides of nitrogen (NOx), oxides of sulfur (SOx), and volatile organic compounds (VOCs).
2 USEPA’s default health effect functions in BenMAP for PM use fine particulate (PM2.5) as the causal PM agent, so the health effects of PM10 are represented using PM2.5 as a surrogate. 4106
California State University – Dominguez Hills
Introduction 2 Ramboll
proposed Project, Ramboll applied a photochemical grid model (PGM), Comprehensive Air Quality Model with extensions (CAMx),3 to estimate the small increases in concentrations of ozone and PM2.5 in the region as a result of the emissions of criteria and precursor pollutants from the Project. We then applied a USEPA-authored program, the Benefits Mapping and Analysis Program (BenMAP)4, to estimate the resulting health impacts from the small increases in concentration. Only the impacts of ozone and PM2.5 are estimated, as those are the pollutants that USEPA uses in BenMAP to estimate the impact of emissions of NOx, VOCs, CO, SO2, and PM2.5. Ozone and PM2.5 have the most critical health impacts and thus are the emissions evaluated to determine the Project’s health impacts. 3 Comprehensive Air Quality Model with Extensions.
4 https://www.epa.gov/benmap/benmap-ce-manual-and-appendices. 4107
California State University – Dominguez Hills
Technical Approach 3 Ramboll

2. TECHNICAL APPROACH
The first step in the process is to run the PGM with appropriate information to assess the small increases in ambient air concentrations that the Project emissions may cause. PGMs require a database of information, including the spatial allocation of emissions, in the area to be modeled. This includes both base (background/existing) emissions and Project emissions. The latest publicly available PGM database for Southern California, which contains base emissions, was developed by the South Coast Air Quality Management District (SCAQMD) in support of its adopted 2016 Air Quality Management Plan (AQMP)5 and was adapted for use in this analysis. This PGM database is tailored for Southern California (including Los Angeles County) using California-specific input tools (e.g., the Emission FACtors (EMFAC)6 mobile source emissions model) and uses a high-resolution 4- kilometer (km) horizontal grid to better simulate meteorology and air quality in the complex terrain and coastal environment of California.

Project emissions included NOX, SO2, CO, respirable (PM10) and fine (PM2.5) primary particulate matter (PM), and VOCs. As discussed above, NOX and VOC are precursors to ozone and, along with SO2, are also precursors to secondarily formed PM2.5. CO also plays a smaller role in the formation of ozone and is thus conservatively evaluated here.

The USEPA’s air quality modeling guidelines (Appendix W7) and ozone and PM2.5 modeling guidance8 recommend using a PGM to estimate ozone and secondary PM2.5 concentrations. The USEPA’s modeling guidance does not recommend specific PGMs but provides procedures for determining an appropriate PGM on a case-by-case basis. Both the modeling guidelines and guidance note that the CAMx9 and the Community Multiscale Air Quality (CMAQ10) PGMs have been used extensively in the past and would be acceptable PGMs. As such, the USEPA has prepared a memorandum11 documenting the suitability for using CAMx and CMAQ for ozone and secondary PM2.5 modeling of single-sources or group of sources.

To estimate the potential impacts of the proposed Project’s emissions on ambient air concentrations, the Project’s emissions were added to the CAMx 4-km annual PGM modeling database.12 Operational and construction emissions from the Project were estimated as described in the Air Quality Section of the Draft EIR.13 For almost all pollutants, for any year, the maximum operational emissions at full buildout were greater than construction emissions. The exception is VOCs from architectural coatings during one year of construction. In order to estimate the worst-case impacts, the emissions from the highest year of construction VOCs were added to the full buildout emissions of all other pollutants. By 5 https://www.aqmd.gov/home/air-quality/clean-air-plans/air-quality-mgt-plan/final-2016-aqmp. 6 https://www.arb.ca.gov/emfac/.
7 https://www3.epa.gov/ttn/scram/appendix_w/2016/AppendixW_2017.pdf. 8 https://www3.epa.gov/ttn/scram/guidance/guide/O3-PM-RH-Modeling_Guidance-2018.pdf. 9 http://www.camx.com/.
10 https://www.epa.gov/cmaq.
11 https://www3.epa.gov/ttn/scram/guidance/clarification/20170804- Photochemical_Grid_Model_Clarification_Memo.pdf.
12 SCAQMD performed WRF meteorological modeling for the CCOS 4-km domain and 2012 calendar year that has been processed by WRFCAMx to generate CAMx 2012 4-km meteorological inputs for the CCOS domain. The CMAQ 2012 emissions have been converted to the format used by CAMx using the CMAQ2CAMx processor. 13 To the extent that the Draft EIR used conservative inputs to estimate Project-related criteria pollutants and precursors, the analysis provided herein also is conservatively influenced by those inputs. 4108
California State University – Dominguez Hills
Technical Approach 4 Ramboll
doing this, the results below present a worst-case analysis for the construction years and operational years.

For use in PGMs, each Project emissions source must be spatially distributed across the modeling grid cells so that they can be incorporated into the gridded emission inventory. The total unmitigated emission inventory for the Project was used in the analysis. This includes architectural coatings, VOCs in consumer products, natural gas combustion, landscaping, and emissions associated with motor vehicle use. The emissions from architectural coatings, consumer products, natural gas combustion, and landscaping are located onsite, and were therefore allocated to the grid cells representing the Project site (the University campus). The mobile source category includes both passenger vehicles and trucks. The mobile sources are also spatially distributed in both the site’s grid cells, as well as the immediately adjacent grid cells. While it is expected that passenger vehicles and trucks may travel some distance outside of the Project site, they were conservatively distributed near the site’s grid cells based on travel routes. Annual emission estimates from the Project were spatially gridded, temporally allocated, and chemically speciated to be used for photochemical grid modelling using the Sparse Matrix Operating Kernel Emissions (SMOKE) emissions modelling system supported by the USEPA. The emissions inventory, spatial allocation, and SMOKE inputs and outputs are shown in Appendix A.

As discussed above, the SCAQMD’s Southern California 2016 AQMP modeling database was used for this Project. The Southern California 4-km CAMx modeling databases is based on a 2012 base meteorological year and includes future year emission scenarios. The 2023 future year projections were used for this analysis, as that is the nearest future year with base emissions available as of the date of this report. The Project’s emissions were tagged for treatment by the source apportionment tools in CAMx to obtain the incremental ozone and PM2.5 concentration impacts due to the Project’s emissions. More details and inputs for the PGM modeling are included in Appendix B.

Following completion of the CAMx source apportionment modeling, Ramboll used the USEPA’s BenMAP14, 15 program to estimate the potential health impacts of the Project’s contribution to ozone and PM2.5 concentration. BenMAP uses the concentration estimates produced by CAMx, along with population and health effect concentration-response (C-R) functions, to estimate various health effects of the concentration increases. BenMAP has a wide history of applications by the USEPA and others, including for local-scale analysis16 as needed for assessing the health impacts of a project’s emissions.

We used the USEPA default BenMAP health effects C-R functions that are typically used in national rulemaking, such as the health effects impact assessment17 for the 2012 PM2.5 National Ambient Air Quality Standard (NAAQS). The health effects that we used for PM2.5 include mortality (all causes), hospital admissions (respiratory, asthma, cardiovascular), emergency room visits (asthma), and acute myocardial infarction (non-fatal). For ozone, the endpoints are mortality, emergency room visits (respiratory) and hospital admissions (respiratory). Details on the BenMAP inputs and outputs and definitions for the health outcomes are shown in Appendix C. 14 https://www.epa.gov/benmap/how-benmap-ce-estimates-health-and-economic-effects-air-pollution. 15 https://www.epa.gov/sites/production/files/2015-04/documents/benmap-ce_user_manual_march_2015.pdf. 16 https://www.epa.gov/benmap/benmap-ce-applications-articles-and-presentations#local. 17 https://www3.epa.gov/ttn/naaqs/standards/pm/data/PM_RA_FINAL_June_2010.pdf. 4109
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3. RESULTS
This section presents the results of the health impact analysis for the incremental increases in PM2.5 and ozone resulting from primary and precursor emissions for these constituents18.

PM2.5-related health outcomes attributed to Project-related increases in ambient air concentrations included asthma-related emergency room visits (4.38 incidences per year), asthma-related hospital admissions (0.38 incidences per year), all cardiovascular-related hospital admissions (not including myocardial infarctions) (1.05 incidences per year), all respiratory-related hospital admissions (2.44 incidences per year), mortality (10.31 incidences per year), and nonfatal acute myocardial infarction (less than 0.53 incidences per year for all age groups).

Ozone-related health outcomes attributed to Project-related increases in ambient air concentrations included respiratory-related hospital admissions (0.67 incidences per year), mortality (0.28 incidences per year), and asthma-related emergency room visits for any age range (lower than 3.38 incidences per year for all age groups).

For all these health endpoints, the number of estimated incidences is less than 0.0058% of the background health incidence. The “background health incidence” is the actual incidence of health effects as measured in the local population in the absence of additional emissions from the Project. When taken into context, the small increase in incidences and the very small percent of the number of background incidences indicate that these health impacts are negligible in a developed, urban environment. Because the health impacts from ozone and PM2.5 were negligible in light of background incidences, and health impacts from other criteria pollutants would be even smaller, the health impacts of those other criteria pollutants were not quantified.

UNCERTAINTY
Analyses that evaluate the increases in concentrations resulting from individual sources, and the health impacts of increases or decreases in pollutants as a result of regulation on a localized basis are routinely done. This analysis does not tie the increase in concentration to a specific health impact in an individual; however, it does use scientific correlations of certain types of health impacts from pollution to estimate increases in effects to the population at large.

There is a degree of uncertainty in these results from a combination of the uncertainty of the increase in concentration resulting from the PGM and the uncertainty of the application of the C-R increase. All simulations of physical processes, whether ambient air concentrations, or health impacts from air pollution, have a level of uncertainty associated with them, due to simplifying assumptions. The overall uncertainty is a combination of the uncertainty associated with each piece of the modeling study, in this case, the emissions model, the PGM, and BenMAP. While these results reflect a level of uncertainty, regulatory agencies, including the USEPA have judged that, even with the uncertainty in the results, the results provide sufficient information to the public to allow them to understand the health effects of increases or decreases in air pollution. In addition, the health impacts estimation using this method presumes that impacts seen at large concentration differences can be linearly scaled down to small increases in concentration. This 18 Health outcomes presented above also conservatively utilize maximum daily emissions, assumed to occur for an entire year. Should average daily emissions be used, results would be even lower. Specifically for mortality impacts from PM2.5 emissions, average daily emissions would be approximately 20% lower, and the corresponding morality incidence rate would be similarly lower. 4110
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Results 6 Ramboll
methodology of linearly scaling impacts is broadly accepted for use in regulatory evaluations and is considered as being health protective.19 These health impacts are conservatively estimated, and the actual impacts may be zero.
19 USEPA (2010). Quantitative Risk Assessment for Particulate Matter – Final Report. Office of Air Quality Planning and Standards, U.S. Environmental Protection Agency, Research Triangle Park, NC. EPA-452/R10-005. June 2010. Available:
https://www3.epa.gov/ttn/naaqs/standards/pm/data/PM_RA_FINAL_June_2010.pdf. 4111
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Ramboll

APPENDIX A

EMISSIONS INVENTORY, SPATIAL ALLOCATION, AND SMOKE SETUP 4112
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APPENDIX A

EMISSIONS INVENTORY, SPATIAL ALLOCATION, AND SMOKE SETUP CALIFORNIA STATE UNIVERSITY – DOMINGUEZ HILLS

CARSON, CALIFORNIA
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1. INTRODUCTION
As set forth in the Project’s Draft Environmental Impact Report (EIR), construction and operational emissions from the Project were estimated using methodologies consistent with the California Emissions Estimator Model (CalEEMod®) and Project-specific data, where available. The model employs widely accepted calculation methodologies for emission estimates combined with appropriate default data if site-specific information is not available.

Annual emission estimates from CalEEMod® need to be spatially gridded, temporally allocated, and chemically speciated to be used for photochemical grid modeling. The Sparse Matrix Operating Kernel Emissions (SMOKE) emissions modeling system (Coats, 1996; Coats and Houyoux, 1996)1 is used for this process.

Development of the gridded Project emissions is described in detail in Section 0.

2. PROJECT EMISSIONS AND SPATIAL ALLOCATION
Emissions were estimated for the Project to support the photochemical grid model (PGM) and are allocated into 4 kilometer (km) x 4 km grid cells. This section describes those emissions and how they were spatially allocated.

2.1 Project Emissions and Spatial Allocation
For use in PGMs, emissions must be spatially allocated over the area so that they can be incorporated into the gridded emission inventory. The total incremental emission inventory for the Project is below in Table 2-1. Mobile source emissions were split into categories based on the EMFAC2014 emission rates. For particulate matter, less than 2.5 microns in diameter (PM2.5) emissions are used in the modelling; less than 10 microns in diameter (PM10) emissions are presented for information below.

Table 2-1. Maximum Daily Criteria Air Pollutant Emissions Estimates Emission Category
ROG NOx PM10 PM2.5 SO2 CO
lbs/day lbs/day lbs/day lbs/day lbs/day lbs/day
Mobile 38.4 220.2 284.2 76.8 2.6 499.2
Diurnal 2.4 0.0 0.0 0.0 0.0 0.0
Hotsoak 5.8 0.0 0.0 0.0 0.0 0.0
Idling Exhaust 0.2 1.3 0.0 0.0 0.0 2.0
Brakewear 0.0 0.0 1.0 1.0 0.0 0.0
Tirewear 0.0 0.0 0.2 0.1 0.0 0.0
Resting Loss 2.4 0.0 0.0 0.0 0.0 0.0
Road Dust 0.0 0.0 283.0 75.7 0.0 0.0
Running Exhaust 5.1 181.4 0.0 0.1 2.5 381.7
Running Loss 19.6 0.0 0.0 0.0 0.0 0.0
Starting Exhaust 2.8 37.5 0.0 0.0 0.1 115.5
Energy 2.0 17.4 1.4 1.4 0.1 12.1
Consumer Products 93.9 0.0 0.0 0.0 0.0 0.0
1 https://www.cmascenter.org/smoke/.
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Landscaping 6.5 2.5 1.2 1.2 0.0 216.3
Architectural Coatings 341.9 0.0 0.0 0.0 0.0 0.0
Operational 9.9 0.0 0.0 0.0 0.0 0.0
Construction (2024) 332 0.0 0.0 0.0 0.0 0.0
Abbreviations:

CO - Carbon Monoxide
lbs – Pounds
NOx - Nitrogen Oxides
PM2.5. - Particulate Matter less than 2.5 microns in diameter PM10. - Particulate Matter less than 10 microns in diameter ROG - Reactive Organic Gas
SO2 - Sulfur Dioxide
All emissions listed in Table 2-1 represent the maximum daily operational emissions estimated for the proposed Project’s 2035 buildout scenario, aside from the construction architectural coatings emissions (labeled as such). This analysis utilizes the 2035 operational emissions as they constitute the highest maximum daily emissions for the Project, with the exception of 2024 Reactive Organic Gas (ROG) emissions from architectural coatings during construction. Those emissions were also included as a conservative approach, as they represent the highest maximum daily total Volatile Organic Compounds (VOC)2 emissions for the Project. The analysis presented here conservatively assumes maximum daily emissions occur over an entire year. Should average daily emissions be used, corresponding results would be approximately 20% lower.

Mobile emissions include light, medium, and heavy-duty vehicles. Table 2-2 below provides a summary of the spatial distribution of mobile emissions broken down by major freeway. Values in this table were calculated based on estimated average vehicle miles traveled (VMT) during the operational phase of the Project. VMT were estimated based on peak hour traffic demands on various freeway routes located near the Project site, using data provided in the proposed Project’s Transportation Impact Study3(Appendix F of the Draft EIR).

Table 2-2. Mobile Emission Distribution
Freeway Distribution (%)
State Route 91 25.0%
Interstate 110 46.6%
Interstate 405 26.8%
Interstate 710 1.6%
Project emissions are allocated evenly across the Project site into 4 km x 4 km grid cells for the PGM.

Figure 2-1 below shows the Project boundary overlay with the 4-km grid. The Project site is shown in 2 ROG means total organic gases minus ARB's "exempt" compounds (e.g., methane, ethane, CFCs, etc.). ROG is similar, but not identical, to USEPA's term "VOC", which is based on USEPA's exempt list, which is slightly different from ARB’s list.
3 Appendix F of the Draft Environmental Impact Report for the 2018 Campus Master Plan. Available at:
https://www.csudh.edu/Assets/csudh-sites/fpcm/docs/campus-master-plan/csudh-cmp-deir-2019-appendicesupdated.pdf. Accessed: June 2019. 4115
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green, and the major roadways are shown in red. The 4x3 grid is presented on the figure with 12 blue grid cells. For major roadways that cross into multiple cells, emissions were allocated proportionally based on the length of roadway within each cell.

Figure 2-1. Overlap of Model Grid Cells on Project Site

2.2 Convert Project Inventories to SMOKE Input Format
The first step in the emissions processing was to convert the Project emission inventory into the Flat File 2010 (FF10) format for input to SMOKE. We assigned appropriate Source Classification Codes (SCCs) to the Project emissions sources. Table 2-3 provides the SCC assigned to each Project source.

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Table 2-3. Assigned SCC to Project Emission Sources
Emission Source SCC SCC Description
Energy 2102006000
Stationary Source Fuel Combustion; Industrial; Natural Gas; Total: Boilers and IC Engines
Landscaping 2265004010
Mobile Sources; Off-highway Vehicle Gasoline, 4-Stroke; Lawn and Garden Equipment; Lawn Mowers (Residential)
Fugitive Dust 2294000000
Mobile Sources; Paved Roads; All Paved Roads; Total:

Fugitives
Architectural Coating 2401001000
Solvent Utilization; Surface Coating; Architectural Coatings; Total: All Solvent Types
Consumer Products 2460000000
Solvent Utilization; Miscellaneous Non-industrial: Consumer and Commercial; All Processes; Total: All Solvent Types Consumer Products 2460100000
Solvent Utilization; Miscellaneous Non-industrial: Consumer and Commercial; All Personal Care Products; Total: All
Solvent Types
Consumer Products 2460200000
Solvent Utilization; Miscellaneous Non-industrial: Consumer and Commercial; All Household Products; Total: All Solvent Types
Consumer Products 2460400000
Solvent Utilization; Miscellaneous Non-industrial: Consumer and Commercial; All Automotive Aftermarket Products; Total:

All Solvent Types
Consumer Products 2460500000
Solvent Utilization; Miscellaneous Non-industrial: Consumer and Commercial; All Coatings and Related Products; Total: All Solvent Types
Consumer Products 2460600000
Solvent Utilization; Miscellaneous Non-industrial: Consumer and Commercial; All Adhesives and Sealants; Total: All
Solvent Types
Consumer Products 2460800000
Solvent Utilization; Miscellaneous Non-industrial: Consumer and Commercial; All FIFRA Related Products; Total: All
Solvent Types
Consumer Products 2460900000
Solvent Utilization; Miscellaneous Non-industrial: Consumer and Commercial; Miscellaneous Products (Not Otherwise
Covered); Total: All Solvent Types
Mobile -LDA 220100111B
Mobile Sources; Highway Vehicles - Gasoline; Light Duty Gasoline Vehicles (LDGV); Rural4 Interstate: Brake Wear Mobile -LDA 220100111R
Mobile Sources; Highway Vehicles - Gasoline; Light Duty Gasoline Vehicles (LDGV); Rural Interstate: Resting Loss Mobile -LDA 220100111S
Mobile Sources; Highway Vehicles - Gasoline; Light Duty Gasoline Vehicles (LDGV); Rural Interstate: Start
Mobile -LDA 220100111T
Mobile Sources; Highway Vehicles - Gasoline; Light Duty Gasoline Vehicles (LDGV); Rural Interstate: Tire Wear
Mobile -LDA 220100111V
Mobile Sources; Highway Vehicles - Gasoline; Light Duty Gasoline Vehicles (LDGV); Rural Interstate: Evap (except Refueling)
Mobile -LDA 220100111X
Mobile Sources; Highway Vehicles - Gasoline; Light Duty Gasoline Vehicles (LDGV); Rural Interstate: Exhaust
4 Rural and Urban mobile designations provide equivalent chemical speciation and temporal distributions, as the EMFAC mobile emissions model does not distinguish between the two. 4117
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Emission Source SCC SCC Description
Mobile -LDT1 220102011B
Mobile Sources; Highway Vehicles - Gasoline; Light Duty Gasoline Trucks 1 & 2 (M6) = LDGT1 (M5); Rural Interstate:

Brake Wear
Mobile -LDT1 220102011R
Mobile Sources; Highway Vehicles - Gasoline; Light Duty Gasoline Trucks 1 & 2 (M6) = LDGT1 (M5); Rural Interstate:

Resting Loss
Mobile -LDT1 220102011S
Mobile Sources; Highway Vehicles - Gasoline; Light Duty Gasoline Trucks 1 & 2 (M6) = LDGT1 (M5); Rural Interstate:

Start
Mobile -LDT1 220102011T
Mobile Sources; Highway Vehicles - Gasoline; Light Duty Gasoline Trucks 1 & 2 (M6) = LDGT1 (M5); Rural Interstate:

Tire Wear
Mobile -LDT1 220102011V
Mobile Sources; Highway Vehicles - Gasoline; Light Duty Gasoline Trucks 1 & 2 (M6) = LDGT1 (M5); Rural Interstate:

Evap (except Refueling)
Mobile -LDT1 220102011X
Mobile Sources; Highway Vehicles - Gasoline; Light Duty Gasoline Trucks 1 & 2 (M6) = LDGT1 (M5); Rural Interstate:

Exhaust
Mobile -HHDT 220107011B
Mobile Sources; Highway Vehicles - Gasoline; Heavy Duty Gasoline Vehicles 2B thru 8B & Buses (HDGV); Rural
Interstate: Brake Wear
Mobile -LHDT1 220107011I
Mobile Sources; Highway Vehicles - Diesel; Heavy Duty Diesel Vehicles (HDDV) Class 2B; Rural Interstate: Idling
Mobile -HHDT 220107011R
Mobile Sources; Highway Vehicles - Gasoline; Heavy Duty Gasoline Vehicles 2B thru 8B & Buses (HDGV); Rural
Interstate: Resting Loss
Mobile -HHDT 220107011S
Mobile Sources; Highway Vehicles - Gasoline; Heavy Duty Gasoline Vehicles 2B thru 8B & Buses (HDGV); Rural
Interstate: Start
Mobile -HHDT 220107011T
Mobile Sources; Highway Vehicles - Gasoline; Heavy Duty Gasoline Vehicles 2B thru 8B & Buses (HDGV); Rural
Interstate: Tire Wear
Mobile -HHDT 220107011V
Mobile Sources; Highway Vehicles - Gasoline; Heavy Duty Gasoline Vehicles 2B thru 8B & Buses (HDGV); Rural
Interstate: Evap (except Refueling)
Mobile -HHDT 220107011X
Mobile Sources; Highway Vehicles - Gasoline; Heavy Duty Gasoline Vehicles 2B thru 8B & Buses (HDGV); Rural
Interstate: Exhaust
Mobile -OBUS 220107013B
Mobile Sources; Highway Vehicles - Gasoline; Heavy Duty Gasoline Vehicles 2B thru 8B & Buses (HDGV); Rural Other Principal Arterial: Brake Wear
Mobile -OBUS 220107013I
Mobile Sources; Highway Vehicles - Gasoline; Heavy Duty Gasoline Vehicles 2B thru 8B & Buses (HDGV); Rural Other Principal Arterial: Idling
Mobile -OBUS 220107013R
Mobile Sources; Highway Vehicles - Gasoline; Heavy Duty Gasoline Vehicles 2B thru 8B & Buses (HDGV); Rural Other Principal Arterial: Resting Loss
Mobile -OBUS 220107013S
Mobile Sources; Highway Vehicles - Gasoline; Heavy Duty Gasoline Vehicles 2B thru 8B & Buses (HDGV); Rural Other Principal Arterial: Start
Mobile -OBUS 220107013T
Mobile Sources; Highway Vehicles - Gasoline; Heavy Duty Gasoline Vehicles 2B thru 8B & Buses (HDGV); Rural Other Principal Arterial: Tire Wear
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Emission Source SCC SCC Description
Mobile -OBUS 220107013V
Mobile Sources; Highway Vehicles - Gasoline; Heavy Duty Gasoline Vehicles 2B thru 8B & Buses (HDGV); Rural Other Principal Arterial: Evap (except Refueling)
Mobile -OBUS 220107013X
Mobile Sources; Highway Vehicles - Gasoline; Heavy Duty Gasoline Vehicles 2B thru 8B & Buses (HDGV); Rural Other Principal Arterial: Exhaust
Mobile -MCY 220108011B
Mobile Sources; Highway Vehicles - Gasoline; Motorcycles (MC); Rural Interstate: Brake Wear
Mobile -MCY 220108011R
Mobile Sources; Highway Vehicles - Gasoline; Motorcycles (MC); Rural Interstate: Resting Loss
Mobile -MCY 220108011S
Mobile Sources; Highway Vehicles - Gasoline; Motorcycles (MC); Rural Interstate: Start
Mobile -MCY 220108011T
Mobile Sources; Highway Vehicles - Gasoline; Motorcycles (MC); Rural Interstate: Tire Wear
Mobile -MCY 220108011V
Mobile Sources; Highway Vehicles - Gasoline; Motorcycles (MC); Rural Interstate: Evap (except Refueling)
Mobile -MCY 220108011X
Mobile Sources; Highway Vehicles - Gasoline; Motorcycles (MC); Rural Interstate: Exhaust
Mobile -LDA 223000111B
Mobile Sources; Highway Vehicles - Diesel; Light Duty Diesel Vehicles (LDDV); Rural Interstate: Brake Wear
Mobile -LDA 223000111T
Mobile Sources; Highway Vehicles - Diesel; Light Duty Diesel Vehicles (LDDV); Rural Interstate: Tire Wear
Mobile -LDA 223000111X
Mobile Sources; Highway Vehicles - Diesel; Light Duty Diesel Vehicles (LDDV); Rural Interstate: Exhaust
Mobile -LDT1 223006011B
Mobile Sources; Highway Vehicles - Diesel; Light Duty Diesel Trucks 1 thru 4 (M6) (LDDT); Rural Interstate: Brake Wear Mobile -LDT1 223006011T
Mobile Sources; Highway Vehicles - Diesel; Light Duty Diesel Trucks 1 thru 4 (M6) (LDDT); Rural Interstate: Tire Wear Mobile -LDT1 223006011X
Mobile Sources; Highway Vehicles - Diesel; Light Duty Diesel Trucks 1 thru 4 (M6) (LDDT); Rural Interstate: Exhaust
Mobile -LHDT1 223007111B
Mobile Sources; Highway Vehicles - Diesel; Heavy Duty Diesel Vehicles (HDDV) Class 2B; Rural Interstate: Brake Wear
Mobile -LHDT1 223007111I
Mobile Sources; Highway Vehicles – Diesel; Heavy Duty
Diesel Vehicles (HDDV) Class 2B; Rural Interstate: Idling Mobile -LHDT1 223007111T
Mobile Sources; Highway Vehicles - Diesel; Heavy Duty Diesel Vehicles (HDDV) Class 2B; Rural Interstate: Tire Wear
Mobile -LHDT1 223007111X
Mobile Sources; Highway Vehicles - Diesel; Heavy Duty Diesel Vehicles (HDDV) Class 2B; Rural Interstate: Exhaust
Mobile -MHDT 2230072110
Mobile Sources; Highway Vehicles - Diesel; Heavy Duty Diesel Vehicles (HDDV) Class 3, 4, & 5; Rural Interstate: Total Mobile -LHDT2 223007211B
Mobile Sources; Highway Vehicles - Diesel; Heavy Duty Diesel Vehicles (HDDV) Class 3, 4, & 5; Rural Interstate: Brake Wear
Mobile -LHDT2 223007211I
Mobile Sources; Highway Vehicles - Diesel; Heavy Duty Diesel Vehicles (HDDV) Class 3, 4, & 5; Rural Interstate: Idling 4119
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Emission Source SCC SCC Description
Mobile -LHDT2 223007211T
Mobile Sources; Highway Vehicles - Diesel; Heavy Duty Diesel Vehicles (HDDV) Class 3, 4, & 5; Rural Interstate: Tire Wear Mobile -LHDT2 223007211X
Mobile Sources; Highway Vehicles - Diesel; Heavy Duty Diesel Vehicles (HDDV) Class 3, 4, & 5; Rural Interstate: Exhaust Mobile -HHDT 223007311B
Mobile Sources; Highway Vehicles - Diesel; Heavy Duty Diesel Vehicles (HDDV) Class 6 & 7; Rural Interstate: Brake Wear Mobile -HHDT 223007311I
Mobile Sources; Highway Vehicles - Diesel; Heavy Duty Diesel Vehicles (HDDV) Class 6 & 7; Rural Interstate: Idling
Mobile -HHDT 223007311S
Mobile Sources; Highway Vehicles - Diesel; Heavy Duty Diesel Vehicles (HDDV) Class 6 & 7; Rural Interstate: Start
Mobile -HHDT 223007311T
Mobile Sources; Highway Vehicles - Diesel; Heavy Duty Diesel Vehicles (HDDV) Class 6 & 7; Rural Interstate: Tire Wear Mobile -HHDT 223007311X
Mobile Sources; Highway Vehicles - Diesel; Heavy Duty Diesel Vehicles (HDDV) Class 6 & 7; Rural Interstate: Exhaust
Mobile -OBUS 223007513B
Mobile Sources; Highway Vehicles - Diesel; Heavy Duty Diesel Buses (School & Transit); Rural Other Principal Arterial:

Brake Wear
Mobile -OBUS 223007513I
Mobile Sources; Highway Vehicles - Diesel; Heavy Duty Diesel Buses (School & Transit); Rural Other Principal Arterial: Idling Mobile -OBUS 223007513S
Mobile Sources; Highway Vehicles - Diesel; Heavy Duty Diesel Buses (School & Transit); Rural Other Principal Arterial: Start Mobile -OBUS 223007513T
Mobile Sources; Highway Vehicles - Diesel; Heavy Duty Diesel Buses (School & Transit); Rural Other Principal Arterial: Tire Wear
Mobile -OBUS 223007513X
Mobile Sources; Highway Vehicles - Diesel; Heavy Duty Diesel Buses (School & Transit); Rural Other Principal Arterial:

Exhaust

2.2.1 Generate Spatial Surrogates for 4-km Domains
As part of the analysis, the Project source emissions need to be spatially allocated to appropriate geographic locations. The emissions can be allocated to modeling grid cells using gridding surrogates.

To process the Project emissions, a Project area-based spatial surrogate was developed. The surrogate was developed using the US Environmental Protection Agency (USEPA’s) Spatial Allocation Tool,5 which combines geographical information system (GIS)-based data (shapefiles) and modeling domain definitions to generate the appropriate gridded surrogate data set. The Project sources were then assigned specific surrogates for gridding by cross-referencing the SCCs. As mentioned above, all Project emissions were distributed in the modeling grid cells where the Project is located as shown in Figure 2-1. The mobile sources are spatially distributed in the site’s grid cells and surrounding grid cells, as outlined in Table 2-2.

2.2.2 SMOKE 4 km Processing of Project Emissions
SMOKE system was used to process emissions for the Southern California 4-km modeling grid shown in Figure 2-1. A representative week from each month (seven days a month) was used to represent 5 https://www.cmascenter.org/sa-tools/documentation/4.2/html/srgtool/SurrogateToolUserGuide_4_2.pdf 4120
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the entire month’s emissions. Holidays were modeled separately as if they were a Sunday. SMOKE was applied to perform following tasks:

1. Chemical Speciation: Emission estimates of criteria pollutants were speciated for the SAPRC07 AERO6 chemical mechanism employed in Community Multiscale Air Quality (CMAQ) in SMOKE processing. We used speciation profiles compatible with the SAPRC07 AERO6 mechanism from the SCAQMD’s modeling system to be consistent with the regional modeling emissions. We then converted those emissions into Comprehensive Air Quality Model with extensions (CAMx)-ready formats using CMAQ2CAMx conversion program and species mapping.

2. Temporal Allocation: Annual emission estimates were resolved on an hourly timescale for CAMx modeling. These allocations were determined from the particular source category, specified by the SCC. Monthly, weekly, and diurnal profiles were cross-referenced to the SCCs to provide the appropriate temporal resolution. The temporal profiles were also obtained from the BAAQMD’s emissions modeling system, as they were unavailable from South Coast Air Quality Management District (SCAQMD).

