Agenda, regular meeting, second session — San Bruno City Council, January 24, 2023 (part 5 of 8)

Table 1: Racial Isolation Index Values for Segregation within San Bruno San Bruno Bay Area
Average
Race 2000 2010 2020 2020
Asian/Pacific Islander 0.239 0.315 0.369 0.245
Black/African American 0.025 0.024 0.019 0.053
Latinx 0.322 0.378 0.355 0.251
White 0.518 0.414 0.340 0.491
Universe: Population.

Source: IPUMS National Historical Geographic Information System (NHGIS). U.S. Census Bureau, 2020 Census State Redistricting Data (Public Law 94-171) Summary File, 2020 Census of Population and Housing, Table P002. Data from 2010 is from U.S. Census Bureau, Census 2010, Table P4. Data for 2000 is standardized to 2010 census tract geographies and is from U.S. Census Bureau, Census 2000, Table P004.

Figure 2 below shows how racial isolation index values in San Bruno compare to values in other Bay Area jurisdictions. In this chart, each dot represents a Bay Area jurisdiction. For each racial group, the spread of dots represents the range of isolation index values among Bay Area jurisdictions.

Additionally, the black line within each racial group notes the isolation index value for that group in City of San Bruno, and each dashed red line represents the Bay Area average for the isolation index for that group. Local staff can use this chart to contextualize how segregation levels for racial groups in their jurisdiction compare to other jurisdictions in the region.

10 This average only includes the 104 jurisdictions that have more than one census tract, which is true for all comparisons of Bay Area jurisdictions’ segregation measures in this report. The segregation measures in this report are calculated by comparing the demographics of a jurisdiction’s census tracts to the jurisdiction’s demographics, and such calculations cannot be made for the five jurisdictions with only one census tract (Brisbane, Calistoga, Portola Valley, Rio Vista, and Yountville).
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11 Figure 2: Racial Isolation Index Values for San Bruno Compared to Other Bay Area Jurisdictions (2020)
Universe: Bay Area Jurisdictions.

Another way to measure segregation is by using a dissimilarity index:
• This index measures how evenly any two groups are distributed across neighborhoods relative to their representation in a city overall. The dissimilarity index at the jurisdiction level can be interpreted as the share of one group that would have to move neighborhoods to create perfect integration for these two groups.
• The dissimilarity index ranges from 0 to 1. Higher values indicate that groups are more unevenly distributed (e.g. they tend to live in different neighborhoods). 1111 of 1863
12 Dissimilarity Index Guidance for Cities with Small Racial Group Populations The analysis conducted for this report suggests that dissimilarity index values are unreliable for a population group if that group represents approximately less than 5% of the jurisdiction’s total population.

HCD’s AFFH guidance requires the Housing Element to include the dissimilarity index values for racial groups, but also offers flexibility in emphasizing the importance of various measures. ABAG/MTC recommends that when cities have population groups that are less than 5% of the jurisdiction’s population (see Table 4), jurisdiction staff use the isolation index or Thiel’s H-Index to gain a more accurate understanding of their jurisdiction’s neighborhood-level segregation patterns (intra-city segregation).

If a jurisdiction has a very small population of a racial group, this indicates that segregation between the jurisdiction and the region (inter-city segregation) is likely to be an important feature of the jurisdiction’s segregation patterns.

In City of San Bruno, the Black/African American group is 1.6 percent of the population - so staff should be aware of this small population size when evaluating dissimilarity index values involving this group.

Table 2 below provides the dissimilarity index values indicating the level of segregation in San Bruno between white residents and residents who are Black, Latinx, or Asian/Pacific Islander. The table also provides the dissimilarity index between white residents and all residents of color in the jurisdiction, and all dissimilarity index values are shown across three time periods (2000, 2010, and 2020).

In San Bruno the highest segregation is between Latinx and white residents (see Table 2). San Bruno’s Latinx /white dissimilarity index of 0.362 means that 36.2% of Latinx (or white) residents would need to move to a different neighborhood to create perfect integration between Latinx residents and white residents.

The “Bay Area Average” column in this table provides the average dissimilarity index values for these racial group pairings across Bay Area jurisdictions in 2020. The data in this column can be used as a comparison to provide context for the levels of segregation between communities of color are from white residents in this jurisdiction.
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13 For example, Table 2 indicates that the average Latinx/white dissimilarity index for a Bay Area jurisdiction is 0.207, so on average 20.7% of Latinx (or white residents) in a Bay Area jurisdiction would need to move to a different neighborhood within the jurisdiction to create perfect integration between Latinx and white residents in that jurisdiction.

Table 2: Racial Dissimilarity Index Values for Segregation within San Bruno San Bruno Bay Area
Average
Race 2000 2010 2020 2020
Asian/Pacific Islander vs. White 0.244 0.252 0.229 0.185 Black/African American vs. White 0.279* 0.252* 0.269* 0.244 Latinx vs. White 0.378 0.383 0.362 0.207
People of Color vs. White 0.259 0.262 0.241 0.168
Universe: Population.

Source: IPUMS National Historical Geographic Information System (NHGIS). U.S. Census Bureau, 2020 Census State Redistricting Data (Public Law 94-171) Summary File, 2020 Census of Population and Housing, Table P002. Data from 2010 is from U.S. Census Bureau, Census 2010, Table P4. Data for 2000 is standardized to 2010 census tract geographies and is from U.S. Census Bureau, Census 2000, Table P004.

Note: If a number is marked with an asterisk (*), it indicates that the index is based on a racial group making up less than 5 percent of the jurisdiction population, leading to unreliable numbers.

Figure 3 below shows how dissimilarity index values in City of San Bruno compare to values in other Bay Area jurisdictions. In this chart, each dot represents a Bay Area jurisdiction. For each racial group pairing, the spread of dots represents the range of dissimilarity index values among Bay Area jurisdictions. Additionally, the black line within each racial group pairing notes the dissimilarity index value in San Bruno, and each dashed red line represents the Bay Area average for the dissimilarity index for that pairing. Similar to Figure 2, local staff can use this chart to contextualize how segregation levels between white residents and communities of color in their jurisdiction compare to the rest of the region. However, staff should be mindful of whether a racial group in their jurisdiction has a small population (approximately less than 5% of the jurisdiction’s population), as the dissimilarity index value is less reliable for small populations.
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14 Figure 3: Racial Dissimilarity Index Values for San Bruno Compared to Other Bay Area Jurisdictions (2020)
Universe: Bay Area Jurisdictions.

Note: The analysis conducted for this report suggests that dissimilarity index values are unreliable for a population group if that group represents approximately less than 5% of the jurisdiction’s total population. ABAG/MTC recommends that when cities have population groups that are less than 5% of the jurisdiction’s population (see Table 4), jurisdiction staff could focus on the isolation index or Thiel’s H-Index to gain a more accurate understanding of neighborhood-level racial segregation in their jurisdiction.

The Theil’s H Index can be used to measure segregation between all groups within a jurisdiction:
• This index measures how diverse each neighborhood is compared to the diversity of the whole city. Neighborhoods are weighted by their size, so that larger neighborhoods play a more significant role in determining the total measure of segregation. • The index ranges from 0 to 1. A Theil’s H Index value of 0 would mean all neighborhoods within a city have the same demographics as the whole city. A value of 1 would mean each group lives exclusively in their own, separate neighborhood.
• For jurisdictions with a high degree of diversity (multiple racial groups comprise more than 10% of the population), Theil’s H offers the clearest summary of overall segregation.

The Theil’s H Index values for neighborhood racial segregation in San Bruno for the years 2000, 2010, and 2020 can be found in Table 3 below. The “Bay Area Average” column in the table provides the average Theil’s H Index across Bay Area jurisdictions in 2020. Between 2010 and 2020, the Theil’s H Index for racial segregation in San Bruno declined, suggesting that there is now less neighborhood level racial segregation within the jurisdiction. In 2020, the Theil’s H Index for racial segregation in San 1114 of 1863
15 Bruno was higher than the average value for Bay Area jurisdictions, indicating that neighborhood level racial segregation in San Bruno is more than in the average Bay Area city.

Table 3: Theil’s H Index Values for Racial Segregation within San Bruno San Bruno Bay Area
Average
Index 2000 2010 2020 2020
Theil's H Multi-racial 0.063 0.065 0.054 0.042
Universe: Population.

Source: IPUMS National Historical Geographic Information System (NHGIS). U.S. Census Bureau, 2020 Census State Redistricting Data (Public Law 94-171) Summary File, 2020 Census of Population and Housing, Table P002. Data from 2010 is from U.S. Census Bureau, Census 2010, Table P4. Data for 2000 is standardized to 2010 census tract geographies and is from U.S. Census Bureau, Census 2000, Table P004.

Figure 4 below shows how Theil’s H index values for racial segregation in San Bruno compare to values in other Bay Area jurisdictions in 2020. In this chart, each dot represents a Bay Area jurisdiction.

Additionally, the black line notes the Theil’s H index value for neighborhood racial segregation in San Bruno, and the dashed red line represents the average Theil’s H index value across Bay Area jurisdictions. Local staff can use this chart to compare how neighborhood racial segregation levels in their jurisdiction compare to other jurisdictions in the region.

Figure 4: Theil’s H Index Values for Racial Segregation in San Bruno Compared to Other Bay Area Jurisdictions (2020)
Universe: Bay Area Jurisdictions.

Source: IPUMS National Historical Geographic Information System (NHGIS). U.S. Census Bureau, 2020 Census State Redistricting Data (Public Law 94-171) Summary File, 2020 Census of Population and Housing, Table P002. 1115 of 1863
16 2.2 Regional Racial Segregation (between San Bruno and other jurisdictions)
At the regional level, segregation is measured between cities instead of between neighborhoods. Racial dot maps are not only useful for examining neighborhood racial segregation within a jurisdiction, but these maps can also be used to explore the racial demographic differences between different jurisdictions in the region. Figure 5 below presents a racial dot map showing the spatial distribution of racial groups in San Bruno as well as in nearby Bay Area cities.

Figure 5: Racial Dot Map of San Bruno and Surrounding Areas (2020) Universe: Population.

Source: U.S. Census Bureau, 2020 Census State Redistricting Data (Public Law 94-171) Summary File, 2020 Census of Population and Housing, Table P002.

Note: The plot shows the racial distribution at the census block level for City of San Bruno and vicinity. Dots in each census block are randomly placed and should not be construed as actual placement of people.

To understand how each city contributes to the total segregation of the Bay Area, one can look at the difference in the racial composition of a jurisdiction compared to the racial composition of the region as a whole. The racial demographics in San Bruno for the years 2000, 2010, and 2020 can be found in Table 4 below. The table also provides the racial composition of the nine-county Bay Area. As of 2020, San Bruno has a lower share of white residents than the Bay Area as a whole, a higher share of Latinx residents, a lower share of Black residents, and a higher share of Asian/Pacific Islander residents. 1116 of 1863
17 Table 4: Population by Racial Group, San Bruno and the Region San Bruno Bay Area
Race 2000 2010 2020 2020
Asian/Pacific Islander 18.4% 28.1% 34.3% 28.2%
Black/African American 1.9% 2.0% 1.6% 5.6%
Latinx 24.1% 29.2% 28.0% 24.4%
Other or Multiple Races 8.7% 4.6% 6.6% 5.9%
White 46.9% 36.0% 29.6% 35.8%
Universe: Population.

Source: IPUMS National Historical Geographic Information System (NHGIS). U.S. Census Bureau, 2020 Census State Redistricting Data (Public Law 94-171) Summary File, 2020 Census of Population and Housing, Table P002. Data from 2010 is from U.S. Census Bureau, Census 2010, Table P4. Data for 2000 is standardized to 2010 census tract geographies and is from U.S. Census Bureau, Census 2000, Table P004.

Figure 6 below compares the racial demographics in San Bruno to those of all 109 Bay Area jurisdictions.11 In this chart, each dot represents a Bay Area jurisdiction. For each racial group, the spread of dots represents the range of that group’s representation among Bay Area jurisdictions.

Additionally, the black line within each racial group notes the percentage of the population of City of San Bruno represented by that group and how that percentage ranks among all 109 jurisdictions. Local staff can use this chart to compare the representation of different racial groups in their jurisdiction to those groups’ representation in other jurisdictions in the region, which can indicate the extent of segregation between this jurisdiction and the region.

11 While comparisons of segregation measures are made only using the 104 jurisdictions with more than one census tract, this comparison of jurisdiction level demographic data can be made using all 109 jurisdictions. 1117 of 1863
18 Figure 6: Racial Demographics of San Bruno Compared to All Bay Area Jurisdictions (2020)
Universe: Bay Area Jurisdictions.

Source U.S. Census Bureau, 2020 Census State Redistricting Data (Public Law 94-171) Summary File, 2020 Census of Population and Housing, Table P002.

The map in Figure 7 below also illustrates regional racial segregation between San Bruno and other jurisdictions. This map demonstrates how the percentage of people of color in San Bruno and surrounding jurisdictions compares to the Bay Area as a whole:
• Jurisdictions shaded orange have a share of people of color that is less than the Bay Area as a whole, and the degree of difference is greater than five percentage points. • Jurisdictions shaded white have a share of people of color comparable to the regional percentage of people of color (within five percentage points). • Jurisdictions shaded grey have a share of people of color that is more than five percentage points greater than the regional percentage of people of color. 1118 of 1863
19 Figure 7: Comparing the Share of People of Color in San Bruno and Vicinity to the Bay Area (2020)
Universe: Population.

Source: U.S. Census Bureau, 2020 Census State Redistricting Data (Public Law 94-171) Summary File, 2020 Census of Population and Housing, Table P002.

Note: People of color refer to persons not identifying as non-Hispanic white. The nine-county Bay Area is the reference region for this map.

Segregation between jurisdictions in the region can also be analyzed by calculating regional values for the segregation indices discussed previously. Table 5 presents dissimilarity index, isolation index, and Theil’s H index values for racial segregation for the entire nine-county Bay Area in 2010 and 2020. In the previous section of this report focused on neighborhood level racial segregation, these indices were calculated by comparing the racial demographics of the census tracts within a jurisdiction to the demographics of the jurisdiction as a whole. In Table 5, these measures are calculated by comparing the racial demographics of local jurisdictions to the region’s racial makeup. For example, looking at the 2020 data, Table 5 shows the white isolation index value for the region is 0.429, meaning that on average white Bay Area residents live in a jurisdiction that is 42.9% white in 2020. An example of regional dissimilarity index values in Table 5 is the Black/white dissimilarity index value of 0.459, which means that across the region 45.9% of Black (or white) residents would need to move to a different jurisdiction to evenly distribute Black and white residents across Bay Area jurisdictions. The dissimilarity index values in Table 5 reflect recommendations made in HCD’s AFFH guidance for calculating dissimilarity at the region level.12 The regional value for the Theil’s H index measures how

12 For more information on HCD’s recommendations regarding data considerations for analyzing integration and segregation patterns, see page 31 of the AFFH Guidance Memo. 1119 of 1863
20 diverse each Bay Area jurisdiction is compared to the racial diversity of the whole region. A Theil’s H Index value of 0 would mean all jurisdictions within the Bay Area have the same racial demographics as the entire region, while a value of 1 would mean each racial group lives exclusively in their own separate jurisdiction. The regional Theil’s H index value for racial segregation decreased slightly between 2010 and 2020, meaning that racial groups in the Bay Area are now slightly less separated by the borders between jurisdictions.

Table 5: Regional Racial Segregation Measures
Index Group 2010 2020
Isolation Index Regional Level
Asian/Pacific Islander 0.317 0.378
Black/African American 0.144 0.118
Latinx 0.283 0.291
White 0.496 0.429
People of Color 0.629 0.682
Dissimilarity Index Regional Level
Asian/Pacific Islander vs. White 0.384 0.369
Black/African American vs. White 0.475 0.459
Latinx vs. White 0.301 0.297
People of Color vs. White 0.296 0.293
Theil's H Multi-racial All Racial Groups 0.103 0.097
Universe: Population.

Source: IPUMS National Historical Geographic Information System (NHGIS). U.S. Census Bureau, 2020 Census State Redistricting Data (Public Law 94-171) Summary File, 2020 Census of Population and Housing, Table P002. Data from 2010 is from U.S. Census Bureau, 2010 Census of Population and Housing, Table P4. 1120 of 1863
21 3 INCOME SEGREGATION IN CITY OF SAN BRUNO
Definition of Terms - Income Groups
When analyzing segregation by income, this report uses income group designations consistent with the Regional Housing Needs Allocation and the Housing Element:

Very low-income: individuals earning less than 50% of Area Median Income (AMI)
Low-income: individuals earning 50%-80% of AMI
Moderate-income: individuals earning 80%-120% of AMI
Above moderate-income: individuals earning 120% or more of AMI Additionally, this report uses the term “lower-income” to refer to all people who earn less than 80% of AMI, which includes both low-income and very low-income individuals.

The income groups described above are based on U.S. Department of Housing and Urban Development (HUD) calculations for AMI. HUD calculates the AMI for different metropolitan areas, and the nine county Bay Area includes the following metropolitan areas: Napa Metro Area (Napa County), Oakland-Fremont Metro Area (Alameda and Contra Costa Counties), San Francisco Metro Area (Marin, San Francisco, and San Mateo Counties), San Jose-Sunnyvale-Santa Clara Metro Area (Santa Clara County), Santa Rosa Metro Area (Sonoma County), and VallejoFairfield Metro Area (Solano County).

The income categories used in this report are based on the AMI for the HUD metro area where this jurisdiction is located.

3.1 Neighborhood Level Income Segregation (within San Bruno) Income segregation can be measured using similar indices as racial segregation. Income dot maps, similar to the racial dot maps shown in Figures 1 and 5, are useful for visualizing segregation between multiple income groups at the same time. The income dot map of San Bruno in Figure 8 below offers a visual representation of the spatial distribution of income groups within the jurisdiction. As with the racial dot maps, when the dots show lack of a pattern or clustering, income segregation measures tend to be lower, and conversely, when clusters are apparent, the segregation measures may be higher as well.
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22 Figure 8: Income Dot Map of San Bruno (2015)
Universe: Population.

Source: U.S. Department of Housing and Urban Development, American Community Survey 5-Year 2011-2015 Low- and ModerateIncome Summary Data.

Note: The plot shows the income group distribution at the census block group level for City of San Bruno and vicinity. Dots in each block group are randomly placed and should not be construed as actual placement of individuals.

The isolation index values for all income groups in San Bruno for the years 2010 and 2015 can be found in Table 6 below.13 Above Moderate-income residents are the most isolated income group in San Bruno.

San Bruno’s isolation index of 0.296 for these residents means that the average Above Moderateincome resident in San Bruno lives in a neighborhood that is 29.6% Above Moderate-income. Among all income groups, the Above Moderate-income population’s isolation index has changed the most over time, becoming less segregated from other income groups between 2010 and 2015.

Similar to the tables presented earlier for neighborhood racial segregation, the “Bay Area Average” column in Table 6 provides the average isolation index value across Bay Area jurisdictions for different income groups in 2015. The data in this column can be used as a comparison to provide context for the levels of segregation experienced by income groups in this jurisdiction. For example, Table 6 indicates the average isolation index value for very low-income residents across Bay Area jurisdictions is 0.269,

13 This report presents data for income segregation for the years 2010 and 2015, which is different than the time periods used for racial segregation. This deviation stems from the data source recommended for income segregation calculations in HCD’s AFFH Guidelines. This data source most recently updated with data from the 2011-2015 American Community Survey 5-year estimates. For more information on HCD’s recommendations for calculating income segregation, see page 32 of HCD’s AFFH Guidelines. 1122 of 1863
23 meaning that in the average Bay Area jurisdiction a very low-income resident lives in a neighborhood that is 26.9% very low-income.

Table 6: Income Group Isolation Index Values for Segregation within San Bruno San Bruno Bay Area
Average
Income Group 2010 2015 2015
Very Low-Income (<50% AMI) 0.302 0.281 0.269
Low-Income (50%-80% AMI) 0.269 0.266 0.145
Moderate-Income (80%-120% AMI) 0.246 0.248 0.183
Above Moderate-Income (>120% AMI) 0.356 0.296 0.507
Universe: Population.

Figure 9 below shows how income group isolation index values in San Bruno compare to values in other Bay Area jurisdictions. In this chart, each dot represents a Bay Area jurisdiction. For each income group, the spread of dots represents the range of isolation index values among Bay Area jurisdictions.

Additionally, the black line within each income group notes the isolation index value for that group in San Bruno, and each dashed red line represents the Bay Area average for the isolation index for that group. Local staff can use this chart to contextualize how segregation levels for income groups in their jurisdiction compare to the rest of the region.
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24 Figure 9: Income Group Isolation Index Values for San Bruno Compared to Other Bay Area Jurisdictions (2015)
Universe: Bay Area Jurisdictions.

Source: U.S. Department of Housing and Urban Development, American Community Survey 5-Year 2011-2015 Low- and ModerateIncome Summary Data.

Table 7 below provides the dissimilarity index values indicating the level of segregation in San Bruno between residents who are lower-income (earning less than 80% of AMI) and those who are not lowerincome (earning above 80% of AMI). This data aligns with the requirements described in HCD’s AFFH Guidance Memo for identifying dissimilarity for lower-income households.14 Segregation in San Bruno between lower-income residents and residents who are not lower-income decreased between 2010 and 2015. Additionally, Table 7 shows dissimilarity index values for the level of segregation in Albany between residents who are very low-income (earning less than 50% of AMI) and those who are above moderate-income (earning above 120% of AMI). This supplementary data point provides additional nuance to an analysis of income segregation, as this index value indicates the extent to which a jurisdiction’s lowest and highest income residents live in separate neighborhoods.