3. Spatial Allocation: The Project emission estimates were spatially resolved to the grid cells for modeling using spatial surrogates as described above.

2.2.3 QA/QC of Emissions Modeling
Standard quality assurance/quality control (QA/QC) was conducted during all aspects of the SMOKE emissions processing. These steps followed the approach recommended in the USEPA modeling guidance (USEPA, 2007). SMOKE includes quality assurance (QA) and reporting features to keep track of the adjustments at each processing stage and ensure that data integrity is not compromised. We carefully reviewed the SMOKE log files for error messages and ensured that appropriate source profiles were used. All error records reported during processing were reviewed and resolved. This is important to ensure that source categories are correctly characterized. We also compared SMOKE input and output emissions: Summary tables were generated to compare input inventory totals against modelready output totals to confirm consistency. Spatial plots were generated to visually verify correct spatial allocation of the emissions.

2.2.4 Merge SMOKE Pre-merged Emissions to Generate CAMx-ready Emission Inputs The final step in the emissions processing is to merge the Project gridded emissions with other regional components through the gridded merge program (MRGUAM) for CAMx. We merged the daily emissions in the time format required by CAMx.

2.2.5 Emissions Summary
Summaries of the Project gridded CAMx model-ready emissions data are provided in this section.

Table 2-4 summarizes the Project emission inventory data input to SMOKE from the FF10 data files in pounds per day by source type. Table 2-5 presents the emissions data after SMOKE processing. The consistency in data in Tables 2-4 and 2-5 offer confidence in the correct operation of the SMOKE emissions processing for CAMx.

Table 2-4. Project Emission Inventory Data Input to SMOKE by Source Type (lbs/day) Type CO NOX VOC SO2 PM10 PM2.5
Mobile 499.2 220.2 38.4 2.6 284.2 76.8
Energy 12.1 17.4 2.0 0.1 1.4 1.4
Consumer Products 0.0 0.0 93.9 0.0 0.0 0.0
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Landscaping 216.3 2.5 6.5 0.0 1.2 1.2
Architectural Coatings 0.0 0.0 341.9 0.0 0.0 0.0
Total 727.6 240.1 482.6 2.7 286.8 79.5
Abbreviations:

CO - Carbon Monoxide
NOx - Nitrogen Oxides
PM2.5. - Particulate Matter less than 2.5 microns in diameter PM10. - Particulate Matter less than 10 microns in diameter SO2 - Sulfur Dioxide
VOC - Volatile Organic Compounds
Table 2-5. Emission Inventory Data Output from SMOKE by Project Region (lbs/day) Type CO NOX VOC SO2 PM10 PM2_5
Mobile 499.2 220.2 38.4 2.6 284.2 76.8
Energy 12.1 17.4 2.0 0.1 1.4 1.4
Consumer Products 0.0 0.0 93.9 0.0 0.0 0.0
Landscaping 216.3 2.5 6.5 0.0 1.2 1.2
Architectural Coatings 0.0 0.0 341.9 0.0 0.0 0.0
Total 727.6 240.1 482.6 2.8 286.8 79.4
Abbreviations:

CO - Carbon Monoxide
NOx - Nitrogen Oxides
PM2.5. - Particulate Matter less than 2.5 microns in diameter PM10. - Particulate Matter less than 10 microns in diameter SO2 - Sulfur Dioxide
VOC - Volatile Organic Compounds
Spatial displays of the gridded emissions data are presented below. We examined the gridded emissions in 4-km grid to verify accurate spatial allocation by SMOKE. Figures 2-2 through 2-7 displays gridded emissions for the Project inventory in the 4-km modeling grid. 4122
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Figure 2-2. Spatial Distribution of CO Emissions (in lbs/day) for the Project in the Southern California 4-km Domain
Figure 2-3. Spatial Distribution of NOx Emissions (in lbs/day) for the Project in the Southern California 4-km Domain
CSU-DH -emissions CSU-DH emissions - COg COg Daily_Average Daily_Average 105.0 102 105.0 60

94.5 94.5

84.0 84.0

73.5 73.5

63.0 63.0

52.5 ~0= 52.5

42.0 42.0

31.5 "' 31.5

21.0 \, 21.0

10.5 10.5

0.0 0.0 lbs/day lbs/day 45 156 64 BO
December B,2002 o:oo :oo December B.2002 o:oo :oo
Min-0.0 at (1.1 i Max-273.9 at (72,54) Mln- o.o at(64,4Si Max- 273.9 at (72,54) CSU-DH emissions CSU-DH emissions - - NOX NOX
Daily _Average Daily_Average

15.0 102 15.0 60

13.5 13.5

12.0 12.0

10.5 10.5

9.0 9.0

7.5 7.5

6.0 6.0

4.5 4.5

3.0 \, 3.0

1.5 1.5

0.0 0.0
lbs/day lbs/day 45 156 64 80
December 8.2002 o :oo:oo December 8,2002 0:00 :00
Min- o.o at (1, n Max- 81.0 at (72,54) Min-0.0 at (64,4Si Max• 81 .o at (72,54) 4123
California State University – Dominguez Hills 12
Figure 2-4. Spatial Distribution of VOC Emissions (in lbs/day) for the Project in the Southern California 4-km Domain
Figure 2-5. Spatial Distribution of SO2 Emissions (in lbs/day) for the Project in the Southern California 4-km Domain

1.00 102

0.90 0.80

0.70 0.60

0.50 O.'IO

0.30 0.20

0.10 0.00
lbs/day
O.'IOO 102

0.360

0.320

0.280

0.2<10

0.200

0.160

0.120

0.080
O.O'IO

0.000
lbs/day
CSU-DH emissions -
voe Daily_Average
~-o=
"' \,
December 8.2002 O :00 :00 Min-o.oo at (1.1 ~ Max-6.05 at (72,54) CSU-DH_ emissions
6-o=
"'
S02g
Daily_Average
\,
December 8,2002 0:00 :00
Min=0.000 at(l.1 i Max=0.883 at (72,54)

1.00 60

0.90 0.80

0.70 0.60

0.50 0.40

0.30 0.20

0.10 0.00 lbs/day 45 156

0.400

0.360

0.320

0.280

0.240

0.200

0.160

0.120

0.080

0.040

0.000
156 lbs/day
64 CSU-DH emissions -
voe Daily_Average
80 December 8,2002 0:00:00
Mln- 0.00 at (64,45~ Max- 6.05 at (72,54)
CSU-DH emissions
S02g
Daily_Average
45 '----------------
64 BO
December 8,2002 O :00:00
Mln-0.000 at (64,45~ Max• 0.883 al(72,54)
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California State University – Dominguez Hills 13
Figure 2-6. Spatial Distribution of PM10 Emissions (in lbs/day) for the Project in the Southern California 4-km Domain
Figure 2-7. Spatial Distribution of PM2.5 Emissions (in lbs/day) for the Project in the Southern California 4-km Domain

50.0 102

45.0 40.0

35.0 30.0

25.0 20.0

15.0 10.0

5.0 0.0
lbs/day

15.00 102

13.50 12.00

10.50 9.00

7.50 6.00

4.50 3.00

1.50 0.00 lbs/day
CSU-DH emissions -
PMlO
Daily_Average
=s::::, =
">
December 8,2002 o :00 :00
Min-o.o at (1.1), Max-88.4 at (72,54)
CSU-DH_emissions
C,
PM25
Daily_Average
~
156
156

50.0 60

45.0 40.0

35.0 30.0

25.0 20.0

15.0 10.0

5.0 0.0
lbs/day 4S

15.00 13.50

12.00 10.50

9.00 7.50

6.00 4.50

3.00 1.50
CSU-DH emissions -
PMlO
Daily_Average
64 December 8,2002 0:00:00
Min-0.0 at (64,45), Max=88.4 at (72,54)
CSU-DH_emissions
PM25 Dally_Average

0.00 lbs/day
45c_ ____________ _J
~ 80
December 8,2002 0:00:00 December 8,2002 0:00:00
Min-0.00 at(l,1), Max-24.75 at (72,54) Min-0.00 at(64,45), Max-24.75 at (72,54) 80 4125
California State University – Dominguez Hills 14

3. REFERENCES
/1/ Coats Jr., C.J., 1996. High-performance algorithms in the Sparse Matrix Operator Kernel Emissions (SMOKE) modeling system. Proc. Ninth AMS Joint Conference on Applications of Air Pollution Meteorology with AWMA. Amer. Meteor. Soc., Atlanta, GA, 584-588. /2/ Coats Jr., C.J., Houyoux, M.R., 1996. Fast Emissions Modeling with the Sparse Matrix Operator Kernel Emissions (SMOKE) Modeling System. The Emission Inventory: Key to Planning, Permits, Compliance, and Reporting, Air & Waste Management Association. New Orleans, Louisiana.
/3/ USEPA, 2007. Guidance on the Use of Models and Other Analyses for Demonstrating Attainment of Air Quality Goals for Ozone, PM2.5 and Regional Haze. Office of Air Quality Planning and Standards, U.S. Environmental Protection Agency, Research Triangle Park, NC.

EPA-454/B-07-002.
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Ramboll

APPENDIX B

PGM INPUTS, OUTPUTS, AND ASSUMPTIONS
4127
California State University – Dominguez Hills 1

APPENDIX B

PGM INPUTS, OUTPUTS, AND ASSUMPTIONS
CALIFORNIA STATE UNIVERSITY – DOMINGUEZ HILLS

CARSON, CALIFORNIA
4128
California State University – Dominguez Hills 2

1. REGIONAL AIR QUALITY MODELING PLATFORM
The Southern California 2012 4- kilometer (km) Comprehensive Air Quality Model with extensions (CAMx) modeling database and a projected 2023 emissions database were used in this assessment.

The 2012 base case is based on a Photochemical Grid Model (PGM) database developed by the South Coast Air Quality Management District (SCAQMD) as part of the modeling and attainment demonstration for their 2016 Air Quality Management Plan1. This PGM database is tailored for Southern California and reflects updated emissions estimates, new technical information and enhanced air quality modeling techniques. The database uses a high-resolution 4-km horizontal grid to better simulate meteorology and air quality in the complex terrain and coastal environment of California.

This contrasts with the United States Environmental Protection Agency’s (USEPA’s) national modeling platforms2 used for national rulemakings (e.g., transport rules such as CSAPR3 or defining new National Ambient Air Quality Standards [NAAQS]) that use a coarser 12-km horizontal grid resolution.

Details of the model inputs, configuration, and results are presented in Section 2 of this Appendix.

Figure 1-1. Air Quality Modeling Domain for Southern California4 1 http://www.aqmd.gov/home/air-quality/clean-air-plans/air-quality-mgt-plan/final-2016-aqmp. 2 https://www.epa.gov/air-emissions-modeling/2014-2016-version-7-air-emissions-modeling-platforms. 3 https://www.epa.gov/csapr.
4 https://ww3.arb.ca.gov/research/cabots/docs/9a-cabots-baaqmd-20170419.pdf.

Legend
• Ozone Monilonng Sites
D 4 km Modeling Doma1n
Soulh C<:ia:.I Air Basin
I
0 30
I
60 I
120 Knomelers
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2. REGIONAL GRID MODELING
In this section, we describe the regional PGM modeling setup to assess the impact of the Project emissions on the ambient Particulate Matter less than 2.5 microns in diameter (PM2.5) levels in the region. The 2012 base case modeling databases were developed by the SCAQMD for the Community Multiscale Air Quality (CMAQ) PGM. The CMAQ annual 2012 4-km modeling database and annual 2012 4-km Weather Research and Forecasting (WRF) meteorological model output files were obtained from the SCAQMD. The SCAQMD CMAQ and WRF 2012 4-km data were then processed to generate a 2012 4-km annual PGM modeling database suitable for the CAMx. The following paragraphs describe how Ramboll developed the CAMx 2012 4-km annual database used in this study, starting with the SCAQMD CMAQ and WRF 2012 4-km data.

2.1 Model Inputs and Configuration
The SCAQMD emissions database has both 2012 and 2023 future year projections for CMAQ area and in-line point emissions. Ramboll converted both years’ emissions to corresponding CAMx area and point-source emissions files using the CMAQ2CAMx interface program5. Sea salt emissions were developed using an emissions processor that integrates published sea spray flux algorithms to estimate sea salt PM emissions for input to CAMx. The CAMx sea salt emissions were then merged with area emissions files.

The most commonly used prognostic meteorological models to provide meteorological fields for air quality modeling are the WRF model (Skamarock et al., 2005) and the Fifth-Generation Mesoscale Model (MM5; Grell et al, 1994). MM5 is a nonhydrostatic, prognostic meteorological model developed in the 1970s by Pennsylvania State University and the National Center for Atmospheric Research (NCAR) and has been widely used for urban- and regional-scale photochemical, fine particulate, and regional haze regulatory modeling studies. However, development of MM5 ceased in 2006, and WRF has become the new standard model used in place of the older MM5 for regulatory air quality applications in the US. Developed jointly by NCAR and the National Center for Environmental Prediction in late 1990s, WRF has been under continuous development, improvement, testing and open peer-review for more than 10 years and used world-wide by hundreds of researchers and practitioners around the globe for a variety of mesoscale studies. SCAQMD adopted WRF version 3.6 for the 2012 simulations. For the current application, the meteorology remains unchanged for the future year simulation and SCAQMD WRF 2012 4-km model outputs were processed using the WRFCAMx6 processor to generate the meteorological fields ready for CAMx. The WRF model employs a terrain-following coordinate system defined by pressure, using multiple layers that extend from the surface to 50 millibars (approximately 19 kilometers above ground level [AGL]). A layer averaging scheme is adopted for CAMx simulations to reduce the computational burden. Table 2-1 presents the mapping from the WRF vertical layer structure to the CAMx vertical layers. 5 http://www.camx.com/download/support-software.aspx.
6 WRFCAMx is available on the CAMx website (http://www.camx.com/download/support-software.aspx). 4130
California State University – Dominguez Hills 4
Table 2-1 Vertical Layer Structure for WRF and CAMx Modeling WRF CAMx
Layer Height (m) Layer Height (m) Thickness (m) Sigma
30 19260 18 19260 4769 0.0000
29 17456
28 15900
27 14492 17 14492 6027 0.0788
26 13185
25 11945
24 10755
23 9597
22 8465 16 8465 4906 0.2930
21 7345
20 6237
19 5177
18 4295
17 3559 15 3559 1560 0.6254
16 2944
15 2430
14 1999 14 1999 358 0.7733
13 1641 13 1641 300 0.8107
12 1341 12 1341 251 0.8431
11 1090 11 1090 209 0.8709
10 881 10 881 175 0.8946
9 706 9 706 146 0.9148
8 561 8 561 121 0.9319
7 439 7 439 101 0.9463
6 338 6 338 85 0.9585
5 253 5 253 70 0.9688
4 183 4 183 59 0.9774
3 124 3 124 49 0.9846
2 75 2 75 41 0.9907
1 34 1 34 34 0.9958
0 0 0 0 1
The SCAQMD data set provided the lateral boundary conditions (BCs) for the 4-km state-wide modeling grid. The SCAQMD simulated a 12-km domain whose boundary concentrations were extracted from a global model simulation for the year 2012. The Model for Ozone and Related Chemical Tracers Version 4 (MOZART-4; Emmons et al., 2010) is a global chemical transport model 4131
California State University – Dominguez Hills 5
developed jointly by NCAR, the Geophysical Fluid Dynamics Laboratory, and the Max Planck Institute for Meteorology, and simulates chemistry and transport of tropospheric gases and bulk aerosols. The 12-km outputs were saved and used to derive the boundary conditions for the 4-km domain. The CMAQ2CAMX processor was used to convert the CMAQ 4-km boundary conditions to suitable CAMx BCs. The model was initialized from clean initial concentrations and five days of spin-up period were used for the 4-km grids to minimize their influence.

Additional data used in the air quality modeling include ozone column data from the Ozone Monitoring Instrument (OMI), which continues the Total Ozone Mapping Spectrometer (TOMS) record for total ozone and other atmospheric parameters related to ozone chemistry (OMI officially replaced the TOMS ozone column satellite data on January 1, 2006). OMI data are available every 24-hours and are obtained from the TOMS ftp site7. The CAMx O3MAP program reads the OMI ozone column txt file data and interpolates to fill gaps and generated gridded daily ozone column input data. The OMI data is used in the CAMx (TUV) radiation models, which is a radiative transfer model that develops clear-sky photolysis rate inputs for CAMx. The land use file was generated with the WRFCAMx processor and modified to remove lakes and set coastal waters with a surf zone width of 50 m; this file was used to update the emissions database and provide more realistic representation of sea salt emissions.

Table 2-2 presents the CAMx configuration used for the modeling in this Project analysis. In the past, the Carbon-Bond IV (CB4) chemical mechanism (Gery et al., 1989) has been predominantly used for the California State Implementation Plan (SIP) modeling. In 1999, however, the California Air Resources Board’s (CARB’s) Reactivity Scientific Advisory Committee recommended switching to the 1999 State-wide Air Pollution Research Center (SAPRC99) chemical mechanism (Carter, 2000) based on a comprehensive review by Stockwell (1999), and SAPRC99 has since been the mechanism of choice for the California SIPs. The 2007 update to the SAPRC chemistry mechanism, called SAPRC07 (Carter, 2010), replaced the dated SAPRC99 mechanism. The version implemented in CAMx is SAPRC07TC, which includes additional model species to explicitly represent selected toxics and reactive organic compounds and uses numerical expressions of rate constants that are compatible with the current chemistry mechanism solver. The partitioning of inorganic aerosol constituents (sulfate, nitrate ammonium and chloride) between gas and aerosol phases is performed using the ISORROPIA module. The SOAP semi-volatile equilibrium scheme performs the organic aerosol-gas partitioning. These processes are described in more detailed in the CAMx user guide. 7 ftp://toms.gsfc.nasa.gov/pub/omi/data/.
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Table 2-2. CAMx Modeling Configuration
Science Option Configuration Notes
Model Code CAMx v6.5 Released June 2010
Horizontal Grid 4-km 1-way nesting
O3 and PM 4-km 156 x 102 grid cells
Vertical Grid 18 vertical layers extending up to
~19 km AGL
Collapsed from 30 WRF layers
(see Table 3-1)
Initial Conditions Clean initial conditions 5-day spin-up for 4-km domain
Boundary Conditions CMAQ 4km lateral concentrations
converted to CAMx
Photolysis Rate Photolysis rates lookup table Derived from satellite measurements and TUV
processor
Gas-phase Chemistry SAPRC07TC Solved by the Euler Backward Iterative (EBI) solver
Aerosol-phase Chemistry ISORROPIA (inorganic aerosol)
SOAP v2.1 (organic aerosol)
Meteorological Input
Preprocessor
WRFCAMx v4.7
Advection Piecewise Parabolic Method (PPM)
Diffusion Eddy diffusion algorithm

2.2 Model Results
The future modeling scenario was simulated using the CAMx source apportionment technology. Both cumulative concentrations from all the sources and the concentrations from Project-specific emissions are derived from a single simulation following the previous section model configuration. The model results of hourly PM2.5 concentrations were processed into aggregated metrics that are relevant to health effects.

The metrics relevant to the PM2.5 health effects selected in this study are 24-hour annual average concentrations (see Appendix C). Figure 2-1 shows spatial plots of annual average and a single day episode maximum 24-hour average PM2.5 concentrations from the base case. In the base case, the Los Angeles County is the region most impacted along with the southern portion of Imperial County.

Annual PM2.5 concentrations in these counties range between 10 and 20 micrograms per cubic meter (mg/m3) with isolated regions that could reach up to 25 mg/m3. Contributions of the Project emissions to annual average PM2.5 are about 0.16 mg/m3 at the most impacted areas and contributions to the maximum 24-hour average are as large as 0.42 mg/m3 at the most impacted areas. Figure 2-2 presents increases in annual average and maximum 24-hour average PM2.5 due to the Project by PM2.5 4133
California State University – Dominguez Hills 7
component at the grid cell of maximum impact. It confirms that the PM2.5 increases due to the Project are mostly due to primary PM components.

Figure 2-1. Results of the 4 km PM2.5 Modeling Domain
PM2.5 Concentrations from the Base Case Scenario (left panels); Increases in PM2.5 due to the Project (center and right panels); Annual Averages (top panels);
Maximum 24-hour Averages (bottom panels)
NWUIIA...-.gePll:Z5Concenhtian
,.,,.,,
--
Mu2'.flAYgPM25Cot.:entration
,.,,.,,
.... eu.

NWUII A~ PM2, Concenlrrion ,.,,.,,
CSU-OHS-WAttr1bution
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Mu 24-f'I Avg PM25 Concentmion mm
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'-vAnnuet ...... ""25 Concenntion ,.,,.,,
---
Mu~ A"I PIGS Conclntntlofl mm
CSU-OH SouK:e Allribulioft
µg/m'
µg/m'
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California State University – Dominguez Hills 8
Figure 2-2. Increases in Annual Average and Episode Maximum 24-hour Average PM2.5 Concentrations due to the Project by PM2.5 Component: fine particulate sulfate (SO4), nitrate (NO3), ammonium (NH4), primary organic aerosol (POA), elemental carbon (EC), and other primary PM (Other); Where the Maximum Impact of the Project’s Emissions Occurred

0.45 0.4

0.35 0.3
ffl
E 'o:o 0.25
:t
GI
"' Ill
GI 0.2 ...
u
.:

0.15 0.1

0.05 0
Ann. Avg Max 24-h Avg
■ Other
■ EC
■ POA
■ NH4
■ N03
504
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California State University – Dominguez Hills 9
The metrics relevant to the ozone health effects selected in this study are consistent with the ozone NAAQS (see Appendix C). The model provides hourly concentrations that are further post-processed to produce maximum daily average 8-hour (MDA8) ozone concentrations for each day. Figure 2-3 displays spatial plots of the annual highest MDA8 ozone for the 2023 emissions scenario and the increases in highest MDA8 ozone concentrations due to the Projects emissions. In the 2023 base case emissions scenario, the western Los Angeles, northern Orange, southern San Bernardino and eastern Riverside counties show the highest MDA8 ozone concentration between 90 and 100 ppb. The maximum increase in the highest MDA8 ozone concentrations due to the Project is 0.112 ppb in southern Los Angeles County.

Figure 2-4 displays MDA8 ozone for the base case and increases in MDA8 ozone due to the project on August 13, the day that the Project has the highest ozone contribution. The highest MDA8 ozone contribution due to the Project is 0.121 ppb (Figure 2-4, right) that occurs in southern Los Angeles County where total MDA8 ozone concentrations are 75 ppb.

Figure 2-3. Highest MDA8 Ozone Concentrations from the Base Case Scenario (left) and Increases in Highest MDA8 Ozone Concentrations due to the Project (right) for the Annual Modeling of the 2023 Emissions Scenario
Figure 2-4. MDA8 Ozone Concentrations from the Base Case Scenario (left) and Increases in MDA8 Ozone Concentrations due to the Project (right) on August 13, the Day with the Highest Project Ozone Contributions for the Annual Modeling of the 2023 Emissions Scenario
... llffll.Wn &-Hout OMAX 03 Concentmion
FY202'
--
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FY202'
-Co•
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"49,111 13 . .,..__ DMAX 03 COflCJ1tll.itlo
mm
csu-ot1 Sowcl Allllbullon
ppbv
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3. REFERENCES
/1/ Carter, W.P.L., 2000. Documentation of the SAPRC99 Chemical Mechanism for VOC Reactivity Assessment, Final Report to California Air Resources Board, Contract No. 92-329, and (in part) 95-308, May 8, 2000. http://www.engr.ucr.edu/~carter/reactdat.htm /2/ Emmons, L.K., Walters, S., Hess, P.G., Lamarque, J.F., Pfister, G.G., Fillmore, D., Granier, C., Guenther, A., Kinnison, D., Laepple, T., Orlando, J., Tie, X., Tyndall, G., Wiedinmyer, C., Baughcum, S.L., Kloster, S., 2010. Description and evaluation of the Model for Ozone and Related chemical Tracers, Version 4 (MOZART-4), Geoscientific Model Development, 3, 43-67. /3/ Gery, M.W., Whitten, G.Z., Killus, J.P., Dodge, M.C., 1989. A Photochemical Kinetics Mechanism for Urban and Regional Scale Computer Modeling. J. Geophys. Res., 94, 925-956. /4/ Grell, G.A., Dundhia, J., Stauffer, D.R., 1994. A description of the Fifth-Generation Penn State/NCAR Mesoscale Model (MM5), National Center for Atmospheric Research, Boulder, CO, NCAR/TN-398+STR.
/5/ Skamarock, W.C., Klemp, J.B., Dudhia, J., Gill, G.O., Barker, D.M., Wang, W., Powers, J.G., 2005. A description of the Advanced Research WRF Version 2. NCAR Technical Note NCAR/TN-468+STR, June 2005.
/6/ Stockwell, W.R., 1999. Review of the updated maximum incremental reactivity scale of Dr.

William Carter. Division of Atmospheric Sciences, Desert Research Institute, November 29, 1999. http://www.cert.ucr.edu/~carter/pubs/stockrev.pdf 4137
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Ramboll

APPENDIX C

BENMAP AND HEALTH OUTCOMES
4138
California State University - Dominguez Hills 1

APPENDIX C

BENMAP AND HEALTH OUTCOMES

CALIFORNIA STATE UNIVERSITY, DOMINGUEZ HILLS

CARSON, CALIFORNIA
4139
California State University - Dominguez Hills 2

1. HEALTH IMPACT ANALYSIS
The potential health effects of ozone and Particulate Matter less than 2.5 microns in diameter (PM2.5) concentrations due to the Project’s emissions were estimated using the Environmental Benefits Mapping and Analysis Program (BenMAP), Community Edition v1.4 (July 2018).1 BenMAP, originally developed by the United States Environmental Protection Agency (USEPA), is a powerful and flexible tool that helps users estimate human health impacts and economic benefits resulted from changes in air quality. BenMAP outputs include PM- and ozone-related health endpoints such as premature mortality, hospital admissions, and emergency room visits. BenMAP uses the following formula to relate changes in ambient air pollution to certain health endpoints (AAI, 2018):

Health Effect = Air Quality Change ´ Health Effect Estimate ´ Exposed Population ´ Background Health Incidence
· Air Quality Change - The difference between the starting air pollution level (the base) and the air pollution level after some change, such as a new source. · Health Effect Estimate - An estimate of the percentage change in an adverse health effect due to a one unit change in ambient air pollution. Effect estimates, also referred to as concentrationresponse functions (CRFs), are obtained from epidemiological studies. · Exposed Population - The number of people affected by the air quality change. The government census office is a good source for this information. This analysis uses data from PopGrid, which is an add-on program to BenMAP that allocates the block-level U.S. Census population to a userdefined grid.2 · Background Health Incidence - An estimate of the average number of people that die (or suffer from some adverse health effect) in a given population over a given period of time. For example, the health incidence rate might be the probability that a person will die in a given year. Health incidence rates and other health data are typically collected by the government as well as the World Health Organization.

The health endpoints analyzed in this study and the BenMAP results are presented in Section 2 of this appendix.

2. HEALTH IMPACT ANALYSIS
This section presents the health impact of the Project emissions on the population in the southern California domain, estimated by the BenMAP model. The Comprehensive Air Quality Model with extensions (CAMx) modeling results are processed to generate aggregated daily averages PM2.5 and maximum daily 8-hour ozone appropriate for various health endpoints. The CAMx simulation results from the full year (January to December) are used to estimate the health effects of PM2.5 and ozone.

BenMAP translates increases in the pollutant concentration due to the Project emissions to changes in the incidence rate for each health effect using a CRF derived from previously published epidemiological studies. BenMAP often provides multiple CRFs based on different epidemiological studies for a given health endpoint. We used the USEPA default CRFs when evaluating health impacts. This analysis uses 1 http://www.epa.gov/air/benmap/
2 https://www.epa.gov/benmap/benmap-community-edition
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California State University - Dominguez Hills 3
population data from PopGrid, which allocates the census population to each modeled 4x4 kilometer (km) grid cell.

The population used for both the quantified health effects and the background health incidence presented here is future year 2035, for consistency with the Project buildout year.

2.1 PM2.5 Health Impact
Although there are a large number of potential health endpoints that could be included in the analysis as described above, we selected the key health endpoints that have been the focus of recent United States Environmental Protection Agency (USEPA) risk assessments (e.g., USEPA, 2010; USEPA, 2014).

For example, the USEPA notes that health endpoints were selected based on consideration of at-risk populations (e.g. asthmatics), endpoints that have public health significance, and endpoints for which information is sufficient to support a quantitative concentration-response relationship (USEPA, 2014).

The health endpoints and associated CRFs examined in this study are presented in Table 2-1. Each CRF is based on a certain age range for the given health endpoint depending on the underlying epidemiological study on which it is based. Increases in the BenMAP-estimated health effect incidences and percent of background health incidence due to the Project emissions are presented in Table 2-2.

These values reflect the total health impact in California across the Project domain.

Table 2-1. Summary of PM2.5 Health Endpoints Used in this Study Health Endpoint Age
Range
Daily
Metric
Seasonal
Metric
Annual
Metric
CRF Selected
Emergency Room Visits, Asthma 0-99 24-hr mean Mar et al., 20101 Mortality, All Cause 30-99 24-hr mean Quarterly
mean
Mean Krewski et al., 20091
Hospital Admissions, Asthma 0-64 24-hr mean - - Sheppard, 20031 Hospital Admissions, All Cardiovascular (less
Myocardial Infarctions)
65-99 24-hr mean
-
- Bell, 20121
Hospital Admissions, All Respiratory 65-99 24-hr mean - - Zanobetti et al., 20091 Acute Myocardial Infarction, Nonfatal 18-24 24-hr mean - - Zanobetti et al., 20091 Acute Myocardial Infarction, Nonfatal 25-44 24-hr mean - - Acute Myocardial Infarction, Nonfatal 45-54 24-hr mean - - Acute Myocardial Infarction, Nonfatal 55-64 24-hr mean - - Acute Myocardial Infarction, Nonfatal 65-99 24-hr mean - - 1 CRFs available in BenMAP (AAI, 2018)
The results show that the highest impact is for all-cause mortality, with an estimated mean increased incidence of 10.31 deaths per year due to the Project emissions. Smaller mean increased incidences per year were estimated for other relevant PM2.5-related health outcomes: 4.38 increase in incidence of asthma related emergency room visits, 2.44 increase in incidence of respiratory hospital admissions, and 1.05 increase in incidence of cardiovascular hospital admissions. 4141
California State University - Dominguez Hills 4
It should be noted, however, that the estimated increased incidence in those health effects are quite minor compared to the background health incidence values (shown in Table 2-2 as percent of Background Health Incidence). For example, for mortality, the increase of 10.31 deaths per year due to Project emissions represents 0.0032% of the total all-cause mortality for people ages 30 to 99.

It is also important to note the uncertainty and conservative nature of the results presented, particularly for all-cause mortality. These estimates are based on a single epidemiological study that found an association between PM2.5 concentrations and mortality. While similar studies suggest that such an association exists, there remains uncertainty regarding a clear causal link. This uncertainty stems from the limitations of epidemiological studies, such as inadequate exposure estimates and the inability to control for many factors that could explain the association between PM2.5 and mortality such as lifestyle factors like smoking. In addition, the components of PM that may be associated with adverse health effects are yet unknown, but the analysis assumes that all PM is equally toxic, making it very conservative.

Table 2-2. BenMAP-Estimated Mean PM2.5 Health Effects of the Project Emissions Across the Southern California Domain1
Health Endpoint2 Incidences (Mean) Percent of Background Health Incidence (%)
Emergency Room Visits, Asthma [0-99] 4.38 0.0033%
Mortality, All Cause [30-99] 10.31 0.0032%
Hospital Admissions, Asthma [0-64] 0.38 0.0021%
Hospital Admissions, All Cardiovascular (less
Myocardial Infarctions) [65-99]

1.05 0.00047%
Hospital Admissions, All Respiratory [65-99] 2.44 0.0013% Acute Myocardial Infarction, Nonfatal [18-24] 0.00044 0.0012% Acute Myocardial Infarction, Nonfatal [25-44] 0.024 0.0013% Acute Myocardial Infarction, Nonfatal [45-54] 0.068 0.0013% Acute Myocardial Infarction, Nonfatal [55-64] 0.13 0.0014% Acute Myocardial Infarction, Nonfatal [65-99] 0.53 0.0013% 1 Health effects are shown terms of incidences of each health endpoint and how it compares to the base (2035 base year health effect incidences) values.
2 Affected age ranges are shown in square brackets.

2.2 Ozone Health Impact
As noted above, although a larger number of health endpoints could be evaluated, we selected the health endpoints based on recent USEPA risk assessments (USEPA, 2010; USEPA, 2014). The health endpoints and associated CRFs examined in this study are presented in Table 2-3. Each CRF is associated with a certain age range for the given health endpoint depending on the epidemiological study on which it is based. Increases in the BenMAP-estimated health effect incidences and percent of 4142
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background health incidence due to the Project emissions are presented in Table 2-4. These values reflect the total health impact in California across the Project domain.

Table 2-3. Summary of Ozone Health Endpoints Used in this Study.

Health Endpoint Age
Range
Daily
Metric
Seasonal
Metric
Annual
Metric
CRF Selected
Hospital Admissions, All Respiratory 65 - 99 MDA8 - - Katsouyanni et al., 20091 Mortality, Non-Accidental 0 - 99 MDA8 - - Smith et al., 20091 Emergency Room Visits, Asthma 0 - 17 MDA8 - - Mar and Koenig, 20091 Emergency Room Visits, Asthma 18 - 99 MDA8 - - Mar and Koenig, 20091 1 CRFs available in BenMAP (AAI, 2018)
For this Project, asthma-related emergency room visits are associated with the highest health impacts due to the Project emissions in the southern California domain (3.38 incidences per year for adults ages 18 to 99 and 2.92 incidences per year for children ages 0 to 17). Hospital admissions due to respiratory issues for adults age 65-99 and non-accidental mortality have lower incidence increases (0.67 and 0.28 incidences per year, respectively).

It should be noted, however, that the estimated increases in those health effect incidences are quite minor compared to the background health incidence (shown in Table 2-4 as percent of Background Health Incidence). For example, the increase in asthma emergency room visits represents 0.0058% of the total asthma-related emergency room visits for children.

Table 2-4. BenMAP-Estimated Mean Ozone Health Effects of the Project Emissions Across the Southern California Domain1
Health Endpoint2 Incidences (Mean) Percent of Background Health Incidence (%)
Hospital Admissions, All Respiratory [65-99] 0.67 0.00034% Mortality, Non-Accidental [0-99] 0.28 0.00013%
Emergency Room Visits, Asthma [0-17] 2.92 0.0058%
Emergency Room Visits, Asthma [18-99] 3.38 0.0042%
1 Health effects are shown terms of incidences of each health endpoint and how it compares to the base (2035 base year health effect incidences) values.
2 Affected age ranges are shown in square brackets.

2.3 Conclusion
The PM2.5 and ozone concentration changes modeled by CAMx were converted to impacts on various health endpoints including premature mortality, hospitalizations, and emergency room visits, using the BenMAP health impact assessment model and USEPA defaults for health endpoints. Estimated changes in the health effect incidences are presented across the California grids in the southern California domain. For the PM2.5-related health endpoints, the health impact on mortality is the highest 4143
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(Incidence = 10.31). For ozone-related health endpoints, asthma-related emergency room visits are most affected (Incidence = 3.38 for adults ages 18 to 99 and Incidence = 2.92 for children ages 0 to 17). Other health effect incidences are lower. Across the board, the estimated increases in those health effect incidences are quite minor compared to the background health incidence values with the largest PM2.5 health impact (all-cause mortality) representing only 0.0032% of the total of all deaths, and the largest impact for ozone (asthma related emergency room visits by adults) representing

0.0042% of all emergency room visits.

Health outcomes presented above conservatively utilize maximum daily emissions, assumed to occur for an entire year. Should average daily emissions be used, results would be even lower. Specifically for mortality impacts from PM2.5 emissions, average daily emissions would be approximately 20% lower, and the corresponding morality incidence rate would be similarly lower. Overall, the estimated health impacts from the Project are low and represent only a very small fraction of the total background health incidence.
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3. REFERENCES
/1/ AAI, 2018. BenMAP Environmental Benefits Mapping and Analysis Program – Community Edition User’s Manual. Prepared for US Environmental Protection Agency, Abt Associates Inc., Cambridge, Massachusetts.
/2/ USEPA, 2010. Quantitative Health Risk Assessment for Particulate Matter. Office of Air Quality Planning and Standards, U.S. Environmental Protection Agency. EPA-452/R-10-005. /3/ USEPA, 2014. Health Risk and Exposure Assessment for Ozone Final Report. Risk and Benefits Group, Health and Environmental Impacts Division, Office of Air Quality Planning and Standards, U.S. Environmental Protection Agency.EPA-452/R-14-004a. 4145
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APPENDIX D

RESUMES OF TECHNICAL STAFF
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SHARI BETH LIBICKI, PHD
Principal
Air Quality Service Line Leader
Dr. Shari Beth Libicki, Ramboll Environ’s global Air Quality Service Line Leader, has over 25 years of chemical fate and transport experience, as applied to managing greenhouse gas (GHG) emissions, odor evaluations, and estimating air emissions and dispersion from chemical processes, landfills and new developments.

Her experience includes providing technical expertise to entitlement and litigation teams, negotiating complex technical agreements and permits with agencies and assisting facilities with compliance programs. She is an expert on GHG evaluations for California Environmental Quality Act (CEQA) documents, and is at the forefront of developing regulations in California, having served on the Regional Targets Advisory Council. She has conducted extensive air quality regulatory assessments for New Source Review/Prevention of Significant Deterioration (NSR/PRD) permitting and compliance auditing. Shari has lectured widely on evaluating climate change impacts for new developments and estimating chemical exposure for risk assessments. She currently serves as a Lecturer in the Department of Chemical Engineering at Stanford University.

EDUCATION
PhD, Chemical Engineering, Stanford University, 1985
MS, Chemical Engineering, Stanford University, 1981
BSE, Chemical Engineering, University of Michigan, 1979

EXPERIENCE HIGHLIGHTS
Land Use Entitlement
 Project director for online tool to display risks from rail and freeways for the SMAQMD. The tool is designed to provide a first tier analysis of traffic and rail risks for land use decision making.
 Project director for air quality and greenhouse gas analyses for a new marine terminal in Northern California. Critical
evaluation issues included risks from diesel exhaust of maritime vessels and GHG emissions reductions from a “green cement” production plant.
 Prepared comprehensive air quality analysis for two large municipal solid waste landfills in Southern California.

Evaluation included impact of exhaust from non-road heavy equipment, dust from waste operations, and emissions from landfill gas escaping the collection system, and flares and turbines used to destroy the landfill gas. Projects included public testimony on results of analysis.

CONTACT INFORMATION
Shari Beth Libicki, PhD
[email protected]
+1 (415) 796.1933
Ramboll
201 California Street
Suite 1200
San Francisco, 94111
United States of America

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 Analyzed the impacts of potential accident scenarios prior to the construction of several new industrial facilities. The results of the analyses were used to make recommendations as to how to improve the safety and minimize the risks to the surrounding community.  Project director for the Chevron Renewal Project Revised Environmental Impact Report. The Revised EIR is intended to fulfill the requirements of a court decision with specific focus on the Climate Change and Air Quality sections of the EIR. The revision of the Climate Change section will describe mitigation measures and quantification of the efficacy of those mitigation measures. The Air Quality section will address a range of process alternatives in the refinery.  Project director for the development of the California Air Pollution Control Officer’s Association (CAPCOA) manual on quantifying mitigation for a wide variety of carbon reduction measures that can be used for residential and commercial development.  Project director for CalEEMod®, a new software package to estimate GHG, air toxics and criteria pollutant emissions from new development projects in California.  Evaluated climate change impacts of dozens of new projects under CEQA and National Environmental Policy Act (NEPA). Specific types of projects include large, multi-use developments, landfill expansions, and transportation hubs.
 Provided innovative air quality services for entitlement activities, including evaluating the impacts of freeways on air quality, the estimation of emissions from complex industrial facilities, and the impact on public health of those emissions. Provided testimony at public hearings in support of technical analyses.

Monitoring
 Conceptualized, designed and implemented a mobile application to characterize, locate, obtain meteorological data for, and time-stamp odor observations. The OdorApp allows the management of odor observations, and also allows easy display of odor observations in a manner that allows for analysis of odor complaints.
 Directed a yearlong ambient air-monitoring program to measure particulate matter and diesel particulate matter (DPM) at the boundary of a large landfill in Los Angeles and a nearby school. The results of the monitoring program were analyzed temporally and as a function of meteorology. The results of the program showed that nearby freeways provided an overwhelming fraction of the measured DPM.
 Designed a complex fourteen-station ambient air monitoring network around a co-disposal landfill to measure the concentrations of 19 toxic chemicals in both gaseous and particulate phase for risk assessment purposes and negotiated approval with local, state and federal regulators.  Analyzed the results of a complex multi-year total suspended particulate monitoring program to understand the sources of arsenic in the ambient air, and to evaluate the health risks of the arsenic levels that could be related to nearby facility emissions.  Designed and conducted the compliance ambient air monitoring program for a large hazardous waste facility. The ongoing program collects whole air and total suspended particulate samples at five stationary sites. Prepared risk assessment based on the program, and quarterly reports for review by the local air district and the California Environmental Protection Agency’s (EPA')s Department of Toxic Substances and Control (DTSC).
 Designed, negotiated and managed a novel cost-effective ambient air monitoring program that yielded real-time information on the health impacts of a site remediation. This study is the basis of a well-received paper.

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Permitting and Enforcement
 Provided nationwide compliance assistance to six iron and steel mini-mills. Work conducted includes: preparation of Title V permit applications and supporting emissions estimates; preparation of PSD permits and associated emissions and dispersion modeling; evaluation of RACT controls for mini-mills.
 Managed PSD permit applications for two aluminum smelting facilities. This work included preparation of the emissions inventories, managing the Class I and Class II modeling effort, conducting the best available control technology (BACT) analysis, and preparing the technical document. She also negotiated permit conditions with the agencies, and assisted with cross-border discussions with other impacted agencies.
 Assisted a large landfill in Southern California respond to a series of Notices of Violation surrounding odor issues. Ramboll Environ conducted computational fluid dynamic (CFD) modeling study to evaluate the sources of odors at the landfill, as well as to predict where odors might occur in the neighborhood and under what conditions. Ramboll Environ also conducted a surrogate sampling study where it was found that ethanol was a surrogate for odors. Finally, Ramboll Environ assisted in the negotiations which allowed the landfill to continue operations.  Managed the preparation of an application for an Authority to Construct for a state-of-the-art hazardous waste treatment storage and disposal facility, which included a risk assessment for the project, and successfully negotiated permit conditions with state and local agencies. Currently working with facility and regulators to implement permit conditions.  Worked as a technical advisor to the Imperial County Air Pollution Control District (ICAPCD) for the permitting of a rail-haul landfill. This landfill is proposed to be the largest landfill in the United States, and had monitoring, modeling, and enforceability issues associated with the permit. Of particular interest was a phased permitting approach that allowed the landfill operator to take advantage of newer technologies that could reduce emissions of criteria pollutants over time.  Prepared and submitted several Federal Operating Permit Applications under Title V of the Clean Air Act for industrial facilities. Currently working on ongoing negotiation for permits.

Other
 Evaluated the transport of perfluorooctanoic acid (PFOA) in the air and in the ocean as a part of a large multiphase study being carried out by DuPont. The study resulted in a poster presentation at the American Geophysical Union and centered on how the chemical properties of PFOA impact its transport.
 Provided support to a large shipping company in evaluating the effectiveness of its emissions reduction programs; oversaw design of an automated database system to track fuel use and emissions reductions from a variety of innovative programs to improve reporting and streamline the program.
 Conducted preliminary evaluation of whether patterns of measured lead in soil supported contention that lead resulted from airborne emissions from a lead emitting stack located at the site. Concluded that insufficient data was available for analysis.  Designed a protocol for estimating the quantities of specific hazardous chemicals disposed of in California by region and waste type, and worked with the Department of Health Services to verify protocol.

Prior to joining Ramboll Environ, Shari held the following positions:
 Physical Sciences Officer, Bureau of Oceans and Environmental and Scientific Affairs, US Department of State
– Developed and implemented a successful negotiation strategy for cooperative scientific projects with Japan and the Soviet Union.
– Worked with Japan's Science and Technology Agency to initiate a Japanese funding organization for innovative international biotechnological studies.
 Staff Scientist, Alza Corporation

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– Led teams that created, designed, tested, and patented controlled release transdermal and osmotic pump drug delivery systems.
– Studied the correlation between drug physical chemical data and dermal transport and absorption.
– Designed and implemented systems to provide effective membrane thickness control in the manufacture of miniature osmotic pumps.
 Lecturer, Department of Chemical Engineering, Stanford University – Taught courses in Chemical Engineering Laboratory and Technical Speaking and Writing.

CREDENTIALS
Awards and Honors
American Association for the Advancement of Sciences Diplomacy Fellow, 1987-1988 United States Department of State Meritorious Honor Award, March 1989

PROFESSIONAL AFFILIATIONS AND ACTIVITIES
Member, American Institute of Chemical Engineers
Member, Air & Waste Management Association

PATENTS
H.F. Sanders, Y.L. Cheng, D.J. Enscore, S.B. Libicki. Transdermal Drug Composition with Dual Permeation Enhancers. Patent Number: 4,820,720. April 11, 1989.

R.M. Gale, D.J. Enscore, D.E. Nedberge, M. Nelson, Y.L. Cheng, S.B. Libicki. Transdermal Administration of Progesterone, Estradiol Esters, and Mixtures Thereof. Patent Number: 4,788,062. November 29, 1988.

PUBLICATIONS & PRESENTATIONS
Klug, S.E., K.L. Krieger, D.W. Weaver, M.T. Keinath, S.B. Libicki. 2012. “Quantifying Filtration Impacts on Indoor Exposure to Particulates.” Presented at Air & Waste Management Association Conference and Exposition. June 19, 2012.

Bowie, T.; S.B. Libicki, K.L. Davis, C. Emery. 2011. “Strategies for Designing an Odor Monitoring Program for Municipal Solid Waste Landfills.” Presented at Air & Waste Management Association Conference and Exposition. June 22, 2011.

Keinath, M.T. and S.B. Libicki. 2010. “Preventing GHG Leakage: Benchmarking Emissions to Design a Fair Cap and Trade System under AB32.” Presented at the 2010 California Construction and Industrial Materials Association (CalCIMA) Educatoin Conference. San Diego, CA. September.

Van de Griend, R., R.W. Andersen, S.B. Libicki, J. Ilisco, U. Senturk. 2009. Arsenic In Glass Highway Marking Beads. A&WMA’s 102nd Annual Conference & Exhibition, Detroit, MI. June.

Hou, M., M.T. Keinath, C. Helvestine, S.B. Libicki. 2008. Predicting Human Exposure near Freeways: A Comparison of AERMOD and CAL3QHCR. AWMA Annual Conference, Portland, Oregon. June.

Weaver D.W., S.B. Libicki, K.L. Davis. 2008. VMT, GHG Reduction, and Planning: Looking Under the Hood. Presented at American Planning Association California Chapter (APACA) Conference.

September 21-24.

Keinath, M.T. and S.B. Libicki. 2008. Local Sourcing for Green Building: How Homegrown Materials Can Reduce Your Carbon Footprint. California Construction & Industrial Materials Association (CalCIMA) Annual Conference. September.

DiBiase, M. and S.B. Libicki. 2008. Emissions and the Shipping Industry: Emission Reductions for Ocean-Going Vessels in California Air & Waste Management Association Conference. June.

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Libicki, S.B., D. Weaver, and D. Kim. 2007. A Technical Approach to Addressing Climate Change in Environmental Impact Reports. 2007 Environmental Law Conference at Yosemite. Environmental Law Section of the State Bar of California. October.

Kemball-Cook, S.R. and S.B. Libicki. 2006. “Using surface drifter buoys to estimate oceanic transport of surfactants”. Presented at the American Geophysical Union Ocean Sciences Meeting.

Libicki, S.B. 1999. When Good Data Goes Bad: What the Numbers Really Mean. American Bar Association Section of Environment, Energy and Resources 7th Section Fall Meeting, San Diego, California. October.

Libicki, S.B. and R. Van de Griend. 1996. RMPs, RMPPs and SB 1889: Consolidation of State and Federal Risk Management Programs. Presented as a Minimum Continuing Legal Education course at various law firms. San Francisco, California. November-December.

Stuart, A.L., S. Jain and S.B. Libicki. 1996. The Use of Long-Term Meteorological Information to Predict Impact Probabilities Resulting from Toxic Chemical Releases. PSA 96-International Topical Meeting on Probabilistic Safety Assessment. American Nuclear Society, Park City, Utah. October.

Libicki, S.B. 1995. The Use of Simplified Quantitative Risk Analysis in Risk Management Decisions at Small and Medium-Sized Process Plants. 88th Annual Air & Waste Management Association Annual Meeting, San Antonio. June.

Jain, S. and Libicki, S.B. 1995. Estimating the Additional Airborne Release Due to Heat of Reaction and Aerosolization When Strong Acids React With Water during a Release. Air & Waste Management Association Annual Meeting, San Antonio. June.

Libicki, S.B. 1994. Emergency Release Modeling: Software options and usage strategies. Southwest Safety Congress and Exposition. May.

Libicki, S.B. and R. van de Griend. 1994. Practical Compliance Strategies for Laboratory and Production:

Ensuring Compliance from the Ground Up. Bio International '94. Toronto. May.

Libicki, S.B., A. Andersen and R. Scofield. 1994. The Use of Ambient Air Monitoring Data for the Evaluation of Risks due to Particulate-Borne Metals: A Case Study. California Mining Association Annual Meeting. April.

Libicki, S.B. and R. Scofield. 1993. Issues and Solutions in Air Toxics Source Impacted Ambient Air Monitoring for Use in Risk Assessment. Fourth Annual West Coast Regional Conference: Current Issues in Air Toxics. November.

Gates, L.J., S.B. Libicki, R. Scofield, and J. Wilhelmi. 1993. A flexible real-time ambient air monitoring program during Superfund Site redevelopment. EPA/AWMA Field Screening Methods for Hazardous wastes and Toxic Chemicals. February 24-26.

P.M. Salmon, S.B. Libicki, and C.R. Robertson. 1988. A theoretical investigation of convective transport in the hollow fiber reactor. Chemical Engineering Communications 66:221 248.

Libicki, S.B., P.M. Salmon, and C.R. Robertson. 1986. Measurement of inert gas permeabilities in compact bacterial cell aggregates using an annular reactor. Annals of the New York Academy of Sciences, Vol. IV; and Biochemical Engineering 469:145 151.

Karel, S., S. Libicki, and C.R. Robertson. 1985. The immobilization of whole cells: Engineering principles. Chemical Engineering Science 40(8):1321 1354.

Campbell, J.H., P. Peters, S.B. Libicki, M.L. Gregg, and J.E. Clarkson. 1981. Analysis of the operation of Occidental's modified in situ retort 6. In Fourteenth Oil Shale Symposium Proceedings, Golden, Colo.: Colorado School of Mines Press.

Campbell, J.H., J.H. Raley, F.H. Ackerman, W.A. Sandholtz, and S.B. Libicki. 1980. Investigation of critical parameters in modified in situ retorting. In Thirteenth Oil Shale Symposium Proceedings, Golden, Colo.: Colorado School of Mines Press

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RALPH E MORRIS
Managing Principal
Ralph Morris is the Managing Principal at Ramboll’s North California, Utah and Colorado Offices, where he directs air quality modeling and analysis, emission inventory development, control strategy evaluation, and regulatory air issues projects. With almost 40 years of air quality experience, Ralph is one of the original developers of many of the photochemical air quality models that are being or have been used for regulatory decision making in the United States and around the world, including co-developer of Ramboll’s Comprehensive Air Quality Model with extensions (CAMx) as well as the UAM and UAM-V models.

In the late 1970s and 1980s, Ralph was one of the pioneers in modeling air pollution in Los Angeles using one of the first ever photochemical grid models (PGM), the Urban Airshed Model (UAM).

The UAM was used to identify the optimal emissions control strategies for reducing ozone in Los Angeles targeting reducing ozone precursors that most efficiently reduce ozone and avoid reducing emissions from sources that would increase ozone. In the late 1980s, Ralph performed the EPA Five Cities UAM Study for the United States Environmental Protection Agency (USEPA) that demonstrated the use the UAM PGM for ozone air quality planning culminating in the delivery of the UAM to USEPA in 1990 as the USEPA-recommended ozone model. In the late 1980s and early 1990s, Ralph developed the next generation variable grid PGM (UAM-V) that treats urban city and regional transport issues within the same model and was used by the Ozone Transport Assessment Group (OTAG) to define the first regional control strategies designed to reduce the contributions of transport in the eastern U.S. (i.e., NOx SIP Call). Ralph also led the development of ozone and PM2.5 State Implemental Plans (SIPs) for numerous cities to allow them to achieve clean air. After joining Ramboll Environ in 1994, Ralph was one of the leaders in the development of the Comprehensive Air-quality Model with extensions (CAMx) PGM that is being used today around the world for air quality planning, including for USEPA’s transport rules. During the 1990s Ralph was involved in numerous ozone and PM2.5 SIP modeling studies and analyzed long-range transport of air pollutants.

In the 2000s, Ralph directed the development of an updated Pollutants in the ATmosphere for Hong Kong (PATH) air quality modeling system for the Hong Kong Environmental Protection Department (HKEPD) and applied it to southeast Asia to assess regional transport and urban ozone and particulate matter formation. During this time he directed the application of regional particulate matter (PM), ozone and visibility modeling using CMAQ and CAMx photochemical grid models for the southeastern (VISTA/ASIP), western (WRAP) and central (CENRAP) US Regional Planning Organizations (RPOs) for the development of the first round of regional haze State Implementation Plans (SIPs) that were due in 2007.

CONTACT INFORMATION
Ralph E Morris
[email protected]
+1 (415) 8990708
Ramboll
773 San Marin Drive
Suite 2115
Novato, CA 94998
United States of America

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For the last decade Ralph has been leading regional air quality modeling for Alberta Environment and Park for a variety of issues including to assess the impacts of oil sands, development of modeling databases for various regions in Alberta and most recently to model the high winter PM2.5 occurrences in Edmonton and Red Deer. He led or is leading the application of the CMAQ and CAMx models to address numerous ozone and PM2.5 State implementation Plans (SIPs), as well as to address other air quality and air quality-related value (AQRV) issues associated with oil and gas development projects.

Ralph has also addressed NO2 and SO2 issues including SIPs. Ralph was an original member of USEPA’s ozone and fine particulate guidance workgroup and the CMAS Models-3/CMAQ External Advisory Committee (EAC).

CAREER
1994-Present
Managing Principal
Ramboll (formerly Ramboll Environ and ENVIRON), Northern California, United States 1979-1994
Manager Advanced Modeling Group and Director of Model Development Program ICF/Systems Applications International, San Rafael, California, United States 1977-1979
Associate Professor
University of California, Davis, California, United States

EDUCATION
1977-1979
MA, Mathematics
University of California, Davis, California, United States 1974-1976
BA, Mathematics
University of California, Berkeley, California, United States 1972-1974
University of California, San Diego, California, United States

EXPERIENCE
Over the last 39 years, Ralph has been involved in thousands of air quality studies. These studies include the development of clean air plans for cities and states so that they attain the health-based air quality standards and the evaluation of the air quality impacts of numerous types of sources. A few examples for some of Ralph’s more recent projects are provided below. . WRAP Regional Haze Photochemical Modeling. Ralph is currently leading the development of photochemical modeling databases for western states to be used in the next round of reginal haze SIPs due July 2021. For the Western Regional Air Partnership (WRAP), Ralph has set up the CMAQ and CAMx models for the 2014 calendar year and conducted model performance evaluations. Denver 2020 and 2023 Ozone Attainment Demonstration Modeling. Ralph is currently leading the next round of Denver ozone attainment demonstration modeling. The CAMx and CMAQ models are being set-up for the 2016 summer ozone season and 2020 and 2023 future year attainment demonstration modeling is being conducted to address attainment of the 2008 and 2015 ozone NAAQS, respectively.
Allegheny County Annual PM2.5 State Implementation Plan. Project Director for performing the air quality modeling to define emissions control strategy to demonstrate that Allegheny County

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(Pittsburgh), Pennsylvania will attain the annual PM2.5 National Ambient Air Quality Standard (NAAQS). Performed 36/ 12/ 4/1.30.444 km WRF meteorological modeling for the 2011 year.

SMOKE emissions modeling for 2011 and 2021. CAMx regional 36/12 km modeling to provided boundary conditions for mesoscale 4/1.33 km PM source apportionment modeling for 2011 base and 2021 future years. 2021 PM control strategy evaluation. Evaluation of USEPA’s 2011 National Air Toxics Assessment (NATA). Evaluated and assessed USEA’s 2011 NATA modeling approach and results for modeling hundreds of air toxics compounds on a national scale. The 2011 NATA combined CMAQ national modeling results for reactive and non-reactive pollutants at 12 km grid cell resolution with AERMOD local-scale non-reactive modeling results by using the AERMOD results for receptors in the 12 km grid cell in a relative fashion to scale the CMAQ 12 km average concentrations. This unique method of model fusion of the CMAQ and AERMOD modeling results overcomes some of the issues associated with other techniques (e.g., CMAQ zero-out runs) when combining modeling results with disparate formulations.
Dynamic Evaluation of Ozone Models for the South Coast (Los Angeles) Air Basin (SoCAB). Project Manager for conducting a dynamic evaluation of the CMAQ photochemical grid model in the SoCAB (Los Angeles, California region) using a 2008 and 2012 CMAQ modeling database. The dynamic evaluation compared the CMAQ modeled ozone trends over a long time period (1990-2015) with the observed ozone trends and found the CMAQ model underestuimat6ed the observed rate of ozone reductions over time. Potential reasons for this included the likely underestimation of VOC or overestimation of NOx emissions in the region.
Denver 2017 Ozone SIP Modeling. For over a decade, Ralph has led the Denver ozone SIP modeling for the 2003, 2008 and ow the 2017 Denver ozone SIPs. For the Denver 2017 ozone SIP modeling we developed 2011 CAMx PGM modeling database using WRF meteorological and SMOKE emissions modeling. This included high-resolution mobile source emissions for the Denver region using linkbased activity data from a Transportation Demand Model (TDM) and mobile source emission factors from MOVES2014. Conducted CAMx 2011 base case modeling and model performance evaluation.

Projected emission to 20017 and 2023 and conducted emission reduction control strategy modeling to demonstrate attainment of the ozone standard.
Allegheny County 1-Hour SO2 State Implementation Plan. Project Manager for performing the air quality modeling to define emissions control strategy to demonstrate that Allegheny County (Pittsburgh), Pennsylvania will attain the 1-hour SO2 National Ambient Air Quality Standard (NAAQS). Perform 36/ 12/ 4/1.3 km WRF meteorological modeling for multiple years. Conduct model shoot-out using multiple models (e.g., AERMOD, CALPUFF and SCICHEM) and model configurations to determine best performing model for simulating SO2 and use model to demonstrate attainment of the SO2 NAAQS.
BLM Environmental Impact Statement and Resource Management Plan for Oklahoma, Texas and Kansas. Project Manager for preparing the air quality and climate change sections of the Environmental Impact Statement (EIS)/ Resource Management Plan (RMP) for the U.S. Bureau of Land Management (BLM) and Bureau of Indian Affairs (BIA) to guide the management of BLM- and BIA-administered lands in the states of Oklahoma, Texas and Kansas Navajo Generating Station Environmental Impact Statement. Project Manager for coordinating the Environmental Impact Statement (EIS) required under the National Environmental Policy Act (NEPA) for the Navajo Generating Station coal-fired power plant and Kayenta Coal Mine Complex in Arizona.

Technical services include air quality modeling and analysis of air monitoring data for criteria and hazardous air pollutants, assessments of human health risk and ecological risk due to atmospheric deposition from the emission sources, and preparation of Technical Support Documents for the EIS. Western Air Quality Study (WAQS). Project Manager for WRF meteorological, SMOKE emissions and CMAQ/CAMx air quality modeling of the western U.S. to develop the next generation air quality modeling databases to address ozone, PM2.5, visibility and deposition issues in the western U.S..

Develop new 2008, 2011 and 2014 regional modeling platforms and distribute using the Intermountain West Data Warehouse (IWDW). Assess the role of regional transport on ozone, PM and visibility issues in western U.S. states.
Air Quality Impacts of Off-Shore Oil and Gas Production. Ralph is currently leading two studies for BOEM to estimate the on-shore air quality impacts due to off-shore oil and gas development in the

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Arctic Sea near Alaska and the Gulf of Mexico. This multi-year multi-million dollar study will project future year emissions and air quality impacts and develop emission exception screening thresholds. Air Quality Impacts of Fires. Project Manager of studies to assess the contributions of wildfires, prescribed burns and agricultural burning to ozone and PM air quality throughout the USA. Develop fire emission inventories and use the CAMx photochemical grid model source apportionment tool to calculate the contributions of fires to ozone and PM air quality. Results are used to identify exceptional events and assist planners in fire management practices. BLM Montana/Dakotas Photochemical Grid Model Modeling Study. Project Manager for the BLM Montana/Dakotas PGM modeling study to assess the air quality and AQRV impacts due to oil and gas development. The Bakken Shale formation in the Montana/Dakotas region is the most rapidly growing oil and gas development area in the U.S. Under this study, Ramboll is developing a comprehensive oil and gas emissions inventory and performing base year 2012/2013 and future year 2032 modeling using the CAMx photochemical grid model. Allegheny County PM2.5 SIP Modeling. The PM2.5 problem in Allegheny County (Pittsburgh), Pennsylvania is due to a combination of regional transport from upwind states and local sources within a river valley complex terrain environment. Ralph Morris led the Allegheny County PM2.5 SIP modeling effort that used the CAMx photochemical grid model with a 36 km CONUS, 12 km Midwest, 4 km southeastern Pennsylvania and 0.8 km Allegheny County grid nests to demonstrate the area would achieve the 24-hour PM2.5 standard by 2010. CAMx was run on the 36/ 12/ 4/0.8 km grids using two-way grid nesting. Local sources were treated using the CAMx subgrid-scale Plumein-Grid treatment. Development of Air Quality Modeling System for Hong Kong. Ralph was Project Manager and led the development of a new air quality modeling system for Hong Kong. The WRF/MM5 meteorological, SMOKE/CONCEPT emissions and CMAQ/CAMx air quality models were set up for a 27/ 9/ 3/1 km modeling domain with the 36 km domain covering Asia and the 1 km domain focused on Hong Kong. The modeling system was delivered to the HKEPD as a turn-key system. St. Louis Ozone and PM2.5 SIP. Ralph led the air quality modeling efforts for the development of clean air plans for St. Louis, Missouri that were included in the St. Louis ozone and PM2.5 State Implementation Plans (SIPs). He worked with the states of Missouri and Illinois to identify the optimal control plan for the region and performed air quality modeling to demonstrate that St.

Louis would achieve the ozone and PM2.5 standards.
Air Quality Assessments in Alberta, Canada. For almost a decade, Ralph Morris has been leading air quality studies for Alberta Environment to address Canada wide standards and Province air quality goals and objectives. These activities have included developing emission inventories for the Alberta oil sands region and urban areas, conducting meteorological modeling and performing air quality modeling using the CMAQ model to address ozone, PM2.5, SO2, NO2, exposure and deposition issues in the Province.
Expert Testimony for Air Quality Related Issues. Because of Ralph’s vast expertise in air quality issues and in particular air quality modeling, over the last two decades he has served as an expert witness in numerous litigation cases.
Ameren Rush Island: Ralph was an expert witness and testified at trial in St. Louis April 2019 in a case where the Rush Island coal-fired power plant was accused of causing health effect impacts due to alleged illegal emissions since it failed to obtain a PSD permit and install BACT. LG&E Cane Run Class Action Suit: Starting in 2015, Mr. Morris is serving as an expert witness led by Hunton and Williams in a case involving nuisance dust deposition from the Louisville Gas and Electric Cane Run coal-fired EGU.
Minnesota Power Plant Damage Assessment: During 2015, Ralph performed air quality modeling of the potential damages and costs associated with fossil-fueled power generation in Minnesota and prepared testimony.
Mead Westvaco Luke Mill: Expert witness and testify at trial in a case where a Maryland paper mill was accused of violating the Clean Air Act (CAA) and emitting illegal emissions (2012-2016).