Similar to other tables in this report, the “Bay Area Average” column shows the average dissimilarity index values for these income group pairings across Bay Area jurisdictions in 2015. For example, Table 7 indicates that the average dissimilarity index between lower-income residents and other residents in a Bay Area jurisdiction is 0.198, so on average 19.8% of lower-income residents in a Bay Area jurisdiction would need to move to a different neighborhood within the jurisdiction to create perfect income group integration in that jurisdiction.

14 For more information, see page 32 of HCD’s AFFH Guidance Memo. 1124 of 1863
25 In 2015, the income segregation in San Bruno between lower-income residents and other residents was higher than the average value for Bay Area jurisdictions (See Table 7). This means that the lowerincome residents are more segregated from other residents within San Bruno compared to other Jurisdictions in the region.

Table 7: Income Group Dissimilarity Index Values for Segregation within San Bruno
San Bruno Bay Area
Average
Income Group 2010 2015 2015
Below 80% AMI vs. Above 80% AMI 0.327 0.225 0.198
Below 50% AMI vs. Above 120% AMI 0.436 0.289 0.253
Universe: Population.

Figure 10 below shows how dissimilarity index values for income segregation in San Bruno compare to values in other Bay Area jurisdictions. In this chart, each dot represents a Bay Area jurisdiction. For each income group pairing, the spread of dots represents the range of dissimilarity index values among Bay Area jurisdictions. Additionally, the black line within each income group pairing notes the dissimilarity index value in San Bruno, and each dashed red line represents the Bay Area average for the dissimilarity index for that pairing. Local staff can use this chart to contextualize how segregation levels between lower-income residents and wealthier residents in their jurisdiction compared to the rest of the region.
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26 Figure 10: Income Group Dissimilarity Index Values for San Bruno Compared to Other Bay Area Jurisdictions (2015)
Universe: Bay Area Jurisdictions.

Source: U.S. Department of Housing and Urban Development, American Community Survey 5-Year 2011-2015 Low- and ModerateIncome Summary Data.

The Theil’s H Index values for neighborhood income group segregation in San Bruno for the years 2010 and 2015 can be found in Table 8 below. The “Bay Area Average” column in this table provides the average Theil’s H Index value across Bay Area jurisdictions for different income groups in 2015. By 2015, the Theil’s H Index value for income segregation in San Bruno was less than it had been in 2010.

In 2015, the Theil’s H Index value for income group segregation in San Bruno was lower than the average value for Bay Area jurisdictions, indicating there is less neighborhood level income segregation in San Bruno than in the average Bay Area city.

Table 8: Theil’s H Index Values for Income Segregation within San Bruno San Bruno Bay Area
Average
Index 2010 2015 2015
Theil's H Multi-income 0.067 0.035 0.043
Universe: Population.

Source: Data for 2015 is from U.S. Department of Housing and Urban Development, American Community Survey 5-Year 2011- 2015 Low- and Moderate-Income Summary Data. Data for 2010 is from U.S. Department of Housing and Urban Development, American Community Survey 5-Year 2006-2010 Low- and Moderate-Income Summary Data. 1126 of 1863
27 Figure 11 below shows how Theil’s H index values for income group segregation in San Bruno compare to values in other Bay Area jurisdictions in 2015. In this chart, each dot represents a Bay Area jurisdiction. Additionally, the black line notes the Theil’s H index value for income group segregation in San Bruno, and the dashed red line represents the average Theil’s H index value across Bay Area jurisdictions. Local staff can use this chart to compare how neighborhood income group segregation levels in their jurisdiction compare to other jurisdictions in the region.

Figure 11: Income Group Theil’s H Index Values for San Bruno Compared to Other Bay Area Jurisdictions (2015)
Universe: Bay Area Jurisdictions.

Source: U.S. Department of Housing and Urban Development, American Community Survey 5-Year 2011-2015 Low- and ModerateIncome Summary Data.

3.2 Regional Income Segregation (between San Bruno and other jurisdictions)
At the regional level, segregation is measured between jurisdictions instead of between neighborhoods.

Income dot maps are not only useful for examining neighborhood income segregation within a jurisdiction, but these maps can also be used to explore income demographic differences between jurisdictions in the region. Figure 12 below presents an income dot map showing the spatial distribution of income groups in San Bruno as well as in nearby Bay Area jurisdictions. 1127 of 1863
28 Figure 12: Income Dot Map of San Bruno and Surrounding Areas (2015) Universe: Population.

Source: U.S. Department of Housing and Urban Development, American Community Survey 5-Year 2011-2015 Low- and ModerateIncome Summary Data.

When looking at income segregation between jurisdictions in the Bay Area, one can examine how San Bruno differs from the region. The income demographics in San Bruno for the years 2010 and 2015 can be found in Table 9 below. The table also provides the income composition of the nine-county Bay Area in 2015. As of that year, San Bruno had a lower share of very low-income residents than the Bay Area as a whole, a higher share of low-income residents, a higher share of moderate-income residents, and a lower share of above moderate-income residents.

Table 9: Population by Income Group, San Bruno and the Region San Bruno Bay Area
Income Group 2010 2015 2015
Very Low-Income (<50% AMI) 25.12% 26.55% 28.7%
Low-Income (50%-80% AMI) 23.68% 24.57% 14.3%
Moderate-Income (80%-120% AMI) 23.36% 23.56% 17.6%
Above Moderate-Income (>120% AMI) 27.84% 25.32% 39.4%
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29 Universe: Population.

Source: Data for 2015 is from Housing U.S. Department of and Urban Development, American Community Survey 5-Year 2011- 2015 Low- and Moderate-Income Summary Data. Data for 2010 is from U.S. Department of Housing and Urban Development, American Community Survey 5-Year 2006-2010 Low- and Moderate-Income Summary Data.

Figure 13 below compares the income demographics in San Bruno to other Bay Area jurisdictions.15 Like the chart in Figure 3, each dot represents a Bay Area jurisdiction. For each income group, the spread of dots represents the range of that group’s representation among Bay Area jurisdictions. The smallest range is among jurisdictions’ moderate-income populations, while Bay Area jurisdictions vary the most in the share of their population that is above moderate-income. Additionally, the black lines within each income group note the percentage of San Bruno population represented by that group and how that percentage ranks among other jurisdictions. Local staff can use this chart to compare the representation of different income groups in their jurisdiction to those groups’ representation in other jurisdictions in the region, which can indicate the extent of segregation between this jurisdiction and the region.

Figure 13: Income Demographics of San Bruno Compared to Other Bay Area Jurisdictions (2015)
Universe: Bay Area Jurisdictions.

Source: U.S. Department of Housing and Urban Development, American Community Survey 5-Year 2011-2015 Low- and ModerateIncome Summary Data.

15 While comparisons of segregation measures are made only using the 104 jurisdictions with more than one census tract, this comparison of jurisdiction level demographic data can be made using all 109 jurisdictions. 1129 of 1863
30 Income segregation between jurisdictions in the region can also be analyzed by calculating regional values for the segregation indices discussed previously. Similar to the regional racial segregation measures shown in Table 5, Table 10 presents dissimilarity index, isolation index, and Theil’s H index values for income segregation for the entire nine-county Bay Area in 2010 and 2015. In the previous section of this report focused on neighborhood level income segregation, segregation indices were calculated by comparing the income demographics of the census tracts within a jurisdiction to the demographics of the jurisdiction as a whole. In Table 10, these measures are calculated by comparing the income demographics of local jurisdictions to the region’s income group makeup. For example, looking at 2015 data, Table 10 shows the regional isolation index value for very low-income residents is

0.315 for 2015, meaning that on average very low-income Bay Area residents live in a jurisdiction that is 31.5% very low-income. The regional dissimilarity index for lower-income residents and other residents is 0.194 in 2015, which means that across the region 19.4% of lower-income residents would need to move to a different jurisdiction to create perfect income group integration in the Bay Area as a whole. The regional value for the Theil’s H index measures how diverse each Bay Area jurisdiction is compared to the income group diversity of the whole region. A Theil’s H Index value of 0 would mean all jurisdictions within the Bay Area have the same income demographics as the entire region, while a value of 1 would mean each income group lives exclusively in their own separate jurisdiction. The regional Theil’s H index value for income segregation decreased slightly between 2010 and 2015, meaning that income groups in the Bay Area are now slightly less separated by the borders between jurisdictions.

Table 10: Regional Income Segregation Measures
Index Group 2010 2015
Isolation Index Regional Level
Very Low-Income (<50% AMI) 0.277 0.315
Low-Income (50%-80% AMI) 0.157 0.154
Moderate-Income (80%-120% AMI) 0.185 0.180
Above Moderate-Income (>120% AMI) 0.467 0.435
Dissimilarity Index Regional Level
Below 80% AMI vs. Above 80% AMI 0.186 0.194
Below 50% AMI vs. Above 120% AMI 0.238 0.248
Theil's H Multi-income All Income Groups 0.034 0.032
Universe: Population.

4.1 Segregation in City of San Bruno
• The isolation index measures the segregation of a single group, and the dissimilarity index measures segregation between two different groups. The Theil’s H-Index can be used to measure segregation between all racial or income groups across the city at once. • As of 2020, Asian residents are the most segregated compared to other racial groups in San Bruno, as measured by the isolation index. Asian residents live in neighborhoods where they are less likely to come into contact with other racial groups. • Among all racial groups, the white population’s isolation index value has changed the most over time, becoming less segregated from other racial groups between 2000 and 2020. • According to the dissimilarity index, within San Bruno the highest level of racial segregation is between Latinx and white residents.16
• According to the Theil’s H-Index, neighborhood racial segregation in San Bruno declined between 2010 and 2020. Neighborhood income segregation declined between 2010 and 2015. • Above Moderate-income residents are the most segregated compared to other income groups in San Bruno. Above Moderate-income residents live in neighborhoods where they are less likely to encounter residents of other income groups.
• Among all income groups, the Above Moderate-income population’s segregation measure has changed the most over time, becoming less segregated from other income groups between 2010 and 2015.
• According to the dissimilarity index, segregation between lower-income residents and residents who are not lower-income has decreased between 2010 and 2015. In 2015, the income segregation in San Bruno between lower-income residents and other residents was higher than the average value for Bay Area jurisdictions.

4.2 Segregation Between City of San Bruno and Other jurisdictions in the Bay Area Region
• San Bruno has a lower share of white residents than other jurisdictions in the Bay Area as a whole, a higher share of Latinx residents, a lower share of Black residents, and a higher share of Asian/Pacific Islander residents.

16 The analysis conducted for this report suggests that dissimilarity index values are unreliable for a population group if that group represents approximately less than 5% of the jurisdiction’s total population. ABAG/MTC recommends that when cities have population groups that are less than 5% of the jurisdiction’s population (see Table 15 in Appendix 2), jurisdiction staff could focus on the isolation index or Thiel’s H-Index to gain a more accurate understanding of neighborhood-level racial segregation in their jurisdiction. 1131 of 1863
32 • Regarding income groups, San Bruno has a lower share of very low-income residents than other jurisdictions in the Bay Area as a whole, a higher share of low-income residents, a higher share of moderate-income residents, and a lower share of above moderate-income residents. 1132 of 1863
33 5 APPENDIX 2: SEGREGATION DATA
Appendix 2 combines tabular data presented throughout this report into a more condensed format. This data compilation is intended to enable local jurisdiction staff and their consultants to easily reference this data and re-use the data in the Housing Element or other relevant documents/analyses.

Table 11 in this appendix combines data from Table 1, Table 2, and Table 3 in the body of the report.

Table 12 in this appendix combines data from Table 6, Table 7, and Table 8 in the body of the report.

Table 13 represents a duplication of Table 5 in the body of the report; Table 14 represents a duplication of Table 10 in the body of the report; Table 15 in this appendix represents a duplication of Table 4 in the body of the report, while Table 16 represents a duplication of Table 9 in the body of the report.

Table 11: Neighborhood Racial Segregation Levels in San Bruno San Bruno Bay Area
Average
Index Race 2000 2010 2020 2020
Isolation
Asian/Pacific Islander 0.239 0.315 0.369 0.245
Black/African American 0.025 0.024 0.019 0.053
Latinx 0.322 0.378 0.355 0.251
White 0.518 0.414 0.340 0.491
Dissimilarity
Asian/Pacific Islander vs. White 0.244 0.252 0.229 0.185 Black/African American vs. White 0.279* 0.252* 0.269* 0.244 Latinx vs. White 0.378 0.383 0.362 0.207
People of Color vs. White 0.259 0.262 0.241 0.168
Theil's H Multi-racial All 0.063 0.065 0.054 0.042
Universe: Population.

Source: IPUMS National Historical Geographic Information System (NHGIS). U.S. Census Bureau, 2020 Census State Redistricting Data (Public Law 94-171) Summary File, 2020 Census of Population and Housing, Table P002. Data from 2010 is from U.S. Census Bureau, 2010 Census of Population and Housing, Table P4. Data for 2000 is standardized to 2010 census tract geographies and is from U.S. Census Bureau, Census 2000, Table P004.

Note: If a number is marked with an asterisk (*), it indicates that the index is based on a racial group making up less than 5 percent of the jurisdiction population, leading to unreliable numbers. 1133 of 1863
34 Table 12: Neighborhood Income Segregation Levels in San Bruno San Bruno Bay Area
Average
Index Income Group 2010 2015 2015
Isolation
Very Low-Income (<50% AMI) 0.302 0.281 0.269
Low-Income (50%-80% AMI) 0.269 0.266 0.145
Moderate-Income (80%-120% AMI) 0.246 0.248 0.183
Above Moderate-Income (>120% AMI) 0.356 0.296 0.507
Dissimilarity
Below 80% AMI vs. Above 80% AMI 0.327 0.225 0.198
Below 50% AMI vs. Above 120% AMI 0.436 0.289 0.253
Theil's H Multi-racial All 0.067 0.035 0.043
Universe: Population.

Source: Income data for 2015 is from U.S. Department of Housing and Urban Development, American Community Survey 5-Year 2011-2015 Low- and Moderate-Income Summary Data. Data for 2010 is from U.S. Department of Housing and Urban Development, American Community Survey 5-Year 2006-2010 Low- and Moderate-Income Summary Data. 1134 of 1863
35 Table 13: Regional Racial Segregation Measures
Index Group 2010 2020
Isolation Index Regional Level
Asian/Pacific Islander 0.317 0.378
Black/African American 0.144 0.118
Latinx 0.283 0.291
White 0.496 0.429
People of Color 0.629 0.682
Dissimilarity Index Regional Level
Asian/Pacific Islander vs. White 0.384 0.369
Black/African American vs. White 0.475 0.459
Latinx vs. White 0.301 0.297
People of Color vs. White 0.296 0.293
Theil's H Multi-racial All Racial Groups 0.103 0.097
Universe: Population.

Table 14: Regional Income Segregation Measures
Index Group 2010 2015
Isolation Index Regional Level
Very Low-Income (<50% AMI) 0.277 0.315
Low-Income (50%-80% AMI) 0.157 0.154
Moderate-Income (80%-120% AMI) 0.185 0.180
Above Moderate-Income (>120% AMI) 0.467 0.435
Dissimilarity Index Regional Level
Below 80% AMI vs. Above 80% AMI 0.186 0.194
Below 50% AMI vs. Above 120% AMI 0.238 0.248
Theil's H Multi-income All Income Groups 0.034 0.032
Universe: Population.

Source: Data for 2015 is from U.S. Department of Housing and Urban Development, American Community Survey 5-Year 2011- 2015 Low- and Moderate-Income Summary Data. Data for 2010 is from U.S. Department of Housing and Urban Development, American Community Survey 5-Year 2006-2010 Low- and Moderate-Income Summary Data. 1135 of 1863
36 Table 15: Population by Racial Group, San Bruno and the Region San Bruno Bay Area
Race 2000 2010 2020 2020
Asian/Pacific Islander 18.41% 28.14% 34.28% 35.8%
Black/African American 1.87% 2.05% 1.59% 5.6%
Latinx 24.12% 29.23% 27.97% 28.2%
Other or Multiple Races 8.74% 4.64% 6.59% 24.4%
White 46.86% 35.95% 29.57% 5.9%
Universe: Population.

Source: IPUMS National Historical Geographic Information System (NHGIS). U.S. Census Bureau, 2020 Census State Redistricting Data (Public Law 94-171) Summary File, 2020 Census of Population and Housing, Table P002. Data from 2010 is from U.S. Census Bureau, 2010 Census of Population and Housing, Table P4. Data for 2000 is standardized to 2010 census tract geographies and is from U.S. Census Bureau, Census 2000, Table P004.

Table 16: Population by Income Group, San Bruno and the Region San Bruno Bay Area
Income Group 2010 2015 2015
Very Low-Income (<50% AMI) 25.12% 26.55% 28.7%
Low-Income (50%-80% AMI) 23.68% 24.57% 14.3%
Moderate-Income (80%-120% AMI) 23.36% 23.56% 17.6%
Above Moderate-Income (>120% AMI) 27.84% 25.32% 39.4%
Universe: Population.

66. Bayer, Patrick, Robert McMillan, and Kim S. Rueben. 2004. “What Drives Racial Segregation? New Evidence using Census Microdata,” Journal of Urban Economics 56(3): 514-535.

Burch, Traci. 2014. “The Old Jim Crow: Racial Residential Segregation and Imprisonment,” Law and Policy 36(3): 223-255.

Chetty, Raj and Nathanial Hendren. 2018. “The Impacts of Neighborhoods on Intergenerational Mobility I: Childhood Exposure Effects,” The Quarterly Journal of Economics 133(3):1107-1162 Cutler, David M., and Edward L. Glaeser. 1997. “Are ghettos good or bad?,” The Quarterly Journal of Economics 112(3): 827-72.

Lens, Michael and Paavo Monkkonen. 2016. “Do Strict Land Use Regulations Make Metropolitan Areas More Segregated by Income?,” Journal of the American Planning Association 82(1): 6–21.

Pendall, Rolf. 2000. “Local Land-Use Regulation and the Chain of Exclusion,” Journal of the American Planning Association 66(2): 125-142.

Rothstein, Richard. 2017. The Color of Law: A Forgotten History of how our Government Segregated America. New York: Liveright Publishing.

Sampson, Robert J. 2012. Great American city: Chicago and the enduring neighborhood effect.

Chicago: University of Chicago Press.

Sharkey, Patrick. 2013. Stuck in place: Urban neighborhoods and the end of progress toward racial equality. Chicago: University of Chicago Press.

Trounstine, Jessica. 2015. “Segregation and Inequality in Public Goods,” American Journal of Political Science 60(3): 709-725.

Trounstine, Jessica. 2018. Segregation by Design: Local Politics and Inequality in American Cities. New York: Cambridge University Press.
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ROOT POLICY RESEARCH RESIDENT SURVEY APPENDIX, PAGE 1
Appendix F
AFFH Resident Survey Analysis
This section reports the findings from the resident survey conducted of San Mateo County residents to support the AFFH analysis of Housing Elements. It explores residents’ housing, affordability, and neighborhood challenges and experiences with displacement and housing discrimination. The survey also asks about residents’ access to economic opportunity, captured through residents’ reported challenges with transportation, employment, and K-12 education. The survey was offered in both English and Spanish.

The resident survey was available online, in both Spanish and English, in a format accessible to screen readers, and promoted through jurisdictional communications and social media and through partner networks. A total of 2,382 residents participated.

The survey instrument included questions about residents’ current housing situation, housing, neighborhood and affordability challenges, healthy neighborhood indicators, access to opportunity, and experience with displacement and housing discrimination.

Explanation of terms. Throughout this section, several terms are used that require explanation.
 “Precariously housed” includes residents who are currently homeless or living in transitional or temporary/emergency housing, as well as residents who live with friends or family but are not themselves on the lease or property title. These residents may (or may not) make financial contributions to pay housing costs or contribute to the household in exchange for housing (e.g., childcare, healthcare services).  “Disability” indicates that the respondent or a member of the respondent’s household has a disability of some type—physical, mental, intellectual, developmental.  “Single parent” are respondents living with their children only or with their children and other adults but not a spouse/partner.
 “Tenure” in the housing industry means rentership or ownership.  “Large households” are considered those with five or more persons residing in a respective household.
 “Seriously Looked for Housing” includes touring or searching for homes or apartments, putting in applications or pursuing mortgage financing. 1138 of 1863
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Sampling note. The survey respondents do not represent a random sample of the county or jurisdictions’ population. A true random sample is a sample in which each individual in the population has an equal chance of being selected for the survey. The selfselected nature of the survey prevents the collection of a true random sample. Important insights and themes can still be gained from the survey results, however, with an understanding of the differences among resident groups and between jurisdictions and the county overall. Overall, the data provide a rich source of information about the county’s households and their experience with housing choice and access to opportunity in the communities where they live.

Jurisdiction-level data are reported for cities with 50 responses or more. Response by jurisdiction and demographics are shown in the figure below. Overall, the survey received a very strong response from typically underrepresented residents including: people of color, renters, precariously housed residents, very low income households, households with children, large households, single parents, and residents with disabilities. 1139 of 1863
ROOT POLICY RESEARCH RESIDENT SURVEY APPENDIX, PAGE 3
Figure 1.

Resident Survey Sample Sizes by Jurisdictions and Selected Characteristics Note: Numbers do not aggregate either due to multiple responses or that respondents chose not to provide a response to all demographic and socioeconomic questions.

Source: Root Policy Research from the 2021-2022 21 Elements AFFH Resident Survey.

Belmont
Total Responses 2,382 89 82 173 130 53 148 63 59 55 84 163 99 175 832 Race/Ethnicity
African American 134 5 7 4 9 8 10 6 4 4 5 14 4 17 15
Hispanic 397 7 9 14 26 27 13 8 1 8 12 59 13 31 149
Asian 500 18 9 26 43 6 32 6 8 13 14 11 19 23 249
Other Race 149 7 10 6 8 3 14 3 3 3 3 9 7 13 47
Non-Hispanic White 757 41 35 89 27 4 44 27 27 15 35 54 36 58 195 Tenure
Homeowner 1,088 39 51 96 39 9 89 26 46 18 42 37 48 58 409 Renter 1,029 40 30 65 67 36 43 28 7 33 38 105 41 88 324 Precariously Housed 309 10 8 12 26 12 17 14 5 7 13 23 16 29 87 Income
Less than $25,000 282 14 11 12 21 15 12 11 5 6 7 40 11 29 61 $25,000-$49,999 265 13 9 10 22 9 8 6 3 6 7 28 5 20 97
$50,000-$99,999 517 10 14 38 43 10 26 11 3 10 17 37 22 40 206 Above $100,000 721 38 24 69 16 8 64 12 30 14 32 31 40 40 251 Household Characteristics
Children under 18 840 38 24 53 50 26 44 17 18 20 29 61 37 64 287 Large households 284 5 7 11 20 18 8 3 5 7 8 20 13 15 133 Single Parent 240 14 8 15 19 11 12 9 3 7 7 30 9 21 49
Disability 711 28 25 41 38 22 40 22 13 17 29 62 34 65 210 Older Adults (age 65+) 736 25 27 66 37 11 54 25 25 18 33 44 32 37 248 San
Mateo
South San
Francisco
Half
Moon
Bay Hillsborough Milbrae Pacifica
Redwood
City
San
Bruno
Foster
County Brisbane Burlingame City
Daly
City
East
Palo
Alto
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Primary Findings
The survey data present a unique picture of the housing choices, challenges, needs, and access to economic opportunity of San Mateo County residents.

Top level findings from residents’ perspectives and experiences:
 The limited supply of housing that accommodates voucher holders presents several challenges. Specifically,
➢ Eight out of 10 voucher holders represented by the survey find a landlord that accepts a housing voucher to be “difficult” or “very difficult.” ➢ According to the survey data, vouchers not being enough to cover the places residents want to live is a top impediment for residents who want to move in San Mateo County, as well as for African American, Asian, and Hispanic residents, households with children under 18, single parents, older adults, households with a member experiencing a disability, and several jurisdictions.
 Low income is a barrier to accessing housing. The impacts are highest for precariously housed respondents. large households, Hispanic households, and residents in Daly City and Redwood City.
 Nearly 4 in 10 respondents who looked for housing experienced denial of housing. African American/Black respondents, single parent households, precariously housed respondents, and households with income below $50,000 reported the highest denial rates.
 1 in 5 residents have been displaced from their home in the past five years. One of the main reasons cited for displacement was the rent increased more than I could pay. African American households, single parents, households that make less than $25,000, and precariously housed respondents reported the highest rates of displacement.
 For households with children that were displaced in the past five years, 60% of children in those households have changed schools. The most common outcomes identified by households with children who have changed schools include school is more challenging, they feel less safe at the new school, and they are in a worse school.
 Nearly 1 in 5 residents reported they have experienced discrimination in the past five years. African American, single parent, and precariously housed respondents reported the highest rates of discrimination. The most common actions 1141 of 1863
ROOT POLICY RESEARCH RESIDENT SURVEY APPENDIX, PAGE 5
in response to discrimination cited by survey respondents were Nothing/I wasn’t sure what to do and Moved/found another place to live.
 Of respondents reporting a disability, about 25% report that their current housing situation does not meet their accessibility needs. The three top greatest housing needs identified by respondents included installation of grab bars in bathroom or bench in shower, supportive services to help maintain housing, and ramps.
 On average, respondents are fairly satisfied with their transportation situation. Groups with the highest proportion of respondents somewhat or not at all satisfied with their transportation options included African American, single parents, precariously housed, and Brisbane respondents.

There are some housing, affordability, and neighborhood challenges unique to specific resident groups. These include:
 Would like to move but can’t afford it—Most likely to be a challenge for Daly City, East Palo Alto, and Redwood City respondents, as well as Hispanic, renter, precariously housed, households making less than $50,000, and large household respondents.
 My house or apartment isn’t big enough for my family—Most likely to be a challenge for East Palo Alto respondents, as well as Hispanic households, large and single parent households, and households with children under 18.  I’m often late on my rent payments—Most likely to be a challenge for East Palo Alto and renter respondents, as well as households that make less than $25,000.  I can’t keep up with my utility payments—Most likely to be a challenge for East Palo Alto, Daly City, and San Mateo respondents, as well as African American and Hispanic respondents, single parent households, households with children under 18, and households that make less than $50,000.
 Bus/rail does not go where I need to go or does not operate during the times I need— Most likely to be a challenge for African American, precariously housed, single parent households, Brisbane and Pacifica respondents.  Schools in my neighborhood are poor quality—Most likely to be a challenge for East Palo Alto, Redwood City, San Bruno and South San Francisco respondents, as well as Hispanic respondents and households with children under 18. 1142 of 1863
ROOT POLICY RESEARCH RESIDENT SURVEY APPENDIX, PAGE 6
Resident Survey Findings
Of survey respondents who reported their race or ethnicity, nearly 40% of survey respondents identified as non-Hispanic White, followed by Asian (26%), Hispanic (20%), African American (7%), and Other Minority (8%) residents (Figure 2). Overall, 45% of the survey respondents were homeowners, followed by 42% of renter respondents. Thirteen percent of respondents reported they are precariously housed (Figure 3). Four in ten respondents reported having household income greater than $100,000. Nearly 30% of respondents reported a household income between $50,000-99,999, followed by 15% of respondents who made between $25,000-49,999 and 16% of respondents making less than $25,000 (Figure 4).

The survey analysis also included selected demographic characteristics of respondents, including those with children under the age of 18 residing in their household, adults over the age of 65, respondents whose household includes a member experiencing a disability, those who live in large households, and single parents. Thirty five percent of respondents indicated they had children in their household, while 31% indicated they were older adults.

Thirty percent of respondents indicated they or a member of their household experienced a disability, 12% of respondents reported having large households, and 10% were single parents (Figure 5).
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ROOT POLICY RESEARCH RESIDENT SURVEY APPENDIX, PAGE 7
Figure 2.

Survey Respondents
by Race/Ethnicity
Note:
n=1,937; 535 respondents did not
indicate their race or ethnicity.

Source:

Root Policy Research from the 2021-
2022 21 Elements AFFH Resident
Survey.

Figure 3.

Survey Respondents
by Tenure
Note:
n=2,426.

Source:

Root Policy Research from the 2021-
2022 21 Elements AFFH Resident
Survey.

Figure 4.

Survey Respondents
by Income
Note:
n=1,785.

Source:

Root Policy Research from the 2021-
2022 21 Elements AFFH Resident
Survey.
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ROOT POLICY RESEARCH RESIDENT SURVEY APPENDIX, PAGE 8
Figure 5.

Survey Respondents
by Selected
Household
Characteristics
Note:

Denominator is total responses to the
survey (n=2,382)
Source:

Root Policy Research from the 2021-
2022 21 Elements AFFH Resident
Survey.

Housing, Neighborhood and Affordability Challenges
Housing challenges: overall. Survey respondents were asked to select the housing challenges they currently experience from a list of 34 different housing, neighborhood, and affordability challenges. Figures 6a through 8c present the top 10 housing and neighborhood challenges and top 5 affordability challenges experienced by jurisdiction, race/ethnicity, tenure, income, and selected household characteristics.

These responses allow a way to compare the jurisdictions to the county for housing challenges for which other types of data do not exist. In this analysis, “above the county”—shaded in light red or pink—is defined as the proportion of responses that is 25% higher than the overall county proportion. “Below the county”—shown in light blue—occurs when the proportion of responses is 25% lower than the overall county proportion.

As shown in Figure 6a, residents in Redwood City and East Palo Alto experience several housing challenges at a higher rate than the county overall. Conversely, Foster City and Hillsborough residents experience nearly all identified housing challenges at a lower rate than the county.

Notable trends in housing, neighborhood, and affordability challenges by geographic area include:
 Residents in Daly City, East Palo Alto, and Redwood City are less likely to move due to the lack of available affordable housing options.
 East Palo Alto, Redwood City, and San Mateo residents report living in housing that is too small for their families.
 Millbrae, Belmont, and Redwood City residents report being more reticent to request a repair to their unit in fear that their landlord will raise their rent or evict them.  Nearly 1 in 5 Pacifica survey respondents report that their home or apartment is in bad condition.
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ROOT POLICY RESEARCH RESIDENT SURVEY APPENDIX, PAGE 9
 Brisbane and East Palo Alto residents are more likely to experience a landlord refusing to make repairs to their unit.
 Residents in Daly City and Millbrae are more likely to report that they don’t feel safe in their neighborhood or building.
 Half Moon Bay and East Palo Alto respondents expressed the greatest need for assistance in taking care of themselves or their home.

When compared to the county overall, the most common areas where respondents’ needs were higher than the county overall were:
 Overall, half of the jurisdictions’ respondents reported I need help taking care of myself/my home and can’t find or afford to hire someone at a higher rate than the county.  Over 40% of jurisdictions’ respondents reported a higher rate than the county for the following housing challenge: My home/apartment is in bad condition.  Nearly 40% of jurisdictions’ respondents reported a higher rate than the county for the following housing challenges: My landlord refuses to make repairs despite my requests and I don’t feel safe in my neighborhood/building.
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ROOT POLICY RESEARCH RESIDENT SURVEY APPENDIX, PAGE 10
Figure 6a.

Top 10 Housing Challenges Experienced by Jurisdiction
Source: Root Policy Research from the 2021-2022 21 Elements AFFH Resident Survey. 25% Above County average
25% Below County average
2,159 82 73 158 118 49 135 59 50 53 79 151 93 163 738
31% 27% 12% 20% 51% 41% 16% 25% 4% 32% 28% 43% 30% 38% 35% 20% 22% 11% 14% 24% 35% 10% 12% 4% 21% 11% 26% 20% 26% 21% 14% 21% 10% 13% 17% 14% 9% 10% 2% 23% 15% 20% 11% 15% 13% 11% 15% 14% 9% 15% 12% 3% 7% 0% 11% 18% 14% 5% 15% 10%
6% 6% 14% 3% 5% 12% 4% 5% 2% 2% 9% 9% 5% 10% 5%
6% 6% 5% 4% 8% 4% 5% 8% 6% 6% 3% 8% 4% 7% 5%
6% 7% 5% 5% 13% 8% 0% 7% 6% 11% 10% 8% 3% 6% 3%
5% 2% 7% 7% 7% 10% 2% 14% 2% 8% 9% 3% 4% 8% 4%
5% 10% 5% 4% 3% 16% 2% 3% 4% 6% 9% 11% 6% 4% 3%
4% 2% 5% 1% 3% 8% 11% 3% 2% 4% 5% 3% 3% 4% 2%
42% 37% 48% 50% 20% 33% 55% 44% 76% 36% 47% 28% 45% 35% 46% I have bed bugs/insects or rodent
infestation
The HOA in my neighborhood won't
let me make changes to my house
or property
None of the above
I need help taking care of
myself/my home and can't find or
afford to hire someone
South San
Milbrae Francisco
Housing or Neighborhood
Condition
Valid cases
Half
Moon
Bay Hillsborough Pacifica
Redwood
City
San
Bruno
San
County Brisbane Burlingame Mateo
I would like to move but I can't
afford anything that is
available/income too low
My house or apartment isn't big
enough for my family
Daly
City
East
Palo
Alto
Foster
City
I live too far from family/
friends/my community
I don't feel safe in my building/
neighborhood
I worry that if I request a repair it
will result in a rent increase or
eviction
My home/apartment is in bad
condition
My landlord refuses to make repairs
despite my requests
Belmont
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The following two figures segment the answers by:
 Housing affordability challenges only; and
 Neighborhood challenges only.

Housing affordability challenges. As shown in Figure 6b, residents in San Mateo, Daly City, East Palo Alto, and Pacifica experience affordability challenges at a higher rate than the county overall. Conversely, Belmont, Hillsborough, Burlingame, and South San Francisco residents experience affordability challenges at a lower rate than the county.

The most significant geographic variations occur in:
 San Mateo city residents experience all five affordability challenges at a greater rate than the county overall. In addition to being less likely to pay utility bills or rent on time, San Mateo residents are more than twice as likely than the average county respondent to have bad credit or a history of eviction/foreclosure that impacts their ability to rent.  East Palo Alto, San Mateo, and Daly City residents are most likely to experience difficulty paying utility bills.
 Residents in East Palo Alto and Redwood City are most likely to be late on their rent payments.
 Millbrae residents experience the greatest difficultly paying their property taxes among jurisdictions in San Mateo County.
 Respondents from Brisbane, Half Moon Bay, and Pacifica are also more likely to have trouble keeping up with property taxes.
 Daly City, City of San Mateo, and Redwood City respondents are more likely to have bad credit or an eviction history impacting their ability to rent.

Overall, over a third of jurisdictions’ respondents experienced the following affordability challenges at a higher rate than the county: I can’t keep up with my property taxes and I have bad credit/history of evictions/foreclosure and cannot find a place to rent. .
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Figure 6b.

Top 5 Affordability Challenges Experienced by Jurisdiction Source: Root Policy Research from the 2021-2022 21 Elements AFFH Resident Survey. 25% Above County average
25% Below County average
2,130 83 73 157 115 51 134 58 50 50 77 147 93 160 728
10% 6% 5% 6% 15% 16% 5% 12% 4% 12% 8% 12% 9% 15% 9%
8% 6% 5% 6% 10% 20% 3% 7% 2% 8% 4% 12% 4% 11% 7%
6% 2% 10% 4% 3% 2% 8% 10% 0% 16% 10% 3% 5% 9% 5%
4% 1% 4% 2% 13% 6% 0% 0% 2% 0% 5% 8% 4% 10% 2%
4% 2% 7% 3% 3% 2% 7% 3% 4% 4% 5% 3% 3% 6% 2%
73% 73% 68% 80% 65% 59% 78% 66% 88% 64% 71% 70% 77% 63% 80% I have bad credit/history of
evictions/foreclosure and cannot
find a place to rent
I have Section 8 and I am worried my
landlord will raise my rent higher
than my voucher payment
None of the above
Affordability Challenges
San
Mateo
Foster
Belmont City
South San
Francisco
Valid cases
I can't keep up with my utilities
I'm often late on my rent payments
I can't keep up with my property
taxes
Half
Moon
Bay Hillsborough Milbrae Pacifica
Redwood
City
San
County Brisbane Burlingame Bruno
Daly
City
East
Palo
Alto
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Neighborhood challenges. As shown in Figure 6c, residents in East Palo Alto, Brisbane, Daly City, and Pacifica experience neighborhood challenges at a higher rate than the county.

Burlingame and Foster City both experience neighborhood challenges at a lower rate than the county.

Hillsborough and Belmont residents report divergent experiences related to neighborhood challenges — respondents identified more challenges around neighborhood infrastructure and access to transit but fewer challenges around school quality and job opportunities.

There are a handful of jurisdictions who experience specific neighborhood challenges at a disproportionate rate compared to the county.  For instance, East Palo Alto and Belmont residents experience neighborhood infrastructure issues (e.g., bad sidewalks, no lighting) more acutely than county residents overall.  Brisbane residents experience transportation challenges in their neighborhoods.  East Palo Alto, Redwood City, San Bruno, and South San Francisco experience challenges with school quality in their neighborhoods.
 Residents in Brisbane, Hillsborough, Pacifica, Belmont, and Half Moon Bay report the highest rates of difficulty accessing public transit.
 Daly City, Millbrae, San Mateo, and East Palo Alto residents were more likely to identify the lack of job opportunities available in their neighborhoods.

Over a third of jurisdictions’ respondents experienced the following neighborhood challenges at a higher rate than the county: I can’t get to public transit/bus/light rail easily or safely. 1150 of 1863
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Figure 6c.

Top 5 Neighborhood Challenges Experienced by Jurisdiction Source: Root Policy Research from the 2021-2022 21 Elements AFFH Resident Survey. 25% Above County average
25% Below County average
2,079 80 72 153 116 48 130 56 53 46 75 145 91 151 712
17% 31% 18% 13% 25% 40% 4% 18% 23% 20% 15% 21% 14% 12% 16% 15% 6% 18% 3% 17% 25% 4% 14% 2% 7% 13% 20% 20% 15% 20%
15% 14% 24% 8% 14% 15% 21% 18% 9% 15% 24% 17% 14% 17% 10% 14% 19% 29% 7% 9% 10% 14% 18% 25% 17% 21% 12% 13% 15% 10% 12% 9% 8% 7% 20% 17% 8% 14% 0% 20% 13% 11% 11% 18% 12%
50% 41% 28% 69% 45% 33% 62% 46% 57% 50% 52% 41% 52% 52% 55% Bus/rail does not go where I need to
go or does not operate during the
times I need
I can't get to public transit/bus/light
rail easily or safely
There are not enough job
opportunities in the area
None of the above
San
Mateo
Foster
Belmont City
South San
Neighborhood Challenges Francisco
Valid cases
My neighborhood does not have good
sidewalks, walking areas, and/or
lighting
Schools in my neighborhood are poor
quality
Half
Moon
Bay Hillsborough Milbrae Pacifica
Redwood
City
San
County Brisbane Burlingame Bruno
Daly
City
East
Palo
Alto
1151 of 1863
ROOT POLICY RESEARCH RESIDENT SURVEY APPENDIX, PAGE 15
Differences in needs by race and ethnicity and housing tenure. As shown in Figure 7a, and compared to the county overall:
 African American, Hispanic, and Other Race respondents, as well as Renters and those who are precariously housed experience several housing challenges at a higher rate than the county overall.
 Conversely, non-Hispanic White residents and homeowners are less likely to experience housing challenges.

Specifically,
 Black or African American residents are more than three times as likely to have a landlord not make a repair to their unit after a request compared to county residents overall.

Renters, Hispanic, Other Race, and Precariously housed residents are also more likely to experience this challenge.
 African American, Asian, Hispanic, Renter, and Precariously Housed households are more likely to experience bed bugs or rodent infestation in their homes.  African American, Other Race, Renter, and Precariously Housed households are also more likely to live further away from family, friends, and their community.  African Americans are three times more likely than the average county respondent to be told by their HOA they cannot make changes to their house or property. Asian households are twice as likely to experience this challenge.
 Renter, Hispanic, and Other Race respondents are more likely to worry that if they request a repair it will result in a rent increase or eviction and to report that their homes are in bad condition.
1152 of 1863
ROOT POLICY RESEARCH RESIDENT SURVEY APPENDIX, PAGE 16
Figure 7a.

Top 10 Housing Challenges Experienced by Race/Ethnicity and Tenure Source: Root Policy Research from the 2021-2022 21 Elements AFFH Resident Survey. 25% Above County average
25% Below County average
2,159 132 489 392 144 734 986 974 301
31% 30% 32% 50% 31% 20% 7% 48% 56%
20% 16% 21% 35% 22% 11% 12% 29% 18%
14% 17% 13% 23% 19% 11% 2% 28% 13%
11% 12% 9% 16% 17% 10% 6% 17% 10%
6% 20% 7% 10% 10% 5% 2% 13% 10%
6% 15% 6% 6% 13% 6% 5% 8% 9%
6% 13% 6% 6% 9% 5% 4% 8% 7%
5% 14% 7% 5% 6% 5% 5% 6% 11%
5% 14% 8% 7% 5% 4% 4% 9% 9%
4% 14% 8% 4% 3% 3% 5% 3% 7%
42% 18% 37% 24% 38% 58% 68% 21% 13%
I need help taking care of myself/my home and can't find or afford to hire someone
I have bed bugs/insects or rodent infestation
The HOA in my neighborhood won't let me make changes
to my house or property
County
African
American Asian Hispanic
I would like to move but I can't afford anything that is available/income too low
Homeowner Renter
Precariously
Housing or Neighborhood Condition Housed
Valid cases
Other
Race
Non-Hispanic
White
None of the above
My house or apartment isn't big enough for my family
I worry that if I request a repair it will result in a rent increase or eviction
My home/apartment is in bad condition
My landlord refuses to make repairs despite my requests I live too far from family/ friends/my community
I don't feel safe in my building/ neighborhood
1153 of 1863
ROOT POLICY RESEARCH RESIDENT SURVEY APPENDIX, PAGE 17
The above trends are similar for the most acute housing affordability challenges. As shown in Figure 7b, African American and Hispanic households, as well as renters and those precariously housed, experience affordability challenges at a higher rate than the county overall. Non-Hispanic White residents and homeowners experience these same challenges at a lower rate than the county.
 African American residents experience all five affordability challenges at a greater rate than the county overall.
 In addition to being more likely to not pay utility bills or rent on time, African American residents are more than four times as likely than the average county respondent to have a Section 8 voucher and worry that their landlord will raise their rent more than the voucher payment.
 Along with African American residents, Hispanic households, renters, and precariously housed households are most likely to experience difficulty paying utility bills, as well as have bad credit or eviction/foreclosure history impacting their ability to find a place to rent.  These groups, with the exception of those precariously housed, are also more likely to be late on their rent payments.
1154 of 1863
ROOT POLICY RESEARCH RESIDENT SURVEY APPENDIX, PAGE 18
Figure 7b.