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DTE Energy Monroe: In 2010-2011 Ralph was retained as an expert witness by Hunton and Williams and prepared expert report and attended trial in Detroit for the USDOJ NOV case against then Monroe coal-fired power plant in the Detroit, Michigan region. AEP NOV: Ralph was an expert witness for American Electric Power (AEP) from 2003-2006 through Sidley Austin in the US DOJ NOV charges against 9 coal-fired power plants in the Midwestern US.
Illinois Power/Dynegy Baldwin NOV: Ralph was an expert witness for Illinois Power through Akin Gump in the US DOJ Notice of Violation case against the Baldwin Power Plant in Illinois. Ralph prepared expert reports and was deposed on the ozone and PM impacts of the alleged excess emissions including a review and critique of the plaintiffs CALPUFF modeling that found errors and omissions.
First Energy Sammis: Expert witness for the Sammis coal fired power plant in Ohio NOV case. Louisiana Generating Big Cajun 2: Ralph was an expert witness for a USDOJ NOV case against the Big Cajun 2 coal-fired power plant in Baton Rouge, Louisiana during 2012. WE Energies Power the Future: In 2004, Ralph performed air quality modeling using CAMx and testified in front of a judge in Madison, WI on the Wisconsin Electric’s plans to retire an old and build a new coal fired power plant at the Oak Creek facility. Testimony also included a critical review of CALPUFF modeling performed by the opponents.
Minnesota Acid Rain Legislation: In the early 1980s Ralph performed modeling and testified in Minneapolis, MN in front of a judge for Northern States Power regarding the impacts of local sources in Minnesota on acid deposition in Minnesota.
Oil and Gas Environmental Impact Statements. Ralph has led the air quality modeling component of several oil and gas Environmental Impact Statements to assess the air quality, visibility and deposition impact of oil and gas development in Colorado, Utah, Wyoming and New Mexico Air Quality Permitting Studies. As part of the permitting process, Ralph has conducted numerous air quality modeling studies to demonstrate that new sources would be compliant with air quality standard and thresholds of concern. Sources evaluated include coal and natural gas powered electricity generation; cement plans and oil and gas production, distribution and refining. Air Quality Impacts of Mobile Sources. Ralph has performed numerous studies to assess the air quality impacts of alternative engine technologies and fuels. In the 1980s he modeled the air quality impacts of alternative fuels in five cities for the USEPA. In the 1990s he led the air quality modeling component of the $20M Auto/Oil Program for the automobile manufacturers and oil companies. He also led the assessment of the air quality impacts of hybrid vehicles for a joint study by General Motors and Toyota. More recently he evaluated air quality impacts of passenger vehicles for Toyota and the air quality impacts in California due to the use of biodiesel in on-road and non-road diesel engines.
Technical Assistance to USEPA. For over three decades, Ralph has provided technical assistance to the USEPA to assist them in implementing their air program and developing the USEPA air quality modeling guidelines. This assistance included demonstrating how photochemical grid models (PGMs) can be used in ozone air quality planning and delivering the UAM PGM to USEPA in 1990 as a turn-key PGM ozone modeling system. In 2012 Ralph evaluated six long range transport (LRT) models using atmospheric field study tracer tests, evaluated chemical dispersion models using aircraft data and demonstrated how a PGM can be used for single-source modeling that helped EPA formulate their new July 2015 air quality modeling guidelines. More recently he is assisting USEPA to update the chemical mechanisms in the CAMx and CMAQ models and implement improved aqueous-chemistry and secondary organic aerosol modules. Various Clients. Prior to joining ENVIRON, Ralph worked for over 15 years at Systems Applications International (SAI) in San Rafael (now part of ICF Consulting), California, where he was Director of the Advanced Modeling Program, managed model development activities and air quality modeling and analysis studies. His work at SAI included the development and application of the RPM, UAM, UAM-V and REMSAD modeling systems.

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PEER-REVIEWED PUBLICATIONS
Posner, L.N., G. Theodoritsi, A. Robinson, G. Yarwood, B. Koo, R. Morris, M. Mavko, T. Moore and S.

Pandis. 2019. “Simulation of Fresh and Chemically-Aged Biomass Burning Organic Aerosol.” Atmos. Env. 196 (2019) 27-37.

Karamchandani, P., R. Morris, G. Yarwood, B. Brashers, D. Henn, I. Sykes, E. Knipping and N. Kumar. “SCICHEM: An Alternative Photochemical Model to Calculate Single Source Impacts of Ozone and Fine Particulate Matter.” A&WMA EM Magazine, October 2018.

Karamchandani, P., R. Morris, A. Wentland, T. Shah, and J. Lester. 2017. “Dynamic evaluation of photochemical grid model response to emission changes in the South Coast Air Basin in California.” Atmosphere,2017,8, 145; doi:10.3390/atmos8080145.

Brashers, B., R. Morris and J. Maranche. 2017. “The Challenges of Modeling Air Quality in Allegheny County, Pennsylvania.” A&WMA EM Magazine, June 2017.

Koo, B., P. Piyachaturawat, R. Morris and E. Knipping. 2012. “Evaluation of the Variability in Chemical Transport Model Performance for Deposition and Ambient Concentrations of Nitrogen and Sulfur Compounds.” Atmosphere, V3, pp 400-418. August.

Cho, S., R. Morris, P. McEachern, T. Shah, J. Johnson and U. Nopmongcol. 2012. “Emission Sources Sensitivity Study for Ground-Level Ozone and PM2.5 Due to Oil Sands Development Using Air Quality Modeling System: Part I – Model Evaluation for Current Year Base Case Simulation.” Atmos.

Env., V55, pp 533-541.

Cho, S., R. Morris, P. McEachern, T. Shah, J. Johnson and U. Nopmongcol. 2012. “Emission Sources Sensitivity Study for Ground-Level Ozone and PM2.5 Due to Oil Sands Development Using Air Quality Modeling System: Part II – Source apportionment modeling.” Atmos. Env., V55, pp 542- 556.

Emery, C.A., J. Jung, N. Downey, J. Johnson, M. Jimenez, G. Yarwood, R.E. Morris. 2012. “Regional and Global Modeling Estimates of Policy Relevant Background Ozone Over the United States.” Atmos.

Env., V47, pp 206-217. February.

Emery, C.A., E. Tai, R.E. Morris and G. Yarwood. 2011. “Investigation into Approaches to Reduce Excessive Vertical Transport Over Complex Terrain in a Regional Photochemical Grid Model.” Atmos.

Env., V45, Issue 39, pp 7341-7351. December.

Koo, B., C. Chien, G. Tonnesen, R.E. Morris, J.R. Johnson, T. Sakulyanontvittaya, G. Yarwood. 2010. “Natural Emissions for Regional Modeling of Background Ozone and Particulate Matter and Impacts on Emissions Control Strategies.” Atmos Environ., 44 (2010) 2372-2382, (doi:10.1016/j.atmosenv.2010.02.041) June.

Koo, B., G. M. Wilson, R. E. Morris, A. M. Dunker, and G. Yarwood. 2009. Comparison of Source Apportionment and Sensitivity Analysis in a Particulate Matter Air Quality Model. Environ. Sci.

Technol., 43, 6669-6675.

Wagstrom, K., M. Spyros, N. Pandis, G. Yarwood, G.M. Wilson and R.E. Morris. 2008. “Development and Application of a Computationally Efficient Particulate Matter Apportionment Algorithm in a ThreeDimensional Chemical Transport Model.” Atmos Env, 42: 5650-5659. July.

Morris, R.E., B. Koo, A. Guenther, G. Yarwood, D. McNally, T. Tesche, G. Tonnesen, J. Boylan and P.

Brewer. 2006. “Model Sensitivity Evaluation for Organic Carbon Using Two Multi-Pollutant Air Quality Models that Simulate Haze in the Southeastern United States.” Atmos. Env. 40 (2006) 4960-4972.

Morris, R., T.W. Tesche, G. Tonnesen, D. McNally, J. Boylan and P. Brewer. 2006. “CMAQ/CAMx Annual 2002 Performance Evaluation Over the Eastern U.S.” Atmos. Env. 40 4906-4919.

Morris, R., B. Koo and G. Yarwood. 2005. “Evaluation of Multisectional and two-Section Particulate Matter Photochemical Grid Models in the Western United States.” J. Air & Waste Man. Assoc., V55, No. 11, pp1683-1693. November.

Morris, R., D. McNally, T.W. Tesche, G. Tonnesen, J. Boylan and P. Brewer. 2005. “Preliminary Evaluation of the Community Multiscale Air Quality Model for 2002 Over the Southeastern United States.” J. Air & Waste Man. Assoc., V55, No. 11, pp1694-1708. November.

Morris, R.E., B. Koo, Alex Guenther, G. Yarwood, D. McNally, T.W. Tesche, G. Tonnesen, J. Boylan, P.

Brewer. 2004. “Diagnostic Model Performance Evaluation Using Multiple Air Quality Models For

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Simulating Ozone, Particulate Matter and Regional Haze in the Southeastern United States.” Atmos Env., March.

Morris, R.E., and R.D. Scheffe. 1993. “A Review of the Development and Application of the Urban Airshed Model.” Atmos Env. V27B, No. 1, pp 23-39.

PRESENTATIONS
Morris, R. 2019. Single-Source Visibility Ranking and Modeling Techniques for Regional Haze SIPs.

Presented at A&WMA 112th Annual Conference and Exhibition, Quebec City, Canada. June 25-28, 2019.

Morris, R., M. Zatko, B. Brashers and J. Maranche. 2019. PM2.5 Precursor Insignificance Demonstration for Allegheny County, Pennsylvania. Presented at A&WMA Guideline on Air Quality Models: Planning Ahead. Durham, North Carolina. March 19-21, 2019.

Morris, R., 2019. Air Quality Modeling of the Gulf of Mexico Region. Presented at A&WMA Guideline on Air Quality Models: Planning Ahead. Durham, North Carolina. March 19-21, 2019.

Morris, R. and B. Brashers. Introduction to CAMx. Half Day Course Presented at A&WMA Guideline on Air Quality Models: Planning Ahead. Durham, North Carolina. March 19-21, 2019.

Morris, R., L. Parker and T. Stoeckenius. 2019. Analysis of Recent Observed Ozone Increases in the South Coast Air Basin in 2016-2018 While Emissions Are Reduced. Presented at Coordinating Research Council (CRC) 29th Real World Emissions Conference, Long Beach, California. March 11- 13, 2019.

Morris, R. Denver Ozone Modeling Update. Presented at David Graham and Stubbs Air Quality Summit, Denver, Colorado. September 13, 2018.

Morris, R., L. Parker and T. Stoeckenius. 2018. Effects of Meteorology and Other Processes on Observed and Modeling Ozone in the SoCAB. Presented at Southern California Ozone Research Symposium (SCORES), UC Riverside, California. June 6-7, 2018.

Morris, R. 2018. Contributions of International Emissions to Ozone Attainment in the United States.

Presented at 111th A&WMA Conference and Exhibition, Hartford, Connecticut. June 25-28, 2018.

Morris, R. 2018. Assessment of the Air Quality Impacts due to Oil and Gas Development in the Gulf of Mexico Region. Presented at 111th A&WMA Conference and Exhibition, Hartford, Connecticut. June 25-28, 2018.

Morris, R. and U. Nopmongcol. 2018. Source Contribution to Secondary PM2.5 in Central Alberta.

Presented at 2018 A&MA CPANS Conference -- Western Canada: Environment State of the Union.

Calgary, Alberta. May 9, 2018.

Morris, R., L. Parker and T. Stoeckenius. 2018. Analysis of Recent Ozone Increases in the South Coast Air Basin. Presented at CRC 28th Real World Emissions Conference, Garden Grove, California.

March 18-21, 2018.

Morris. 2017. Fires and International Uncontrollable Emissions. Presented at Regional Haze Planning Workshop, Denver, CO. December 5-7, 2017.

Morris, R. and D. McNally. 2017. Preliminary Future Ozone Projections and Source Contributions.

Regional Air Quality Council Board Meeting. Denver, CO. November 3, 2017.

Morris, R. and D. McNally. 2017. Modeling Sensitivities Overview. Denver Ozone Modeling Forum.

Denver, CO. November 2, 2017.

Morris, R. and D. McNally. 2017. Local Source 2017 Ozone Source Apportionment Modeling. Denver Ozone Modeling Forum. Denver, CO. November 2, 2017.

Morris, R. and D. McNally. 2017. Ozone Contributions of International Emissions using 2011 Modeling Platform. Denver Ozone Modeling Forum. Denver, CO. November 2, 2017.

Morris, R. and D. McNally. 2017. 2023 Preliminary Modeling: 2023 Ozone Projections and VOC/NOx Sensitivity. Denver Ozone Modeling Forum. Denver, CO. November 2, 2017.

Morris, R. BOEM Photochemical Modeling of Offshore Oil and Gas Development in the Arctic. Presented at U.S. Canada Northern Oil and Gas Research Forum, Anchorage, Alaska. October 11-13, 2017.

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Morris, R. 2017. Evaluation of Visibility Metrics for Demonstrating Reasonable Progress Goals under the Regional Haze Rule. Presented at 4th Biannual Western Modeling Workshop, Boulder, Colorado.

September 6, 2017.

Morris, R., Z. Adelman, T. Moore and R. Bates. 2017. Southern New Mexico Ozone Modeling Study and the Section 179B Option. Presented at 4th Biannual Western Modeling Workshop, Boulder, Colorado.

September 6, 2017.

Morris, R., J. Jung, M. Zatko and D. McNally. 2017. Zero-Out Global Emissions Modeling Analysis of the Denver/NFR Ozone Nonattainment Area. Presented at 4th Biannual Western Modeling Workshop, Boulder, Colorado. September 6, 2017.

Morris, R. 2017. Windows Version of CAMx. Presented at A&WMA Guideline on Air Quality Models: A New Path, Chapel Hill, North Carolina. November 14-16, 2017.

Morris, R. and B. Brashers. Introduction to CAMx with Single-Source Discussion. Half Day Course Presented at A&WMA Guideline on Air Quality Models: A New Path, Chapel Hill, North Carolina.

November 13, 2017.

Morris, R., P. Karamchandani, A. Wentland, T. Shah and J. Lester. 2017. Measured versus Modeled Ozone Trends in California’s South Coast Air Basin and Effects on Mobile Source Controls. Presented at CRC 27th Real World Emissions Conference, Long Beach, California. March 26-29, 2019.

Morris, R., J. Jung, B. Brashers and J. Maranche and A. Sadar. 2017. Hybrid Grid/Plume Modeling for the Allegheny County 24-Hour PM2.5 Attainment Demonstration. Presented at 110th Annual Conference and Exhibition, Pittsburgh, Pennsylvania. June 5-8, 2017.

Morris, R. 2017. Measurements, Emissions and Modeling. Presented at the Critical Review in the 110th Annual Conference and Exhibition, Pittsburgh, Pennsylvania. June 5-8, 2017.

Morris, R., Z. Adelman, and T. Moore. Development and Application of Photochemical Modeling Systems to Address Ozone, Particulate Matter, Visibility and Deposition Issues in the Rocky Mountain Region.

Presented at the 2-17 Air Quality Conference of the Rocky Mountain States Section of the A&MA, Denver, Colorado. April 13, 2017.

Kemball-Cook, S., R. Morris and G. Yarwood. 2016. Identifying the Influence of Exceptional Events and International Transport – An Overview of When and How to Apply Clean Air Act Provisions for Background Ozone. Presented at the American Fuel and Petrochemical Manufactures 2016 Annual Conference, San Francisco, California. March 13-15, 2017.

Vijayaraghavan, K., Beardsley, R., Jung, J., Yarwood G. & Morris, R. 2016. “The Contribution of Emissions Sources and Atmospheric Deposition to Mercury in South Florida and the Everglades.” Society of Environmental Toxicology and Chemistry. Orlando, FL. November.

Morris, R.. 2016. SMOKE-MOVES Processing – Incorporate Travel Demand Model Data in Denver Ozone Modeling. Presented at 15th Annual CMAS Conference, Chapel Hill, NC, October 24-36.

Morris, R. 2016. “Modeling of Single-Source Secondary Impacts using the Higher Order Direct Decoupled Method Sensitivity.” Presented at 15th Annual CMAS Conference, Chapel Hill, NC, October 24-36.

Nopmongcol. U., R. Morris, C. Archuleta, J. Adlhoch. 2016. “A Conceptual Approach to Address Anthropogenic / Non-Anthropogenic Emission Sources to Help Develop a More Accurate Regional Haze Program Glidepath.” Presented at the A&WMA Visibility Conference, Jackson Hole, WY, September 27-30.

Morris R. and U. Nopmongcol. 2016. “Assessment of the Contributions to Visibility Impairment in the Western US and Effect of New Guidance for Tracking Progress.” Presented at the A&WMA Visibility Conference, Jackson Hole, WY, September 27-30.

Morris. 2016. “Evaluation of Revised Uniform Rate of Progress Goals for Western United States.” Presented at the A&WMA Visibility Conference, Jackson Hole, WY, September 27-30.

Morris. 2016. “BOEM Air Quality Studies.” Presented at A&WMA 109th Annual Conference, New Orleans, LA. June.

Nopmongcol, U., Z. Liu, J. Johnson, T. Shah., R. Morris. 2016. “Formation of Secondary Particulate Matter in Capital Region.” Presented at AWMA Annual Conference, Alberta, Canada. May.

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Morris. 2016. “Single-Source Ozone Modeling Studies.” Presented at A&WMA Guidelines on Air Quality Models Conference, Chapel Hill, NC. April.

Karamchandani, P., B. Chowdhury, B. Brashers, L. Parker, G. Yarwood, R. Morris, A. Kaulfus, E.

Knipping. 2015. “SCICHEM 3.0: Improvements, Testing and Evaluation.” Poster presentation at the 14th Annual CMAS Conference, Chapel Hill, NC., October.

Parker, L.K., R.E. Morris, J. Zapert, F. Cook, C. Meister, B. Koo, D.J. Rasmussen, J. Jung, J. Grant, J.

Johnson, T. Shah and T. Pavlovic. 2015. “Photochemical Grid Modeling Study to Assess Potential Air Quality Impacts Associated with Energy Development in Colorado and Northern New Mexico.” Presented at the Fall 2015 AGU Conference.

Morris, R.E. 2014. Ozone and PM Source Apportionment Modeling for Reducing Regional Transport.

Presented at 4th International Workshop on Regional Air Quality Management in Rapidly Developing Economic Regions (4RAQM), January 14-17, 2014, Hong Kong, China.

Koo, B., R. Morris and G. Yarwood. 2013. “Transformation Rate of SO2 to Sulfate for the Houston Ship Channel based on TexAQS 2006 Data.” Presented at the Texas AQRP Workshop, Austin, TX.

November.

Karamchandani, P., R. Morris, B. Brashers, G. Yarwood, L. Parker, E. Knipping, N. Kumar, B.

Chowdhury, and I. Sykes. 2013. “Application of SCICHEM for Near-Field and Far-Field Single Source Impacts”. Presented at the AWMA Guideline on Air Quality Models: The Path Forward Conference, Raleigh, NC, March.

Karamchandani, P., R. Morris, G. Yarwood, B. Brashers, E. Knipping, B. Chowdhury, and Ian Sykes. 2012. “Application of the Reactive Plume Model, SCICHEM-2012, to Simulate Near-Source 1-hour NO2 Concentrations”. Presented at the 11th Annual CMAS Conference, Chapel Hill, NC, October.

Emery, C., J. Jung, G. Yarwood, R. Morris. 2011. “Regional/Global Modeling of PRB Ozone Over the US.” Presented at the 10th Annual CMAS Conference, Chapel Hill, NC, October.

Bar-Ilan,A., J. Grant, R. Parikh, A. Pollack, R. Morris, D. Henderer, K. Sgamma. 2010. “A Comprehensive Emissions Inventory of Upstream Oil and Gas Activities in the Rocky Mountain States.” Presented at the 19th International Emission Inventory Conference, "Emission Inventories - Informing Emerging Issues." San Antonio, TX, September.

Kemball-Cook, S. T. Shah and R. Morris. 2010. “Challenges for Making Ozone, PM2.5 and Visibility Projections in Remote Regions with Sparse Measurement Databases.” Presented at AWMA 103rd Annual Conference, Alberta, Canada. June.

Bar-Ilan, A., J. Grant, R. Parikh, A. Pollack, R. Morris, D. Henderer, K. Sgamma. 2010. “A Comprehensive Emissions Inventory of Upstream Oil and Gas Activities in the Rocky Mountain States.” Presented at the AWMA 103rd Annual Conference, Alberta, Canada. June.

Morris, R., U. Nopmongcol, G. Mansell, C. Mooney, S. Cho. 2010. “Assessment of the Air Quality Impacts of Alberta Oil Sands Development on Tropospheric Ozone and Particulate Matter.” Presented at AWMA 103rd Annual Conference, Alberta, Canada. June.

Emery, C.A., E. Tai, R.E. Morris and G. Yarwood. 2010. “A New Algorithm in CAMx to Reduce Excessive Vertical Transport over Complex Terrain.” Presented at AWMA 103rd Annual Conference. Alberta, Canada. June.

Kemball-Cook, S., T. Shah and R. Morris. 2010. “Challenges for Making Ozone, PM2.5 and Visibility Projections in Remote Regions with Sparse Measurement Databases.” Presented at AWMA 103rd Annual Conference, Alberta, Canada. June.

Morris, R.E., G.E. Mansell, A.K. Pollack, D. Yeung, B. Ho, C. Fung, K. Leung. 2009. “Development of a New Air Quality Modeling System for the Hong Kong and Vicinity Regions.” Presented at The 2nd International Workshop on Regional Air Quality Management in Rapidly Developing Economic Regions; International Conference Centre, South China University of Technology, University City, Guangzhou, China. November.

Morris, R.E., S. Kemball-Cook, U. Nopmongcol, L. Parker. 2009. “Fine-Scale Modeling with CMAQ and CAMx for Air Toxics, PM and Ozone in Detroit.” Presented at AWMA Guideline on Air Quality Models:

Next Generation of Models Conference, Research Triangle Park, NC. October.

Morris, R.E., S. R. Kemball-Cook, U. Nopmongcol and L. K. Parker. 2009. “Use of Photochemical Grid Models to Address Far-Field Air Quality and Air Quality Related Value Impacts of Proposed New

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Sources.” Presented at AWMA Guideline on Air Quality Models: Next Generation of Models Conference, Research Triangle Park, NC. October.

Emery, C.E., E. Tai, R.E. Morris, G. Yarwood. 2009. “Reducing Vertical Transport Over Complex Terrain in Photochemical Grid Models.” Presented at the CMAS 8th Annual Conference, Chapel Hill, NC.

October.

Morris, R.E., S. Kemball-Cook, B. Koo, T. Stoeckenius, G. Yarwood. 2009. “Simulation of Wintertime High Ozone Concentrations in Southwestern Wyoming.” Presented at CMAS 8th Annual Conference, Chapel Hill, NC. October.

Koo, B., G.M. Wilson, R.E. Morris, G. Yarwood. 2009. “Comparison of PM Source Apportionment and Sensitivity Analysis in CAMx.” Presented at CMAS 8th Annual Conference, Chapel Hill, NC. October.

Morris, R.E., J. Jung, E. Fujita, P. Brewer. 2009. “Assessment of the Sources of Organic Carbon at Monitoring Sites in the Southeastern US Using Receptor and Deterministic Models.” Presented at CMAS 8th Annual Conference, Chapel Hill, NC. October.

Morris, R.E., C. Emery, B. Koo, E. Tai, G. Stella, C. Loomis, D. McNally, G. Schewe. 2009. “Use of Hybrid AERMOD Plume and Photochemical Grid Modeling for PM2.5 Attainment Demonstration Modeling in the Birmingham and St. Louis Nonattainment Areas.” Presented at the AW&MA 102nd Annual conference and Exhibition, Detroit, MI. June.

Morris, R.E., J. Jung, E. Fujita, P. Brewer. 2009. “Assessment of the Sources of Organic Carbon at Monitoring Sites in the Southeastern United States Using Receptor and Deterministic Models.” Presented at the AW&MA 102nd Annual Conference and Exhibition, Detroit, MI. June.

Morris, R.E., S. Kemball-Cook, T. Shah and B. Koo. 2009. “Assessment of the Ozone, Air Quality and AQRV Impacts of Proposed Oil and Gas Production Projects in the Western U.S. Using Photochemical Grid Models.” Presented at the AW&MA 102nd Annual Conference and Exhibition, Detroit, MI. June.

Kemball-Cook, S., R. Morris, B. Koo, U. Nopmongcol, J. Johnson, T. Shah. 2009. “ Use of the CAMx Photochemical Grid Model to Assess the Air Quality and AQRV Impacts of Proposed Oil and Gas Production Projects in the Western U.S. Presented at the International Technical Meeting on Air Pollution Modelling and its Application, San Francisco, CA. May.

Koo, B., G. Yarwood, and R. Morris. 2008. “Evaluation of Secondary Organic Aerosol Formation in CAMx for Urban and Rural Area.” Presented at the AAAR 27th Annual Conference, Orlando, FL, October.

Wilson, G., B. Wang, C. Emery, R. Morris and G. Yarwood. 2008. “Applying a 3-D Photochemical Model (CAMx) in Multi-Processor Cluster (MPI) and Shared-Memory (Open-MP) Computing Environments.” Presented at the 7th Annual CMAS Conference, University of North Carolina, October 6-8.

Morris, R., B. Koo and T. Sakulyanontvittaya. 2008. “Use of Hybrid Grid/Plume Modeling to Address PM2.5 Attainment in the St. Louis Nonattainment Area.” Presented at the 7th Annual CMAS Conference, University of North Carolina, October 6-8.

Morris, R., T. Sakulyanontvittaya, J. Johnson, D. McNally, C. Loomis, and P. Brewer. 2008. “Use of PM Source Apportionment to Assess the Contributions of Individual Point Sources to PM2.5 Concentrations in the Eastern U.S.” Presented at the 7th Annual CMAS Conference, University of North Carolina, October 6-8.

Morris, R., B. Koo and T. Sakulyanontvittaya. 2008. “Use of Hybrid Grid/Plume Modeling to Address PM2.5 Attainment in the St. Louis Nonattainment Area.” Presented at the Air & Waste Management 101st Annual Conference, Portland, OR. June.

Pollack, A., R. Morris, D. Yeung, P. Sham, C. Fung, and K. Leung. 2008. “Emission Inventory Development for the Hong Kong Special Administrative Region.” Presented at the Air & Waste Management 101st Annual Conference, Portland, OR. June.

Pollack, A., R. Morris, D. Yeung, P. Sham, C. Fung, and K. Leung. 2008. “Application of Emission Processing Tools in Air Quality Modeling for Hong Kong Special Administrative Region.” Presented at the Air & Waste Management 101st Annual Conference, Portland, OR. June.

Emery, C.A., R. Morris and E. Tai, J. Wilkinson. 2008. “Columbia River Gorge Air Quality Study (CRGAQS): Photochemical Grid Modeling Results.” Presented at the Air & Waste Management 101st Annual Conference, Portland, OR. June.

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Morris, R., S. Kemball-Cook, D. Strohm, J. Johnson, and E. Tai. 2008. “Use of Photochemical Grid Models to Assess PSD Pollutant, Ozone, Visibility and Deposition Impacts Due to Proposed New Sources.” Presented at the Air & Waste Management 101st Annual Conference, Portland, OR. June.

Yeung D., P. Sham, R. Morris, A. Pollack, C. Fung, and K. Leung. 2008. “Development of a New Air Quality Modeling System for the Hong Kong Special Administrative Region.” Presented at the Air & Waste Management 101st Annual Conference, Portland, OR. June.

Emery, C.A., E. Tai, R.E. Morris, J.G. Wilkinson, P. Mairose. 2008. “CAMx Visibility Modeling Conducted for the Columbia River Gorge National Scenic Area Air Quality Study.” Presented at the Air & Waste Management Association’s Aerosol & Atmospheric Optics: Visual Air Quality and Radiation Conference. Moab, UT. April.

Morris, R.E., J. Johnson, B. Koo and B. Wang. 2008. “Deterministic Source Apportionment Modeling to Assess the Source Regions and Categories Contributions to Regional Haze in the Central United States.” Presented at the Air & Waste Management Association’s Aerosol & Atmospheric Optics:

Visual Air Quality and Radiation Conference. Moab, UT. April.

Morris, R., B. Koo, B. Wang, G. Stella, D. McNally, C. Loomis, G. Tonnesen, M. Omary and C.J. Chien. 2008. “Challenges in Modeling Visibility to Support the Development of Regional Haze State Implementation Plans.” Presented at the Air & Waste Management Association’s Aerosol & Atmospheric Optics: Visual Air Quality and Radiation Conference. Moab, UT. April.

Kemball-Cook, S., E. Tai, J. Johnson, and R. Morris. 2008. “Use of Photochemical Grid Models to Assess the Air Quality and AQRV Impacts of Proposed Oil and Gas Production Projects in the Western U.S.” Presented at the Air & Waste Management Association’s Aerosol & Atmospheric Optics: Visual Air Quality and Radiation Conference. Moab, UT. April.

Morris, R.E., B. Koo, J. Johnson and G. Yarwood, J. Turner and J. Garlock. 2007. “Hybrid Plume/Grid Modeling for the St. Louis PM2.5 SIP.” Presented at International Aerosol Modeling Algorithms Conference, UC Davis, CA. December.

Koo, B., G. Yarwood, R. Morris, K. Baker. 2007. “Evaluation of New Approaches to Modeling Atmospheric Organic PM in CAMx.” Presented at International Aerosol Modeling Algorithms Conference, UC Davis, CA. December.

Koo, B., G. Yarwood, R. Morris, T. Gaydos, and S. Pandis. 2007. “Equilibrium, Dynamic, and Hybrid Approaches for Atmospheric Aerosol Modeling.” Presented at International Aerosol Modeling Algorithms Conference, UC Davis, CA. December.

Morris, R.E., B. Koo, J. Johnson and G. Yarwood, J. Turner and J. Garlock, C. Ku, W. Vit, A. Alsharafi and J. Bennett. 2007. “Use of Hybrid Plume/Grid Modeling and the St. Louis Super Site Data to Model PM2.5 Concentrations in the St. Louis Area.” Presented at the 6th Annual CMAS Conference, UNCChapel Hill, NC. October.

Morris, R.E., B. Koo, B. Wang, G. Yarwood, G. Tonnesen, C. Chien, D. McNally, G. Stella. 2007. “Regulatory Decision Making using Advancements in Aerosol Science.” Presented at the AAAR 26th Annual Conference, Grand Sierra Resort, Reno, NV. September.

Koo, B., G. Yarwood, R. Morris, K. Baker. 2007. “Evaluation of New Approaches to Modeling Organic Particulate Matter in CAMx.” Presented at the AAAR 26th Annual Conference, Grand Sierra Resort, Reno, NV. September.

Morris, R.E., B. Koo, J. Johnson, G. Yarwood, J. Turner, J. Garlock, C. Ku, W. Vit, A. Alsharafi. 2007. “Improvements in Modeling Urban PM Concentrations using the St. Louis Super Site Data.” Presented at the AAAR 26th Annual Conference, Grand Sierra Resort, Reno, NV. September.

Nopmongcol, U., C. Emery, G. Yarwood and R. Morris. 2007. “Guidance in the Use of Photochemical Grid Models for Determining Whether Sources Have a Significant Contribution to Visibility Impairment at Class I Areas.” Presented at A&WMA’s 100th Annual Conference, Pittsburg, PA. June.

Morris R. E., B. Wang, B. Koo, G. Tonnesen and C. Chien, T.W. Tesche, D. McNally, C. Loomis and G.

Stella. 2007. “Regional Modeling to Demonstrate Reasonable Progress toward Natural Visibility Conditions at Class I Areas throughout the United States.” Presented at A&WMA’s 100th Annual Conference, Pittsburg, PA. June.

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Morris, R.E., G. Yarwood, C. Emery, G. Wilson, B. Koo. 2006. “Regional Modeling Using OneAtmospheric Models to Address Regional Haze, 8-Hour Ozone and PM2.5 Air Quality Issues.” Presented at the 99th Annual AWMA Conference, New Orleans, LA. June.

Morris, R., C. Emery and G. Yarwood. 2006. “Use of an Advanced Hybrid Plume/Grid Photochemical Model to Perform Single Source Assessments for PSD and BART Analysis.” Presented at the AWMA Guidelines on Air Quality Models Conference, Denver, Colorado. April 26-28.

Morris, R., S. Lau, B. Koo, A. Hoats and G. Yarwood. 2006. “Further Evaluation of the Chemistry Algorithms Used in the CALPUFF Modeling System.” Presented at the AWMA Guidelines on Air Quality Models Conference, Denver, Colorado. April 26-28.

Morris, R., B. Koo, G. Mansell, G. Yarwood, G. Tonnesen, C.J. Chien, M. Omary. 2005. “Annual Application of Regional Particulate Matter Photochemical Grid Models to the Central US to Support the Requirements of the Regional Haze Rule.” Presented at the International Aerosol Conference (AAAR) 2005, Austin, Texas. October.

Morris, R., D. McNally, T. Tesche, G. Tonnesen, J. Boylan, P. Brewer. 2005. “Use of The CMAQ Modeling Systems For Estimating Visibility Progress in the Southeastern US For Complying with the Requirements of the Regional Haze Rule.” Presented at The 4th Annual CMAS Models-3 Conference, Chapel Hill, N.C. September.

Morris, R.E., S. Lau, B. Koo. 2005. “Evaluation of the CALPUFF Chemistry Algorithms.” Presented at the 98th Annual Air and Waste Management Conference, Minneapolis, MN. June.

Morris, R.E., G. Yarwood, C. Emery, G. Wilson and B. Koo. 2005. “Recent Advances in One-Atmospheric Modeling Using the Comprehensive Air-quality Model with Extensions”. Presented at the 98th Annual Air and Waste Management Conference, Minneapolis, MN. June.

Morris, R.E., B. Koo, G. Yarwood, C. Emery, G. Wilson. 2005. “Regional Modeling of Particulate Matter (PM), Ozone and Visibility Using the CMAQ and CAMx Photochemical Grid Models.” Presented at Atmospheric Sciences and Air Quality Conference (ASAQC), San Francisco, CA. April.

Morris, R.E., G. Wilson, G. Yarwood. 2005. “Use of a Full-Science 3-D Photochemical Grid Model to Address the BART Visibility Modeling Requirements.” Presented at the 8th Annual Electric Utilities Environmental Conference, Tucson, AZ. January.

Morris R.E., D. McNally, T. W. Tesche, G. Tonnesen, J. Boylan, P. Brewer. 2004. “Regional Haze Modeling Over the VISTAS States: Preliminary Verification of Models-3/CMAQ for the 2002 Annual Period.” Presented at A&WMA’s Regional and Global Perspectives on Haze: Causes, Consequences and Controversies – Visibility Specialty Conference. Asheville, North Carolina. October.

Morris, R.E., G. Tonnesen, T.W. Tesche, J. Boylan, P. Brewer. 2004. “VISTAS Phase I Regional Fine Particulate Sensitivity Modeling to Identify Optimal Model Configuration for Simulating Regional Haze in the Southeastern US.” Presented at A&WMA’s Regional and Global Perspectives on Haze:

Causes, Consequences and Controversies – Visibility Specialty Conference. Asheville, North Carolina.

October.

Morris, R E., B. Koo, G. Yarwood. 2004. “Particulate Matter Multi-Model Performance Evaluation.” Presented at CMAS Models-3 User’s Workshop October 18-20, 2004 Research Triangle Park, NC.

October.

Morris, R.E., G. Yarwood, G. Wilson. 2004. “Particulate Matter Source Apportionment Technology (PSAT) in the CAMx Photochemical Grid Model.” Presented at the ITM 27th NATO Conference, Banff Centre, Canada. October.

Morris, R., G. Yarwood, C. Emery and B. Koo. 2004. “Development and Application of the CAMx Regional One-Atmosphere Model to Treat Ozone, Particulate Matter, Visibility, Air Toxics and Mercury.” Presented at 97th Annual Conference and Exhibition of the Air and Waste Management Association, Indianapolis, IN. June.

Morris, R., G. Tonnesen, T.W. Tesche, James Boylan, Patricia Brewer. 2004. “Testing and Evaluation of Model Configurations for Regional Haze and PM Modeling of the Southeast U.S. Under VISTAS Phase I.” Presented at 97th Annual Conference and Exhibition of the Air and Waste Management Association, Indianapolis, IN. June.

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Morris R E., G. Yarwood, C. Emery, B. Koo. 2003. “Synergisms in the Development of the CMAQ and CAMx PM/Ozone Models.” Presented at CMAS Models-3 User’s Workshop October 18-20, 2004 Research Triangle Park, NC. October.

Morris, R.E., C. Tana, G. Yarwood. 2003. “Evaluation of the Sulfate and Nitrate Formation Mechanism in the CALPUFF Modeling System.” Presented at AWMA Specialty Conference Guideline on Air Quality Models: The Path Forward, Mystic, CT. October.

Morris, R.E., G. Yarwood, C.A. Emery, B. Koo, G. M. Wilson. 2003. “Development of the CAMx OneAtmosphere Air Quality Model to Treat Ozone, Particulate Matter, Visibility and Air Toxics and Application for State Implementation Plans (SIPs).” Presented at AWMA Specialty Conference Guideline on Air Quality Models: The Path Forward, Mystic, CT. October.

Morris R.E., S. Lau and G. Yarwood. 2003. “Development and Application of an Advanced Air Toxics Hybrid Photochemical Grid Modeling System.” Presented at 96th Annual Conference and Exhibition of the Air and Waste Management Association, San Diego, California. June.

Morris R.E., G. Yarwood, C. Emery, Spyros Pandis and F. Lurmann. 2003. “Implementation of State-ofScience PM Modules into the PMCAMx Photochemical Grid Model.” Presented at 96th Annual Conference and Exhibition of the Air and Waste Management Association, San Diego, California.

June.

Morris R.E., G. Tonnesen, M. Uhl, K. Briggs, J. Vimont and T. Moore. 2003. “The WRAP Regional Modeling Center – Application and Evaluation of Regional Visibility Models.” Presented at 96th Annual Conference and Exhibition of the Air and Waste Management Association, San Diego, California. June.

Morris R.E., C. Emery and E. Tai. 2003. “Sensitivity Analysis and Intercomparison of the Models-3/CMAQ and CAMx Models for the July 1995 NARSTO-Northeast Episode.” Presented at 96th Annual Conference and Exhibition of the Air and Waste Management Association, San Diego, CA. June.

Morris, R.E., G. Wilson, G. Yarwood, T. Darlington, J. Heiken, J. Heuss, G. Wolff, A. Dunker, S. Yamazaki and S. Chatani. 2002. “Evaluation of the Air Quality Impacts of Zero Emission Vehicles (ZEVs) and a No ZEV Alternative in the South Coast Air Basin of California.” Presented at 95th Annual Conference and Exhibition Air & Waste Management Association Baltimore, Maryland.

Morris, R.E., G. Yarwood, C.A. Emery, and G. Wilson. 2002. “Recent Advances in Photochemical Air Quality Modeling Using the CAMx Model: Current Update and Ozone Modeling of Point Source Impacts.” Presented at 95th Annual Conference and Exhibition Air & Waste Management Association Baltimore, Maryland.

Morris R.E., G. Yarwood, S. Lau and G. Wilson. 2002. “Development and Application of an Advanced Air Toxics Hybrid Photochemical Grid Modeling System.” Presented at CRC Air Toxics Modeling Workshop, Houston Texas. February.

Morris, R.E., G. Yarwood, C. Emery, and G. Wilson. 2001. “Recent Advances in CAMx Air Quality Modeling.” Presented at the AWMA Annual Meeting & Exhibition, Orlando, FL. June.

Morris, R.E., E. Tai, and G. Wilson. 2001. “Assessment of the Effects of the Tier 2/Low Sulfur and Other Mobile Source Emission Control Strategies on Ozone Nonattainment Using High-Resolution Photochemical Modeling.” Presented at the AWMA Annual Meeting & Exhibition, Orlando, FL. June.

Morris, R.E. and E. Tai, C. Hersey, C. Fitzner, M. Rodenberg and M. Lebeis, L. Pocalujka, and G. Wolff. 2001. “A Methodology for Quantifying Ozone Transport and Assessing the Benefits of Alternative Control Strategies.” Presented at the AWMA Annual Meeting & Exhibition, Orlando, FL. June.

Morris, R.E. and G. Yarwood. 2001. “Recent Advances in CAMx Air Quality Modeling.” Presented at the 2nd International Conference on Air Pollution Modeling and Simulation (APMS’20), Paris, France.

April.

Morris, R.E., C. Emery, and E. Tai. 2001. “Application of the CALPUFF Model to Address Visibility Issues in the Western US.” Presented at AWMA Guideline on Air Quality Models: A New Beginning, Newport, RI. April.

Morris, R.E., G. Yarwood, C. Emery, and G. Wilson. 2001. “Recent Development and Applications of the Comprehensive Air Quality Model with extensions (CAMx).” Presented at AWMA Guideline on Air Quality Models: A New Beginning, Newport, RI. April.

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Morris, R.E., C. Emery, N. Kumar, F. Lurmann, and H. Feldman. 1998. “Performance Evaluation of Two Particulate Matter Grid Models Using the 1995 Enhanced Measurement Database in the South Coast Air Basin.” Presented at the 91st Annual Meeting of the Air and Waste Management Association, San Diego, CA. June.

Morris, R.E., E. Tai, G. Wilson, and D. Weiss. 1998. “Use of Advanced Ozone Source Apportionment Techniques to Estimate Area of Influence (AOI) of Emissions Contributions to Elevated Ozone Concentrations.” Presented at the 91st Annual Meeting of the Air and Waste Management Association, San Diego, CA. June.

Morris, R.E., F. Lurmann, and H. Feldman. 1997. “Multi-Model Model Performance Evaluation of Particulate Matter Grid Models Using the 1995 Enhanced Measurement Database in the South Coast Air Basin.” Presented at the 9oth Annual Meeting of the Air and Waste Management Association, New Orleans, LA. June.

Morris, R.E., G. Yarwood, and M. Yocke. 1997. “Recent Advanced in Regional Photochemical Grid Modeling and Application Using the OTAG Modeling Databases.” Presented at the 90th Annual Meeting of the Air and Waste Management Association, New Orleans, LA. June.

Morris, R.E., M.A. Yocke, G. Yarwood, and C.A. Emery. 1996. “The Extended Urban/Regional Airshed Model (UAMX) - Initial Development and Testing of an Advanced, Publicly-Available, Nested-Grid Ozone Model that will Emulate UAM-V and Other Advanced Grid Models.” Presented at the 89th Annual Meeting of the Air and Waste Management Association, Nashville, Tennessee. June.

Morris, R.E., G. Yarwood, M.A. Yocke, H. Hogo and T. Chico. 1996. “Development of a Methodology for Source Apportionment of Ozone Concentration Estimates from a Photochemical Grid Model.” Presented at the 89th Annual Meeting of the Air and Waste Management Association, Nashville, Tennessee. June.

Morris, R.E. 1996. “The Ozone Nonattainment Problem in the Northeast US: A Review of Recent Measurement and Regional Modeling Studies, Common Findings and Implications.” Presented at the 89th Annual Meeting of the Air and Waste Management Association, Nashville, Tennessee. June.

Morris, R.E., C. A. Emery, and M.A. Yocke. 1996. “Application and Evaluation of the CALMET/CALPUFF Modeling System using the Mount Zirkel Visibility Study Enhanced Database.” Presented at the 89th Annual Meeting of the Air and Waste Management Association, Nashville, Tennessee. June.

Morris, R.E, G. E. Mansell, and R. Caiazza. 1995. “Preliminary Estimate of the Effects of Regional Emission Control Strategies on Ozone Concentrations in the Northeast US.” Presented at the 88th Annual AWMA Meeting & Exhibition, San Antonio, Texas.

Morris, R.E., P.D. Guthrie, and C.A. Knopes. 1995. “Photochemical Modeling Analysis Under Global Warming Conditions.” Presented at the 88th Annual AWMA Meeting & Exhibition, San Antonio, Texas.

Morris, R.E., C. O’Donnell, D.F. Shearer, and L. Kawaski. 1995. “Development of an Alternative Ozone Attainment Plan for the Los Angeles Region for Use in the 1994 State Implementation Plan.” Presented at the 88th Annual AWMA Meeting & Exhibition, San Antonio, Texas.

Morris, R. E., P.D. Guthrie, D. Axelrad, and R. Scheffe. 1995. “Development of a Grid-Based Model to Estimate Particulate Matter and Deposition of Toxic Compounds onto the Great Waters.” Presented at the 88th Annual AWMA Meeting & Exhibition, San Antonio, Texas.

Morris, R. E., T. C. Myers, and M. A. Yocke. 1994. “Evaluation of the Nested-Grid Urban Airshed Model (UAM-V) using the Extensive Lake Michigan Ozone Study (LMOS) Field Study Data Base.” Presented at 87th Annual AWMA Meeting and Exhibition, Cincinnati, OH. June.

Morris, R. E. and G. E. Mansell. 1994. “Application and Evaluation of the Nested-Grid Urban Airshed Model to the Northeast US.” Presented at the AWMA Specialty Conference “Tropospheric Ozone:

Critical Issues in the Regulatory Process” Orlando, FL. May.

Morris, R. E., A. K. Pollack, J. Heuss, J. Shiller, and H. Wimette. 1994. “Evaluation of the Air Quality Impacts of the Low Emissions Vehicle/Clean Fuels (LEV/CF) Program in the Baltimore-Washington D.C. Nonattainment Region.” Presented at the AWMA Specialty Conference "Tropospheric Ozone:

Critical Issues in the Regulatory Process" Orlando, FL.

Morris, R. E., T. C. Myers, M. A. Yocke, and T. W. Tesche. 1994. “Evaluation of the Nested-Grid Urban Airshed Model Using the Extensive Lake Michigan Ozone Study (LMOS) Field Study Data Base.”

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Presented at AWMA Specialty Conference Regional Photochemical Measurement and Modeling Studies, San Diego, CA. November.

Morris, R. E., M. A. Yocke, and T. C. Myers. 1993. “Application and Evaluation of the Nested-Grid Urban Airshed Model (UAM-V) in the Lake Michigan Ozone Study (LMOS).” Presented at Regional Photochemical Measurements and Modeling Studies, San Diego, CA. November.

Morris, R. E. and G. E. Mansell. 1993. “Procedures for Developing Boundary Conditions and Sensitivity of Simulating Ozone Formation in the Lake Michigan to the Definition of Boundary Conditions.” Presented at Regional Photochemical Measurements and Modeling Studies, San Diego, CA.

November.

Morris, R. E., T. C. Myers, and M. A. Yocke. 1993. “Design of the UAM-V Integrated Photochemical Modeling System -- Discussion of Model Components and Adaptation of the System to the Lake Michigan, Gulf Coast, and Northeast US Regions.” Presented at Regional Photochemical Measurements and Modeling Studies, San Diego, CA. November.

Morris, R. E., C. A. Emery, and J. E. Langstaff. 1993. “Ozone Modeling Study to Assess the Contribution of Power Plant Emissions to Ozone in the Philadelphia Nonattainment Region. ”Presented at 86th Annual AWMA Meeting and Exhibition, Denver, CO. June.

Morris, R. E. and C. A. Emery. 1992. “Sensitivity of the Urban Airshed Model to Meteorological Inputs When Applied to the New York Metropolitan Region Using the ROM-UAM Interface.” Presented at the AWMA specialty conference Tropospheric Ozone: Nonattainment and Design Value Issues, Boston, MA. November.

Morris, R. E., T. C. Myers, and M. A. Yocke. 1992. “Overview of the Variable Grid Urban Airshed Model (UAM-V).” Presented at the 85th Annual AWMA Meeting and Exhibition, Kansas City MO. June.

Morris, R. E., A. M. Dunker, C. H. Schleyer, and A. K. Pollack. 1992. “Methodology for Trajectory and Grid Modeling to Determine the Impact of Different Vehicle/Fuel Systems on Air Quality--Auto/Oil Air Quality Improvement Research Program.” Presented at the 85th Annual AWMA Meeting and Exhibition, Kansas City, MO. June.

Morris, R. E., M. A. Yocke, T. C. Myers, and R. C. Kessler. 1991. “Development and Testing of a NestedGrid Version of the Urban Airshed Model.” Presented at the Air and Waste Management Association Specialty Conference: Tropospheric Ozone and the Environment II, Atlanta, GA. November.

Morris, R. E. 1991. “Evaluation of the Sensitivity of Emissions Controls to Grid Resolution Using the Urban Airshed Model.” Presented at the Air and Waste Management Association Specialty Conference: Tropospheric Ozone and the Environment II, Atlanta, GA. November.

Morris, R. E., G. Z. Whitten, and S. M. Greenfield. 1991. “Preliminary Assessment of the Effects of Global Climate Change on Tropospheric Ozone Concentrations.” Presented at the Air and Waste Management Association Specialty Conference: Tropospheric Ozone and the Environment II, Atlanta, GA. November.

Morris, R. E., T. C. Myers, S. G. Douglas, M. A. Yocke, and V. Mirabella. 1991. “Development of a Nested-Grid Urban Airshed Model and Application to Southern California.” Presented at the 84th Annual AWMA Meeting and Exhibition, Vancouver BC. June.

Morris, R. E. and R. C. Kessler. 1991. “Mesoscale Simulation of Photochemical Air Quality in the San Joaquin Valley of California.” Presented at the 84th Annual AWMA Meeting and Exhibition, Vancouver BC. June.

Morris, R. E. and A. K. Pollack. 1991. “Methodology for Evaluation of the Air Quality Impacts of Auto/Oil Reformulated and Alternative Fuels Using the Urban Airshed Model.” Presented at the AWMA Specialty Conference: Tropospheric Ozone and the Environment II, Atlanta, GA. November.

Morris, R. E., T. C. Myers, and M. A. Yocke. 1991. “Effects of Grid Resolution in the UAM on the Evaluation of Emission Control Strategies.” Presented at AWMA Specialty Conference: Tropospheric Ozone and the Environment II, Atlanta, GA. November.

Morris, R. E. and others. 1990. “Use of the Urban Airshed Model to Assess the Effects of Ethanol Blended Fuels on Ozone Concentration in New York and St. Louis.” Presented at the 83rd Annual AWMA Meeting and Exhibition, Anaheim, CA. June.

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TEACHING EXPERIENCE
1977-1979
Calculus, University of California at Davis

MEMBERSHIPS
Air and Waste Management Association (AWMA)
Air Quality Modeling Subcommittee (AQMS) of the Science Advisory Board (SAB) EPA Fine Particulate Modeling Guidance Workgroup
EPA UAM Guidance Workgroup
Modeling Peer-Review Group for the Los Angeles SIP Air Quality Modeling

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TEJAS SHAH
Managing Consultant
Tejas Shah has over 15 years’ experience with air pollution analyses.

His expertise includes emission modeling, air quality modeling, emission inventory development, spatial analysis with GIS, database tool development, control-measure evaluation and economic impact analysis. He provided GIS support to developing oil and gas emissions inventories for current and future years in the western US for the Western Regional Air Partnership (WRAP). He has recently managed a review of available emission inventories for Mexico that are used in photochemical modeling studies of North America in which we used satellite-derived data products for sulfur dioxide (SO2), nitrogen dioxide (NO2) and natural gas flaring to evaluate spatial characterization and magnitude of the emissions inventories. Tejas has managed photochemical modeling studies for the US and other world regions in which key model inputs, such as the emission inventories and landuse inputs, depend on GIS analyses of geospatial data. Additionally, he has extensive experience using the RPOs emissions inventory, the USEPA’s national emissions inventory (NEI) and the Environment Canada national inventory.

Tejas’ work at Ramboll includes Sparse Matrix Operator Kernel Emissions (SMOKE) processing of regional and project-level emission inventories for various oil and gas EIS projects in the Intermountain West; preparing gridding surrogates and speciation profiles for the SMOKE model input; augmenting SPECIATE— a repository of speciation profiles; spatial analyses and preparing landuse/landcover files for the Comprehensive Air Quality Model with extensions (CAMx) and MEGAN models using GIS; and
developing database tools.

EDUCATION
2000-2003
MS, Chemical Engineering
Lamar University, Beaumont, Texas, United States
1996-2000
BS, Chemical Engineering
Mumbai University, Mumbai, India

SELECTED RELEVANT EXPERIENCE
Ozone Air Quality Modeling of the Arabian Gulf
Managed emission inventory modeling for a confidential air quality study in the Middle East.

Ramboll developed a photochemical ozone modeling system based on the Comprehensive Air quality Model with extensions (CAMx).
Developed a comprehensive emission inventory of ozone precursors (NOx, VOC and CO) for the Kingdom of Bahrain. The inventory was compiled using publicly-available data to characterize

CONTACT INFORMATION
Tejas Shah
[email protected]
+1 (415) 8990735
Ramboll
7250 Redwood Boulevard
Suite 105
Novato, CA 94945
United States of America

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stationary sources, mobile sources and area sources and support photochemical ozone modeling.
Managing emission inventory modeling for a confidential study in the Middle East to assess the environmental impacts of changes to transportation infrastructure and emissions.

Air Quality and Emissions Modeling Support to EPA OAQPS Developed ancillary files for processing oil and gas emissions for use in the EPA’s national modeling platform. Work included development and assignment of speciation profiles for WRAP Phase III oil and gas source categories, development and assignment of spatial surrogates, and preparation of inventory input files for SMOKE.

BOEM Air Quality Impacts of Off-Shore Oil and Gas Production Currently managing regional emissions modeling for analyzing the on-shore air quality impacts of outer continental shelf oil and gas development in the Arctic Sea near Alaska and the Gulf of Mexico. This multi-year multi-million dollar study will project future year emissions and air quality impacts and develop emission exception screening thresholds.

Allegheny County PM2.5 State Implementation Plans
Task Manager for developing emissions input for air quality modeling to demonstrate that Allegheny County (Pittsburgh), Pennsylvania will attain the PM2.5 National Ambient Air Quality Standard (NAAQS).

Western Regional Air Partnership (WRAP) Region-Wide Emissions Inventory Provided GIS support in developing a region-wide O&G emissions inventory for current and future years in the western US for the Western Regional Air Partnership (WRAP). It includes performing spatial analyses using ARC/GIS tools, preparing map displays using ARC/MAP and developing gridding surrogates based on O&G activities using ARC Macro Language (AML) scripts.

Development of Gridded Ocean-Going Vessel Emissions Inventories Prepared gridded Commercial Marine Vessel Emissions Inventory for EPA. Detailed US port emission inventory was spatially allocated into a gridded format. The port emissions were then blended with the STEEM data, which together create the merged, gridded commercial marine vessel emissions inventory. ARC/GIS buffer tool was used to define various distance regions (25, 50, 100, and 200 nautical miles) from the US shore line.

Development of California Emission Estimator Model (CalEEMod) Assisted in the development of CalEEMod - a statewide land use emissions computer model designed to provide a uniform platform to quantify potential criteria pollutant and greenhouse gas (GHG) emissions associated with both construction and operational from a variety of land use projects.

Rosebud Mine, Montana EIS
Emissions modeling Task Manager to develop regional and project-specific emissions inputs for photochemical modeling study to assess direct effects due to the Rosebud mine and indirect effects due to the nearby power plant under NEPA.

BLM Oklahoma-Kansas-Texas (OKT) EIS and Resource Management Plan Managed emissions modeling task of the BLM Oklahoma-Kansas-Texas (OKT) modeling study to assess the air quality impacts of oil and gas development and coal mines on federal and nonfederal lands and other cumulative regional sources. Emissions of criteria air pollutants from predicted oil and gas development in the three-state area were developed for this study.

BLM Colorado Air Resource Management Modeling Study (CARMMS) Emissions Modeling Lead for the BLM CARMMS study that assess the air quality (AQ) and air quality related value (AQRV) impacts of new federal oil and gas and other cumulative sources including non-federal O&G, mining and other regional emissions in each of the BLM Colorado Field Office planning areas, as well as the Mancos Shale area in northwest New Mexico. Air quality modeling emissions inputs were developed for high, medium and low O&G development scenarios for future years 2021 and 2025.

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BLM Montana/Dakotas PGM Modeling Study
Task Manager for developing air quality modeling emissions for the BLM Montana/Dakotas PGM modeling study to assess the AQ and AQRV impacts due to oil and gas development. The Bakken Shale formation in the Montana/Dakotas region is the most rapidly growing oil and gas development area in the U.S. Under this study, Ramboll Environ is developing a comprehensive oil and gas emissions inventory and performing base year 2012/2013 and future year 2032 modeling using the CAMx photochemical grid model.

Navajo Generating Stations (NGS) EIS Assessment
Task Manager for developing criteria and HAP emission inventory for NGS for lease extension EIS. This was the most comprehensive and complete AQ, ecological and human health assessment ever performed for an EIS.

SMOKE-MOVES Processing for Denver Ozone Modeling
Developed an approach to use link-based data from TDM models as input to SMOKE-MOVES processing tool. Processed detailed vehicular activity data to prepare model-ready emissions for onroad sources. The pre-gridded activity data was input to the tool for the on-network processing and treated each grid cell and speed class as a pseudo-county. The off-network emissions were spatially allocated using surrogates developed from trip starts (start exhaust) and trip ends (for evaporative processes) by Traffic Analysis Zone (TAZ). This approach takes advantage of detailed link-based spatial and temporal varying activity data available from the TDM model and the robust emissions calculation methodology of SMOKE-MOVES that takes into account temporal and spatial variations in meteorology and has EPA approval and support.

Air Quality Assessments in Alberta, Canada
Performed emissions modeling of regional emission inventories for North East Alberta modeling studies and North Saskatchewan Region of Alberta.

PRESENTATIONS & PUBLICATIONS
Shah, T. 2017. “Composition of Organic Gas Emissions from Flaring Natural Gas” Presented at the EPA’s 2017 International Emissions Inventory Conference. August https://www.epa.gov/sites/production/files/2017-11/documents/organic_gas.pdf Shah, T., Y. Alvarez, M. Jimenez, R. Morris, A. Brimmer and K. Lloyd. 2016. “Incorporate Traffic Demand Model Data in SMOKE-MOVES Processing for Denver Ozone Modeling” Presented at the 2016 CMAS Conference. October
Nopmongcol, U., J. Grant, E. Knipping, M. Alexander, R. Schurhoff, D. Young, J. Jung, T. Shah, G.

Yarwood. 2017. “Air Quality Impacts of Electrifying Vehicles and Equipment across the United States.” Environmental Science & Technology. http://dx.doi.org/10.1021/acs.est.6b04868 Karamchandani, P., R. Morris, A. Wentland, T. Shah, and J. Lester. 2017. “Dynamic evaluation of photochemical grid model response to emission changes in the South Coast Air Basin in California.” Atmosphere, in review.

Collet, S., T. Kidokoro, P. Karamchandani, T. Shah, and J. Jung. 2017. “Future year ozone prediction for the United States using updated models and inputs.” J. Air Waste Manage. Assoc., in review.

Vijayaraghavan, K., C. Lindhjem, B. Koo, A. DenBleyker, E. Tai, T. Shah, Y. Alvarez, G. Yarwood. 2016. “Source Apportionment of Emissions from Light-Duty Gasoline Vehicles and Other Sources in the United States for Ozone and Particulate Matter.” Journal of the Air & Waste Management Association, 66, 2, 98-119. doi: 10.1080/10962247.2015.1112316.

Cho, S., R. Morris, P. McEachern, T. Shah, J. Johnson and U. Nopmongcol. 2012. “Emission sources Sensitivity Study for Ground-Level Ozone and PM2.5 Due to Oil Sands Development Using Air Quality Modeling System: Part I – Model Evaluation for Current Year Base Case Simulation.” Atmos.

Env., Volume 55, pp 533-541.

Cho, S., R. Morris, P. McEachern, T. Shah, J. Johnson and U. Nopmongcol. 2012. “Emission Sources Sensitivity Study for Ground-Level Ozone and PM2.5 Due to Oil Sands Development Using Air Quality Modeling System: Part II – Source Apportionment Modeling.” Atmos. Env., Volume 55, pp 542-556.

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MARCO A. RODRIGUEZ, PHD
Senior Consultant
Dr. Marco Antonio Rodriguez is a Senior Consultant and recognized expert with 18 years of experience using analytical techniques to solve complex air quality problems. Marco has worked on issues including oil and gas development and Better-than-BART assessments and has provided modeling advice to legal firms in cases involving litigation. He is intimately familiar with CAMx and CMAQ, and has evaluated modeling datasets using R, FORTRAN and Python. He is passionate about applying data science techniques to environmental and air quality issues.

CAREER
2018
Senior Consultant
Ramboll (formerly Ramboll Environ)
2012-2018
Air Quality Scientist, Project Manager
AECOM, Fort Collings, Colorado
managed photochemical grid modeling projects, including evaluation, application and data analysis
provided air quality support for impact assessments
involving the National Environmental Policy Act (NEPA), oil and gas projects, winter ozone modeling, and regional haze assessment of coal-fired power plants.
2005–2012
Research Scientist, Air Quality Modeler
Cooperative Institute for Research in the Atmosphere, Fort Collins, Colorado
provided data preparation, model setup and analysis of CAMx modeling for various environmental assessment
projects funded by the national park service (NPS).
performed nitrogen deposition modeling for NPS.
evaluated air quality impacts from oil and gas on class i areas.
acted as linux system administrator
2004–2005
Postgraduate Researcher
Advanced Power and Energy Program, University of California, Irvine

CONTACT INFORMATION
MARCO A. RODRIGUEZ
[email protected]
+1 (970) 2374332
Ramboll
7250 Redwood Boulevard
Suite 105
Novato, 94945
United States of America

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acted as principal air quality modeler of a project funded by the California Air Resources Board to analyze the air quality impacts in the South Coast Air Basin of California (SoCAB) caused by the implementation of distributed power generation.

EDUCATION
2004
Ph.D., Mechanical and Aerospace Engineering
University of California, Irvine, United States
2001
MS, Mechanical and Aerospace Engineering
University of California, Irvine, United States
1997
BA, Physics
Universidad Autónoma Metropolitana Iztapalapa, México

EXPERIENCE (PRIOR TO RAMBOLL)
Wyoming Department of Environmental Quality, Wyoming Photochemical Grid.

Assistant project manager and air quality modeler lead for a project studying winter ozone formation in the Upper Green River Basin (UGRB). Elevated levels of ozone have been measured during winter in the UGRB since 2005. Ongoing studies have led scientists to believe that oil and gas development activities combined with specific meteorological conditions are contributing to elevated levels of ozone in winter. The study evaluated the results of two photochemical grid models to determine if the models can reproduce ozone events with sufficient accuracy to be used as a tool for regulatory planning purposes. Drafted all analysis documents and reports. Arizona Public Service Company, Four Corners Power Plant NEPA Services. Assistant task manager of the ozone modeling effort for a project to retrofit the power plant with emissions controls. Responsibilities included study design and planning efforts, coordinating with the proponent and interagency review team, senior oversight of emissions inventory development, task management, oversight of photochemical modeling, and authoring sections of the air quality technical support document.
US Bureau of Land Management - Utah State Office, Air Resource Management Strategy Modeling. Senior photochemical modeler and data analyst for a regional cumulative air impact assessment. The study was conducted to provide a reusable modeling platform for BLM air management decisions and future NEPA analyses in the Uinta Basin. An evaluation of two photochemical grid models was conducted and the better performing model (CMAQ) was selected for analysis of future year air quality conditions, including winter ozone. Environmental Impact Statement, Casper, Wyoming. Senior photochemical grid modeler for a programmatic oil and gas development EIS project for an area that covers approximately

1.5 million acres. The proposed development would involve drilling 5,000 new wells on 1,500 new well pads producing from multiple horizons, plus an additional 450 pads for supporting ancillary facilities. The EIS is being developed under the direction of the BLM Casper Field Office as the lead agency. Major issues include air quality (potential ozone impacts); flaring and associated noise; water supply/disposal and water quality; wildlife (impacts to sage grouse); range (impacts to grazing allotments); and transportation impacts associated with increased truck traffic. In addition to numerous cooperating agencies, a key co-operator is the US Forest Service, the federal agency responsible for management of the Thunder Basin National Grasslands that comprise approximately 4% of the surface ownership in the project area Cooperative Institute for Research in the Atmosphere, Rocky Mountain Sulfur and Nitrogen Study, Colorado. Lead photochemical air quality modeler for the RoMANS project.