Top 5 Affordability Challenges Experienced by Race/Ethnicity and Tenure Source: Root Policy Research from the 2021-2022 21 Elements AFFH Resident Survey. 25% Above County average
25% Below County average
2,130 132 487 391 146 739 983 953 293
10% 22% 11% 17% 14% 5% 5% 15% 15%
8% 13% 6% 12% 12% 4% 1% 15% 8%
6% 16% 8% 4% 5% 7% 9% 5% 14%
4% 5% 3% 8% 4% 2% 1% 6% 11%
4% 18% 5% 6% 7% 2% 2% 7% 8%
None of the above 73% 32% 70% 63% 64% 83% 84% 61% 54%
County
African
American Asian Hispanic
Valid cases
I can't keep up with my utilities
I'm often late on my rent payments
I can't keep up with my property taxes
I have bad credit/history of evictions/foreclosure
and cannot find a place to rent
I have Section 8 and I am worried my landlord will
raise my rent higher than my voucher payment
Non-Hispanic
White Homeowner Renter
Precariously
Affordability Challenges Housed
Other
Race
1155 of 1863
ROOT POLICY RESEARCH RESIDENT SURVEY APPENDIX, PAGE 19
As shown in Figure 7c, African American and precariously housed residents experience neighborhood challenges at a higher rate than the county. These two groups experience neighborhood issues related to transportation more acutely than county residents overall. In addition to Other Race respondents, they are also more likely to identify the lack of job opportunities in their respective neighborhoods.

Additionally, Hispanic residents are more likely to live in neighborhoods with poor performing schools than the average county respondent. Homeowners are also more likely to report that they cannot access public transit easily or safely.
1156 of 1863
ROOT POLICY RESEARCH RESIDENT SURVEY APPENDIX, PAGE 20
Figure 7c.

Top 5 Neighborhood Challenges Experienced by Race/Ethnicity and Tenure Source: Root Policy Research from the 2021-2022 21 Elements AFFH Resident Survey. 25% Above County average
25% Below County average
2,079 133 486 389 146 737 975 918 284
17% 14% 17% 19% 16% 18% 18% 15% 18%
15% 13% 18% 20% 17% 13% 18% 13% 13%
15% 33% 16% 13% 17% 17% 17% 14% 24%
14% 24% 15% 11% 16% 16% 18% 11% 19%
12% 22% 14% 12% 19% 9% 9% 15% 20%
50% 23% 46% 48% 45% 53% 49% 51% 36%
My neighborhood does not have good sidewalks, walking
areas, and/or lighting
County
African
American Asian Hispanic Homeowner Renter
Precariously
Neighborhood Challenges Housed
Valid cases
Other
Race
NonHispanic
White
Schools in my neighborhood are poor quality
Bus/rail does not go where I need to go or does not
operate during the times I need
I can't get to public transit/bus/light rail easily or safely There are not enough job opportunities in the area
None of the above
1157 of 1863
ROOT POLICY RESEARCH RESIDENT SURVEY APPENDIX, PAGE 21
Differences in needs by household status. As shown in Figure 8a, single parents, households making less than $50,000, households with children under 18 and households with a member experiencing a disability are more likely to experience housing challenges.

Conversely, households making more than $100,000 experience nearly all specified housing challenges at a lower rate than the county.

Single parents experience all ten housing challenges at a greater rate than the county overall.

Households making less than $25,000 also experience every challenge at a higher rate, with the exception of I worry that if I request a repair it will result in a rent increase or eviction.

Households making less than $50,000, single parents, and households with children under 18 are more likely to experience the following challenges:
 My house or apartment isn’t big enough for my family;  My house or apartment is in bad condition;
 My landlord refuses to make repairs despite my request;  I live too far from family/friends/my community;
 I don’t feel safe in my building/neighborhood;
 I need help taking care of myself/my home and can’t find or afford to hire someone; and  I have bed bugs/insects or rodent infestation.

Households with a member experiencing a disability are also more likely to experience landlords refusing their requests to make repairs, living further away from family/friends/community, and not being able to find or afford someone to help take care of themselves or their homes. These households are also more likely to experience bed bugs, insects, or rodent infestation, as well as HOA restrictions impacting their ability to make changes to their home or property.

Additionally, large households have the highest proportion of respondents among the selected groups that would like to move but can’t afford anything that is available. 1158 of 1863
ROOT POLICY RESEARCH RESIDENT SURVEY APPENDIX, PAGE 22
Figure 8a.

Top 10 Housing Challenges Experienced by Income and Household Characteristics Source: Root Policy Research from the 2021-2022 21 Elements AFFH Resident Survey. 25% Above County average
25% Below County average
2,159 280 260 505 701 827 278 240 701 709
31% 47% 48% 37% 16% 35% 51% 40% 36% 25%
20% 25% 25% 23% 16% 34% 43% 32% 20% 13%
14% 16% 18% 19% 9% 19% 19% 28% 16% 11%
11% 15% 20% 12% 6% 15% 17% 17% 12% 9%
6% 13% 13% 8% 2% 9% 8% 14% 10% 6%
6% 9% 9% 6% 5% 10% 5% 10% 8% 6%
6% 9% 9% 6% 3% 8% 4% 10% 7% 5%
5% 9% 9% 5% 3% 7% 6% 12% 11% 6%
5% 10% 9% 5% 3% 9% 4% 15% 9% 6%
4% 7% 3% 4% 3% 7% 4% 11% 6% 5%
42% 21% 21% 37% 61% 28% 26% 12% 32% 49%
Above
Housing or Neighborhood Condition $100,000
Valid cases
I would like to move but I can't afford anything
that is available/income too low
My house or apartment isn't big enough for my
family
I worry that if I request a repair it will result in a
rent increase or eviction
My home/apartment is in bad condition
My landlord refuses to make repairs despite my
requests
None of the above
County
Less than
$25,000
$25,000-
$49,999
$50,000-
$99,999
I live too far from family/ friends/my community
I don't feel safe in my building/ neighborhood
I need help taking care of myself/my home and
can't find or afford to hire someone
I have bed bugs/insects or rodent infestation
The HOA in my neighborhood won't let me make
changes to my house or property
Children
under 18
Large
Households
Single
Parent Disability
Adults
(age 65+)
1159 of 1863
ROOT POLICY RESEARCH RESIDENT SURVEY APPENDIX, PAGE 23
As shown in Figure 8b, households making less than $50,000, as well as large households, single parents, households with children under 18, and households with a member experience a disability, experience the most acute affordability challenges at a higher rate than the county overall. Households making more than $50,000 and adults over the age of 65 are less likely to experience affordability challenges.

Households making between $25,000-$50,000, single parents, and households with children under 18 experience all five affordability challenges at a greater rate than the average county respondent.

Of households experiencing major affordability issues, single parent households are most acutely impacted. These households are more than three times as likely to have a Section 8 voucher and fear their landlord will raise the rent impacting the viability of their voucher, more than twice as likely to miss utility payments and have bad credit/eviction or foreclosure history impacting their ability to rent, and twice as likely to have trouble keeping up with their property taxes.
1160 of 1863
ROOT POLICY RESEARCH RESIDENT SURVEY APPENDIX, PAGE 24
Figure 8b.

Top 5 Affordability Challenges Experienced by Income and Household Characteristics Source: Root Policy Research from the 2021-2022 21 Elements AFFH Resident Survey. 25% Above County average
25% Below County average
2,130 276 260 509 703 830 279 239 699 716
10% 16% 16% 12% 3% 16% 14% 23% 15% 8%
8% 19% 16% 6% 1% 11% 12% 15% 11% 4%
6% 7% 9% 8% 5% 9% 4% 12% 8% 7%
4% 8% 7% 4% 1% 5% 6% 10% 6% 3%
4% 11% 6% 4% 1% 7% 3% 14% 8% 5%
73% 46% 56% 72% 90% 59% 70% 32% 59% 75%
Adults
(age 65+)
I have Section 8 and I am worried my landlord
will raise my rent higher than my voucher
payment
None of the above
County
Less than
$25,000
$25,000-
$49,999
$50,000-
Affordability Challenges $99,999
Valid cases
I can't keep up with my utilities
I'm often late on my rent payments
I can't keep up with my property taxes
I have bad credit/history of
evictions/foreclosure and cannot find a place
to rent
Above
$100,000
Children
under 18
Large
Households
Single
Parent Disability
1161 of 1863
ROOT POLICY RESEARCH RESIDENT SURVEY APPENDIX, PAGE 25
As shown in Figure 8c, households with children under 18, as well as single parents, households with a member experiencing a disability, and households making less than $25,000 are more likely to experience neighborhood challenges. These households are most likely to report that the bus/rail does not go where I need to go or does not operate during the times I need. In addition to households that make between $25,000-$100,000, these groups are more likely to identify the lack of job opportunities in their respective neighborhoods.

Households with children under 18 are more likely to live in neighborhoods with poor quality schools. Large households are more likely to report issues with neighborhood infrastructure (e.g., bad sidewalks, poor lighting) and households with a member experiencing a disability are more likely to report they cannot access public transit easily or safely. 1162 of 1863
ROOT POLICY RESEARCH RESIDENT SURVEY APPENDIX, PAGE 26
Figure 8c.

Top 5 Neighborhood Challenges Experienced by Income and Household Characteristics Source: Root Policy Research from the 2021-2022 21 Elements AFFH Resident Survey. 25% Above County average
25% Below County average
County
2,079 273 259 503 709 824 277 234 692 714
17% 17% 15% 18% 17% 19% 22% 16% 19% 14%
15% 17% 14% 11% 19% 24% 19% 17% 14% 9%
15% 19% 16% 15% 16% 19% 11% 28% 19% 16%
14% 15% 12% 14% 14% 15% 12% 15% 19% 17%
12% 21% 17% 16% 6% 17% 12% 19% 15% 11%
50% 40% 45% 51% 53% 38% 48% 31% 41% 53%
Above
Neighborhood Challenges $100,000
Valid cases
My neighborhood does not have good
sidewalks, walking areas, and/or lighting
Schools in my neighborhood are poor
quality
There are not enough job opportunities
in the area
None of the above
Less than
$25,000
$25,000-
$49,999
$50,000-
$99,999
Bus/rail does not go where I need to go or
does not operate during the times I need
I can't get to public transit/bus/light rail
easily or safely
Children
under 18
Large
Households
Single
Parent Disability
Adults
(age 65+)
1163 of 1863
ROOT POLICY RESEARCH RESIDENT SURVEY APPENDIX, PAGE 27
Experience Finding Housing
This section explores residents’ experience seeking a place to rent or buy in the county and the extent to which displacement—having to move when they do not want to move—is prevalent.

For those respondents who seriously looked for housing in the past five years, this section also examines the extent to which respondents were denied housing to rent or buy and the reasons why they were denied.

Recent experience seeking housing to rent. Figure 9 presents the proportion of respondents who seriously looked to rent housing for the county, jurisdictions, and selected respondent characteristics, as well as the reasons for denial.

Over half of county respondents (56%) have seriously looked for housing in the past five years.

The most common reasons for denial included:
 Landlord not returning the respondent’s call (26%),
 Landlord told me the unit was available over the phone but when I showed up in person, it was no longer available (22%), and
 Landlord told me it would cost more because of my service or emotional support animal (14%).

Jurisdictions with the highest percentage of respondents who seriously looked for housing include Millbrae (74%), San Mateo (73%), and Redwood City (72%). While all three jurisdictions reported that landlord not returning the respondent’s call was one of their main reasons for denial, 18% of Redwood City respondents identified landlord told me they do not accept Section 8 vouchers as a main reason for denial.

Among respondents by race/ethnicity, 80% of African American respondents reported that they had seriously looked for housing in the past five years while the lowest percentage of respondents who reported seriously looking for housing were non-Hispanic White (46%). The main reasons for denial experienced by African American respondents included landlord told me the unit was available over the phone but when I showed up in person, it was no longer available (39%), landlord told me it would cost more because of my service or emotional support animal (34%), and landlord told me I couldn’t have a service or emotional support animal (28%).

Among respondents by tenure, renters (75%) and precariously housed (74%) respondents reported the highest rates of seriously looking for housing.

Among respondents by income, households making less than $25,000 (71%) had the highest rate. The main reasons for denial reported by these households were landlord told me I couldn’t have a service or emotional support animal (36%) and landlord told me it would cost more because of my service or emotional support animal (30%).
1164 of 1863
ROOT POLICY RESEARCH RESIDENT SURVEY APPENDIX, PAGE 28
Single parents (79%) and households with children under 18 (66%) also reported the highest percentage of those who seriously looked for housing in the past five years among the selected household characteristics respondent groups. In addition to sharing the top two reasons for denial with the county, 25% of single parent household respondents also reported they were denied housing because the landlord told me I can’t have a service or emotional support animal. 1165 of 1863
ROOT POLICY RESEARCH RESIDENT SURVEY APPENDIX, PAGE 29
Figure 9. If you looked seriously for housing to rent in San Mateo County in the past five years, were you ever denied housing?
Note: The "Percent Seriously Looked for Housing" column includes all respondents, not just those who indicated they rent.

Source: Root Policy Research from the 2021-2022 21 Elements AFFH Resident Survey.

Jurisdiction
County 56% 26% 22% 14% 45% 928
Belmont 62% 33% 27% 31% 49
Brisbane 59% 41% 22% 26% 27
Burlingame 48% 19% 23% 54% 57
Daly City 63% 33% 16% 16% 44% 61
East Palo Alto 58% 35% 30% 26% 23
Foster City 50% 12% 16% 14% 55% 51
Half Moon Bay 68% 17% 17% 48% 29
Hillsborough 42% 14% 29% 14% 57% 14
Milbrae 74% 25% 46% 36% 28
Pacifica 51% 16% 26% 16% 55% 31
Redwood City 72% 31% 18% 40% 99
San Bruno 57% 22% 22% 39% 36
San Mateo 73% 30% 34% 39% 98
South San Francisco 47% 24% 13% 56% 248
Race/Ethnicity
African American 80% 39% 34% 28% 15% 101
Asian 56% 19% 29% 40% 199
Hispanic 63% 32% 22% 41% 230
Other Race 70% 29% 22% 45% 91
Non-Hispanic White 46% 29% 20% 48% 263
Tenure
Homeowner 36% 25% 15% 54% 183
Renter 75% 29% 22% 43% 641
Precariously Housed 74% 23% 32% 26% 188
Income
Less than $25,000 71% 30% 36% 29% 182
$25,000-$49,999 60% 39% 32% 27% 149
$50,000-$99,999 58% 24% 20% 45% 251
Above $100,000 48% 19% 14% 64% 216
Household Characteristics
Children under 18 66% 30% 29% 33% 447
Large Households 60% 33% 19% 18% 44% 139
Single Parent 79% 25% 35% 25% 19% 173
Disability 63% 24% 24% 34% 386
Older Adults (age 65+) 48% 20% 29% 39% 282
n
Overall
Percent
Seriously
Looked for
Housing
Reason for Denial
Landlord did not
return calls
and/or emails
asking about a
unit
Landlord said unit
was available over
phone, but when I
showed up in
person, it was no
longer available
Landlord told me it
would cost me
more for my
service or
emotional animal
Landlord told me
I can't have a
service or
emotional
support animal
Landlord told
me it would cost
me more to rent
because I have
children
Landlord told me
they don't rent to
families with
children
Landlord told
me they do not
accept Section 8
vouchers
Landlord told me they
couldn't make
changes to the
apartment/ home for
my disability
None
of the
Above
1166 of 1863
ROOT POLICY RESEARCH RESIDENT SURVEY APPENDIX, PAGE 30
Recent experience seeking housing to buy. Figure 10 presents the proportion of respondents who seriously looked to buy housing in the county, by jurisdiction, and selected respondent characteristics, as well as the reasons for denial. As noted above, 56% of county respondents have seriously looked for housing in the past five years.

The most common reasons for denial included:
 Real estate agent told me I would need to show I was prequalified with a bank (29%) and  A bank would not give me a loan to buy a home (23%).

For the jurisdictions with the highest percentage of respondents who seriously looked for housing (Millbrae, San Mateo and Redwood City), all three cities shared the same top two reasons for denial as the county. Additionally, 21% of Millbrae respondents reported that the real estate agent would not make a disability accommodation when I asked.

For African American respondents who looked to buy housing in the last five years, the most common reason for denial was the real estate agent would not make a disability accommodation when I asked (47%).

African Americans, along with Other Races, also most commonly reported that they needed a loan prequalification before real estate agents would work with them. While between 43-54% of respondents from other racial/ethnic groups reported they did not experience any reason for denial when seriously looking to buy housing over the past five years, 12% of African American respondents reported similarly.

Among respondents by income, the main reasons for denial for households making less than $25,000 were the real estate agent told me I would need to show I was prequalified with a bank (32%) and real estate agent only showed me or only suggested homes in neighborhoods where most people were of my same race or ethnicity (26%).

Among the selected housing characteristics category, single parent households and households with children under 18 reported shared the same top two reasons for denial as the county. Additionally, 36% of single parent household respondents reported that the real estate agent would not make a disability accommodation when I asked, as well as 25% of respondents over the age of 65.

Residents in Redwood City, Millbrae, and South San Francisco, as well as large households, also reported that a bank or other lender charged me a high interest rate on my home loan as a reason for denial. 1167 of 1863
ROOT POLICY RESEARCH RESIDENT SURVEY APPENDIX, PAGE 31
Figure 10. If you looked seriously for housing to buy in San Mateo County in the past five years, were you ever denied housing?
Note: The "Percent Seriously Looked for Housing" column includes all respondents, not just those who indicated they buy.

Source: Root Policy Research from the 2021-2022 21 Elements AFFH Resident Survey. n
Jurisdiction
County 56% 29% 23% 50% 870
Belmont 62% 21% 15% 35% 48
Brisbane 59% 36% 30% 42% 33
Burlingame 48% 22% 14% 61% 51
Daly City 63% 19% 27% 56% 52
East Palo Alto 58% 24% 33% 48% 21
Foster City 50% 25% 20% 49% 51
Half Moon Bay 68% 35% 23% 23% 50% 26
Hillsborough 42% 18% 23% 59% 22
Milbrae 74% 25% 29% 21% 21% 54% 28
Pacifica 51% 35% 35% 42% 31
Redwood City 72% 30% 22% 27% 50% 64
San Bruno 57% 14% 21% 62% 42
San Mateo 73% 40% 32% 38% 82
South San Francisco 47% 26% 18% 16% 57% 251
Race/Ethnicity
African American 80% 40% 38% 47% 12% 89
Asian 56% 30% 25% 43% 223
Hispanic 63% 29% 28% 49% 174
Other Race 70% 36% 21% 21% 50% 90
Non-Hispanic White 46% 29% 23% 54% 250
Tenure
Homeowner 36% 29% 17% 54% 332
Renter 75% 32% 27% 46% 467
Precariously Housed 74% 36% 36% 30% 30% 154
Income
Less than $25,000 71% 32% 25% 26% 41% 131
$25,000-$49,999 60% 42% 40% 29% 106
$50,000-$99,999 58% 35% 30% 38% 216
Above $100,000 48% 22% 13% 10% 64% 296
Household Characteristics
Children under 18 66% 33% 28% 40% 443
Large Households 60% 33% 25% 25% 49% 126
Single Parent 79% 38% 43% 36% 24% 143
Disability 63% 35% 26% 38% 330
Older Adults (age 65+) 48% 35% 29% 25% 38% 252
Percent
Seriously
Looked for
Housing
Reason for Denial
The real estate agent told
me I would need to show I
was prequalified with a
bank
A bank or other
lender would not
give me a loan to
buy a home
The real estate agent would
not make a disability
accommodation when I
asked
Only showed homes in
neighborhoods where
most people were same
race/ethnicity
A bank or other lender
charged me a high
interest rate on my
home loan
None of
the
Above
1168 of 1863
ROOT POLICY RESEARCH RESIDENT SURVEY APPENDIX, PAGE 32
Denied housing to rent or buy. Figure 11 presents the proportion of those who looked and were denied housing to rent or buy for the county, jurisdictions, and selected respondent characteristics, as well as reason for denial. As shown, nearly 4 in 10 county respondents who looked for housing experienced denial of housing. African American/Black respondents, precariously housed respondents, households with income below $50,000, and single parent respondents have denial rates of 60% or higher. African American (79%) and single parent (74%) respondents report the highest rates of denial.

Among the reasons for denial:
 Income too low was a major reason for denial for all groups except homeowners and households with incomes above $100,000. Additionally, all jurisdictions report this as a common reason for being denied housing with the exception of Foster City, Hillsborough, and San Bruno.  Haven’t established a credit history or no credit history was also a common reason of denial for most groups. The impacts are higher for Asian, Hispanic and African American households, along with renter and precariously housed respondents, households with income below $50,000, and single parent households, households with children under 18, households with a member experiencing a disability, and several jurisdictions.
 Another top denial reason among certain groups is the landlord didn’t accept the type of income I earn (social security or disability benefit or child support). Source of income was the most common reason for denial among African American households (28%). Other groups with denial rates of 25% or higher for this specific issue include precariously housed respondents, single parent households, and households with a member experiencing a disability, as well as Foster City and San Bruno residents.
 Bad credit is another barrier for accessing housing, particularly for Hispanic and Other Race households, households with income between $50,000-$100,000, and large households. This also impacts East Palo Alto, San Mateo, Daly City, Redwood City, Burlingame, and South San Francisco residents at a higher rate.
1169 of 1863
ROOT POLICY RESEARCH RESIDENT SURVEY APPENDIX, PAGE 33
Figure 11. If you looked seriously for housing to rent or buy in San Mateo County in the past five years, were you ever denied housing?
Source: Root Policy Research from the 2021-2022 21 Elements AFFH Resident Survey.

Jurisdiction
County 39% 1154 18% 44% 19% 21% 449
Belmont 52% 50 38% 27% 27% 26
Brisbane 42% 38 25% 19% 31% 16
Burlingame 30% 71 24% 29% 21
Daly City 49% 73 28% 53% 28% 19% 36
East Palo Alto 55% 29 38% 44% 25% 16
Foster City 30% 63 25% 40% 30% 19
Half Moon Bay 41% 34 29% 29% 14
Hillsborough 23% 22 40% 5
Milbrae 36% 33 67% 25% 33% 25% 12
Pacifica 38% 39 47% 27% 33% 15
Redwood City 41% 105 28% 63% 26% 26% 43
San Bruno 25% 51 31% 31% 38% 13
San Mateo 48% 112 30% 38% 28% 53
South San Francisco 30% 331 19% 58% 28% 17% 98
Race/Ethnicity
African American 79% 107 25% 25% 25% 28% 27% 85
Asian 42% 281 38% 28% 21% 21% 117
Hispanic 49% 253 28% 60% 26% 26% 125
Other Race 43% 105 22% 49% 24% 45
Non-Hispanic White 31% 351 40% 19% 23% 25% 108
Tenure
Homeowner 26% 348 24% 22% 23% 91
Renter 45% 687 48% 20% 24% 310
Precariously Housed 61% 208 42% 22% 25% 126
Income
Less than $25,000 64% 199 47% 31% 29% 127
$25,000-$49,999 65% 158 48% 21% 20% 20% 103
$50,000-$99,999 38% 302 21% 51% 24% 114
Above $100,000 18% 346 27% 16% 20% 16% 64
Household Characteristics
Children under 18 51% 558 42% 26% 19% 283
Large Households 43% 171 27% 64% 41% 74
Single Parent 74% 189 41% 27% 25% 138
Disability 54% 446 39% 21% 25% 239
Older Adults (age 65+) 44% 350 35% 22% 21% 153
Percent
Denied
Housing Total n
Bad
Credit
Eviction
history
Income
too low
I had/
have
COVID Foreclosure n
Reason for Denial
Too many
people in my
household
Other
renter/
applicant
willing to pay
more for rent
Haven't
established a
credit
history/no
credit history
Don't have a
regular/
steady job/
consistent
work history
Landlord didn't
accept the type of
income I earn
(social security or
disability)
Lack of
stable
housing
record
Real or
perceived
sexual
orientation or
gender
identity
1170 of 1863
ROOT POLICY RESEARCH RESIDENT SURVEY APPENDIX, PAGE 34
Experience using housing vouchers. It is “difficult” or “very difficult” for eight out of 10 voucher holders to find a landlord that accepts a housing voucher (Figure 13).

As shown in Figure 12, this is related to the amount of the voucher and current rents and the lack of supply (inability to find a unit in the allotted amount of time). Over half of voucher holders (53%) who experienced difficulty indicated the voucher is not enough to cover the rent for places I want to live and almost half of voucher holders (49%) who experienced difficulty indicated there is not enough time to find a place to live before the voucher expires.

Other significant difficulties using vouchers identified by respondents included landlords have policies of not renting to voucher holders (46%) and can’t find information about landlords that accept Section 8 (36%).

Among respondents by race/ethnicity, African American respondents had the greatest proportion of those with a housing choice voucher (60%). Of those respondents, 76% found it difficult to find a landlord that accepts a housing voucher. While 13% of Hispanic respondents have a housing voucher, 85% have found it difficult to use the voucher. Fourteen percent of Asian respondents have housing vouchers— nearly three quarters of these respondents reported that the voucher is not enough to cover the rent for the places I want to live.

Other groups of respondents with higher proportions of voucher utilization include single parent households (43%), precariously housed respondents (30%), and households with income below $25,000 (29%). For each of the aforementioned groups, more than 75% of their respective respondents reported difficulty in utilizing the housing choice voucher. The voucher is not enough to cover the rent for places I want to live was one of the main reasons cited for not using the voucher. 1171 of 1863
ROOT POLICY RESEARCH RESIDENT SURVEY APPENDIX, PAGE 35
Figure 12.

Why is it difficult to
use a housing
voucher?
Source:

Root Policy Research from the 2021-
2022 21 Elements AFFH Resident
Survey.
1172 of 1863
ROOT POLICY RESEARCH RESIDENT SURVEY APPENDIX, PAGE 36
Figure 13. How difficult is it to find a landlord that accepts a housing voucher? Source: Root Policy Research from the 2021-2022 21 Elements AFFH Resident Survey.

Jurisdiction
County 12% 18% 55% 27% 250 53% 49% 46% 36% 6% 203
Belmont 16% 14% 64% 21% 81 45% 64% 36% 27% 9% 11
Brisbane 22% 20% 73% 7% 15 50% 50% 42% 33% 0% 12
Burlingame 8% 0% 75% 25% 12 50% 50% 25% 8% 0% 12
Daly City 12% 14% 50% 36% 14 83% 25% 42% 17% 25% 12
East Palo Alto 14% 29% 57% 14% 7 20% 20% 40% 60% 0% 5
Foster City 12% 18% 47% 35% 17 47% 40% 27% 33% 7% 15
Half Moon Bay 19% 22% 56% 22% 9 71% 29% 29% 43% 14% 7
Hillsborough 8% 25% 75% 0% 4 67% 67% 33% 0% 0% 3
Milbrae 22% 50% 20% 30% 10 60% 40% 20% 40% 0% 5
Pacifica 11% 13% 50% 38% 8 86% 43% 43% 43% 0% 7
Redwood City 16% 13% 61% 26% 23 40% 50% 70% 45% 5% 20
San Bruno 12% 9% 64% 27% 11 40% 60% 50% 10% 10% 10
San Mateo 24% 24% 50% 26% 38 43% 54% 43% 39% 7% 28
South San Francisco 4% 11% 33% 56% 27 63% 50% 71% 63% 8% 24 Race/Ethnicity
African American 60% 24% 60% 16% 82 55% 52% 40% 31% 6% 62 Asian 14% 23% 63% 14% 71 73% 44% 31% 31% 0% 55
Hispanic 13% 15% 40% 45% 53 58% 42% 51% 49% 11% 45
Other Race 19% 29% 50% 21% 28 55% 45% 65% 35% 5% 20
Non-Hispanic White 8% 14% 61% 25% 64 43% 61% 57% 38% 4% 56 Tenure
Homeowner 8% 23% 59% 18% 78 58% 49% 42% 31% 0% 59
Renter 18% 19% 52% 30% 165 55% 52% 48% 43% 6% 134
Precariously Housed 30% 14% 66% 20% 86 57% 54% 35% 26% 7% 74 Income
Less than $25,000 29% 17% 58% 25% 84 47% 41% 47% 37% 10% 70 $25,000-$49,999 18% 17% 52% 31% 48 63% 55% 63% 40% 5% 40 $50,000-$99,999 12% 23% 52% 26% 62 55% 55% 51% 37% 2% 49 Above $100,000 5% 20% 57% 23% 35 43% 61% 29% 32% 4% 28
Household Characteristics
Children under 18 21% 20% 60% 20% 179 59% 51% 44% 35% 1% 143 Large Households 7% 20% 45% 35% 20 63% 56% 63% 56% 6% 16 Single Parent 43% 17% 58% 24% 103 62% 52% 38% 33% 2% 85 Disability 22% 18% 58% 24% 158 57% 52% 42% 29% 5% 129
Older Adults (age 65+) 17% 18% 63% 19% 123 56% 53% 44% 34% 3% 102 Not enough time to find
a place to live before the
voucher expires
Landlords have
policies of not
renting to voucher
holders
Can't find information
about landlords that
accept Section 8 Other n
Voucher is not enough
to cover the rent for
places I want to live
Percent
with a
Housing
Voucher
Not
difficult
Somewhat
difficult
Very
difficult n
1173 of 1863
ROOT POLICY RESEARCH RESIDENT SURVEY APPENDIX, PAGE 37
Displacement. Figure 14 presents the proportion of residents who experienced displacement in the past five years, as well as the reason for displacement.  Overall, 21% of survey respondents experienced displacement in the past five years. Among all survey respondents, the main reason for displacement was rent increased more than I could pay (29%).
 Respondents who are precariously housed have higher rates of recent displacement than homeowners or renters; this suggests that when displaced a unit these housing-insecure tenants are more likely to couch surf or experience homelessness for some period of time before securing a new place to live.
 Among respondents by race/ethnicity, African American respondents reported the highest rate of displacement (59%). The primary reason reported by African American respondents for their displacement was housing was unsafe (e.g., domestic assault, harassment).

Twenty eight percent also reported that they were forced out for no reason.  Asian households, as well as homeowners, households that make less than $25,000, single parent households, households that include a member experiencing a disability, and Millbrae, Brisbane and Pacifica residents are also more likely than other respondents to have been displaced due to an unsafe housing situation (e.g., domestic assault, harassment).  Additionally, Asian, precariously housed respondents, households making less than $25,000, single parent households, and Hillsborough residents are more likely than other respondents to have been displaced and not given a reason.

For respondents that had experienced displacements, they were asked to identify which city they moved from and which city they moved to. The most common moves to and from cities included:


 Moved within South San Francisco (28 respondents)
 Moved from outside San Mateo County to San Mateo (10 respondents)  Moved from San Bruno to South San Francisco (9 respondents)  Moved from Daly City to South San Francisco (9 respondents)  Moved within Burlingame (8 respondents)
1174 of 1863
ROOT POLICY RESEARCH RESIDENT SURVEY APPENDIX, PAGE 38
Figure 14. Displacement Experience and Reasons for Displacement Source: Root Policy Research from the 2021-2022 21 Elements AFFH Resident Survey.

Jurisdiction
County 21% 2066 29% 19% 18% 417
Belmont 26% 80 25% 25% 30% 20
Brisbane 24% 67 25% 31% 25% 16
Burlingame 22% 152 24% 30% 18% 33
Daly City 25% 115 35% 27% 31% 26
East Palo Alto 32% 50 20% 20% 20% 15
Foster City 11% 130 21% 21% 21% 43% 14
Half Moon Bay 31% 51 31% 25% 16
Hillsborough 12% 52 33% 33% 33% 33% 33% 6
Milbrae 27% 44 42% 33% 25% 25% 12
Pacifica 21% 75 31% 31% 31% 16
Redwood City 29% 146 31% 21% 42
San Bruno 25% 89 33% 29% 24% 21
San Mateo 37% 153 35% 31% 20% 54
South San Francisco 12% 712 42% 15% 16% 81
Race/Ethnicity
African American 59% 134 29% 30% 28% 79
Asian 22% 500 31% 22% 22% 109
Hispanic 29% 397 33% 22% 18% 115
Other Race 28% 149 54% 20% 24% 41
Non-Hispanic White 14% 757 27% 20% 31% 102
Tenure
Homeowner 8% 975 27% 25% 31% 75
Renter 34% 905 32% 18% 22% 292
Precariously Housed 48% 280 23% 24% 23% 132
Income
Less than $25,000 45% 282 28% 20% 20% 20% 127
$25,000-$49,999 30% 265 31% 19% 18% 78
$50,000-$99,999 22% 517 32% 22% 18% 115
Above $100,000 8% 721 27% 20% 23% 60
Household Characteristics
Children under 18 30% 840 27% 20% 19% 249
Large Households 20% 284 32% 19% 18% 57
Single Parent 55% 240 24% 24% 20% 131
Disability 34% 711 26% 20% 20% 20% 241
Older Adults (age 65+) 22% 736 23% 22% 22% 162
Because of
apartment
rules
Landlord
refused to
renew my
lease
Reason for Displacement
Percent
Displaced Total n
Rent
increased
more than I
could pay
Personal/
relationship
reasons
Landlord was
selling the
home/
apartment
Landlord
wanted to
move back
in/move in
family
Landlord
wanted to
rent to
someone
else
Housing was
unsafe (e.g.,
domestic
assault,
harassment)
Forced
out for
no
reason
Health/m
edical
reasons
I was
behind
on rent
Poor
condition of
property
Utilities were
too
expensive/
shut off
Natural
disaster/
flooding/
fire n
1175 of 1863
ROOT POLICY RESEARCH RESIDENT SURVEY APPENDIX, PAGE 39
Children changing schools after displacement. Overall, for households with children that were displaced in the past five years, 60% of children in those households have changed schools. The most common outcomes reported among these respondents included school is more challenging (28%), they feel less safe at the new school (25%), and they are in a worse school (24%) (Figure 15).

Among respondents by race/ethnicity, non-Hispanic White households (44%) were the only subgroup to report that being displaced resulted in their children being in better schools. Of African American households that were displaced and have children, 87% reported that their children changed schools.

Of these respondents, 32% reported that their children feel safer at the new school but also have fewer activities.

Among respondents by tenure, precariously housed (78%) and homeowner (74%) households had the highest proportion of children who changed schools. The most common outcomes for precariously housed households included School is less challenging/they are bored (35%) and their children feel less safe at school (34%). For homeowner households, 39% reported that school is more challenging, followed by 31% who reported that their children feel less safe at school.

Among respondents by selected household characteristics, older adult (77%), single parent (74%), households with a member experiencing a disability (70%), and households with children under 18 (67%) all reported high proportions of children who changed schools. The most common outcomes for these respondents included School is more challenging and they feel less safe at the new school. 1176 of 1863
ROOT POLICY RESEARCH RESIDENT SURVEY APPENDIX, PAGE 40
Figure 15. Children Changing Schools and Outcomes, Displaced Households Source: Root Policy Research from the 2021-2022 21 Elements AFFH Resident Survey.

Jurisdiction
County 60% 306 28% 24% 25% 183
Belmont 45% 20 33% 44% 33% 9
Brisbane 81% 16 38% 31% 31% 13
Burlingame 55% 22 33% 33% 33% 12
Daly City 41% 17 43% 29% 29% 29% 7
East Palo Alto 54% 13 43% 57% 29% 7
Foster City 62% 13 50% 8
Half Moon Bay 58% 12 43% 29% 29% 43% 7
Hillsborough 60% 5 67% 3
Milbrae 82% 11 33% 44% 44% 33% 9
Pacifica 91% 11 50% 10
Redwood City 52% 23 25% 33% 25% 12
San Bruno 67% 18 33% 33% 33% 12
San Mateo 66% 35 32% 32% 22
South San Francisco 36% 56 26% 26% 26% 19
Race/Ethnicity
African American 87% 69 30% 30% 32% 32% 60
Asian 73% 91 27% 32% 32% 27% 66
Hispanic 49% 91 23% 30% 23% 25% 44
Other Race 65% 31 40% 30% 25% 25% 20
Non-Hispanic White 60% 60 28% 31% 44% 28% 36
Tenure
Homeowner 74% 66 39% 29% 31% 49
Renter 58% 213 25% 30% 25% 122
Precariously Housed 78% 104 35% 34% 30% 80
Income
Less than $25,000 65% 92 22% 32% 35% 60
$25,000-$49,999 66% 56 25% 28% 28% 25% 36
$50,000-$99,999 55% 85 30% 28% 23% 47
Above $100,000 59% 44 35% 31% 38% 26
Household Characteristics
Children under 18 67% 237 32% 23% 25% 158
Large Households 45% 44 32% 26% 32% 19
Single Parent 74% 124 32% 28% 29% 92
Disability 70% 188 26% 28% 30% 132
Older Adults (age 65+) 77% 117 35% 29% 29% 89
n
Percent of
Children that
Changed
Schools
School change outcomes
Total n
School is less
challenging/
they are bored
School is more
challenging
They are
in a better
school
They are
in a worse
school
They feel
less safe at
the new
school
They feel
safer at
the new
school
They have
fewer
activities
They have
more
activities
Things are
about the
same
1177 of 1863
ROOT POLICY RESEARCH RESIDENT SURVEY APPENDIX, PAGE 41
Experience with housing discrimination. Overall, 19% of survey respondents felt they were discriminated against when they looked for housing in the area.1 As shown in Figure 16, African American respondents (62%), single parent households (44%) and precariously housed respondents (39%) are most likely to say they experienced housing discrimination. Residents with income above $100,000 and homeowners are least likely (11%).

Respondents who believed they experienced discrimination when looking for housing in the county reported when the discrimination occurred. Nearly half of respondents (45%) reported that the discrimination they experienced occurred between 2 and 5 years ago. Twenty eight percent of respondents reported that the discrimination occurred in the past year, 20% reported more than 5 years ago and 7% of respondents did not remember when the discrimination occurred.

How discrimination was addressed. Respondents who believed they experienced discrimination when looking for housing in the county were asked to describe the actions they took in response to the discrimination. Overall, the most common responses to discrimination experienced by survey respondents were Nothing/I wasn’t sure what to do (42%), Moved/found another place to live (30%), and Nothing/I was afraid of being evicted or harassed (20%).

Among top responses for actions taken in response to experienced discrimination, every group reported Nothing/I wasn’t sure what to do with the exception of African American and single parent households, as well as Brisbane and Hillsborough residents. Similarly, survey respondents from Foster City and Pacifica were the only groups not to include Moved/found another place to live among their top responses. African American and Asian households, as well as single parent households, were more likely than other groups to contact either a housing authority, local fair housing organization, or the California Department of Housing or Civil Rights to report their discrimination incident.

Reasons for discrimination. Respondents who believed they experienced discrimination when looking for housing in the county provided the reasons why they thought they were discriminated against. Note that the basis offered by residents is not necessarily protected by federal, state, or local fair housing law, as respondents could provide open-ended and multiple reasons why they thought they experienced discrimination.

Examples of how respondents described why they felt discriminated against, which they provided as open-ended responses to the survey, include:
1 Note that this question applies to all respondents, not just those who seriously looked for housing in the past five years. 1178 of 1863
ROOT POLICY RESEARCH RESIDENT SURVEY APPENDIX, PAGE 42
Appearance/Characteristics
 “Because of my race and ethnicity”
 “[We] were given a subprime loan for home purchase for being Latinx, low-income and primarily Spanish-speaking; refinance last year was lower than expected.”  “It was clear my disability is the reason”
 “I have a child and a couple places told me they wouldn’t rent to me due to my son.”  “The agent asked if I was a tech worker. When I said no, the agent said the place was just rented, even though it was on the listing as active.”
 “I was approved for the unit and when they met my partner, who is Black, they said [the unit] was rented.”
Source of Income/Credit
 “Income was through SSDI [social security disability insurance]”  “The landlord wanted an excellent credit score…”
 “We were not able to provide all the requirement to rent, like SSN [social security number], income proof, employment, and we don’t make enough income…”
 “They wanted someone with income from employment not due to disability.”  “I was discriminated against because of my race and the fact that I had Section 8 at the time. Being African American and having Section 8 made a lot of people feel like I wouldn’t take care of their property.”
 “I am currently being discriminated against due to my need with rental help and because two of us in our household have a need for an emotional support animal.” Immigration status
 Mi hermana llamo a los departamentos donde yo vivo y la manager le dijo que no había disponible pero no era verdad también le dijo que hablara inglés y le pidió seguro social pensando que no tenia y le dijo que tenía que ganar una cierta cantidad de dinero para poder rentar. (My sister called the apartments where I live and the manager told her that there was no one available but it was not true.

She also told her to speak English and asked for social security thinking that she did not have it and told her that she had to earn a certain amount of money to be able to rent). 1179 of 1863
ROOT POLICY RESEARCH RESIDENT SURVEY APPENDIX, PAGE 43
Figure 16. Percent of respondents who felt they were discriminated against and how was it addressed Source: Root Policy Research from the 2021-2022 21 Elements AFFH Resident Survey. n
Jurisdiction
County 19% 28% 45% 20% 7% 357 42% 30% 20% 359
Belmont 21% 19% 56% 19% 6% 16 38% 38% 50% 16
Brisbane 22% 29% 36% 29% 7% 14 64% 21% 21% 14
Burlingame 14% 25% 50% 20% 5% 20 35% 25% 20% 20% 20
Daly City 15% 20% 40% 33% 7% 15 56% 25% 25% 16
East Palo Alto 29% 23% 54% 15% 8% 13 38% 38% 23% 23% 13 Foster City 18% 15% 40% 45% 0% 20 38% 24% 24% 21
Half Moon Bay 26% 27% 55% 9% 9% 11 27% 36% 36% 11
Hillsborough 15% 14% 71% 0% 14% 7 29% 57% 7
Milbrae 29% 36% 50% 7% 7% 14 31% 23% 38% 23% 13
Pacifica 21% 29% 36% 36% 0% 14 50% 21% 29% 21% 21% 14
Redwood City 24% 34% 34% 19% 13% 32 47% 26% 21% 21% 34
San Bruno 12% 30% 60% 0% 10% 10 50% 30% 30% 30% 10
San Mateo 30% 35% 45% 15% 5% 40 53% 26% 26% 38
South San Francisco 13% 30% 40% 23% 6% 82 59% 27% 83
Race/Ethnicity
African American 62% 16% 59% 25% 0% 83 36% 29% 27% 26% 27% 24% 84 Asian 16% 24% 50% 20% 6% 82 28% 25% 29% 29% 24% 24% 83
Hispanic 27% 25% 42% 24% 8% 107 52% 27% 107
Other Race 30% 28% 47% 14% 12% 43 47% 30% 26% 43
Non-Hispanic White 12% 38% 41% 14% 7% 91 44% 27% 18% 91 Tenure
Homeowner 11% 26% 46% 20% 7% 95 32% 29% 22% 96
Renter 28% 26% 47% 20% 6% 232 42% 32% 23% 232
Precariously Housed 39% 21% 54% 20% 4% 98 24% 28% 35% 26% 100 Income
Less than $25,000 36% 29% 51% 11% 9% 100 39% 30% 25% 102 $25,000-$49,999 24% 31% 41% 22% 6% 64 42% 36% 25% 22% 64 $50,000-$99,999 19% 27% 45% 25% 3% 97 44% 29% 18% 97
Above $100,000 11% 28% 45% 21% 7% 76 45% 22% 16% 16% 76 Household Characteristics
Children under 18 26% 21% 57% 15% 6% 216 36% 31% 26% 218 Large Households 19% 26% 52% 9% 13% 54 65% 24% 15% 55
Single Parent 44% 13% 65% 17% 5% 106 33% 32% 27% 26% 26% 107 Disability 33% 27% 48% 21% 4% 215 33% 30% 22% 219
Older Adults (age 65+) 20% 20% 51% 20% 8% 144 24% 34% 24% 24% 146 Called/
emailed
California
Department
of Housing/
Civil Rights
Called/ emailed
City office,
County office,
or human rights
department/
agency
Filed a
complaint Other
Percent who felt
they were
discriminated
against
In the
past
year
2 to 5
years
ago
More
than 5
years
ago n
Nothing/ I
wasn't
sure what
to do
Moved/
found
another
place to
live
Nothing/ I
was afraid of
being
evicted/
harassed
Called/
emailed
housing
authority
Called/ emailed
local fair
housing
organization
Don't
remember
1180 of 1863
ROOT POLICY RESEARCH RESIDENT SURVEY APPENDIX, PAGE 44
Experience of persons with disabilities. Overall, 35% of respondents’ households include a member experiencing a disability. Of these households, 26% said their housing does not meet their accessibility needs; 74% report that their current housing situation meets their needs. The three top greatest housing needs expressed by respondents included grab bars in bathroom or bench in shower (34%), supportive services to help maintain housing (33%), and ramps (26%). Other needs expressed by a substantial proportion of groups included wider doorways, reserved accessible parking spot by the entrance, and more private space in the facility in which I live.