Responsible for preparation of input datasets required for running CAMx and model performance evaluation with available observations. Excess wet and dry deposition of nitrogen-containing compounds is a concern at a number of national parks. Rocky Mountain National Park provides a

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well-documented example of the role of excess nitrogen deposition in sensitive alpine environments. The RoMANS was conducted during the spring and summer of 2006 to identify the overall mix of ambient and deposited sulfur and nitrogen in the park. The Comprehensive Air Quality Model with extensions (CAMx) was used to simulate the fate of gaseous and particulate species subjected to multiple chemical and physical processes during RoMANS. The work presents an operational evaluation with special emphasis on the model performance of reduced nitrogen species. Results showed that there were large negative biases and errors at RMNP and the entire domain for ammonia; therefore, the model was deemed inadequate for source apportionment applications. The CAMx Integrated Processes Rate (IPR) analysis tool was used here to investigate the reasons behind poor model performance. In particular, IPR served as a tool to diagnose the relative contributions of individual physical and chemical processes to the final concentrations of reduced nitrogen species. Finally, guided by the information provided by the process analysis results, a series of sensitivity simulations were performed to investigate the effects of different deposition velocities in the modeled concentrations. Cooperative Institute for Research in the Atmosphere, Oil and Gas Development on Ozone Formation Regional Impacts. Lead photochemical air quality modeler and performed evaluation of regional impacts of oil and gas development using the Phase I WRAP emissions inventory. The Intermountain West is currently experiencing increased growth in oil and gas production, which has the potential to affect the visibility and air quality of various Class I areas in the region. The project presented an analysis of these impacts using the Comprehensive Air Quality Model with extensions (CAMx). Meteorology and emissions inventories developed by the Western Regional Air Partnership Regional Modeling Center for regional haze analysis and planning were used to establish an ozone baseline simulation for the year 2002. The predicted range of values for ozone in the national parks and other Class I areas in the western US was then evaluated with available observations from the Clean Air Status and Trends Network (CASTNET). The evaluation demonstrated the model’s suitability for subsequent planning, sensitivity, and emissions control strategy modeling. An analysis of the model results was performed to investigate the regional impacts of oil and gas development on the ozone concentrations that affect the air quality of Class I areas. California Energy Commission, Distributed Generation Air Quality Impacts. Lead air quality modeler of a project funded by the California Air Resources Board to understand and analyze the air quality impacts in the South Coast Air Basin of California (SoCAB) caused by the implementation of distributed power generation (DG). Developed a methodology to investigate the spatial effects of placing DG in specific locations within the SoCAB. Distributed energy resources (DER) have the potential to supply a significant portion of increased power demands in California and the rest of the United States. DG is characterized by a dispersion of many stationary power generators throughout an urban air basin. As a result, DG may lead to increased pollutant emissions within an urban air basin, which could adversely affect air quality.

The project developed a systematic approach based on land-use GIS data for characterizing the installation of DER in an urban air basin and simulated the potential air quality impacts using a state-of-the-art 3D computer model. Model sensitivity and model uncertainty analyses were developed in the project. The assessment of the air quality impacts associated with DER was made in the South Coast Air Basin (SoCAB) for the year 2010. Results suggest that DER characterization could be systematically applied to urban air basins, and that realistic DER implementation in SoCAB by the year 2010 only slightly affected concentrations of ozone and particulate matter in the basin. However, DG may increase localized exposure to pollutants, and higher levels of DG penetration in years beyond 2010 may lead to more significant air quality impacts than those presented in this study.

PUBLICATIONS
Paine, R. J., Taylor, C. and Rodriguez, M.A. Ozone and PM2.5: Ongoing Challenges for New Source Permitting. Natural Gas & Electricity, 34: 9–14. doi:10.1002/gas.22015, 2017.

Paine, R., Rodriguez, M. A. and Taylor, C. New Source Review Permitting Challenged by Ozone Modeling Requirements. Natural Gas & Electricity, 33: 10–15. doi:10.1002/gas.21935, 2016.

Malm, W.C., Rodriguez, M. A., Bret A. Schichtel, Kristi A. Gebhart, Tammy M. Thompson, Michael G.

Barna, Katherine B. Benedict, Christian M. Carrico, Jeffrey L. Collett, A hybrid modeling approach for

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estimating reactive nitrogen deposition in Rocky Mountain National Park, In Atmospheric Environment, Volume 126, Pages 258-273, ISSN 1352-2310, 2016.

Thompson, T. M., Rodriguez, M.A., M. G. Barna, K. A. Gebhart, J. L. Hand, D. E. Day, W. C. Malm, K. B.

Benedict, J. L. Collett Jr., and B. A. Schichtel. Rocky Mountain National Park reduced nitrogen source apportionment, J. Geophys. Res. Atmos., 120, 4370–4384. doi:10.1002/2014JD022675, 2015
Gebhart, K.A., Malm, W. C., Rodriguez, M.A. et al., Meteorological and Back Trajectory Modeling for the Rocky Mountain Atmospheric Nitrogen and Sulfur Study II, Advances in Meteorology, vol. 2014, Article ID 414015, 19 pages, doi:10.1155/ 2014/414015, 2014.

Malm, W. C., Schichtel, B.A., Barna, M.G., Gebhart, K.A., Rodriguez, M.A., Collett Jr., J.L., Carrico, C.M., Benedict, K.B. Prenni, A.J., Kreidenweis, S.M. Aerosol species concentrations and source apportionment of ammonia at Rocky Mountain National Park. Journal of the Air & Waste Management Association Vol. 63, Iss. 11, 2013.

Schichtel, B.A., Rodriguez, M.A., Barna, M. G., Gebhart, K. A., M.L. Pitchford, M. L., Malm, W.C. A semi-empirical, receptor-oriented Lagrangian model for simulating fine particulate carbon at rural sites. Atmospheric Environment, Volume 61, 2012, Pages 361-370, 2012.

Rodriguez, M. A., Barna, M. G., Gebhart, K. A., Hand, J. L., Adelman, Z., Schichtel, B. A., Collett Jr., J.

L., and Malm, W. C. Modeling the fate of atmospheric reduced nitrogen during the Rocky Mountain Atmospheric Nitrogen and Sulfur Study (RoMANS): Performance evaluation and diagnosis using integrated processes analysis. Atmospheric Environment, 45, 223–234, doi:10.1016/j.atmosenv.2010.09.011, 2011.

Gebhart, K. A., Schichtel, B. A., Malm, W. C., Barna, M. G., Rodriguez, M. A., and Collett Jr., J. L. BackTrajectory-Based Source Apportionment of Airborne Sulfur and Nitrogen Concentrations at Rocky Mountain National Park, Colorado, USA, Atmospheric Environment 45, 621–633, doi:10.1016/j.atmosenv.2010.10.035, 2011.

Rodriguez, M. A., Barna, M. G., and Moore, T. Regional Impacts of Oil and Gas Development on Ozone Formation in the Western United States, Journal of the Air&Waste Management Association 59, 1111-1118, doi:10.3155/1047-3289.59.9.1111, 2009.

Rodriguez, M. A., Brouwer, J., Samuelsen, G. S., and Dabdub, D. Air Quality Impacts of Distributed Power Generation in the South Coast Air Basin of California 2: Model Uncertainty and sensitivity analysis, Atmospheric Environment 41, 5618–5635, 2007.

Rodriguez, M. A., Carreras-Sospedra, M., Medrano, M., Brouwer, J., Samuelsen, G. S., and Dabdub, D.

Air Quality Impacts of Distributed Power Generation in the South Coast Air Basin of California 1:

Scenario Development and Modeling Analysis, Atmospheric Environment 40, 5508–5521, 2006.

Rodriguez, M. A., and Dabdub, D. Monte Carlo uncertainty and sensitivity analysis of the CACM chemical mechanism, Journal of Geophysical Research Atmospheres 108, (D15), 4443, doi:10.1029/2002JD003281, 2003.

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CHAO-JUNG CHIEN, PHD
Senior Consultant
Dr. Chien is an Atmospheric Scientist with over 18 years of experience in the air quality field. Dr. Chien is an expert in atmospheric chemistry and has comprehensive knowledge of primary and secondary air pollutants formation and their chemistry and transport in complex 3-dimensional urban and regional air quality models. He has performed photochemical grid models (PGMs) such as CMAQ and CAMx, and has
extensive experience in processing/evaluating/validating input and output data for all components of air quality modeling studies, including meteorology, e.g. WRF, emissions, e.g.

SMOKE, MOVES, MEGANS, etc., and pre-processors of each
respective model. He has developed and implemented a model performance software package tool to create comprehensive statistical and graphical results to evaluate model performance.

CAREER
2018
Senior Consultant
Ramboll (formerly Ramboll Environ)
2009-2018
Senior Air Quality Scientist
AECOM, Fort Collings, Colorado
Technical lead on all aspects of emissions processing,
photochemical grid modeling (CAMx and CMAQ) and
dispersion modeling (AERMOD and CALPUFF) practices, and air quality data analysis:
Actively participated in developing regional cumulative air quality impact assessment for various Environmental Impact Studies (EIS) related to Oil and Gas
development projects located in states of Wyoming and
Montana, under supervision of various state (Wyoming)
and federal governments (BLM, EPA region 8).

Challenges among these projects include studying
elevated winter ozone formation due to oil and gas development activities combined with specific meteorological conditions, and areas with pending designation as an ozone nonattainment area. Responsibilities included developing spatially-allocated air resource emissions inventories (EIs), conducting PGMs with CMAQ and CAMx, performing model performance evaluation, and authoring sections of various Air Quality Technical Support Documents. Maintained and administrated Linux-based HPC clusters to provide computing services for various air quality modeling applications throughout the company.

CONTACT INFORMATION
Chao-Jung (Jung) Chien, PhD
[email protected]
+1 (415) 899-0720
Ramboll
7250 Redwood Boulevard
Suite 105
Novato, 94945
United States of America

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2001–2009
Senior Development Engineer, Research Associate
Center of Environmental Research and Technology (CERT), College of Engineering, University of California, Riverside, California
As a core member of Western Regional Air Partnership (WRAP) sponsored Regional Modeling Center (RMC):
Configured and performed air quality model simulations including all components of CMAQ, CAMx, SMOKE, in assisting and supporting various Regional Planning Organization (RPOs), including WRAP, CENRAP, VISTAS (now SESARM), and MRPO/LADCO, for their development of SIPS and the regional component of fine particulate and 8-hour ozone SIPs. Developed and evaluated observation-based methods for assessing ozone sensitivity to precursor reductions (Smog Chamber Studies).
Designed and developed model performance evaluation software (UCR_MPE Tool) for data analysis and evaluation of modeling results.

EDUCATION
2001
Ph.D., Atmospheric Chemistry and Organic Analytical Chemistry University of North Carolina, Chapel Hill, United States 1989
BA, Chemistry
National Cheng Kung University, Taiwan

RELEVANT PROJECT EXPERIENCE
Wyoming Department of Environmental Quality (WDEQ), Wyoming Photochemical Grid. Team lead on performing CMAQ air quality modeling and model shootouts between CMAQ and CAMx for a project studying winter ozone formation in the Upper Green River Basin (UGRB).

Elevated levels of ozone have been measured during winter in the UGRB since 2005. Ongoing studies have led scientists to believe that oil and gas development activities combined with specific meteorological conditions are contributing to elevated levels of ozone in winter. The study evaluated the results of two photochemical grid models, CMAQ and CAMx, to determine if the models can reproduce ozone events with sufficient accuracy to be used as a tool for regulatory planning purposes. Assisted and as a reviewer in all analysis documents and reports. US Bureau of Land Management - Utah State Office, Air Resource Management Strategy Modeling. Team lead on a project for developing a regional cumulative air impact assessment for Utah BLM. Responsibilities included preparing and providing a spatially-allocated Air Resource Emission Inventory (EI) and providing air quality modeling platform using either CMAQ or CAMx to meet the needs of the Utah State Office of BLM for future NEPA and resource management plans (RMP) actions.
California Air Resources Board (CARB). Advanced Data Analysis for the Central California Ozone Study (CCOS). Assisted in developing methods to characterize emissions, meteorology and atmospheric processes affecting the production of ozone in central CA.

Performed model predictions for indicator species to observations to validate model processes.

Model Inter-comparison was also conducted for SAQM, CMAQ and CAMx with CB4 and SAPRC99. Arizona Public Service Company (APS Co.), Four Corners Power Plant NEPA Services.

Team lead on emissions processing for an ozone modeling project conducted to assess the impacts associated with retrofitting the Four Corners Power Plant with emissions controls.

Responsible for the emission inventory processing in SMOKE for the photochemical modeling, and authoring sections of the Air Quality Technical Support Document. Bureau of Land Management (EOG Resources), LaBarge Platform Exploration and Development Project EIS, Wyoming. Team lead on emissions developing and photochemical

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chemical grid modeling for a medium in-fill oil and gas development project in Southwestern Wyoming. This project is anticipated to be particularly challenging due to the area’s pending designation as an ozone non-attainment area. Current responsibilities include developing emissions inventory with SMOKE, conducting photochemical grid model with CAMx, analyzing model performance and authoring sections of the Air Quality Technical Support Document Coordinating research Council (CRC). Accuracy of Regional Simulations of Background Ozone and Particulate Matter. Co-lead in Investigating natural contribution to atmospheric ozone and PM formation. Improved and refined emissions from various natural sources of ozone precursors (such as biogenic, lightning NOx) and PMs, including both direct emissions of primary PM (such as sea salt and volcanautic activities) and emissions of gaseous species that undergo photochemical transformation or condensation to form secondary PM. Conducted annual CMAQ modeling to investigate the effects that natural sources and background concentrations have on the development of ozone and PM attainment emission control strategies.
Regional Modeling Center (RMC), WRAP. Assisted in regional particulate matter, ozone and haze modeling using CMAQ and CAMx for the western (WRAP), central (CENRAP), southeast (VISTAS), and Midwest (MRPO) Regional Planning Organization (RPOs) for the development of Regional Haze State Implementation Plans (SIPs) and the regional component of fine particulate and 8-hour ozone SIPs. Designed and developed model performance evaluation software (UCR_MPE Tool) for data analysis and evaluation of modeling results. Activities include obtaining ambient measurement data from various national ambient monitoring networks, assess the quality and usefulness of these data, and develop procedures of applying these data to validate air quality models.
UC-Riverside. Evaluation of Observation Based Methods (OBM) for Assessing the Sensitivity of Ozone to VOC and NOx. Performed analysis on experimental results from state-of-art smog chamber experiments to determine whether observation based methods (OBMs) can be used reliably to distinguish conditions in which either VOC or NOx controls are more effective for reducing ambient ozone concentrations. More than 40 chamber experiments were carried out and 90 sets of data were accumulated. Key indicator species including H2O2, HNO3, HCHO, NO2, OH and HO2 were also analyzed and compared with computer model simulations using SAPRC-99 photochemical mechanism.

SELECTED PUBLICATIONS
Koo, B., Chien, C.-J., Tonnesen G.S., Yarwood, G., Johnson, J., Sakulyanonitvittaya, T., Piyachaturawat, P., and Morris, R., Natural Emissions for Regional Modeling of Background Ozone and Particulate Matter and Impacts on Emissions Control Strategies., Atmospheric Environment, 44, p2372-2382, 2010.

Wang, Z. S., Chien, C.-J., Tonnesen, G.S., Development of a tagged species source apportionment algorithm to characterize three-dimensional transport and transformation of precursors and secondary pollutants. J. Geophys. Res, 114, D21206, 2009.

Tonnesen, G.S., Wang, Z.S., Omary, M., Chien, C.-J., Formulation and application of regional air quality modeling for integrated assessments of urban and wildland pollution, in Developments in Environmental Science, vol 2, (eds. Bytnerowicz, A., Arbaugh, M., Alonso, R.), pp 1-26. 2008.

Chien, C.-J, Tonnesen, G.S., Wang, Z.S., Omary, M. Bytnerowicz, A., Atmospheric Modeling of Nitrogen Species in San Bernardino Mountain, CA Areas. Presented in 22nd International Meeting for Specialists in Air Pollution Effects on Forest Ecosystems (IUFRO conference), September 10-15, 2006, Riverside, California, USA
Chien, C.-J, Tonnesen, G.S., Wang, Y., Wang, Z.S., Omary, M., Model Performance Evaluations for Fine Particulates Using Unpaired in Space and Time Analysis. Presented in 4th Annual CMAS Models-3 Users’ Conference, September 26-28, 2005, Chapel Hill, North Carolina, USA.

Chien, C.-J ; Tonnesen, G.S.; Wang, B. CMAQ Model Performance Evaluation with the Updated CB4- 2002. Presented in 2nd Annual US-EPA’s Models-3 Users’ Workshop, October 27-29, 2003, Research Triangle Park, North Carolina, USA.

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SONJA SAX
Managing Consultant
Dr. Sonja Sax is an environmental health scientist with over 20 years of exposure and health risk assessment experience. Dr. Sax has particular expertise in assessing exposures and risks from airborne gases and particles, and has performed indoor and outdoor air quality investigations, managed several large environmental projects, conducted critical evaluations of toxicology and epidemiology studies, and helped prepare technical and expert reports. Dr. Sax has authored and co-authored several publications, presented her research and consulting work at various conferences and testified before scientific panels. Dr. Sax earned an MS and doctorate in environmental health from the Harvard T.H. Chan School of Public Health, where she also served as a postdoctoral fellow.

CAREER
2016->>>
Managing Consultant, Ramboll
Senior manager in charge of multiple exposure and health effects projects. Specific tasks include litigation support for toxic torts, conduct systematic reviews of the health effects literature for a number of chemicals, including bitumen fumes, welding fumes, diesel particulate, and carbon black, and critically review epidemiological and toxicological literature.
2005-2015
Senior Project Manager, Gradient
Managed and worked on multiple projects related to evaluation of human exposures and health risks associated with environmental pollutants; routinely conducted air dispersion modeling and exposure assessments to support health risk assessments; reviewed and interpreted epidemiology and toxicology studies for use in preparing expert reports, peer-reviewed publications, regulatory comments, and risk communications.
2003-2005
Postdoctoral Fellow, Harvard School of Public Health
Managed two large exposure assessment projects, developed study protocols, organized field studies, and managed staff. Additional duties included writing grants, analyzing data, and publishing manuscripts in peer-reviewed journals.

CONTACT INFORMATION
Sonja Sax
[email protected]
+1 (413) 8354358
Ramboll
28 Amity Street
Suite 2A
Amherst, MA 01002
United States of America

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1998-2003
Research/Teaching Assistant, Harvard School of Public Health Designed, conducted, and managed a large air pollution exposure assessment study of inner-city teenagers in New York City and Los Angeles; measured and analyzed indoor, outdoor, and personal concentrations of volatile organic compounds (VOCs), carbonyls, PM2.5, and particle-associated metals.

Teaching assistant for an introductory environmental health course. 1995
Intern, Environmental Protection Agency
Analyzed health effects data to assess the impact of ozone concentrations on hospital admissions in Massachusetts.
1994-1997
Research Assistant, Harvard School of Public Health
Proposed, designed, and implemented an indoor air quality study of a green community of homes. 1991-1994
Research Associate, Repligen Corporation
Managed the peptide chemistry lab. Conducted research to improve the synthesis of peptides. Trained and supervised laboratory staff.

EDUCATION
2003
ScD, Environmental Health Sciences
Harvard T.H. Chan School of Public Health
1996
MS, Environmental Health Management
Harvard T.H. Chan School of Public Health
1991
BA, Biological Chemistry
Wellesley College

COURSES/CERTIFICATIONS
Winner of the HERA Human Risk Assessment Paper of the Year Award, 2008 Probabilistic Analysis of Human Health Risks Associated with Background Concentrations of Inorganic Arsenic: Use of a Margin of Exposure Approach. Human and Ecological Risk Assessment 14:1159-1201.

LANGUAGE SKILLS
Spanish (mother tongue), English (mother tongue)

PROJECTS
Cost-benefit Analyses
Conducted cost-benefit analyses of air pollution reductions in the US and Middle East using the US Environmental Protection Agency Benefits Mapping and Analysis (BenMAP) Program.

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Litigation Support
Contributed to the preparation of expert reports in litigation projects that involved a variety of different chemical exposures including volatile organic compounds (e.g., vinyl chloride and formaldehyde), asbestos, carbon black, particulate matter, sulfur dioxide, pesticides, and odors.

Critical Reviews and Syntheses
Conducted an extensive literature search on the toxicity and health effects of several different chemical compounds including cobalt and cobalt alloys found in dental materials, diesel exhaust, carbon black, welding fumes, sulfur dioxide, and odors.

Systematic Reviews
Conducted weight-of-evidence evaluation of cardiovascular and respiratory effects from exposures to ozone, diesel particles, and carbon black. Results of the critical evaluation of toxicology, epidemiology, and mode-of-action studies were published in several peer-reviewed manuscripts.

Exposure and Risk Assessment
For numerous projects prepared technical analyses on exposures and potential health effects associated with various pollutants including volatile organic compounds, asbestos, carbon black, particulate matter, sulfur dioxide, pesticides, and odor. Exposure assessments included air dispersion modeling or indoor air modeling.

Regulatory Support
Provided written and oral testimony on several occasions to the Clean Air Scientific Advisory Committee (CASAC) on human exposure, epidemiology, toxicology, and mechanistic studies and their bearing on US EPA's National Ambient Air Quality Standards (NAAQS) for particulate matter and ozone.

Indoor Exposure and Risk Assessment
Conducted exposure and risk assessments of residential exposures to various chemicals including formaldehyde from wood products, emissions of carbon black from industrial sources, vapor intrusion of tetrachloroethylene, exposures to mercury from wallboard and concrete, exposures to flame retardants from various indoor sources, and odor issues from a composting facility.

PUBLICATIONS
2018
Cancer Risk Associated with Exposure to Bitumen and Bitumen Fumes: An Updated Systematic Review and Meta-Analysis.

Journal of Occupational and Environmental Medicine; 2018 Jan;60(1):e6-e54.

Authors: Mundt KA, Dell LD, Crawford L, Sax SN, Boffetta P 2018
Short-term ozone exposure and asthma severity: Weight-of-evidence analysis.

Environmental Research 2018 Jan;160:391-397.

Authors: Goodman JE, Zu K, Loftus CT, Lynch HN, Prueitt RL, Mohar I, Shubin SP, Sax SN. 2017
Particle size distributions of lead measured in battery manufacturing and secondary smelter facilities and implications in setting workplace lead exposure limits.

Journal of Occupational and Environmental Hygiene 2017 Aug;14(8):594-608.

Authors: Petito Boyce C, Sax SN, Cohen JM

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2015
Are the Elements of the Proposed Ozone National Ambient Air Quality Standards Informed by the Best Available Science?
Regulatory Toxicology and Pharmacology 2015;72(1):134-140 Authors: Goodman JE, Sax SN, Lange SS, Rhomberg LR
2015
Providing Perspective for Interpreting Cardiovascular Mortality Risks Associated with Ozone Exposures.

Regulatory Toxicology and Pharmacology 2015;72(1):107-116.

Authors: Petito Boyce C, Goodman JE, Sax SN, Loftus CT
2015
Rethinking Meta-analysis: Applications for Air Pollution Data and Beyond.

Risk Analysis 2015;35(6):1017-1039.

Authors: Goodman JE, Petito Boyce C, Sax SN, Beyer LA, Prueitt RL 2015
Ozone Exposure and Systemic Biomarkers: Evaluation of Evidence for Adverse Cardiovascular Health Impacts.

Critical Reviews in Toxicology 2015;45(5):412-452.

Authors: Goodman JE, Prueitt RL, Sax SN, Pizzurro DM, Lynch HN, Zu K, Venditti FJ 2014
Weight-of-evidence Evaluation of Short-term Ozone Exposure and Cardiovascular Effects.

Critical Reviews in Toxicology 2014;44(9):725-790.

Authors: Goodman JE, Prueitt RL, Sax SN, Lynch HN, Zu K, Lemay JC, King JM, Venditti FJ 2014
The dubious benefits of further ozone reductions (Op-ed).

The Wall Street Journal May 11, 2014 at
http://online.wsj.com/news/articles/SB10001424052702304178104579536120366671620?mg=reno64- wsj
Authors: Goodman JE, Sax S
2014
Weight-of-evidence Evaluation of Long-term Ozone Exposure and Cardiovascular Effects.

Critical Reviews in Toxicology 2014;44(9):791-822.

Authors: Prueitt RL, Lynch HN, Zu K, Sax SN, Venditti FJ, Goodman JE. 2014
Letter to the editor Re: Long-Term Residential Exposure to Air Pollution and Lung Cancer Risk.

Epidemiology 2014;25(1):159.

Authors: Sax, SN, Goodman JE
2014
Evaluation of adverse human lung function effects in controlled ozone exposure studies.

Journal of Applied Toxicology 2014;34(5):516-24.

Authors: Goodman JE, Prueitt RL, Chandalia J, Sax SN

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2013
Letter re: article, 'Controlled Exposure of Healthy Young Volunteers to Ozone Causes Cardiovascular Effects.'
Circulation 127(4):e432.

Authors: Goodman JE, Sax SN
2013
Evaluation of the causal framework used for setting national ambient air quality standards.

Critical Reviews in Toxicology 2013;43(10):829-49.

Authors: Goodman JE, Prueitt RL, Sax SN, Bailey LA, Rhomberg LR. 2013
Letter to the editor Re: Air pollution and lung cancer incidence in 17 European cohorts: Prospective analyses from the European Study of Cohorts for Air Pollution Effects (ESCAPE).

The Lancet Oncology 2013;14(11):e439-40.

Authors: Sax SN, Zu K, Goodman JE
2013
Letter re: Equivocal evidence for confounding effects of components of particulate matter on the relationship between ozone and mortality [Letter].

American Journal of Epidemiology 2013;177(12): 1460–1462.

Authors: Sax SN, Goodman JE
2012
Potential indoor air exposures and health risks from mercury off-gassing of coal combustion products (CCPs) used in building materials.

Coal Combustion and Gasification Products 2013;4:68-74.

Authors: Long CM, Sax SN, Lewis AS
2011
Particulate matter in new technology diesel exhaust (NTDE) is quantitatively and qualitatively very different from that found in traditional diesel exhaust (TDE).

Journal of the Air & Waste Management Association 2011;61(9):894-913.

Authors: Hesterberg TW, Long CM, Sax SN, Lapin CA, McClellan RO, Bunn WB, Valberg PA. 2011
Human health hazards of exposure to new technology diesel exhaust (NTDE).

Toxicologist - Supplement to Toxicological Sciences 2011;120(Suppl. 2).

Authors: Hesterberg TW, Long CM, Sax SN, Lapin CA, Bunn WB, Valberg PA, McClellan RO 2011
Non-chemical stressors and cumulative risk assessment: An overview of current initiatives and potential air pollutant interactions.

International Journal of Environmental Research and Public Health 2011;8(6):2020-2073.

Authors: Lewis AS, Sax SN, Wason SC, Campleman SL
2011
Risk characterization of the brominated flame retardant decabromodiphenyl ethane in indoor dust.

Toxicologist - Supplement to Toxicological Sciences 2011;120(Suppl. 2):271.

Authors: Dodge DG, Pollock MC, Sax SN, Petito Boyce C, Goodman JE

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2010
Letter re: Xue et al. (2010) article addressing probabilistic modeling of dietary arsenic exposure and dose.

Environmental Health Perspectives 2010;118(8). E-pub ahead of print doi:10.1289/ehp.1002328.

Authors: Petito Boyce C, Lewis AS, Sax SN, Beck BD, Eldan M, Cohen SM 2009
Human exposure to decabromodiphenyl ether, tetrabromobisphenol A, and decabromodiphenyl ethane in indoor dust.

Journal of Environmental Protection Science 3:75-96
Authors: Petito Boyce C, Sax SN, Dodge DG, Pollock MC, Goodman JE 2009
Non-cancer health effects of diesel exhaust: A critical assessment of recent human and animal toxicological literature.

Critical Reviews in Toxicology 2009;39(3):195-227.

Authors: Hesterberg TW, Long CM, Bunn WB, Sax SN, Lapin CA, Valberg PA 2008
Measurement of particle concentrations in a dental office.

Environmental Monitoring and Assessment 2008;137(1-3):351-61.

Authors: Sotiriou M, Ferguson SF, Davey M, Wolfson JM, Demokritou P, Lawrence J, Sax SN, Koutrakis P.
2008
Probabilistic analysis of human health risks associated with background concentrations of inorganic arsenic: Use of a margin of exposure approach.

Human and Ecological Risk Assessment 2008;14:1159-1201. **Winner of the HERA Human Risk Assessment Paper of the Year Award in 2008.

Authors: Petito Boyce C, Lewis AS, Sax SN, Eldan ME, Cohen, SM, Beck BD 2007
Modeling time-location patterns of inner-city high school students in New York and Los Angeles using a longitudinal approach with generalized estimating equations.

Journal of Exposure Science & Environmental Epidemiology 2007;17(3):233-47.

Authors: Decastro BR, Sax SN, Chillrud SN, Kinney PL, Spengler JD. 2007
Trends in the elemental composition of fine particulate matter in Santiago, Chile, from 1998 to 2003.

Journal of the Air & Waste Management Association 2007;57(7):845-855.

Authors: Sax SN, Koutrakis P, Rudolph PA, Cereceda-Balic F, Gramsch E, Oyola P 2006
Integrating studies on carcinogenic risk of carbon black: Epidemiology, animal exposures, and mechanism of action.

Journal of Occupational and Environmental Medicine 2006;48(12):1291-1307.

Authors: Valberg P, Long CM, Sax SN
2006
A cancer health risk assessment of a cohort of inner-city teenagers in New York City and Los Angeles.

Environmental Health Perspectives 2006;114(10):1558-1566.

Authors: Sax SN, Bennett DH, Chillrud SN, Kinney P, Ross J, Spengler JD

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2005
Steel dust in the New York City subway system as a source of manganese, chromium, and iron exposures for transit workers.

Journal of Urban Health 2005;82(1):33-42.

Authors: Chillrud SN, Grass D, Ross JM, Coulibaly D, Slavkovich V, Epstein D, Sax SN, Pederson D, Johnson D, Spengler JD, Kinney PL, Simpson HJ, Brandt-Rauf P. 2005
Analysis of PM10, PM2.5, and PM2.5-10 concentrations in Santiago, Chile, from 1989 to 2001.

Journal of the Air & Waste Management Association 2005;55(3):342-351.

Authors: Koutrakis P, Sax SN, Sarnat JA, Coull B, Demokritou P, Oyola P, Garcia J, Gramsch E 2004
Differences in source emission rates of volatile organic compounds in inner-city residences of New York City and Los Angeles.

Journal of Exposure Analysis and Environmental Epidemiology 2004;14 Suppl 1:S95-S109.

Authors: Sax SN, Bennett DH, Chillrud SN, Kinney PL, Spengler JD 2004
Elevated airborne exposures to manganese, chromium and iron from steel dust in New York City's subway system.

Environmental Science & Technology 2004 Feb;38(3):732-737.

Authors: Chillrud SN, Epstein D, Ross JM, Sax SN, Pederson D, Spengler JD, Kinney PL 2002
Exposures to multiple air toxics in New York City.

Environmental Health Perspectives 2002;110(Suppl. 4):539-546.

Authors: Kinney PL, Chillrud SN, (Sax) Ramstrom S, Ross J

OTHER ACTIVITIES
Technical peer reviewer for the following Journals:

Journal of the Air & Waste Management Association
Journal of Exposure Science and Environmental Epidemiology Environmental Health Perspectives
Atmospheric Environment
Environmental Pollution

MEMBERSHIPS
Air & Waste Management Association (AWMA)
International Society of Exposure Science (ISES)
Society for Risk Analysis (SRA)
Society for Risk Analysis New England Chapter (SRA-NE)

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1/2 CV, JEAN GUO

JEAN GUO
Consultant
Jean Guo, a Consultant at Ramboll, is experienced in air quality modeling, climate change assessment, and health impact analysis. She has conducted air quality modeling studies using models including GEOS-Chem, CAMx, CMAQ, and HYSPLIT, and used the results to evaluate the sources and impacts of air pollutants. She also has experience working with observations from surface monitors including the IMPROVE and EPA AQS networks. She has a strong background in atmospheric chemistry, particularly in ozone and particulate matter pollution. Jean is proficient at programing languages including MATLAB, Python, and Linux, and has extensive experience in ArcGIS, BenMAP, and data analysis and visualization.

CAREER
2018-Present
Consultant
Ramboll (formerly Ramboll Environ)
2015-2018
Graduate Research Assistant
Columbia University, Earth and Environmental Sciences Department, New York, United States
2014
Researcher
NASA Student Airborne Research Program, Irvine, California, United States
2012-2015
Research Assistant
Columbia University, Earth and Environmental Sciences Department, New York, United States

EDUCATION
2017-2018
Master of Philosophy, Earth and Environmental Sciences (Atmospheric Science, Modern and Future Climate, Oceanography)
Columbia University, New York City, New York, United States 2015-2017
Master of Arts, Earth and Environmental Sciences (Atmospheric Science, Modern and Future Climate, Oceanography)
Columbia University, New York City, New York, United States 2011-2015
Bachelor of Arts, Environmental Sciences
Columbia University, New York City, New York, United States

CONTACT INFORMATION
Jean Guo
[email protected]
+1 (415) 8990715
Ramboll
7250 Redwood Blvd
Suite 105
Novato, CA 94945
United States of America

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SELECTED PROJECTS
Health Impact Analyses
• Compared the health impacts of various electrification scenarios on human health and converted the impacts to dollar estimates.
• Ran health impact analyses to compare the health effects of criteria air pollutants under various developments as per the requirements of the California Environmental Quality Act (CEQA). • Visualized the various health impacts of proposed projects on disadvantaged communities.

Climate Change
• Contributed to Environmental Impact Statements for various projects, analyzing the effect of the proposed project on the affected environment and climate. • Analyzed the future projected impacts of natural hazards such as flooding, wild fires, extreme heat, and water stress on various properties.
• Prepared reports to guide property owners and buyers on the potential risks to their properties from future climate change.

Air Quality Modeling
• Modeled the impact of various pollutants on select regions and quantified the source contributions from different sectors.
• Tracked the source of pollution by activity section and geographic location to determine the impact of each sector on specific regions.
• Determined the source contributions to criteria pollutants during days with bad air quality to determine the drivers of non-attainment days in various parts of the U.S.

PUBLICATIONS
Guo, J. J., Fiore, A. M., Murray, L. T., Jaffe, D. A., Schnell, J. L., Moore, T., and Milly, G.: Average versus high surface ozone levels over the continental U.S.A.: Model bias, background influences, and interannual variability, Atmos. Chem. Phys., https://doi.org/10.5194/acp-2018-115, 2018.

Young PJ, Naik V, Fiore AM, Gaudel A, Guo J, Lin MY, et al. Tropospheric Ozone Assessment Report:

Assessment of global-scale model performance for global and regional ozone distributions, variability, and trends. Elem Sci Anth. 2018; 6(1):10. DOI: http://doi.org/10.1525/elementa.265 Guo, J.J.: Interannual Variability in Background Tropospheric O3 in the U.S.A., 2017. Abstract.

Guo, J.J.: Seasonal and Regional Variability in the Relationship between Ground-Level Ozone (O3) and Fine Particulate Matter (PM2.5) in the United States, 2015. Abstract.

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TAYLOR A VENCILL
Senior Managing Consultant
Taylor Vencill is a Senior Managing Consultant in the Air Sciences Practice, currently located in the San Francisco, California office.

Taylor’s experience includes emissions estimation, air dispersion modeling, permitting, regulatory compliance, and greenhouse gas (GHG) emissions analyses and verifications. She has contributed to climate action plan development, climate change technical reports, environmental impact reports (EIRs), permit applications, health risk assessments (HRAs), and litigation support. Taylor’s analytical skills include emissions inventories, air dispersion modeling, and data analysis using Microsoft Excel, Microsoft Access, and Geographic Information Systems (GIS). She has experience with a variety of emissions estimation and air dispersion modeling software including CalEEMod, EMFAC, OFFROAD, AERMOD, CAL3QHCR, and HARP. Taylor is a Registered Professional Engineer (Chemical) in California and a California Air Resources Board-Accredited GHG Lead Verifier with Specialty in Oil & Gas and Process Emissions (Executive Order H18-159).

EDUCATION
MS, Civil and Environmental Engineering, Stanford University, 2014 BS, Chemical Engineering, Cornell University, 2009

EXPERIENCE HIGHLIGHTS
CEQA
• Contributed to and managed GHG, air quality, and energy analyses for various developments under the California
Environmental Quality Act (CEQA).
• Prepared GHG, air quality, and energy technical reports in support of EIRs for various types of development.
• Developed inventories for all aspects of developments including construction, energy use of buildings, mobile sources, area sources, municipal sources and vegetation change.
• Used the California Emissions Estimator Model (CalEEMod), the Emission Factor Model (EMFAC), OFFROAD2007 and the
In-Use Off-Road Equipment Model (2010 and 2011), and
the Urban Emission Model (URBEMIS) to evaluate
construction, area, and mobile emission inventories.

CONTACT INFORMATION
Taylor A Vencill
[email protected]
+1 (415) 426 5017
Ramboll
201 California Street
Suite 1200
San Francisco, 94111
United States of America

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Climate Change
• For various projects, have evaluated and presented mitigation options and potential offsets, showing potential GHG reductions and related costs of implementation. • Evaluated the significance of development emissions in relation to established thresholds. • Led the development of baseline and future GHG inventories for the Port of San Diego in support of their climate action plan (CAP). Incorporated the effect of California regulations on future emissions.
– Following the CAP development, helped evaluate the Port’s progress towards meeting the CAP goals and assisted the Port in implementation efforts. • Provided technical analyses for several GHG verifications under the California Air Resources Board (ARB) Mandatory Reporting Regulation. Verifications have included a poultry processing facility (general stationary combustion source), a transportation fuel supplier, an electricity importer, and an underground natural gas storage facility. Served as Lead Verifier on a setaside verification from Reporting Year 2014 for an onshore petroleum and natural gas production facility.

Emissions Estimation
• Assisted with the development of emissions inventories for various industrial sites for litigation support, permit applications and permit compliance.
• Specifically assisted in preparing emissions inventories for complex industrial facilities in support of an initial Title V application as well as Title V Renewal applications. • Managed development of a Facility-wide emissions inventory for a California refinery. • Assisted in historical emissions estimations and emission source identification for litigation support. Included extensive review of historical documents. • Assisted in development of emissions inventories for proposed modifications to industrial facilities.
– Related permitting efforts included New Source Review (NSR), Prevention of Significant Deterioration (PSD) and Title V applicability analyses. – Used Hotspots Analysis and Reporting Program (HARP) to manage the facilities’ emissions and assess the facilities’ prioritization score.

Air Dispersion Modeling
• Conducted AERMOD, ISCST3, CAL3QHCR and SCREEN3 dispersion modeling for HRAs, permit applications and regulatory compliance.
• Performed the following tasks in relation to air dispersion modeling:
– Meteorological data processing
– Surface parameter analysis
– Model and receptor setup using GIS tools
– Post-processing of model results to analyze the magnitude and location of potential risks • Performed reconciliation of air dispersion modeling and offsite monitoring results to determine source strengths of potential fugitive emission sources. • Managed large-scale air dispersion modelling for traffic and maritime impacts (city-wide scale), to determine PM2.5 and health risk impacts.

Specialized Modeling
• Used Automated Data Inquiry for Oil Spills (ADIOS2) in support of litigation.

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Regulatory Compliance
• Assisted a Class I Hazardous Waste Treatment, Storage, and Disposal Facility (TSDF) with air permit compliance, including an ambient air monitoring program (AAMP) and annual health risk evaluation (HRE).
• Conducted performance audits to evaluate the organic and inorganic sampling procedures, onsite meteorological station, spike test analyses and calibration procedures. • Conducted onsite compliance assistance for a biotechnology company, including tracking for continual air permit compliance and the development of related tools to assist in the tracking efforts.
• Assisted industrial clients with their annual Toxics Release Inventory (TRI) reporting requirements, including applicability determinations and release quantifications. • Assisted various clients with the ARB In-Use Off-Road Diesel-Fueled Fleets Regulation and LSI Fleet Requirements Regulation, including navigation through the regulations, evaluation of current and future fleet compliance to assist in purchasing and retrofit decisions, and assistance with the Diesel Off-Road Online Reporting System (DOORS). – Attended four related ARB training classes: Course #504 – In-Use Off-Road Diesel Vehicle Regulation Training, Course #505 – Large Spark-Ignition Fleet Regulation, Course #520 – How to Comply with CARB Diesel Regulations, Course #521.8 – Diesel Truck Regulation Compliance Course
• Project manager for the preparation of an Air Toxics Hot Spots Information and Assessment Act (AB 2588) HRA for an industrial client, using HARP to assess potential inhalation and multipathway health risk impacts.
• Assisted an industrial facility with evaluation of impact areas and preparation of warnings under Proposition 65.

Prior to joining Ramboll, Taylor held the following positions:
• Intern, Rhodia Inc, Martinez, California
– Used Ultrapipe software to analyze pipe measurements for effects of corrosion, oversaw several maintenance routines while shadowing a process engineer, and was present for the two-week plant shutdown when various inspections took place. • Intern, ENVIRON, Emeryville, California
– Assisted in preparing a Title V Renewal Application, developing carbon footprint analyses and emission inventories, and preparing technical memos, inventory management plans, and technical reports.

CREDENTIALS
Registrations and Certifications
California Air Resources Board-Accredited Greenhouse Gas (GHG) Lead Verifier with Specialty in Oil & Gas and Process Emissions (Executive Order H-18-159)
Registered Professional Engineer (Chemical), California

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CALIFORNIA STATE UNIVERSITY, ENVIRONMENTAL IMPACT REPORT DOMINGUEZ HILLS CAMPUS MASTER PLAN 2018
B.5 Friant Ranch Interim Recommendation
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Friant Ranch
Interim Recommendation
Background
The California Supreme Court in the case of Sierra Club v. County of Fresno (2018) 6 Cal. 5th 502 regarding the proposed Friant Ranch project determined the air quality analysis in the environmental impact report (EIR) was inadequate because it did not make “a reasonable effort to substantively connect the project’s air quality impacts to likely health consequences.” The Court determined that “the EIR should be revised to relate the expected adverse air quality impacts to likely health consequences or explain in meaningful detail why it is not feasible at the time of drafting to provide such an analysis.” Need
Lead agencies and practitioners preparing documents to comply with the California Environmental Quality Act (CEQA) have requested guidance from the Sacramento Metropolitan Air Quality Management District (Sac Metro Air District) on implementing the Friant Ranch decision in the review and analysis of proposed projects in Sacramento County.

Interim Recommendation
The Sac Metro Air District does not currently have a methodology that would correlate the expected air quality emissions of projects to the likely health consequences of the increased emissions. The Sac Metro Air District is in the process of developing a methodology to assess these impacts, and anticipates releasing it in the fall of 2019. In the interim, agencies should follow the Friant Court’s advice to explain in meaningful detail why this analysis is not yet feasible.

This explanation should describe the background underlying air regulations, the regional nature of the regulatory approach, and why the approach is not amenable to project level assessments. This should include a discussion of the public health impact analyses that form the basis for the state and federal health-based pollutant concentration standards, and the application of the standards to regions that were established based upon a commonality of factors impacting air quality. Air districts, in turn, have focused on reducing regional emissions from all sectors to meet the health-based concentration standards, thereby reducing the pollutant specific health impacts for the entire population. For example, the Sac Metro Air District prepared plans to attain and maintain the ozone and particulate matter ambient air quality standards. These attainment plans include emissions inventories, air monitoring data, control measures, modeling, future pollutant-level estimates, and general health information. Attainment planning models rely on regional inputs to determine ozone and particulate matter formation and concentrations in a regional context, not a project specific context. Because of the complexity of ozone formation, the pounds or tons of emissions from a proposed project in a specific geographical location does not equate to a specific concentration of ozone formation in a given area, because in addition to emission levels, ozone formation is affected by atmospheric chemistry, geography, and weather.

Secondary formation of particulate matter is very similar to the complexity of ozone formation, and localized impacts of directly emitted particulate matter do not always equate to local particulate matter concentrations due to transport of emissions. The analysis should explain that because air district attainment plans and supporting air model tools are regional in nature, they do not allow for analysis of the health impacts of specific projects on any given geographic location. More information is included in the threshold justification documents developed by the Sac Metro Air District, and available at our website at www.airquality.org.

The analysis should also discuss the current modelsi used in CEQA in air quality analyses, which, in contrast to attainment models, are designed to calculate and disclose the mass emissions expected from the construction and operation of a proposed project (pounds/day and tons/year). The estimated emissions are then compared to significance thresholds, which are in turn keyed to reducing emissions to levels that will not interfere with the region’s ability to attain the health-based standards. The Sac Metro Air District adopted operational emission thresholds for ozone precursors, nitrogen oxides (NOx) and reactive organic gasses (ROG), with the goal of obtaining 0.45 tons/year of NOx and 0.49 tons/year of ROG reductions from new

SACRAMENTO METROPOLITAN

AIR OUALITY

MANAGEMENT DISTRICT
777 12th Street, 3rd Floor I Sacramento, CA 95814-1908
916/874-4800 I 916/874-4899 fax
www.airquality.org 4191
Friant Ranch Interim Recommendation Page 2 of 3
April 25, 2019
development projects exceeding the thresholds by including emission reducing design features as mitigation.ii More recently, the Sac Metro Air District adopted particulate matter thresholds, PM10 and PM2.5, to align with the new source review permit offset levels, which are designed to prevent new emission sources from affecting attainment progress.iii Sac Metro Air District thresholds are set at 65 pounds/day NOx (11.8 tons/year), 65 pounds/day ROG (11.8 tons/year), 80 pounds/day PM10 (14.6 tons/year), and 82 pounds/day PM2.5 (15 tons/year).iv CEQA thresholds are a tool Sac Metro Air District uses to obtain emission reductions from development projects to support attainment of the Federal and State ambient air quality standards. This protects public health in the overall region, but there is currently no methodology to determine the impact of emissions on concentration levels in specific geographic areas.

The CEQA analysis should consider the degree to which various other tools, such as CalEEMod, EMFAC, OFFROAD, AERMOD, and HARP and CAMx, could assist in assessing specific health impacts of a project, and, where those tools would not be useful, explain why. For example, while CalEEMod may be useful in comparing emissions to significance thresholds, it is not able to assess transport of pollutants or the impacts of external factors (weather, terrain, etc.) on pollutant concentrations at particular locations.

In Sacramento, concentration modeling of ozone has not been an analytical tool used for project level emissions due to the complex nature of pollution concentration formation and numerous regional influences (multiple emission sources, meteorology, atmospheric chemistry and geography). Although some particulate matter concentration modeling has been conducted for project specific emissions for stationary source permitting purposes, concentration modeling has mainly been used to support ozone attainment demonstration.

Outside of these tools, neither the Sac Metro Air District nor any other air district currently have methodologies that would provide Lead Agencies and CEQA practitioners with a consistent, reliable, and meaningful analysis to correlate specific health impacts that may result from a proposed project’s mass emissions.

An expanded discussion of health impacts resulting from specific air pollutants may also be warranted for projects with emissions exceeding the Sac Metro Air District’s thresholds of significance. There is an array of information on health impacts related to exposure to ozonev and particulate mattervi emissions published by the US EPA and the California Air Resources Board. Health studies are used by these agencies to set the Federal and State ambient air quality standards. A more general discussion of health impacts related to air pollution is also available on www.sparetheair.com and in the Sac Metro Air District’s Guide to Air Quality Assessment in Sacramento County.vii None of the health-related information can be directly correlated to the pounds/day or tons/year of emissions estimated from a single, proposed project.

Developing Guidance
The interim recommendation is in place to assist lead agencies and practitioners with CEQA document preparation until Sac Metro Air District develops a methodology that provides a consistent, reliable and meaningful analysis to address the Court’s direction on correlating health impacts to a project’s emissions.

Sac Metro Air District staff have initiated discussions with the other air district’s in the Sacramento Federal Ozone Nonattainment area regarding developing guidance in response to Friant Ranch since we share air quality issues and use the same growth assumptions, mobile source emissions, and modeling efforts to support our ozone and particulate matter attainment plans.

One potentially useful tool in developing a methodology is the US EPA’s BenMap toolviii. According to US EPA’s website, BenMap is an “open-source computer program that calculates the number and economic value of air pollution-related deaths and illnesses. The software incorporates a database that includes many of the concentration-response relationships, population files, and health and economic data needed to quantify these impacts.” BenMap may be able to provide the detailed health information needed for the guidance under development.
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Friant Ranch Interim Recommendation Page 3 of 3
April 25, 2019
Sac Metro Air District is working with its engineering and environmental technical support consultant, Ramboll USA Corporation, to develop a methodology that will provide a consistent, reliable, efficient, and meaningful analysis that correlates health impacts from proposed projects’ emissions for the Sacramento region. The current strategy will analyze how various levels of emissions (the CEQA tonnage estimates) impact attainment pollutant concentration levels, and use BenMap to correlate increases in concentration levels to health impacts. Once a methodology is available, Sac Metro Air District staff will inform interested stakeholders and provide updated guidance in this document and in its Guide to Air Quality Assessment in Sacramento County.

Contact Information
Lead agencies and CEQA practitioners may contact Mr. Paul Philley, CEQA and Land Use Section Program Supervisor at 916-874-4882 or [email protected] regarding Sac Metro Air District’s recommendations. i CalEEMod, Road Construction Emissions Model, EMFAC, OFFROAD ii Foundation for a Threshold, Justification for Air Quality Thresholds of Significance In the Sacramento Federal Nonattainment Area, August 15, 2001, Adopted March 28, 2002.
iii Proposed Particulate Matter CEQA Thresholds of Significance, March 19, 2015, Adopted May 28, 2015. iv Sac Metro Air District, Guide to Air Quality Assessment in Sacramento County, December 2009 (latest update September 2018), Chapter 2, Thresholds of Significance table. http://www.airquality.org/LandUseTransportation/Documents/CH2ThresholdsTable5- 2015.pdf
v https://www.epa.gov/ozone-pollution-and-your-patients-health/health-effects-ozone-general-population vi https://www.arb.ca.gov/research/health/pm-mort/PMmortalityreportFINALR10-24-08.pdf vii Sac Metro Air District, Guide to Air Quality Assessment in Sacramento County, December 2009 (latest update September 2018), Chapter 1. http://www.airquality.org/LandUseTransportation/Documents/Ch1IntroAq%20FINAL12-2016.pdf viii https://www.epa.gov/benmap

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16285-02 Technical Memo 13 Eucalyptus Business Park Specific Plan APPENDIX 2:

COBRA MODEL OUTPUTS
4194
FIPS State County Base PM 2.5 Control PM 2.5 Delta PM 2.5 Base O3 Control O3 Delta O3 $ Total Health Benefits(low estimate) $ Total Health Benefits(high estimate) Total Mortality(low estimate) $ Total Mortality(l Total Mortality(high estimate) 6037 California Los Angeles 2.93 2.93 0.00 10.61 10.62 0.00 -5,881,978.71 -10,668,162.07 -0.35 -5,471,881.65 -0.65 6059 California Orange 2.80 2.81 0.00 8.36 8.36 0.00 -2,115,785.67 -3,752,009.16 -0.13 -1,989,567.63 -0.23 6065 California Riverside 1.63 1.63 0.00 10.59 10.59 0.00 -1,553,946.56 -2,423,016.49 -0.09 -1,404,979.85 -0.14 6071 California San Bernardino 1.43 1.43 0.00 12.67 12.67 0.00 -1,248,005.01 -1,819,838.00 -0.07 -1,101,157.47 -0.11 4195
FIPS State County
6037 California Los Angeles
6059 California Orange
6065 California Riverside
6071 California San Bernardino
$ Total Mortality(high estimate) PM Mortality, All Cause (low) $ PM Mortality, All Cause (low) PM Mortality, All Cause (high) $ PM Mortality, All Cause (high) PM Infant Mortality $ PM Infant Mortality Total O3 Mortality -10,258,065.02 -0.26 -4,160,789.27 -0.57 -8,946,972.63 0.00 -30,919.37 -0.08 -3,625,791.12 -0.10 -1,575,342.58 -0.20 -3,211,566.07 0.00 -8,041.68 -0.03 -2,274,049.77 -0.05 -778,961.17 -0.10 -1,648,031.10 0.00 -6,615.78 -0.04 -1,672,990.46 -0.03 -471,342.34 -0.07 -1,043,175.33 0.00 -6,266.80 -0.04 4196
FIPS State County
6037 California Los Angeles
6059 California Orange
6065 California Riverside
6071 California San Bernardino
$ Total O3 Mortality O3 Mortality (Short-term exposure) $ O3 Mortality (Short term exposure) O3 Mortality (Long-term exposure) $ O3 Mortality (Long-term exposure) Total Asthma Symptoms $ Total Asthma Symptoms -1,280,173.01 0.00 -54,869.73 -0.08 -1,225,303.28 -278.48 -47,635.07 -406,183.36 0.00 -17,417.25 -0.02 -388,766.11 -86.88 -13,935.88 -619,402.89 0.00 -26,602.73 -0.04 -592,800.17 -86.07 -23,345.90 -623,548.33 0.00 -26,778.52 -0.04 -596,769.81 -80.70 -24,567.48 4197
FIPS State County
6037 California Los Angeles
6059 California Orange
6065 California Riverside
6071 California San Bernardino
PM Asthma Symptoms, Albuterol use $ PM Asthma Symptoms, Albuterol use O3 Asthma Symptoms, Chest Tightness $ O3 Asthma Symptoms, Chest Tightness O3 Asthma Symptoms, Cough $ O3 Asthma Symptoms, Cough -164.43 -116.28 -31.42 -13,091.92 -37.06 -15,442.91
-53.53 -37.85 -9.19 -3,829.05 -10.84 -4,516.66
-30.09 -21.28 -15.42 -6,426.19 -18.19 -7,580.15
-21.77 -15.40 -16.23 -6,764.37 -19.15 -7,979.06
4198
FIPS State County
6037 California Los Angeles
6059 California Orange
6065 California Riverside
6071 California San Bernardino
O3 Asthma Symptoms, Shortness of Breath $ O3 Asthma Symptoms, Shortness of Breath O3 Asthma $ O3 Asthma Symptoms, Wheeze Total Incidence, Asthma $ Total Incidence, Asthma PM Inciden $ PM Incidence, Asthma O3 Inciden -15.86 -6,606.91 -29.71 -12,377.04 -1.60 -133,383.44 -0.87 -72,565.41 -0.73 -4.64 -1,932.35 -8.69 -3,619.97 -0.50 -41,850.75 -0.28 -23,779.93 -0.22 -7.78 -3,243.00 -14.58 -6,075.28 -0.53 -44,439.67 -0.17 -13,918.99 -0.37 -8.19 -3,413.66 -15.35 -6,394.99 -0.50 -42,033.75 -0.12 -10,019.09 -0.38 4199
FIPS State County
6037 California Los Angeles
6059 California Orange
6065 California Riverside
6071 California San Bernardino
$ O3 Incidence, Asthma Total Incidence, Hay Fever/Rhinitis $ Total Incidence, Hay Fever/Rhinitis PM Incidence, Hay Fever/Rhinitis $ PM Incidence, Hay Fever/Rhinitis O3 Incidence, Hay Fever/Rhinitis $ O3 Incidence, Hay Fever/Rhinitis -60,818.03 -10.39 -12,782.82 -5.63 -6,921.87 -4.76 -5,860.95 -18,070.82 -3.24 -3,987.17 -1.83 -2,256.81 -1.41 -1,730.35 -30,520.67 -3.36 -4,128.23 -1.04 -1,284.25 -2.31 -2,843.97 -32,014.66 -3.19 -3,921.50 -0.75 -927.76 -2.43 -2,993.74 4200
FIPS State County
6037 California Los Angeles
6059 California Orange
6065 California Riverside
6071 California San Bernardino
Total ER Visits, Respiratory $ Total ER Visits, Respiratory PM ER Visits, Respiratory $ PM ER Visits, Respiratory O3 ER Visits, Respiratory $ O3 ER Visits, Respiratory Total Hospital Admits, All Respiratory $ Total Hospital Admits All Respiratory -0.44 -784.43 -0.21 -368.34 -0.23 -416.09 -0.05 -1,450.18 -0.11 -195.56 -0.05 -96.68 -0.06 -98.89 -0.01 -413.64
-0.15 -263.60 -0.04 -66.66 -0.11 -196.94 -0.01 -237.80
-0.17 -305.41 -0.03 -57.57 -0.14 -247.84 -0.01 -226.65
4201
FIPS State County
6037 California Los Angeles
6059 California Orange
6065 California Riverside
6071 California San Bernardino
PM Hospital Admits, All Respiratory $ PM Hospital Admits All Respiratory O3 Hospital Admits, All Respiratory $ O3 Hospital Admits All Respiratory PM Nonfatal Heart Attacks $ PM Nonfatal Heart Attacks -0.04 -1,192.59 -0.01 -257.59 -0.24 -21,924.23
-0.01 -341.82 0.00 -71.82 -0.07 -6,640.56

0.00 -151.71 0.00 -86.09 -0.04 -3,943.40

0.00 -134.96 0.00 -91.68 -0.03 -2,991.22
4202
FIPS State County
6037 California Los Angeles
6059 California Orange
6065 California Riverside
6071 California San Bernardino
PM Minor Restricted Activity Days $ PM Minor Restricted Activity Days PM Work Loss Days $ PM Work Loss Days PM Incidence Lung Cancer $ PM Incidence Lung Cancer PM HA Cardio Cerebro and Peripheral Vascular Disease -272.76 -37,035.32 -46.23 -15,936.61 -0.02 -1,197.97 -0.05 -89.48 -12,149.38 -15.18 -5,233.88 -0.01 -433.76 -0.02
-44.37 -6,023.87 -7.61 -2,622.49 0.00 -199.88 -0.01
-30.42 -4,130.68 -5.22 -1,799.16 0.00 -114.37 -0.01
4203
FIPS State County
6037 California Los Angeles
6059 California Orange
6065 California Riverside
6071 California San Bernardino
$ PM HA Cardio Cerebro and Peripheral Vascular Disease PM HA Alzheimers Disease $ PM HA Alzheimers Disease PM HA Parkinsons Disease $ PM HA Parkinsons Disease PM Incidence Stroke $ PM Incidence Stroke -1,617.56 -0.14 -3,363.92 -0.02 -446.33 -0.02 -1,389.44 -485.89 -0.06 -1,540.71 -0.01 -163.63 -0.01 -508.93
-242.58 -0.01 -332.31 0.00 -81.18 0.00 -253.96
-176.98 -0.01 -209.88 0.00 -44.71 0.00 -140.24
4204
FIPS State County
6037 California Los Angeles
6059 California Orange
6065 California Riverside
6071 California San Bernardino
PM Incidence Out of Hospital Cardiac Arrest $ PM Incidence Out of Hospital Cardiac Arrest PM ER visits All Cardiac Outcomes $ PM ER visits All Cardiac Outcomes O3 ER Visits, Asthma $ O3 ER Visits, Asthma

0.00 -339.56 -0.09 -224.79 0.00 -1.25

0.00 -116.97 -0.03 -71.07 0.00 -0.24

0.00 -56.72 -0.02 -38.16 0.00 -0.48

0.00 -34.64 -0.01 -29.03 0.00 -0.68
4205
FIPS State County
6037 California Los Angeles
6059 California Orange
6065 California Riverside
6071 California San Bernardino
O3 School Loss Days, All Cause $ O3 School Loss Days, All Cause -70.55 -130,584.14
-20.80 -38,490.03
-33.91 -62,756.50
-35.72 -66,121.17
4206
Ontario Policy Plan Amendment SEIR
CEQA Statement of Overriding Considerations
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EXHIBIT B. STATEMENT OF OVERRIDING CONSIDERATIONS

REGARDING THE FINAL SUPPLEMENTAL ENVIRONMENTAL IMPACT

REPORT FOR THE ONTARIO POLICY PLAN AMENDMENT
STATE CLEARINGHOUSE NO. 2025110102

STATEMENT OF OVERRIDING CONSIDERATIONS
CEQA requires decision makers to balance the benefits of the proposed project against its unavoidable environmental risks when determining whether to approve the project.

If the benefits of the project outweigh the unavoidable adverse effects, those effects may be considered “acceptable” (Public Resources Code Section 21081[b]; State CEQA Guidelines Section 15093[a]). CEQA requires the agency to support, in writing, the specific reasons for considering a project acceptable when significant impacts are infeasible to mitigate. Such reasons must be based on substantial evidence in the FEIR or elsewhere in the administrative record (State CEQA Guidelines Section 15093 [b]). The agency’s statement is referred to as a Statement of Overriding Considerations. (State CEQA Guidelines Section 15093[b]).

SIGNIFICANT AND UNAVOIDABLE IMPACTS
The following describes the project’s significant and unavoidable adverse impact and the justification for adopting a statement of overriding considerations. Although most potential project impacts have been substantially avoided or mitigated, as described above, 14 project impacts remain for which complete mitigation is not feasible (6 pertain to the EBPSP). The SEIR identified the following significant unavoidable adverse project impacts, which would continue to be applicable upon implementation of the proposed project:

Air Quality
Impact AQ-1 (PPA + EBPSP)
 Policy Plan Amendment: As shown in Table 3.2-12, City of Ontario Regional Criteria Air Pollutant Emissions Forecast, of the SEIR, the proposed project would result in a substantial increase in reactive organic gases (ROG) and nitrogen oxides (NOx) compared to TOP 2050 (approved project). At the program level, ROG and NOx emissions cannot be mitigated because the primary sources are outside local control.

ROG emissions largely come from consumer products that are regulated at the manufacturer level, and the City cannot control which products residents purchase or use. Similarly, NOx emissions from the transportation sector depend on the types of vehicles individuals choose to own and operate, which are governed by state and 4207
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CEQA Statement of Overriding Considerations
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federal standards rather than local plans. Accordingly, because of the magnitude and intensity of development accommodated by the proposed project, as well as regional air quality influences beyond the control of the City, impacts associated with consistency with the Air Quality Management Plan (AQMP) would remain significant and unavoidable. No additional feasible mitigation measures or mitigating policies at the program level would ensure consistency of the proposed project with the South Coast Air Quality Management District’s (South Coast AQMD) AQMP. The identification of this program-level impact does not preclude the finding of less-thansignificant impacts for subsequent individual projects that meet applicable projectlevel thresholds of significance.  EBPSP: There is no feasible mitigation that would reduce impacts associated with consistency of the project with the AQMP to less than significant. Impacts would remain significant and unavoidable. This finding is consistent with the impacts previously identified as part of the 2022 Certified EIR. Impact AQ-2 (PPA) Impact AQ-2 (PPA)
 Policy Plan Amendment: Buildout in accordance with the proposed project would generate short-term construction emissions that would exceed South Coast AQMD’s regional significance thresholds and cumulatively contribute to the nonattainment designations of the South Coast Air Basin (SoCAB). Mitigation Measure AIR-1-PPA and applicable goals and policies of the proposed project would reduce constructionrelated air pollutant emissions to the extent feasible. Construction emissions associated with the proposed project would be similar to the approved project because the proposed project would increase in land use intensity, not develop new, previously undeveloped areas of the city that would require substantial landform modification. However, individual projects accommodated under proposed project may exceed the South Coast AQMD regional significance thresholds. Therefore, like the approved project, construction-related regional air quality impacts of developments that would be accommodated by the proposed project would remain significant and unavoidable.

Impact AQ-3 (PPA + EBPSP)
 Policy Plan Amendment: At the programmatic planning level, the City lacks sufficient site-specific information regarding the precise location, configuration, operational characteristics, and receptor relationships of future individual development projects necessary to perform reliable quantitative health risk modeling. Accordingly, health risk analysis for future projects will occur during subsequent project-level CEQA review where sufficient detail exists. Buildout in accordance with the proposed project would generate long-term emissions that would exceed South Coast AQMD’s regional significance thresholds and cumulatively contribute to the nonattainment 4208
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CEQA Statement of Overriding Considerations
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designations of the SoCAB. Mitigation Measures AIR-2-PPA and AIR-3-PPA, in addition to the goals and policies of the Policy Plan Amendment, would reduce air pollutant emissions to the extent feasible. Impact AQ-3 would remain significant and unavoidable due to the increase in ROG and NOx emissions from development associated with the proposed project compared to that of the approved project.  EBPSP: Overlap-period emissions do not constitute a separate impact category requiring independent mitigation beyond the construction and operational mitigation measures already imposed because overlap emissions are temporary, are encompassed within the project’s overall regional emissions profile, and do not materially alter the significance conclusion reached for operational or construction emissions. Although Mitigation Measures AIR-1-SP through AIR-8-SP are designed to reduce operational-source criteria pollutant emissions of the EBPSP, there is no way to meaningfully quantify these reductions in CalEEMod, so no numeric emissions credit has been taken in the analysis. Therefore, even with application of these measures, EBPSP operational-source emissions impacts are considered significant and unavoidable. This finding is consistent with the impacts previously identified as part of the 2022 Certified EIR.