Of respondents by jurisdiction, East Palo Alto (64%) has the lowest proportion of respondents with disabilities whose current housing situation meets their needs. Of these respondents, 63% indicated they needed supportive services to help maintain housing.

The highest proportion of respondents by group reporting that they or a member of their household experiences a disability were African American (71%), households making less than $25,000 (59%), single parent households (58%), and precariously housed respondents (56%). 1181 of 1863
ROOT POLICY RESEARCH RESIDENT SURVEY APPENDIX, PAGE 45
Figure 17. Respondents experiencing a disability and their top three greatest housing needs Source: Root Policy Research from the 2021-2022 21 Elements AFFH Resident Survey. n
Jurisdiction
County 35% 74% 711 34% 33% 26% 171
Belmont 35% 89% 28 67% 67% 3
Brisbane 37% 72% 25 29% 29% 29% 29% 7
Burlingame 27% 80% 41 63% 50% 50% 8
Daly City 34% 68% 38 36% 36% 45% 36% 11
East Palo Alto 44% 64% 22 63% 8
Foster City 31% 83% 40 29% 29% 7
Half Moon Bay 45% 68% 22 29% 29% 7
Hillsborough 26% 100% 13 n/a
Milbrae 40% 82% 17 25% 25% 25% 25% 25% 25% 4
Pacifica 39% 93% 29 100% 2
Redwood City 42% 68% 62 33% 28% 28% 33% 18
San Bruno 40% 82% 34 50% 33% 33% 6
San Mateo 43% 72% 65 41% 47% 41% 17
South San Francisco 30% 68% 210 35% 28% 32% 57
Race/Ethnicity
African American 71% 87% 95 40% 40% 33% 15
Asian 31% 77% 157 29% 34% 26% 26% 35
Hispanic 41% 70% 162 37% 54% 35% 46
Other Race 38% 71% 56 63% 50% 44% 16
Non-Hispanic White 32% 77% 241 33% 27% 21% 52
Tenure
Homeowner 29% 82% 280 35% 37% 37% 43
Renter 39% 73% 347 41% 40% 27% 88
Precariously Housed 56% 71% 154 37% 26% 33% 43
Income
Less than $25,000 59% 71% 167 42% 27% 23% 48
$25,000-$49,999 40% 67% 107 45% 45% 45% 31
$50,000-$99,999 35% 77% 180 43% 26% 24% 42
Above $100,000 23% 82% 167 52% 34% 41% 29
Household Characteristics
Children under 18 35% 78% 293 40% 29% 32% 63
Large Households 35% 70% 99 41% 45% 34% 29
Single Parent 58% 81% 139 48% 28% 41% 29
Older Adults (age 65+) 46% 76% 337 44% 29% 30% 79
Ramps
Percent of
respondents
with a
disability
Current
housing
situation
meeting
needs Total n
Grab bars in
bathroom or
bench in
shower
Supportive
services to
help
maintain
housing
Alarm to
notify if a
non-verbal
child leaves
the home
Fire
alarm/doorbell
made accessible
for person with
hearing
disability/deaf
Better
navigation
for person
who is blind
Wider
doorways
Reserved
accessible
parking spot
by entrance
More
private
space in
the facility
in which I
live
Service or
emotional
support
animal
allowed
Would like to
live alone
(not with a
roommate)
Fewer
restrictions/
more freedom
1182 of 1863
ROOT POLICY RESEARCH RESIDENT SURVEY APPENDIX, PAGE 46
Transportation. Over 80% of respondents indicated the type of transportation used most often is driving a personal vehicle. This share was relatively similar across the majority of jurisdictions and was the number one type of transportation used across all jurisdictions and demographic characteristics.

The groups with the lowest proportion of those who primarily drive included African American (40%), households making less than $25,000 (53%), single parents (57%), and precariously housed (57%) respondents.

As shown in Figure 18, on average respondents are fairly satisfied with their transportation situation.

Those groups somewhat or not at all satisfied with their transportation options include African American (58%), Brisbane (51%), single parents (45%) and precariously housed (44%) respondents. 1183 of 1863
ROOT POLICY RESEARCH RESIDENT SURVEY APPENDIX, PAGE 47
Figure 18.

Are you satisfied
with your current
transportation
options?
Source:

Root Policy Research from the
2021-2022 21 Elements AFFH
Resident Survey.

Jurisdiction
County 29% 45% 20% 6% 1,903
Belmont 21% 42% 27% 10% 78
Brisbane 17% 33% 38% 13% 64
Burlingame 32% 45% 21% 1% 139
Daly City 19% 52% 20% 8% 109
East Palo Alto 31% 36% 24% 9% 45
Foster City 29% 43% 20% 9% 115
Half Moon Bay 30% 35% 26% 9% 46
Hillsborough 50% 34% 14% 2% 44
Milbrae 30% 45% 13% 13% 40
Pacifica 28% 42% 15% 15% 65
Redwood City 30% 36% 27% 8% 142
San Bruno 23% 54% 19% 4% 81
San Mateo 29% 52% 14% 4% 134
South San Francisco 34% 48% 15% 3% 666
Race/Ethnicity
African American 22% 21% 48% 10% 134
Asian 23% 49% 24% 4% 500
Hispanic 29% 43% 22% 7% 397
Other Race 29% 41% 21% 9% 149
Non-Hispanic White 32% 45% 17% 5% 757
Tenure
Homeowner 31% 45% 18% 6% 905
Renter 27% 44% 23% 6% 834
Precariously Housed 20% 36% 35% 9% 254
Income
Less than $25,000 22% 39% 29% 10% 282
$25,000-$49,999 25% 42% 26% 8% 265
$50,000-$99,999 28% 52% 16% 4% 517
Above $100,000 34% 44% 18% 4% 721
Household Characteristics
Children under 18 25% 43% 25% 6% 840
Large Households 29% 50% 18% 4% 284
Single Parent 20% 36% 38% 7% 240
Disability 25% 40% 27% 8% 658
Older Adults (age 65+) 30% 43% 21% 6% 736
Entirely
satisfied
Mostly
satisfied
Somewhat
unsatisfied
Not at all
satisfied n
1184 of 1863
ROOT POLICY RESEARCH RESIDENT SURVEY APPENDIX, PAGE 48
Solutions offered by residents. Respondents were asked a series of questions about how to improve their situations related to housing, employment, health, education and neighborhood.

Improve housing security. When asked what could improve a respondent’s housing security, the top answers among respondents by jurisdiction, race/ethnicity, tenure, income, and other selected housing characteristics were none of the above and help me with a downpayment/purchase.

The highest proportion of respondents among groups that selected None of the above includes:
 Hillsborough residents, 71%
 Owners, 65%
 Income greater than $100,000, 54%
 Foster City residents, 53%
 White, 51%
 Burlingame residents, 50%
The highest proportion of respondents among groups that selected Help me with a downpayment or purchase includes:
 Renters, 44%
 Large households, 42%
 Daly City residents, 41%
 Hispanic, 39%
 Precariously housed, 39%
 City of San Mateo residents, 37%
Other solutions to improve housing security identified by several different groups included Help me with the housing search, help me pay rent each month, and find a landlord who accepts Section 8. The highest proportion of respondents among groups that selected these solutions includes:

Help me with the housing search
 Precariously housed, 39%
 Income less than $25,000, 34%
 Income between $25,000-$50,000, 29%
1185 of 1863
ROOT POLICY RESEARCH RESIDENT SURVEY APPENDIX, PAGE 49
 Half Moon Bay residents, 27%
Help me pay rent each month
 Income less than $25,000, 35%
 Single parent, 31%
Find a landlord who accepts Section 8
 Black or African American, 37%
Improve neighborhood situation. When asked what could improve a respondent’s neighborhood situation, nearly every respondent group by jurisdiction, race/ethnicity, tenure, income, and other selected housing characteristics identified Better lighting. Other solutions flagged by multiple respondent groups to improve their neighborhood situations includes Improve street crossings and none of the above.

The highest proportion of respondents among groups that selected Better lighting includes:
 East Palo Alto residents, 45%
 Millbrae residents, 45%
 Other race, 42%
 Daly City residents, 41%
 Hispanic, 40%
 Income between $25,000-$50,000, 40%
 Income between $50,000-$100,000, 40%
The highest proportion of respondents among groups that selected Improve street crossings includes:
 City of San Mateo residents, 34%
 Single parent, 31%
The highest proportion of respondents among groups that selected None of the above includes:
 Foster City residents, 37%
 Hillsborough residents, 36%
 Burlingame residents, 28%
1186 of 1863
ROOT POLICY RESEARCH RESIDENT SURVEY APPENDIX, PAGE 50
Additionally, 42% of Millbrae respondents chose Reduce crime, 40% of Brisbane respondents chose More stores to meet my needs, and Belmont (34%) and Half Moon Bay (33%) respondents chose Build more sidewalks.

Improve health situation. When asked what could improve a respondent’s health situation, the majority of respondent groups by jurisdiction, race/ethnicity, tenure, income, and other selected housing characteristics selected Make it easier to exercise, More healthy food and None of the above.

The highest proportion of respondents among groups that selected Make it easier to exercise includes:
 Redwood City residents, 48%
 Hispanic, 42%
 South San Francisco residents, 41%
 City of San Mateo residents, 41%
 Asian, 41%
 Renters, 40%
The highest proportion of respondents among groups that selected More healthy food includes:
 East Palo Alto residents, 48%
 Precariously Housed, 47%
 Single parent, 41%
 Daly City residents, 40%
 Income less than $25,000, 38%
 Black or African American, 37%
 Large Households, 37%
The highest proportion of respondents among groups that selected None of the above includes residents from:
 Hillsborough residents, 48%
 Burlingame residents, 47%
 Foster City residents, 42%
 White, 41%
 Owners, 39%
1187 of 1863
ROOT POLICY RESEARCH RESIDENT SURVEY APPENDIX, PAGE 51
Additionally, African American (34%) and San Bruno (29%) respondents identified Better access to mental health care as a solution to help improve their health situations.

Improve job situation. When asked what could improve a respondent’s employment situation, the majority of respondent groups by jurisdiction, race/ethnicity, tenure, income, and other selected housing characteristics selected Increase wages and None of the above.

The highest proportion of respondents among groups that selected Increase wages includes:
 Renters, 52%
 Single parents, 50%
 Hispanic, 49%
 Households with children, 49%
 Daly City residents, 49%
 Income between $50,000-$100,000, 49%
 Large households, 48%
The highest proportion of respondents among groups that selected None of the above includes:
 Hillsborough residents, 76%
 Owners, 58%
 White, 57%
 Over 65+, 53%
 Income greater than $100,000, 53%
 Foster City residents, 53%
Additionally, 29% of households with income less than $25K identified Find a job near my apartment or house as a solution to help improve their situation.

Improve education situation. When asked what could improve a respondent’s education situation for their children, the majority of respondent groups by jurisdiction, race/ethnicity, tenure, income, and other selected housing characteristics selected None of the above, Have more activities, and Stop bullying/crime/drug use at school. 1188 of 1863
ROOT POLICY RESEARCH RESIDENT SURVEY APPENDIX, PAGE 52
The highest proportion of respondents among groups that selected None of the above includes:
 Burlingame residents, 55%
 White, 52%
 Over 65+, 51%
 Hillsborough residents, 49%
 Foster City residents, 46%
 Brisbane residents, 45%
The highest proportion of respondents among groups that selected Have more activities includes:
 Single parent, 45%
 Households with children, 41%
 Large households, 41%
 Other race, 37%
 Daly City residents, 34%
 Hispanic, 34%
The highest proportion of respondents among groups that selected Stop bullying/crime/drug use at school includes:
 East Palo Alto residents, 38%
 Precariously housed, 31%
 Other race, 30%
 Redwood City residents, 29%
 Hispanic, 29%
 San Mateo residents, 28%
Additionally, 29% of Millbrae respondents identified Have better teachers at their schools as a means to improve the education situation in their respective households. 1189 of 1863
ROOT POLICY RESEARCH SITES INVENTORY AFFH SUPPLEMENT, PAGE 1 Appendix G
Sites Inventory AFFH Supplement
Please refer to HCD AFFH Guidance pages 45 to 49 for full details on the analysis and expectations of HCD. This section summarizes the distribution of RHNA units in the City of San Bruno by income target in relation to four factors of segregation including household income, people of color, households with a disability, and households with children. The following figures show the share of units by income within areas that have a concentration of household types compared to the citywide rate. This supplement provides a summary of the data available through ABAG’s HESS mapping tool for evaluating the fair housing impacts of the RHNA sites chosen. Additional analysis and narrative should be added based on local data and other relevant factors to completely satisfy HCD requirements.

Maps of your selected sites overlayed with the following AFFH layers can be downloaded from the HESS tool at: https://hess.abag.ca.gov/login
Additional guidance from Root Policy Research on finishing up the sites inventory and the AFFH analysis can be found in the following memo:
http://www.21elements.com/documents-mainmenu-3/housing-elements/rhna-6-2022- 2030/1344-finishing-up-affh-sections-of-housing-elements/file Segregation and integration. This section summarizes the distribution of RHNA units in the City of San Bruno by income target in relation to four factors of segregation including household income, people of color, households with a disability, and households with children. The following figures show the share of units by income within areas that have a concentration of household types compared to the citywide rate.  Figure 1 shows how many units are allocated to areas of the city (census tracts) with a share of Low-Moderate Income (LMI) households (earning less than 80% AMI) greater than or less than the citywide rate of 44% of households. Most of the proposed RHNA units (74%) are in areas of the city with a higher share of LMI households compared to the citywide rate.
 Figure 2 shows how many units are estimated in areas of the city with a percent of the population that identified as a Person of Color (non-White population) greater than and less than the citywide share of 67% of the population. Again, 74% of units are located in areas with a concentration of People of Color and 26% of proposed units are in areas with a lower share of People of Color.
1190 of 1863
ROOT POLICY RESEARCH SITES INVENTORY AFFH SUPPLEMENT, PAGE 2  Figure 3 shows the share of the proposed units that are located in areas with a concentration of population with a disability compared to the citywide rate of 8% of the population living with a disability. One in four units (26%) are located in areas of the city with a concentration of residents living with a disability.  Figure 4 shows how many units are allocated to areas of the city with a greater share of households with children compared to the citywide rate of 31% of households. Most units (74%) are not within areas with a concentration of households that have children.

Only 26% of proposed units are located in areas with a concentration of families with children.

Figure 1.

Share of RHNA Units by
Income and Share
Households Earning less
than 80% AMI
Note:
44% of households in the City of San Bruno
earn less than 80% AMI.

Source:

ABAG HESS tool and Root Policy Research.

Share of RHNA Units by
Income and Share of
People of Color
Note:
67% of the population in the City of San Bruno
is a Person of Color.

Source:

ABAG HESS tool and Root Policy Research.

Figure 3.

Share of RHNA Units
by Income and Share
of People with a
Disability
Note:
8% of the population in the City of San
Bruno has a disability.

Source:

ABAG HESS tool and Root Policy
Research.

Total 1,716 604
Very Low Income Units 385 137
Low Income Units 219 76
Moderate Income Units 309 112
Above Moderate Income Units 804 278
Total 74% 26%
Very Low Income Units 74% 26%
Low Income Units 74% 26%
Moderate Income Units 73% 27%
Above Moderate Income Units 74% 26%
% People of Color
Greater than
Citywide rate
Less than
Citywide rate
Total 604 1,716
Very Low Income Units 137 385
Low Income Units 76 219
Moderate Income Units 112 309
Above Moderate Income Units 278 804
Total 26% 74%
Very Low Income Units 26% 74%
Low Income Units 26% 74%
Moderate Income Units 27% 73%
Above Moderate Income Units 26% 74%
% People with a Disability
Greater than
Citywide rate
Less than
Citywide rate
1192 of 1863
ROOT POLICY RESEARCH SITES INVENTORY AFFH SUPPLEMENT, PAGE 4 Figure 4.

Share of RHNA
Units by Income
and Share of
Households with
Children
Note:
31% of households in the City of
San Bruno have child(ren).

Source:

ABAG HESS tool and Root Policy
Research.

Racially and Ethnically Concentrated Areas of Poverty and Affluence. None of the proposed units are within an R/ECAP or RCAA.

Disparities in access to opportunity. This section summarizes the distribution of RHNA units in the City of San Bruno by income target by TCAC defined resource areas.  Figure 5 shows the proposed units by TCAC resource areas including low, moderate, and high resource areas in the City of San Bruno. The vast majority of units (80%) are in moderate resources areas compared to low (14%) or high (7%) resource areas.

There are no highest resource areas in the City of San Bruno.

Figure 5.

Total 614 1,706
Very Low Income Units 142 380
Low Income Units 76 219
Moderate Income Units 114 307
Above Moderate Income Units 283 799
Total 26% 74%
Very Low Income Units 27% 73%
Low Income Units 26% 74%
Moderate Income Units 27% 73%
Above Moderate Income Units 26% 74%
% Households with Children
Greater than
Citywide rate
Less than
Citywide rate
1193 of 1863
ROOT POLICY RESEARCH SITES INVENTORY AFFH SUPPLEMENT, PAGE 5 Share of RHNA Units by TCAC Resource Area
Source: ABAG HESS Tool and Root Policy Research.

Disproportionate housing needs. This section summarizes the distribution of RHNA units in the City of San Bruno by income target based on three indicators of disproportionate housing needs including housing cost burden, overcrowding, and displacement risk.
 Figure 6 shows the estimated share of units in areas of the city with a higher rate of cost burden among households compared to the citywide rate of 38%. All of the RHNA units are proposed in areas of the city with a lower than average rate of housing cost burden.
 Figure 7 shows the proposed share of units in areas of the city with a higher or lower rate of overcrowding compared to the citywide rate of 8%. Again, all of the proposed units are in areas that have lower than average rates of overcrowding.  Figure 8 shows the estimated share of units by displacement risk. Most units (80%) are within areas that are moderate or mixed stable neighborhoods. The remaining units (14%) are in areas that are exclusive or becoming exclusive.

Total 317 1,846 157
Very Low Income Units 73 414 35
Low Income Units 40 234 21
Moderate Income Units 57 336 28
Above Moderate Income Units 148 861 73
Total 14% 80% 7%
Very Low Income Units 14% 79% 7%
Low Income Units 14% 79% 7%
Moderate Income Units 14% 80% 7%
Above Moderate Income Units 14% 80% 7%
TCAC Resource Areas
Low Resource
Moderate
Resource
High
Resource
1194 of 1863
ROOT POLICY RESEARCH SITES INVENTORY AFFH SUPPLEMENT, PAGE 6 Figure 6.

Share of RHNA
Units by Income
and Share of
Cost Burdened
Households
Note:
38% of households in the City
of San Bruno are cost
burdened.

Source:

ABAG HESS tool and Root
Policy Research.

Figure 7.

Share of RHNA
Units by Income
and Share of
Overcrowded
Households
Note:
8% of households in the City
of San Bruno are
overcrowded. Areas with no
data have too few
observations to disclose.

Source:

ABAG HESS tool and Root
Policy Research.

Total 0 2,320
Very Low Income Units 0 522
Low Income Units 0 295
Moderate Income Units 0 421
Above Moderate Income Units 0 1,082
Total 0% 100%
Very Low Income Units 0% 100%
Low Income Units 0% 100%
Moderate Income Units 0% 100%
Above Moderate Income Units 0% 100%
% Households Cost Burdened
Greater than
Citywide rate
Less than Citywide
rate
Total 0 1,866 454
Very Low Income Units 0 418 104
Low Income Units 0 238 57
Moderate Income Units 0 336 85
Above Moderate Income Units 0 874 208
Total 0% 80% 20%
Very Low Income Units 0% 80% 20%
Low Income Units 0% 81% 19%
Moderate Income Units 0% 80% 20%
Above Moderate Income Units 0% 81% 19%
% Households Overcrowded
Greater than
Citywide rate
Less than
Citywide rate No data
1195 of 1863
ROOT POLICY RESEARCH SITES INVENTORY AFFH SUPPLEMENT, PAGE 7 Figure 8.

Share of RHNA Units by Displacement Risk
Source: ABAG HESS Tool and Root Policy Research.