Impact AQ-4 (PPA)
 Policy Plan Amendment: Construction activities associated with the proposed project could expose sensitive receptors to substantial concentrations of criteria air pollutants and toxic air contaminants (TAC). Mitigation Measure AIR-1-PPA would require that future development projects incorporate measures to reduce construction emissions that would minimize exposure of sensitive receptors to elevated concentrations of criteria air pollutant emissions and TACs. Additionally, review of development projects by South Coast AQMD for permitted sources of air toxics (e.g., industrial facilities, dry cleaners, and gasoline dispensing facilities) would ensure that health risks are minimized. Individual development projects would be required to achieve the incremental risk thresholds established by South Coast AQMD, and TACs would be less than significant. However, because existing sensitive receptors may be close to project-related construction activities and because of the programmatic nature of the proposed project, construction emissions generated by individual development projects have the potential to exceed South Coast AQMD’s localized significance thresholds (LSTs) and contribute to higher levels of cancer risk in the SoCAB. Consequently, Impact AQ-4 would remain significant and unavoidable.

Impact AQ-5 (PPA)
 Policy Plan Amendment: At the programmatic planning level, the City lacks sufficient site specific information regarding the precise location, configuration, operational characteristics, and receptor relationships of future individual development projects 4209
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CEQA Statement of Overriding Considerations
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necessary to perform reliable quantitative health risk modeling. Accordingly, health risk analysis for future projects will occur during subsequent project-level environmental review where sufficient detail exists. Buildout of the proposed project and the approved project could expose sensitive receptors to substantial concentrations of TACs. Buildout could result in new sources of criteria air pollutant emissions and/or TACs near existing or planned sensitive receptors. Review of development projects by South Coast AQMD for permitted sources of air toxics (e.g., industrial facilities, dry cleaners, and gasoline dispensing facilities) would ensure that health risks are minimized. Additionally, Policy ER-4.9 would ensure mobile sources of TACs not covered under South Coast AQMD permits are considered during subsequent project-level environmental review by the City of Ontario. Individual development projects would be required to achieve the incremental risk thresholds established by South Coast AQMD, and TACs would be less than significant. However, implementation of the proposed project would generate TACs that could contribute to elevated levels in the air basin. This effect is more substantial with the proposed project compared to the approved project because of the increase in industrial land use allowed under the proposed project. Though individual projects may achieve the project-level risk threshold of 10 per million, they would nonetheless contribute to higher levels of cancer risk in the SoCAB, and therefore would result in a cumulatively considerable impact. Therefore, the proposed project’s cumulative contribution to health risk is significant and unavoidable.

Cultural Resources
Impact CUL-1 (PPA)
 Policy Plan Amendment: Implementation of the Policy Plan Amendment could impact historical resources. Mitigation Measure CUL-1-PPA would require historic and potentially historic resources to be evaluated for historic significance through the City’s Development Code tier system, except those in Ontario Ranch. Mitigation Measures CUL-1-PPA and CUL-2-PPA establish requirements for historic resources classified as Tier III and II (in Ontario Ranch) and potentially historic resources (identified through survey evaluation) in Ontario Ranch to minimize significant impacts. Major modification or demolition of historic resources may be appropriate under certain circumstances. In the case of demolition, the City requires historic resources to be documented, historic features to be salvaged, and a demolition mitigation fee. Therefore, the Development Code does not provide a high level of protection for Tier III or Tier II historic resources in Ontario Ranch or potentially significant historic resources identified through a survey in Ontario Ranch. Impact CUL-1 would remain significant and unavoidable.
4210
Ontario Policy Plan Amendment SEIR
CEQA Statement of Overriding Considerations
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Greenhouse Gas Emissions
Impact GHG-1 (PPA + EBPSP)
 Policy Plan Amendment: Implementation of Mitigation Measure GHG-1-PPA would ensure that the City aligns its Community Climate Action Plan (CCAP) update with the GHG reduction targets of AB 1279 and the statewide legislative GHG emission reduction targets that are in effect at the time of the CCAP update. Implementation of CCAP measures that increase the efficiency of energy and water use and offset electricity use through solar panels would reduce GHG emissions from land uses accommodated under the proposed project to the extent feasible. Given the growth in population and employment in the city, the emissions reductions needed from existing development, the overall magnitude of emissions reductions needed to achieve the GHG reduction target from existing and new development, and federal legal constraints on the implementation and effectiveness of State actions for emissions reduction, it is uncertain whether implementation of Mitigation Measure GHG-1-PPA would achieve the substantial reductions needed to align with the GHG reduction targets of Assembly Bill (AB) 1279. In addition, the City cannot ensure that Mitigation Measure GHG-1-PPA would be implemented prior to the generation of new GHG emissions from development facilitated under the proposed project, which could further limit the effectiveness of this mitigation measure in achieving the required emissions reductions.

It would be infeasible to require rooftop solar sufficient for 100 percent of warehouse energy demands. At the programmatic planning stage evaluated in the Draft SEIR, the identities of future tenants, specific building configurations, operational characteristics, and ultimate energy demands associated with future development within the PPA are not currently known. It would be infeasible at this time to require 100 percent of future operational electricity demand to be supplied exclusively through on-site rooftop solar generation. Future demands may vary substantially depending on tenant-specific operational needs, including refrigeration systems, warehouse automation, industrial processes, HVAC requirements, electric vehicle fleet charging, equipment chagrining, data processing systems, and other energy-intensive commercial or industrial activities that cannot presently be quantified with precision.

In addition, the amount of rooftop area suitable for photovoltaic installation may vary considerably among future buildings due to structural engineering requirements, rooftop mechanical equipment, ventilation systems, skylights, fire access pathways, screening features, shading conditions, roof orientation, and applicable building and fire code setback requirements. These constraints may substantially reduce the area available for solar installations and, in some cases, may prevent rooftop systems from generating sufficient electricity to offset project demand. Further, photovoltaic generation is inherently intermittent and may not 4211
Ontario Policy Plan Amendment SEIR
CEQA Statement of Overriding Considerations
- 6 -
coincide with periods of peak operational electricity demand associated with future industrial or logistics uses.

It would also be infeasible to require warehouse development to maximize electric truck infrastructure. The City’s land use authority extends to regulation of development proposals and land uses within its jurisdiction, but not to independently owned third-party trucking companies, interstate commerce carriers, regional freight operators, or off-site fleet operations utilizing public roadways. Truck fleets serving future development facilitated by the proposed project may include independent owner-operators, regional distribution fleets, interstate carriers, and logistics providers across multiple jurisdictions. The City lacks direct regulatory authority to mandate vehicle technology standards for such off-site fleets operating on public highways, which are primarily regulated through State and federal mobile source programs administered by the California Air Resources Board and the U.S.

Environmental Protection Agency. Accordingly, a mitigation measure requiring that only ZE trucks serve future development would attempt to regulate third-party activities beyond the City’s practical enforcement authority.

In addition, future project applicants may not possess direct control over the technologies utilized by freight carriers serving their facilities. Warehousing, logistics, manufacturing, and distribution tenants frequently rely upon common carriers operating mixed fleets throughout the regional and interstate supply chains. At present, heavy-duty ZE truck technologies continue to face operational limitations related to vehicle range, charging duration, payload impacts, charging availability, and fleet deployment capacity, particularly for long-haul freight operations and highintensity logistics uses. Consequently, requiring immediate universal conversion to ZE technologies for all future truck trips associated with speculative future industrial and logistics development may not presently be technologically or commercially feasible across all potential operational scenarios.

Widespread deployment of heavy-duty ZE truck fleets would require substantial supporting infrastructure, including utility distribution upgrades, transformer capacity expansion, substation improvements, transmission interconnections, highcapacity charging equipment, and coordination with local regional utility providers.

Such infrastructure improvements are dependent upon future utility planning, regional electrical grid capacity, technological advancement, and third-party implementation schedules that are presently unknown and outside the City’s control. The amount and timing of electrical infrastructure necessary to support future heavy-duty truck electrification cannot presently be determined because future tenant operations, vehicle fleet compositions, charging schedules, and energy demands remain speculative.

Nevertheless, the Draft SEIR identifies multiple mechanisms intended to facilitate future transition toward lower-emission freight operations and reduce operational emissions associated with future development. Pursuant to Mitigation Measure AIR4212 Ontario Policy Plan Amendment SEIR
CEQA Statement of Overriding Considerations
- 7 -
1PPA and AIR-3-PPA, future projects subject to CEQA review would be required to prepare project-specific technical analyses evaluating operational air quality impacts and to implement feasible mitigation measures where warranted. Depending on characteristics of future projects, such measures as individual electric truck charging infrastructure, loading dock electrical hookups, renewable energy systems, transportation demand management measures, renewable energy procurement, and other operational emission reduction strategies. Therefore, GHG emissions impacts of the proposed project compared to the approved project are considered significant and unavoidable.
 EBPSP: Preliminary CCAP measures to be implemented by the EBPSP are presented in Table 3.8-12, EBPSP CCAP Screening Table, of the SEIR. These measures are subject to change throughout the development process so long as the requisite 100 points are achieved, as required by Mitigation Measure GHG-1-SP. As shown in the table, measures implemented by the EBPSP would achieve a total of 101 points. As part of the EBPSP’s CCAP compliance measures, the EBPSP has committed to a rooftop solar system with sufficient capacity to offset 45 percent of the electrical demands. Tables

3.8-13, EBPSP GHG Emissions: Phase 1 (Mitigated); 3.8-14, EBPSP GHG Emissions:

Phases 1 and 2 (Mitigated); and 3.8-15, EBPSP GHG Emissions: Phases 1, 2, and 3 (Mitigated), in the SEIR present the estimated operational GHG emissions for all phases of the EBPSP with the incorporation of the rooftop solar system. Even with the incorporation of rooftop solar, the EBPSP would result in GHG emissions of approximately 45,539 metric tons of carbon dioxide equivalent per year (MTCO2e/yr) at buildout and would still exceed the numeric threshold of 3,000 MTCO2e/yr. Other features to be implemented through compliance with Mitigation Measure GHG-1-SP and Mitigation Measures AIR-1-SP through AIR-8-SP, as listed in Table 3.8-14 in the SEIR, would also reduce GHG emissions, but these reductions are not quantifiable.

In addition, the amount of rooftop area suitable for photovoltaic installation may vary considerably among future buildings due to structural engineering requirements, rooftop mechanical equipment, ventilation systems, skylights, fire 4213
Ontario Policy Plan Amendment SEIR
CEQA Statement of Overriding Considerations
- 8 -
access pathways, screening features, shading conditions, roof orientation, and applicable building and fire code setback requirements. These constraints may substantially reduce the area available for solar installations and, in some cases, may prevent rooftop systems from generating sufficient electricity to offset project demand. Further, photovoltaic generation is inherently intermittent and may not coincide with periods of peak operational electricity demand associated with future industrial or logistics uses.

Such infrastructure improvements are dependent upon future utility planning, regional electrical grid capacity, technological advancement, and third-party implementation schedules that are presently unknown and outside the City’s control. The amount and timing of electrical infrastructure necessary to support future heavy-duty truck electrification cannot presently be determined because 4214
Ontario Policy Plan Amendment SEIR
CEQA Statement of Overriding Considerations
- 9 -
future tenant operations, vehicle fleet compositions, charging schedules, and energy demands remain speculative.

Accordingly, no additional feasible mitigation measures are available at this time that would substantially lessen the identified impacts associated with full buildout of the EBPSP area. Therefore, the EBPSP would result in significant and unavoidable GHG emissions.

Impact GHG-2 (PPA + EBPSP)
 Policy Plan Amendment: Implementation of CCAP measures that increase energy efficiency, reduce water use, and offset electricity use through solar panels would reduce GHG emissions from land uses accommodated under the proposed project to the extent feasible. However, given the growth in population and employment within the City, the magnitude of emissions reductions needed to achieve the CCAP’s 2050 per capita target, and federal legal constraints on the implementation and effectiveness of State actions for emission reduction, it is uncertain whether implementation of Mitigation Measure GHG-1-PPA would achieve the substantial reductions needed to achieve CCAP’s 2050 per capita target and the State’s carbon neutrality goals. Therefore, GHG emissions impacts of the proposed project compared to the approved project are considered significant and unavoidable.  EBPSP: The CCAP provides guidance on how to analyze GHG emissions and determine impact significance during the CEQA review of proposed development projects. Because the CCAP addresses GHG emissions reductions and is consistent with the requirements of AB 32, Senate Bill (SB) 32, and international efforts to reduce GHG emissions, compliance with the CCAP fulfills the requirement for mitigation pursuant to the State CEQA Guidelines. As shown in Table 3.8-12, with the implementation of Mitigation Measure GHG-SP-1, the EBPSP would attain the minimum requisite 100 Screening Table points. However, because the EBPSP is not consistent with the land use pattern and subsequent communitywide GHG emissions projections of the CCAP, the EBPSP is determined to be inconsistent with the CCAP 4215
Ontario Policy Plan Amendment SEIR
CEQA Statement of Overriding Considerations
- 10 -
and would result in a significant and unavoidable GHG impact, which was not anticipated as part of the 2022 Certified EIR.

Noise
Impact NOI-1 (PPA)
 Policy Plan Amendment: Mitigation Measure NOI-1-PPA would reduce potential impacts associated with construction of individual development projects to the extent feasible; however, due to the potential for construction activities near sensitive uses, the potential for numerous simultaneous construction projects, and the potential duration of construction activities, Impact NOI-1 could still result in a temporary substantial increase in noise levels above ambient conditions and the 80 dBA Leq threshold. Therefore, project and cumulative impacts would be significant and unavoidable. It should be noted that the identification of this program-level impact does not preclude the finding of less-than-significant impacts for subsequent projects analyzed at the project level.

Impact NOI-2 (PPA + EBPSP)
 Policy Plan Amendment: Measures applied to individual development projects, such as constructing noise walls, evaluating and installing upgraded windows and doors, or applying rubberized asphalt on impacted roadway segments could reduce potential traffic noise impacts. However, impacted homes are on private property, outside of the control of future project developers, who may have limited admittance onto these properties to implement such mitigation. The cost-to-benefit ratio for the number of households benefited may not be feasible and reasonable in all cases. There are no funding mechanisms and procedures that would guarantee that the implementation of sound insulation features at each affected home would reduce traffic noise in interior areas. Therefore, project impacts would remain significant and unavoidable. It should be noted that the identification of this program-level impact does not preclude the finding of less-than-significant impacts for subsequent projects analyzed at the project level.
 EBPSP: Due to the infeasibility of both quiet pavement and off-site noise barriers, EBPSP-related off-site traffic noise increases at adjacent noise-sensitive land uses are considered a significant and unavoidable impact.

Impact NOI-3 (PPA)
 Policy Plan Amendment: Mitigation Measure NOI-2-PPA would reduce potential impacts associated with construction vibration from individual development projects to the extent feasible. However, due to the potential for construction activities in proximity to sensitive uses, the potential for numerous simultaneous construction 4216
Ontario Policy Plan Amendment SEIR
CEQA Statement of Overriding Considerations
- 11 -
projects, and the potential duration of construction activities, construction vibration impacts would be significant and unavoidable. It should be noted that the identification of this program-level impact does not preclude the finding of less-thansignificant impacts for subsequent projects analyzed at the project level.

Impact NOI-4 (PPA)
 Policy Plan Amendment: Revisions to Policy M-4.1 of TOP 2050 would reduce vibration annoyance impacts from individual development projects associated with heavy truck travel along City haul routes to the extent feasible. Reducing heavy truck travel speeds provides safe and efficient transport of goods on impacted roadway segments and could reduce potential heavy truck vibration annoyance impacts.

However, impacted receptors may still perceive an annoyance. Therefore, heavy truck vibration impacts associated with the proposed project would remain significant and unavoidable. It should be noted that the identification of this program-level impact does not preclude the finding of less-than-significant impacts for subsequent projects analyzed at the project level.

Impact NOI-5 (PPA)
 Policy Plan Amendment: With the implementation of Mitigation Measure NOI-3-PPA and TOP 2050 policies, impacts to future sensitive receptors from excessive airportrelated noise from operations at the Ontario International Airport (ONT) would be reduced to comply with interior noise level thresholds of 45 dBA CNEL or less. While interior noise levels are required to achieve the interior noise limits of the California Building Standards, Title 24 and Title 25 of the California Code of Regulations, exterior noise levels may continue to exceed the noise compatibility criteria for the City. Consequently, airport noise compatibility impacts of the proposed project would remain significant and unavoidable. It should be noted that the identification of this program-level impact does not preclude the finding of less-than-significant impacts for subsequent projects analyzed at the project level.

Transportation
Impact TRA-2 (PPA + EBPSP)
 Policy Plan Amendment: The proposed project would increase vehicle miles traveled per service population (VMT/SP) and total VMT compared to the approved project.

Mitigation Measure TRA-1-PPA would reduce potential impacts of future development projects to the extent feasible. Future development projects consistent with the proposed project would need to consider transportation demand management (TDM) measures consistent with those identified in the Mobility Element. TDM techniques include incentives to use transit; incentives to form carpools rather than drive alone; and making home, work, and shopping closer 4217
Ontario Policy Plan Amendment SEIR
CEQA Statement of Overriding Considerations
- 12 -
together to shorten travel distances. Project-level and cumulative VMT impacts under the proposed project would remain. Therefore, the impact would be significant and unavoidable.
 EBPSP: VMT/SP and total VMT would increase under the EBPSP. Mitigation Measure TRA-1-SP would reduce commute-related VMT by 7.2 percent. However, the City’s significance standard considers all trip types and does not isolate commute-related trips. Therefore, the 7.2 percent reduction applies only to a portion of the EBPSP’s total VMT and is not sufficient to fully mitigate the overall impact. Project-level and cumulative VMT impacts under the EBPSP would remain. Therefore, the impact would be significant and unavoidable.

PROJECT BENEFITS IN SUPPORT OF THE STATEMENT OF

OVERRIDING CONSIDERATIONS
This section describes the benefits of the proposed project that outweigh the project’s unavoidable adverse effects and provides specific reasons for considering the project acceptable even though the Final SEIR indicated 14 significant project impacts that cannot be mitigated to less than significant. Pursuant to CEQA Guidelines Section15093(c), this statement of overriding considerations will be included in the record of the project approval and will also be noted in the Notice of Determination.

Each of the benefits identified below provides a separate and independent basis for overriding the significant environmental effects of the proposed project.

Having reduced the potential effects of the proposed project through all feasible mitigation measures, as described previously, and balancing the benefits of the proposed project against its potential unavoidable adverse impacts on air quality, cultural resources, greenhouse gas emissions, noise, and transportation, the City finds that the following legal requirements and benefits of the proposed project individually and collectively outweigh the potentially significant unavoidable adverse impacts.

1. IMPLEMENTS THE OBJECTIVES ESTABLISHED FOR THE PROPOSED

PROJECT
The proposed project would implement and advance numerous long-range planning, housing, infrastructure, mobility, economic development, and public policy objectives established by the TOP 2050, the EBPSP, the Housing Element, and related City planning documents. The City finds that implementation of these objectives constitutes a substantial public benefit because the project establishes a coordinated framework for future development, infrastructure delivery, mobility planning, open space preservation, and economic activity within southern Ontario.
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Policy Plan Amendment
 Comprehensively plan for and assess land use changes requested by property owners while ensuring compliance with state laws and maintaining the vision and objectives of current TOP 2050.
 Reposition the planned employment center in southwest Ontario from a mix of office, retail, and residential uses to a concentration of business park uses.  Ensure there is no net loss in overall housing capacity within the City, consistent with the requirements of state law.
 Plan for adequate housing capacity to ensure the City continues to meet the requirements of the City’s sixth-cycle RHNA obligation.  Update the City’s truck routes based on proposed land use changes to ensure the City continues to comply with state law and ensures a safe and efficient goods movement network while minimizing the exposure of existing and future sensitive receptors to noise, vibration, and air pollution generated by heavy trucks.  Update the Policy Plan component of TOP 2050 for internal consistency with proposed land use and circulation changes.

Specific Plan
 To provide a land use plan that implements The Ontario Plan’s vision and appropriately positions business park and public parkland uses north of Eucalyptus Avenue, between Campus Avenue and Walker Avenue.
 To facilitate the development of a variety of employment-generating uses in a business park setting.
 To provide business park uses that are compatible with surrounding land uses.  To provide opportunities for positive economic benefit to the City, including new net revenues to the General Fund that can be used for vital City services.  To provide opportunities for the development of passive use parks consistent with the City of Ontario’s Grand Park Master Plan.
 To provide landscaped open space within the Specific Plan area, including pedestrian trails adjacent to public arterial and collector streets.  To improve connectivity in the area by providing pedestrian paths, bicycle routes, and comfort amenities such as bike racks that encourage circulation by means not dependent on a motorized vehicle.
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 To identify and construct capital improvements for water, recycled water, sewer, storm drain, and circulation facilities that serve planned land uses within and adjacent to the Specific Plan area.
 To set forth a development phasing sequence that allows for logical development and aligns with installation of on-site and off-site infrastructure.  To define guidelines and standards that provide a cohesive design for architecture, landscaping, streetscapes, entry monuments, corner treatments, walls and fencing, lighting, and signage within the Specific Plan area.

The City finds that implementation of these planning, housing, mobility, infrastructure, economic development, open space, and urban design objectives constitutes substantial public benefits that outweigh the project’s significant and unavoidable environmental impacts.

2. PROVIDES HIGH-DENSITY HOUSING THAT HELPS EXCEED THE CITY’S

REGIONAL HOUSING NEEDS
The proposed project would provide substantial public benefits by accommodating an estimated population increase of approximately 16,472 people and facilitating the development of approximately 7,226 additional housing units compared to the approved project. (See Table C-7a and Table C-11a, Appendix C, Buildout Methodology).

The additional residential capacity would advance state and regional housing objectives by increasing the supply and diversity of housing opportunities within the City, including housing types needed to serve existing and projected population growth and workforce demand. The approved project exceeds SCAG’s regional housing needs forecasts for Ontario, and therefore the increase in population, housing, and employment as part of the proposed project would also exceed SCAG’s regional forecast for the city. The proposed project would comply with SB 330 and SB 166, and there would be no net loss of residential units in the city with implementation of the proposed project. The proposed project would align jobs with the current employment market. The City finds that the project’s contribution toward expanding housing supply, accommodating population growth, supporting workforce housing needs, and implementing broader state housing policies constitutes a substantial public benefit that outweighs the project’s significant and unavoidable environmental impacts.

3. COMPLIES WITH CURRENT LEGISLATION
The City finds that the proposed project would provide substantial public benefits by implementing and advancing multiple state housing, land use, and goods movement policies enacted to address California’s housing shortage, preserve residential development capacity, and reduce land use conflicts associated with truck traffic. 4220
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SB 330 (No Net-Loss Provisions)
If any proposed rezonings convert land from uses that allow housing to uses that do not allow housing, the City must offset this by concurrently upzoning another property elsewhere to prevent a net loss of housing capacity. Since some of the requested changes would reduce potential housing buildout, the overall amendments include additional land use changes specifically for this offset. To comply with state law, the Housing Element requires updates to TOP housing sites inventory to reflect changes in the list of sites suitable to fulfill the City’s Regional Housing Needs Allocation (RHNA).

The proposed land use changes result in a net gain in housing capacity, increasing the estimated number of allowed units from 129,951 units under TOP 2050 to 137,177 units under the proposed project, an increase of 5.6 percent, meeting the requirements of SB 330. This increase in housing capacity constitutes a substantial public benefit because it expands opportunities for future residential development, supports implementation of state housing policy, and preserves the City’s long-term ability to accommodate population and workforce growth.

SB 166 (Affordable Housing Sites)
Th proposed project would also preserve the City’s ability to satisfy RHNA obligations by maintaining an adequate inventory of appropriately zoned housing sites for lower- and moderate-income residential development. Where land use changes affect properties currently identified in the Housing Element inventory, the proposed project upzones several sites to meet the City’s RHNA obligation. The RHNA strategy relies on a combination of new sites that already had suitable zoning; updated affordability assumptions on existing sites that reflect changes since the element was certified, such as a more current understanding of how the city expects infrastructure to develop in Ontario Ranch and a new 100 percent affordable project that was entitled on Holt Boulevard; and upzoning proposed as part of the project.

The following upzoning statistics include only properties that are identified in the Proposed Housing Element Sites Inventory, that include a land use change as part of the project, and that provide additional housing capacity as a result of the proposed land use change. Upzoning included 76 sites totaling 493 acres across the Holt Boulevard and Ontario Ranch strategy areas. Within the Holt Boulevard strategy area, 9 sites totaling 10 acres were redesignated from Business Park (BP) to Mixed-Use, Holt (MU-HE). Within Ontario Ranch, 67 sites totaling 484 acres were redesignated to allow increased residential density and mixed-use development, including 4 sites totaling 31 acres redesignated from Low Density Residential (LDR) to High Density Residential (HDR); 21 sites totaling 162 acres redesignated from Low Density Residential (LDR) to Medium Density Residential (MDR); 3 sites totaling 30 acres redesignated from Low Density Residential (LDR) to Mixed-Use, Sports Park (MU-SP); 3 sites totaling 17 acres redesignated from Low Medium Density Residential (LMDR) to Medium Density Residential (MDR); 29 sites totaling 209 acres redesignated from Medium Density 4221
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Residential (MDR) to High Density Residential (HDR); 1 site totaling 9 acres redesignated from Medium Density Residential (MDR) to Mixed-Use, Sports Park (MU-SP); 2 sites totaling 9 acres redesignated from Neighborhood Commercial (NC) to Mixed-Use, Sports Park (MU-SP); and 4 sites totaling 18 acres redesignated from Open Space–Parkland (OSR) to Medium Density Residential (MDR). Maintaining sufficient housing opportunity sites to accommodate current and future RHNA obligations is a substantial public benefit that directly advances statewide housing priorities and supports the provision of future affordable and workforce housing opportunities within the City.

AB 98 (Truck Routes)
The proposed project would also result in changes to the truck routes map to address the requirements of AB 98. The intent of AB 98 is to improve community health and the environment by strategizing how and where heavy-duty trucks travel to and from logistics and warehousing facilities. The primary direction of state law is to prioritize routes that maximize the use of freeways or state highways, then larger local roads (arterial and collector roadways). Changes to the City’s truck routes are to avoid, when possible, routing trucks through residential areas and near concentrations of other sensitive uses (such as schools, hospitals, and parks).

In summer 2025, the City conducted outreach and initiated evaluation of its existing truck routes, which resulted in changes to the truck routes in northern Ontario in the Original Model Colony (OMC). The City received comments regarding heavy truck traffic passing residential areas, especially along Ontario Ranch Road and Archibald Avenue.

Specific issues identified by the public regarding truck travel include noise, vibration, and air quality impacts on homes and schools; safety concerns for pedestrians and cyclists; road damage from heavy vehicles; and the need for better enforcement of truck routes.

Based on feedback from the public, the City identified four truck routes concepts for Ontario Ranch. Figure 2-9, Proposed Truck Routes, in the SEIR identifies the truck routes proposed by the City to move forward for the Policy Plan Amendment and to address the requirements of AB 98. The changes to the truck route map would be made to minimize the number of existing and proposed sensitive receptors adjacent to the truck routes. Factors that were considered included:
 Direct access to a freeway interchange.
 Connection to truck routes in other jurisdictions.
 Direct service to Industrial and Business Park land uses.  Larger roads (generally 4 to 6 lanes).
 The presence of sound walls and vegetation.
 The proximity of a parallel truck route.
 Existing and future estimated truck volumes.
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 Fewer gaps in truck routes.
 Presence of existing and planned sensitive uses (e.g., residential areas, Grand Park, and schools).
 Roadway operations.

The City finds that implementation of these truck route changes would provide important public health, mobility, circulation, and land us compatibility benefits by reducing potential conflicts between heavy truck traffic and sensitive uses while supporting the efficient movement of goods within the regional transportation network.

4. TRANSPORTATION SYSTEM IMPROVEMENTS AND GOODS

MOVEMENT EFFICIENCY
The proposed project supports the implementation of updated mobility goals and policies intended to improve transportation system efficiency while minimizing impacts on sensitive land uses. As identified above, the City’s network of truck routes would be updated in compliance with AB 98 and consistent with proposed land use changes.

Minor updates to the City’s Roadway System (Figure M-01) and to multipurpose trails and bikeways, identified on TOP Figure M-02, are also proposed to reflect the City’s longterm plan for roadways and align future bike improvements with the proposed changes in the land use pattern and truck routes in southwestern Ontario. New Mobility policies and implementation actions addressing priority safety corridors consistent with SB 932 are proposed as well as a new policy promoting lower speed limits for trucks in areas adjacent to noise- and vibration-sensitive land uses. Finally, Policy M-3.1 would be expanded to note that the City would prioritize coordinating access to transit in areas near sites identified in the housing element as suitable for lower-income (in addition to Environmental Justice areas), and Policy M-4.1 would clarify that noise-sensitive land uses are intended to include both noise- and vibration-sensitive land uses.

The City finds that these transportation, mobility, circulation, safety, and land use compatibility improvements constitute substantial public benefits because they support safer and more efficient movement of people and goods, improve multimodal connectivity, reduce potential conflicts between truck traffic and sensitive receptors, and further state and local mobility, environmental justice, and infrastructure planning.

5. CREATES JOBS, PROVIDES ECONOMIC BENEFITS, AND MEETS

DEMANDS FOR BUSINESS PARK SPACE
The proposed EBPSP would provide substantial economic, employment, fiscal, and planning benefits to the City and surrounding region by establishing a comprehensive framework for future business park, infrastructure, circulation, and open space development. The EBPSP would allow development of approximately 2,939,000 square feet of Business Park uses on 137.9 acres and 36.15 acres of Open Space–Parkland. The 4223
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project would expand opportunities for employment-generating land uses within the City and help accommodate projected demand for business park and employment uses within the regional economy.

Based on the economic and fiscal analysis, , the EBPSP land uses have the potential to generate up to 1,590 jobs that can be filled by residents of the City and surrounding communities. Temporary construction and long-term operational jobs created by the EBPSP would result in increased spending throughout the region, including in the City of Ontario. It is anticipated that annual personal earnings would increase through the generation of new jobs, and these earnings would ripple through the local and regional economy, creating a one-time increase in output and earnings associated with construction jobs and an on-going increase in output and earnings associated with permanent jobs.

The proposed project establishes the necessary land use plan, development standards, design guidelines, infrastructure systems, and implementation strategies on which subsequent, related development activities would be founded. The proposed EBPSP would improve connectivity in the area by providing pedestrian paths, bicycle routes, and comfort amenities such as bike racks that encourage circulation by means not dependent on a motorized vehicle; define guidelines and standards that provide a cohesive design for architecture, landscaping, streetscapes, entry monuments, corner treatments, walls and fencing, lighting, and signage within the Specific Plan area; and provide opportunities for positive economic benefit to the City, including new net revenues to the General Fund that can be used for vital City services such as police and fire protection, infrastructure maintenance, and parks.

In addition, the Fiscal Impact Study prepared for the project concludes that the EBPSP is anticipated to generate an annual fiscal surplus of approximately $530,000 for the benefit of the City. These revenues may be used to support important municipal services and infrastructure, including police and fire protection, roadway and infrastructure maintenance, parks, and other public facilities and services.

The City finds that the employment, economic, fiscal, infrastructure, mobility, and planning benefits associated with the EBPSP constitute substantial public benefits that outweigh the project’s significant and unavoidable environmental impacts.

6. IMPLEMENTATION OF LONG-RANGE PLANNING AND POLICY

CONSISTENCY
The Policy Plan Amendment advances the City’s TOP 2050 vision by comprehensively updating the TOP land use framework, zoning regulations, and implementing development standards across more than 1,300 acres in southern Ontario. The proposed amendments are intended to improve the coordination of land uses, infrastructure 4224
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planning, mobility systems, goods movement networks, and employment-generating uses in a manner that reflects changing development conditions, evolving state requirements, and the City’s long-term planning goals.

The proposed project would facilitate a more cohesive and internally consistent land use pattern by updating the Policy Plan, zoning map, development code, truck route network, and related implementation policies to better align planned land uses with circulation systems, infrastructure planning, environmental considerations, housing obligations, and economic development objectives. The project also incorporates land use and policy changes intended to improve compatibility between residential neighborhoods, employment areas, goods movement corridors, and sensitive land uses.

In addition, the proposed project would support compliance with evolving state housing, mobility, environmental legislation, including requirements related to housing capacity, truck routing, safety planning, and multimodal transportation. By integrating these updates into a coordinated planning framework, the project would support a more efficient, orderly, and predictable long-term development within the City and reduce the potential for fragmented or inconsistent land use planning decisions.

Ontario City CouncilJune 16, 2026

Ontario City Council
June 16, 2026