Total 317 157 1,846
Very Low Income Units 73 35 414
Low Income Units 40 21 234
Moderate Income Units 57 28 336
Above Moderate Income Units 148 73 861
Total 14% 7% 80%
Very Low Income Units 14% 7% 79%
Low Income Units 14% 7% 79%
Moderate Income Units 14% 7% 80%
Above Moderate Income Units 14% 7% 80%
Displacement Risk
At Risk of
Becoming
Exclusive
Becoming
Exclusive
Stable
Moderate/
Mixed Income
1196 of 1863
ROOT POLICY RESEARCH SECTION V, PAGE 1
Appendix H
Disparate Access to Educational
Opportunities
This section examines the extent to which members of protected classes and those in poverty experience disparities in access to opportunity as measured by access to education. This section draws from data provided by the San Mateo Office of Education, the California Department of Education, and U.S. Census American Community Surveys (ACS). This section discusses the following topics:
 Changes in school enrollment during COVID-19 by race and ethnicity, and by groups with extenuating circumstances;
1  Achievement gaps by race and ethnicity and for groups with extenuating circumstances as measured by test scores, California State University or University of California admissions standards, and college-going rates;  Barriers to success measured by chronic absenteeism, dropout rates, and suspension rates.

After describing this section’s primary findings, we describe the county’s school districts before launching into data measuring achievement gaps and barriers to success.

Primary Findings
Student racial and ethnic diversity is modestly increasing. Student bodies in San Mateo County have become increasingly racially and ethnically diverse.  Hispanic students make up the largest ethnic group in the county’s schools, representing 38% of students in the 2020-2021 academic school year. This a slight increase from the 2010-2011 school year, where Hispanic students made up 37% of the population.
 There has been a large increase in Asian students, with 17% identifying as such in 2020-2021, an increase of 5 percentage points from 2010-2011. 1 The term “extenuating circumstances” is used in this section to capture students whose socioeconomic situations and/or disability may make standard educational environments challenging. 1197 of 1863
ROOT POLICY RESEARCH SECTION V, PAGE 2
 Students identifying as White (26%) have decreased by 3 percentage points since 2010- 2011.

Free and reduced lunch-qualifying students and English language learners are concentrated in a handful of schools. Overall, 29% of public school students in San Mateo County qualify for reduced or free lunch.  The rate of reduced lunch qualification was highest in Ravenswood City Elementary School District, where 83% of students qualify for reduced lunch. Also in Ravenswood City Elementary, 30% of students are experiencing homelessness. This is a large outlier in the county, where overall just 2% are experiencing homelessness.  Countywide, 20% of public school students are English learners. Again, this rate is highest at Ravenswood City Elementary, where 53% of students are English learners.

La Honda-Pescadero Unified School District, Jefferson Union High School, and Redwood City Elementary also have high rates of English learners, representing more than a third of students.

Enrollment is dropping. Public school enrollment reduced substantially in some areas during the pandemic. Total enrollment decreased by 3% between 2019-2020 and 2020-2021 in San Mateo County, which was the largest decrease of the decade.  Portola Valley and La Honda-Pescadero school districts had the largest enrollment decreases during COVID-19, with a 11% and 10% decline in enrollments, respectively.  Decreased enrollment was especially common among Pacific Islander students.

Between 2019-2021, enrollment among Pacific Islander students decreased by 6% (from 1,581 students in 2019-20 to 1,484 students in 2020-21), substantially higher than the 3% countywide average.
 Enrollment among migrant students decreased drastically by 16% over the same period (from 332 students to 279 students).

Learning proficiency is improving yet disparities exist. Across all racial and ethnic groups, the rate at which students met or exceeded English and mathematics testing standards has increased since the 2014-2015 school year. Students with extenuating circumstances (i.e., disability, facing homelessness, learning English) tend to score lower on English and mathematics tests than the overall student body.  Proficiency gaps are especially pronounced among English learning students in Portola Valley Elementary, Woodside Elementary, Menlo Park City Elementary, and Brisbane Elementary, where students with extenuating circumstances met or exceeded mathematics test standards at a rate at least 50 percentage points below the overall test rate in each district.
1198 of 1863
ROOT POLICY RESEARCH SECTION V, PAGE 3
 Students with disabilities in San Carlos Elementary and Las Lomitas Elementary school districts scored far below the overall student body: In these districts, students with disabilities met or exceeded mathematics test standards at 54 percentage points below the overall test rate.

Many students meet admissions standards for CSU or UC schools.  Among the high school districts in San Mateo County, Sequoia Union had the highest rate of graduates who met such admission standards, at 69%. On the other end of the spectrum, Cabrillo Unified and South San Francisco Unified had the lowest rates at 41%.
 Jefferson Union High School District had the most drastic increase in the share of graduates meeting CSU or UC standards: just 21% of students met these standards in 2016-2017 compared to 48% of students in 2019-2020. La Honda-Pescadero Unified School District experienced a 10 percentage point increase in this success rate over the same period.

Most school districts in the county have a college-going rate at 70% or higher—yet there are wide gaps by race and ethnicity.
 In every district, White students have a higher college-going rate than Hispanic students, but the largest gaps are in South San Francisco United, where 91% of White students go to college compared to just 68% of Hispanic students—a 23 percentage point gap.

Students with extenuating circumstances are highly concentrated in a few schools and move schools often due to housing instability.  Students with extenuating circumstances may need additional resources—e.g., onsite health care, free meals, tutoring—to be successful in school. When these students are concentrated into a few schools, the schools bear an unequal responsibility for providing needed resources. K-12 school funding in California has long been inadequate, and, although policymakers have recently allocated additional resources to schools with high proportions of low income children under a “concentration grant” system, funding gaps remain.
 The highest concentration of high needs students is found in Ravenswood City Elementary, where 30% of all students are experiencing homelessness and 83% qualify for free and reduced lunch.
 Currently, students whose families have been evicted do not have protections allowing them to remain in their current school district. This can result in frequent changes in schools for low income children, raising their vulnerability to falling behind in school.

Absenteeism, dropout rates, and discipline rates are highest for students of color, students with disabilities, and students with other extenuating circumstances. While 10% of students were chronically 1199 of 1863
ROOT POLICY RESEARCH SECTION V, PAGE 4
absent during the 2018-2019 school year, chronic absenteeism rates were higher in districts with a large number of students experiencing economic and housing precarity.  For instance, Ravenswood Elementary, which has a 30% rate of homelessness among students, had one of the higher rates of chronic absenteeism at 16%.  Pacific Islander students (26%), Black/African American students (18%), and Hispanic students (15%) had notably higher rates of chronic absenteeism than the overall student population (10%).
 In most districts, chronic absenteeism is higher among students with disabilities. In fact, only Bayshore Elementary’s students with disabilities had a lower rate of chronic absenteeism than the overall student body.

Dropout rates vary across the county:
 Dropout rates were highest in Sequoia Union High School District (10%) and South San Francisco Unified (9%).
 In all school districts in the county, dropout rates are higher for boys than for girls.  Pacific Islander, Black/African American, and Hispanic students in the county often had higher dropout rates than those in other racial and ethnic groups  Students with disabilities, students experiencing homelessness, foster youth, and students learning English had higher dropout rates than the overall population.

Discipline rates also vary by area and race and ethnicity.  In many school districts across San Mateo County, Hispanic students are disciplined at disproportionately higher rates compared to their peers.  In most districts, Black/African American and Pacific Islander students are also overrepresented in terms of suspension rates, but these rates are slight compared to those of Hispanic students.
 Asian and Filipino students were underrepresented in terms of suspension rates.

White students were also underrepresented in discipline rates in most districts except for La Honda-Pescadero.

The demographics of faculty and staff are fairly similar to that of students.  There is a slightly larger share of White and Black/African American staff than students, meaning that Black/African American and White student groups are more likely to interact with same-race staff and faculty than other racial groups.  Asian students are less likely to interact with a same-race staff of faculty member: 17% of the student body is Asian compared to just 8% of staff and faculty. 1200 of 1863
ROOT POLICY RESEARCH SECTION V, PAGE 5
Background
This section describes the school districts in San Mateo County, including their geographic boundaries and a brief history of the school districts’ formation. This section also includes details on how districts’ enrollments and student demographic have changed over time.

San Mateo County School Districts. There are three unified school districts in San Mateo County which include both elementary and high schools. These are Cabrillo Unified School District, La Honda-Pescadero Unified School District, and South San Francisco Unified School District.

In addition to the unified school districts, there are three high school districts, which include: Jefferson Union High School District, San Mateo Union High School District, and Sequoia Union High School District. The elementary schools covering these high schools’ district boundaries areas are described below:
 In the Jefferson Union High School District geographic boundary, elementary school districts are the Bayshore Elementary School District, Brisbane School District, Jefferson Elementary School District, and Pacifica School District.  Within the San Mateo Union High School District geographic boundary, elementary school districts include San Mateo-Foster City School District, Hillsborough City School District, Burlingame School District, San Bruno Park School District, and Millbrae School District.
 Within the Sequoia Union High School District geographic boundary, the elementary schools include Belmont-Redwood Shores School District, San Carlos School District, Redwood City School District, Ravenswood City School District, Menlo Park City School District, Woodside Elementary School District, Las Lomitas Elementary School District, and Portola Valley School District.

Geographic boundaries of school districts. Figure V-1 illustrates the geographic boundaries of the unified school districts as well as the three high school districts. Municipal boundaries are overlayed on the map. 1201 of 1863
ROOT POLICY RESEARCH SECTION V, PAGE 6
Figure V-1.

Unified School Districts and High School Districts in San Mateo County Source: San Mateo County Office of Education.

As illustrated in the map, Cabrillo Unified School District covers Half Moon Bay and some unincorporated areas of San Mateo County. South San Francisco Unified covers South San 1202 of 1863
ROOT POLICY RESEARCH SECTION V, PAGE 7
Francisco and a small portion of Daly City. La Honda-Pescadero Unified School District covers unincorporated areas of San Mateo County.

The other high school districts, Jefferson Union, San Mateo Union, and Sequoia Union, cover the remaining jurisdictions. Jefferson Union covers Brisbane, Colma, Daly City, and Pacifica. San Mateo Union covers Burlingame, Hillsborough, Millbrae, San Bruno, San Mateo City, and Foster City. Sequoia Union covers Atherton, Belmont, Redwood City, East Palo Alto, Menlo Park, San Carlos, Portola Valley, and Woodside.

The county’s elementary school districts cover the same areas as the three high school districts. Their geographic boundaries are illustrated in the map below. 1203 of 1863
ROOT POLICY RESEARCH SECTION V, PAGE 8
Figure V-2.

Elementary School Districts in San Mateo County
Source: San Mateo County Office of Education.
1204 of 1863
ROOT POLICY RESEARCH SECTION V, PAGE 9
Because the elementary school districts are much smaller, many jurisdictions have several elementary schools. The table blow shows each jurisdiction and their associated elementary school.

Figure V-3.

School Districts in San Mateo County’s Jurisdictions
Source: San Mateo County Office of Education.

A brief history of district formation. San Mateo County’s numerous school districts were formed over a century ago, when the county was more rural and scattered:
communities needed elementary schools close to home, and only a few students were attending high school. As young people began going to high school, individual districts often found they had too few students and resources to support their own high schools, so Jurisdiction
Atherton Sequoia Union
Menlo Park City ; Las Lomitas Elementary; Redwood
City
Belmont Sequoia Union Belmont-Redwood Shores
Brisbane Jefferson Union Brisbane; Bayshore Elementary
Burlingame San Mateo Union Burlingame
Colma Jefferson Union Jefferson Elementary
Daly City Jefferson Union; South San Francisco Unified Jefferson; Bayshore Elementary East Palo Alto Sequoia Union Ravenswood City
Foster City San Mateo Union San Mateo-Foster City
Half Moon Bay Cabrillo Unified (none, included in Cabrillo Unified) Hillsborough San Mateo Union Hillsborough City
Menlo Park Sequoia Union
Menlo Park City; Las Lomitas Elementary;
Ravenswood City
Millbrae San Mateo Union Millbrae
Pacifica Jefferson Union Pacifica
Portola Valley Sequoia Union Portola Valley
Redwood City Sequoia Union Redwood City
San Bruno San Mateo Union San Bruno Park
San Carlos Sequoia Union San Carlos; Redwood City
San Mateo San Mateo Union San Mateo-Foster City
South San Francisco South San Francisco Unified (none, included in South San Francisco Unified) Woodside Sequoia Union
Woodside Elementary; Portola Valley; Las Lomitas;
Redwood City
Unified or High School District Elementary School District(s) 1205 of 1863
ROOT POLICY RESEARCH SECTION V, PAGE 10
separate high school districts, covering the territories of two or more elementary districts, were established to meet the communities’ needs.2
Once California’s population grew and San Mateo County became more urbanized, “a jigsaw puzzle of overlapping districts evolved haphazardly.” Since 1920, the state has been pushing elementary districts to unify with the high school districts that serve their communities, citing improved educational quality and equity of opportunity. However, there has been limited success and local voters in San Mateo County have consistently resisted unification.3
Early efforts at unification were more successful in the rural communities along the coast— for example, voters approved the new Cabrillo Unified district for the area around Half Moon Bay and the La Honda-Pescadero Unified district in a 1964 election. Unification was not supported by many suburban communities edging the Bay. The county’s school district committee proposed to split each of the three high school districts and feeder schools into two or three smaller unified districts, but the State Board of Education rejected variations of those plans three times. The Board argued that the county committee’s proposals would create districts with widely varying property tax bases and could contribute to racial segregation. The State Board instead devised a plan that would create a single unified district within each of the existing high school district boundaries. Voters turned down the state plans in all three districts in June 1966, and rejected a similar proposal again in 1972.

In 1973, the Mid-Peninsula Task Force for Integrated Education petitioned the county committees to unify the elementary districts of Menlo Park, Las Lomitas, Portola Valley, Ravenswood and a portion of Sequoia Union High School District across county lines with Palo Alto Unified. Their goal was racial integration, but the county committee did not support the effort.4
Efforts against unification have persisted, leaving the county with several elementary school districts which feed into a high school, rather than a unified district. As a result, some elementary school districts have faced waning budgets and administrative hurtles.

For instance, Brisbane and Bayshore elementary school districts, at the northern end of the county, serve a little more than 1,000 students and long have struggled with tight budgets.

To rectify their budgetary concerns, the districts now share both a superintendent and a chief business officer. They also participate in a special education collaborative with the Jefferson elementary and high school districts.

According to the county’s superintendent of schools Anne Campbell, other districts may find themselves pooling their resources in the future: local identification may be strong, 2 Watson, Aleta. “How Did We End Up With 54 School Districts in San Mateo and Santa Clara Counties?” Silicon Valley Community Foundation, 2012. https://www.siliconvalleycf.org/sites/default/files/report-edu.pdf 3 Ibid.
4 Ibid.
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she says, but financial reality is hard to ignore: “As we move forward in time, I think it’s going to be interesting to see what school districts are going to do, especially as budgets get more bleak.”
5 Enrollment changes. Total public school enrollment in the county has decreased slightly, by just 1%, from the 2010-2011 academic year to 2020-2021. Figure V-4 illustrates enrollment changes by district.

Bayshore Elementary, Ravenswood City, and Portola Valley school districts experienced the largest enrollment decreases (by at least 30%) between 2010-11 and 2020-21. School districts with the largest increases in enrollments were Burlingame (22%) and BelmontRedwood Shores (30%). 5 Ibid.
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Figure V-4.

Enrollment changes by district, 2010-11 to 2020-2021
Source: California Department of Education and Root Policy Research However, it is important to note that many of these enrollment decreases were driven by the pandemic. In fact, total enrollment in these public schools decreased by 3% between School District
Unified School Districts
Cabrillo Unified 3,352 2,934 -12%
La Honda-Pescadero 341 275 -19%
South San Francisco 9,312 8,182 -12%
High & Elementary School Districts
Jefferson Union High School 4,960 4,705 -5%
Bayshore Elementary 543 361 -34%
Brisbane Elementary 545 474 -13%
Jefferson Elementary 6,998 6,653 -5%
Pacifica 3,164 3,006 -5%
San Mateo Union High School 8,406 9,760 16%
Burlingame Elementary 2,771 3,387 22%
Hillsborough City Elementary 1,512 1,268 -16%
Millbrae Elementary 2,222 2,238 1%
San Bruno Park Elementary 2,599 2,275 -12%
San Mateo-Foster City 10,904 10,969 1%
Sequoia Union High School 8,765 10,327 18%
Belmont-Redwood Shores 3,206 4,152 30%
Las Lomitas Elementary 1,336 1,116 -16%
Menlo Park City Elementary 2,629 2,781 6%
Portola Valley Elementary 711 491 -31%
Ravenswood City Elementary 4,285 2,993 -30%
Redwood City Elementary 9,119 8,086 -11%
San Carlos Elementary 3,212 3,265 2%
Woodside Elementary 453 369 -19%
Total Enrollment 91,345 90,067 -1%
2010-2011
Enrollment
2020-2021
Enrollment Percent Change
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2019-2020 and 2020-2021 in San Mateo County: the largest decrease of the decade. As shown in Figure V-5, enrollments actually increased steadily from 2010-2011 to 2017-2018, then began decreasing afterwards.

Figure V-5.

Public School Enrollment Changes, 2010-2011 to 2020-2021 Note: These data exclude enrollments in SBE Everest Public High School District, which in 2015 combined with the Sequoia Union High School District.

Source: California Department of Education and Root Policy Research Portola Valley and La Honda-Pescadero school districts had the largest enrollment decreases during COVID-19, with a 11% and 10% decline in enrollments, respectively. The only school district with increasing enrollments between the 2019-2020 to 2020-2021 school years was Sequoia Union High School District, with a modest 1% increase in enrollments.
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Figure V-6.

Enrollment changes by district during COVID-19, 2019-20 to 2020-21 Source: California Department of Education and Root Policy Research.

Declining enrollments in public schools have been common across the state and country during the COVID-19 pandemic, and enrollment declines in San Mateo County are on par School District
Unified School Districts
Cabrillo Unified 3,136 2,934 -6%
La Honda-Pescadero 306 275 -10%
South San Francisco 8,438 8,182 -3%
High & Elementary School Districts
Jefferson Union High School 4,811 4,705 -2%
Bayshore Elementary 381 361 -5%
Brisbane Elementary 476 474 0%
Jefferson Elementary 6,687 6,653 -1%
Pacifica 3,110 3,006 -3%
San Mateo Union High School 9,885 9,760 -1%
Burlingame Elementary 3,534 3,387 -4%
Hillsborough City Elementary 1,290 1,268 -2%
Millbrae Elementary 2,349 2,238 -5%
San Bruno Park Elementary 2,454 2,275 -7%
San Mateo-Foster City 11,576 10,969 -5%
Sequoia Union High School 10,238 10,327 1%
Belmont-Redwood Shores 4,314 4,152 -4%
Las Lomitas Elementary 1,208 1,116 -8%
Menlo Park City Elementary 2,922 2,781 -5%
Portola Valley Elementary 551 491 -11%
Ravenswood City Elementary 3,269 2,993 -8%
Redwood City Elementary 8,530 8,086 -5%
San Carlos Elementary 3,405 3,265 -4%
Woodside Elementary 376 369 -2%
Total Enrollment 93,246 90,067 -3%
2019-2020
Enrollment
2020-2021
Enrollment Percent Change
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with those across the state. According to a study conducted by the Public Policy Institute of California, public K–12 enrollment declined by 3% in California from the 2019-2020 school year to the 2020-2021 school year. 6
As funding is tied directly to the number of enrolled pupils, schools in San Mateo County could suffer fiscal consequences with continued declines. By law, districts are “held harmless” for declines for one year—that is, school budgets for 2020–2021 were unaffected, but continued enrollment declines could mean cuts in future years.7 Reductions in enrollments, and consequently funding, could also worsen economic inequality in the long-term by reducing students’ resources and access to opportunities.

Demographics: race & ethnicity. Over the last decade, San Mateo County’s school districts have diversified in terms of students’ race and ethnicity. Hispanic students make up the largest ethnic group in the county’s schools: 38% of students identified as Hispanic in the 2020-2021 academic school year. This is just a one percentage point increase from 2010-2011. Many other students are White (26%), though this has decreased by 3 percentage points since 2010-2011, The largest increase was in Asian students, with 17% identifying as such in 2020-2021, an increase of 5 percentage points from 2010-2011.

Other students identify as Filipino (8%), or bi- or multi-racial (8%). A small and decreasing percentage of students identify as Black/African American (1%) and Pacific Islander (2%). 6 Lafortune, Julien & Prunty, Emmanuel. “Digging into Enrollment Drops at California Public Schools.” Public Policy Institute of California. May 14, 2021. https://www.ppic.org/blog/digging-into-enrollment-drops-at-california-publicschools/ 7 Ibid.
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Figure V-7.

Changes in Race and
Ethnicity, 2010-2011 to 2020-
2021
Note: These data exclude enrollments in SBE
Everest Public High School District, which
in 2015 combined with the Sequoia Union
High School District.

Source: California Department of Education and
Root Policy Research
:

Figure V-8 shows the racial and ethnic distribution of students enrolled in public schools by jurisdiction in 2020-2021.
 Portola Valley Elementary School District (66%) and Woodside Elementary School District (64%) had the highest share of White students, making them among the least racially and ethnically diverse districts in the county.  Ravenswood City Elementary School District and Redwood City Elementary School District had the highest share of Hispanic students, at 84% and 70%, respectively.  Ravenswood City also had the highest proportion of Pacific Islander students (7%) and Black/African American students (5%) compared to other districts.  Millbrae Elementary (46%), Hillsborough Elementary (32%), and Belmont-Redwood Shores Elementary (32%) had the highest share of Asian students.  Jefferson Elementary School District and Jefferson Union High School District had the highest portion of Filipino students, at 25% and 29% respectively. 1212 of 1863
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Figure V-8.

Student body by Race and Ethnicity, 2020-2021
Note: In almost all school districts, less than 1% of students were Native American, so they are not included in this table.

Source: California Department of Education and Root Policy Research Enrollment changes due to COVID-19 varied by race and ethnicity. For instance, between 2019-2021, enrollment among Pacific Islander students decreased by 6% (from 1,581 students in 2019-20 to 1,484 students in 2020-21). This is substantially higher than the 3% countywide average. Enrollments among Filipino and Hispanic students decreased by 4% while enrollment among Black/African American students decreased by 2%. On the other School District
Unified School Districts
Cabrillo Unified 1% 0% 1% 52% 0% 40% 5%
La Honda-Pescadero 0% 0% 1% 63% 0% 35% 1%
South San Francisco 14% 1% 23% 48% 2% 6% 6%
High & Elementary School Districts
Jefferson Union High School 15% 1% 29% 31% 1% 14% 7%
Bayshore Elementary 19% 3% 21% 41% 4% 3% 8%
Brisbane Elementary 20% 1% 12% 28% 0% 24% 11%
Jefferson Elementary 19% 2% 25% 36% 1% 11% 5%
Pacifica 8% 1% 9% 26% 0% 39% 16%
San Mateo Union High School 23% 1% 5% 32% 2% 28% 10%
Burlingame Elementary 27% 0% 3% 16% 0% 41% 9%
Hillsborough Elementary 32% 0% 2% 5% 0% 48% 12%
Millbrae Elementary 46% 1% 6% 20% 2% 16% 8%
San Bruno Park Elementary 16% 1% 10% 41% 5% 15% 1%
San Mateo-Foster City 26% 1% 3% 37% 2% 21% 9%
Sequoia Union High School 9% 2% 1% 45% 2% 35% 5%
Belmont-Redwood Shores 32% 1% 3% 12% 1% 34% 14%
Las Lomitas Elementary 18% 1% 1% 13% 0% 53% 14%
Menlo Park City Elementary 13% 1% 1% 17% 1% 55% 11%
Portola Valley Elementary 6% 0% 0% 14% 0% 66% 13%
Ravenswood City Elementary 0% 5% 0% 84% 7% 1% 2%
Redwood City Elementary 4% 1% 1% 70% 1% 19% 4%
San Carlos Elementary 18% 1% 1% 14% 0% 49% 13%
Woodside Elementary 4% 2% 0% 16% 1% 64% 11%
Total 17% 1% 8% 38% 2% 26% 8%
Asian White
Two or
Black Filipino Hispanic more races
Pacific
Islander
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end of the spectrum, there was a 3% increase in enrollment among White students (from 22,308 students to 23,055 students) between 2019-20 and 2020-21. Similarly, there was a 1% increase in enrollment among Asian students and a 4% increase among students of two or more races.

Figure V-9.

Enrollment Changes by Race and Ethnicity, San Mateo County, 2019-20 to 2020-21
Source: California Department of Education and Root Policy Research While many of their families may have simply moved out of San Mateo County during the pandemic, it is possible that Black/African American, Filipino, Hispanic, and Pacific Islander students are otherwise slipping through the cracks of the education system during this period.

Demographics: students with extenuating circumstances. Several students in the county’s public schools are facing additional hurtles to educational ease.

Many are English learners, qualify for reduced lunch, are foster children, are experiencing homelessness, have a disability, or are migrants. Students in these groups often have hindrances to excelling in school because of detrimental circumstances beyond their control. These include financial and social hardships as well as problems within students' families.

Qualification for free and reduced lunch is often used as a proxy for extenuating circumstances. Qualifications are determined based on household size and income. For instance, in the 2020-2021 academic year, students from a household of three making less 1214 of 1863
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than $40,182 annually qualified for reduced price meals, and those making less than $28,236 in a household of three qualified for free meals.8 Free and reduced lunch disparities. Overall, 29% of public school students in San Mateo County qualify for reduced or free lunch. This rate was substantially lower in districts like Hillsborough Elementary, San Carlos Elementary, Portola Valley Elementary, Las Lomitas Elementary, Belmont-Redwood Shores, and Menlo Park City Elementary, where each had less than 10% of students qualify for free or reduced lunch.

The rate of reduced lunch qualification was far higher in Ravenswood City Elementary School District, where 83% of students qualify for reduced lunch.

Disparities in homelessness. In Ravenswood City Elementary, 30% of students are experiencing homelessness. This is an outlier in the county, where overall just 2% are experiencing homelessness. The school district has received media attention due to its astronomically high rate of students experiencing homelessness. Some have noted that rates of homelessness have increased due to escalating costs of living in an area surrounded by affluence.
9 Others have highlighted that ”Having a roof over your head, having a safe place to sleep and study, is fundamental to absolutely everything," and have noted that students who experience homelessness have higher dropout rates and are more likely to experience homelessness as adults.10
School moves related to evictions. Currently, students whose families have been evicted do not have protections allowing them to remain in their current school district.

This means that precarious housing also means precarious schooling for many of the county’s students. Frequent moves by students are closely related to lower educational proficiency.

In the City of San Francisco, a 2010 ordinance protects some students from being evicted during the school year; however, it only relates to owner/relative move-in evictions.11 Children in families who are evicted for other reasons may need to move schools or districts when their housing is lost.

English language learners. Countywide, 20% of public school students are English learners. Again, this rate is highest at Ravenswood City Elementary, where 53% of students are English learners. La Honda-Pescadero Unified School District, Jefferson Union High 8 “Income Eligibility Scales for School Year 2020-2021.” California Department of Education. 9 Bartley, Kaitlyn. “Homelessness: The shadow that hangs over students in this Bay Area school district.” The Mercury News. December 2018.
10 Jones, Carolyn. “California schools see big jump in homeless students.” Palo Alto Online. October 2020. 11 https://sfrb.org/new-amendment-prohibiting-owner-move-evictions-minor-children-during-school-year 1215 of 1863
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School, and Redwood City Elementary also have high rates of English learners, representing more than a third of students.

Less than one percent of students in San Mateo County public school districts are foster youth or migrants. Cabrillo Unified School District had the highest rate of migrant students at 3%. La Honda-Pescadero had the highest rate of foster children at 2%.

School districts without large low income populations also tend to serve very few English language learners. For instance, in Hillsborough Elementary where 0% of students qualify for reduced lunch, only 1% of students are English language learners. 1216 of 1863
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Figure V-10.

Students with Extenuating Circumstances, 2020-2021
Source: California Department of Education and Root Policy Research The overall share of students in these groups has not changed drastically over time. As shown in Figure V-11, there have been slight decreases in the share of students who are English learners and the share of students who qualify for reduced lunch from 2016-2017 School District
Unified School Districts
Cabrillo Unified 20% 37% 0% 2% 3%
La Honda-Pescadero 38% 38% 2% 1% 1%
South San Francisco 21% 34% 0% 1% 1%
High & Elementary School Districts
Jefferson Union High School 36% 44% 0% 0% 0%
Bayshore Elementary 30% 57% 0% 0% 0%
Brisbane Elementary 16% 19% 0% 0% 0%
Jefferson Elementary 14% 27% 0% 1% 0%
Pacifica 9% 18% 0% 1% 0%
San Mateo Union High School 10% 21% 0% 0% 0%
Burlingame Elementary 13% 11% 0% 0% 0%
Hillsborough Elementary 1% 0% 0% 0% 0%
Millbrae Elementary 19% 25% 0% 0% 0%
San Bruno Park Elementary 29% 18% 0% 0% 0%
San Mateo-Foster City 26% 28% 0% 2% 0%
Sequoia Union High School 15% 30% 0% 0% 0%
Belmont-Redwood Shores 10% 7% 0% 0% 0%
Las Lomitas Elementary 7% 6% 0% 0% 0%
Menlo Park City Elementary 6% 7% 0% 0% 0%
Portola Valley Elementary 4% 5% 0% 0% 0%
Ravenswood City Elementary 53% 83% 0% 30% 0%
Redwood City Elementary 38% 56% 0% 2% 1%
San Carlos Elementary 5% 6% 0% 0% 0%
Woodside Elementary 8% 10% 0% 0% 0%
Total 20% 29% <1% 2% <1%
Migrant
Reduced
Lunch
English
Learners
Foster
Children Homeless
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to 2020-2021. Around 2% of students in the county are homeless and this has not changed between 2016-2017 and 2020-2021. Foster youth and migrant students are not shown in the figure, as both have hovered at less than 1% from year to year.

Figure V-11.

Changes in rates of English
Leaners, Reduced Lunch,
and Homelessness, 2016-
2017 to 2020-2021
Note: These data exclude enrollments in SBE
Everest Public High School District, which
in 2015 combined with the Sequoia Union
High School District.

Source: California Department of Education and
Root Policy Research
:

During COVID-19, enrollments decreased by 3% between 2019-2020 and 2020-2021 school years, as families withdrew or did not reenroll their children from public schools.

Enrollment among migrant students decreased much more drastically, by 16% (from 332 students to 279 students). Similarly, enrollment among students who qualify for reduced lunch declined at a higher rate (10%) than the overall student population. Foster children and English learners also experienced enrollment decreases at a rate higher than the total population, with 7% and 10% decreases in enrollment, respectively. 1218 of 1863
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Figure V-12.

Enrollment Changes by Extenuating Circumstance, San Mateo County, 2019-2020 to 2020-2021
Source: California Department of Education and Root Policy Research Achievement Gaps
This section details achievement gaps within school districts. Gaps are measured by test scores, meeting California State University or University of California admissions standards, and college-going rates.

Test scores. Figure V-13 indicates the percent of students who met or exceeded English and mathematics testing standards set by the California State Assessment of Student Performance and Progress. Overall, 62% of students in the county met or exceeded English testing standards and 52% met or exceeded mathematics testing standards.

Of all the districts with high schools, San Mateo Union High School District had the highest student pass rates: 70% of their students met or exceeded standards in English testing and 50% met or exceeded standards in mathematics testing.

Among elementary school districts, Portola Valley Elementary School District and Woodside Elementary School District had the highest rates of success in English, with 87% and 88% of students meeting or exceeding English testing standards, respectively. Woodside Elementary School District and Hillsborough Elementary School District had the highest rates of success in mathematics, with 84% and 85% meeting math testing standards, respectively.

In every school district, girls scored higher on English tests than boys. Overall, girls met or exceeded English testing at a rate of 67% while boys met or exceeded English testing at a rate of 57%. The largest gender gap was in Brisbane Elementary School District, where 72% 1219 of 1863
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of girls met or exceeded English testing standards and just 56% of boys did: a gap of 16 percentage points.

Gender gaps in mathematics were less pronounced, but largest gender gaps were in Cabrillo Unified School District and in La Honda Pescadero Unified School District. In Cabrillo Unified, girls passed mathematics at a rate 7% higher than boys, while in La Honda-Pescadero, boys passed at a rate 6% higher than girls.

Figure V-14.

Students who Met or Exceeded Testing Standards, by Gender and District, 2018-2019
Source: California Department of Education, California Assessment of Student Performance and Progress, and Root Policy Research The gender gap in test scores has started to close in recent years, as indicated in Figure V15. In 2014-2015 there was a 11 percentage point gap in girls’ and boys’ English testing pass District
Unified School Districts
Cabrillo Unified 48% 41% 55% 34% 31% 38%
La Honda-Pescadero 43% 36% 49% 31% 34% 28%
South San Francisco 52% 45% 60% 44% 42% 45%
High & Elementary School Districts
Jefferson Union High School 57% 52% 63% 37% 38% 35%
Bayshore Elementary 27% 24% 31% 27% 27% 28%
Brisbane Elementary 64% 56% 72% 54% 56% 53%
Jefferson Elementary 48% 43% 54% 37% 39% 35%
Pacifica 60% 55% 65% 57% 57% 57%
San Mateo Union High School 70% 66% 76% 50% 50% 50%
Burlingame Elementary 80% 75% 84% 78% 78% 78%
Hillsborough Elementary 85% 81% 89% 85% 86% 84%
Millbrae Elementary 63% 57% 70% 58% 58% 58%
San Bruno Park Elementary 50% 47% 53% 41% 43% 38%
San Mateo-Foster City 62% 58% 67% 56% 56% 56%
Sequoia Union High School 68% 64% 72% 50% 50% 50%
Belmont-Redwood Shores 82% 78% 86% 79% 78% 80%
Las Lomitas Elementary 86% 84% 88% 82% 84% 80%
Menlo Park City Elementary 84% 81% 87% 83% 82% 83%
Portola Valley Elementary 87% 83% 91% 83% 84% 82%
Ravenswood City Elementary 22% 20% 23% 15% 16% 13%
Redwood City Elementary 54% 49% 59% 46% 46% 46%
San Carlos Elementary 80% 77% 83% 75% 76% 74%
Woodside Elementary 88% 85% 91% 84% 85% 83%
Total 62% 57% 67% 52% 52% 52%
English Language Arts/Literacy Mathematics
Total Boys Girls Total Boys Girls
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rates, and by 2018-2019 this was just a 10 percentage point gap. The figure also indicates that there have been steady gains in the share of students meeting or exceeding testing standards in the county.

Figure V-15.

Students who Met or Exceeded Testing Standards, by Gender, 2014-2015 to 2018-2019
Source: California Department of Education, California Assessment of Student Performance and Progress, and Root Policy Research Very large gaps in test scores by race and ethnicity exist among students in some areas.

Figure V-16 illustrates the rate at which students of various racial and ethnic groups met or exceeded English testing standards.

For the past five years in San Mateo County, Asian, White, and Filipino students have met or exceeded English testing standards at rates higher than the overall student population.

Hispanic, Black/African American, and Pacific Islander students, on the other hand, have been underserved in this realm and have consistently scored lower than the overall student body.

However, across all groups, the rate at which students met or exceed English testing standards has increased since the 2014-2015 school year. Hispanic students have made the largest percentage point gain: 34% met standards in 2014-2015 and 40% met standards in 2019-19, an increase of six percentage points.
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Figure V-16.

Students who Met or Exceeded English Testing Standards, by Race and Ethnicity, 2014-2015 to 2018-2019
Source: California Department of Education, California Assessment of Student Performance and Progress, and Root Policy Research A similar narrative holds in Math testing standards, where scores have improved among each racial and ethnic group from 2014-2015 to 2018-2019. Again, White and Asian students meet or exceed math testing standards at rates higher than the overall population while Hispanic, Pacific Islander, and Black/African American students scored lower.

White and Hispanic students have seen the biggest increases in rates of mathematics success: both have experienced a five percentage point increase in the percent of students who met or exceeded math testing standards.
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Figure V-17.

Students who Met or Exceeded mathematics testing standards, by Race and Ethnicity, 2014-2015 to 2018-2019
Source: California Department of Education, California Assessment of Student Performance and Progress, and Root Policy Research Figure V-18 illustrates the rates at which students of various racial and ethnic groups met or exceeded mathematics testing standards by district.

There were several districts in which the gaps between the overall test pass rates and a specific racial groups’ pass rates were especially wide. For instance, in San Carlos Elementary School District, 75% of the total student body met or exceeded math testing standards, but only 11% of Black/African American students met or exceeded math testing standards— a gap of 64 percentage points.

Other school districts with wide gaps between Black/African American and overall math testing success were Las Lomitas Elementary (46 percentage point gap), Menlo Park City Elementary (43 percentage point gap), and Belmont-Redwood Shores (42 percentage point gap).

Some school districts also had similar gaps in Pacific Islander students’ math passing rates and overall passing rates. For instance, in Menlo Park City Elementary School District, 83% of the student body met or exceeded mathematics testing standards but just 35% of Pacific Islander students passed or exceeded mathematics testing standards—a gap of 48 1223 of 1863
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percentage points. Millbrae Elementary School District also had a 47 percentage point gap between Pacific Islander students’ and total students’ math test rates.

Figure V-18.

Students who Met or Exceeded Mathematics Testing Standards, by Race/Ethnicity and District, 2018-2019
Source: California Department of Education, California Assessment of Student Performance and Progress, and Root Policy Research Although racial gaps in English testing were less pronounced, San Carlos Elementary School District also had a wide gap between the total student body and Black/African American School District
Unified School Districts
Cabrillo Unified 34% 65% (no data) 38% 16% (no data) 54% La Honda-Pescadero 31% (no data) (no data) (no data) 20% (no data) 46% South San Francisco 44% 75% 19% 60% 29% 33% 46%
High & Elementary School Districts
Jefferson Union High School 37% 75% (no data) 36% 17% (no data) 42% Bayshore Elementary 27% 44% (no data) 38% 17% 14% (no data) Brisbane Elementary 54% 67% (no data) 65% 38% (no data) 60% Jefferson Elementary 37% 61% 15% 42% 23% 20% 30%
Pacifica 57% 74% 38% 48% 38% (no data) 66%
San Mateo Union High School 50% 84% (no data) 46% 22% 20% 63% Burlingame Elementary 78% 92% 53% 66% 50% (no data) 81% Hillsborough Elementary 85% 92% (no data) (no data) 76% (no data) 82% Millbrae Elementary 58% 75% 31% 63% 27% 11% 51%
San Bruno Park Elementary 41% 69% 23% 64% 25% 27% 50%
San Mateo-Foster City 56% 87% 30% 61% 23% 27% 69%
Sequoia Union High School 50% 81% 18% 53% 22% 11% 76%
Belmont-Redwood Shores 79% 92% 37% 77% 52% 43% 79%
Las Lomitas Elementary 82% 93% 36% (no data) 44% (no data) 87% Menlo Park City Elementary 83% 94% 40% (no data) 55% 35% 88% Portola Valley Elementary 83% 89% (no data) (no data) 56% (no data) 89% Ravenswood City Elementary 15% (no data) 9% (no data) 15% 11% (no data) Redwood City Elementary 46% 92% 22% 76% 34% 44% 75%
San Carlos Elementary 75% 91% 11% 85% 51% (no data) 78% Woodside Elementary 84% 92% (no data) (no data) 52% (no data) 89% Total 52% 82% 18% 50% 27% 21% 71%
Overall Asian Black Filipino Hispanic White
Pacific
Islander
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students. Namely, 80% of the student body met or exceeded English testing standards, but only 19% of Black/African American students met or exceeded testing standards—a 61 percentage point gap. Las Lomitas Elementary had a 41 percentage point gap between overall English testing success and Black/African American English testing success.

Other districts had large gaps between the total student body’s English test scores and Pacific Islander students’ test scores. Namely, in Menlo Park City Elementary School District 84% of students met or exceeded English testing standards, but only 40% of Pacific Islander students—a 44 percentage point gap.
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Figure V-19.

Students who Met or Exceeded English Testing Standards, by Race/Ethnicity and District, 2018-2019
Source: California Department of Education, California Assessment of Student Performance and Progress, and Root Policy Research Students with extenuating circumstances across all districts met or exceeded testing standards at lower rates. However, some districts had especially wide disparities between overall test scores and test scores of students with extenuating circumstances.

School District
Unified School Districts
Cabrillo Unified 48% 78% (no data) 54% 28% (no data) 71% La Honda-Pescadero 43% (no data) (no data) (no data) 27% (no data) 61% South San Francisco 52% 76% 36% 66% 38% 44% 56%
High & Elementary School Districts
Jefferson Union High School 57% 81% (no data) 60% 43% (no data) 59% Bayshore Elementary 27% 49% (no data) 33% 20% 14% (no data) Brisbane Elementary 64% 63% (no data) 75% 51% (no data) 79% Jefferson Elementary 48% 62% 28% 59% 34% 33% 43%
Pacifica 60% 65% 32% 52% 45% (no data) 68%
San Mateo Union High School 70% 88% 55% 79% 50% 34% 81% Burlingame Elementary 80% 88% 61% 73% 55% (no data) 83% Hillsborough Elementary 85% 89% (no data) (no data) 77% (no data) 83% Millbrae Elementary 63% 74% 46% 68% 42% 23% 61%
San Bruno Park Elementary 50% 72% 39% 76% 36% 31% 56%
San Mateo-Foster City 62% 85% 41% 68% 34% 37% 77%
Sequoia Union High School 68% 87% 44% 92% 47% 31% 88%
Belmont-Redwood Shores 82% 91% 44% 81% 64% 61% 83%
Las Lomitas Elementary 86% 91% 45% (no data) 65% (no data) 89% Menlo Park City Elementary 84% 92% 60% (no data) 62% 40% 88% Portola Valley Elementary 87% 92% (no data) (no data) 58% (no data) 93% Ravenswood City Elementary 22% (no data) 24% (no data) 21% 18% (no data) Redwood City Elementary 54% 91% 35% 73% 43% 47% 83%
San Carlos Elementary 80% 90% 19% 76% 60% (no data) 83% Woodside Elementary 88% 92% (no data) (no data) 58% (no data) 92% Total 62% 82% 34% 64% 40% 31% 79%
Overall Asian Black Filipino Hispanic White
Pacific
Islander
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For example, English learning students in Portola Valley Elementary, Woodside Elementary, Menlo Park City Elementary, and Brisbane Elementary each met or exceeded mathematics test standards at a rate at least 50 percentage points below the overall test rate in each district. English learning students in Las Lomitas Elementary (54%) had the highest mathematics pass rates, followed by those in Belmont-Redwood Shores (42%) and Burlingame Elementary (40%).

Students with disabilities scored especially high on mathematics tests in Hillsborough Elementary, where 48% met or exceeded standards. Others in Belmont-Redwood Shores (43%) and Woodside Elementary (41%) had high pass rates as well. Students with disabilities in San Carlos Elementary and Las Lomitas Elementary school districts scored far below the overall student body: in these districts, students with disabilities met or exceeded mathematics test standards at 54 percentage points below the overall test rate.

In Jefferson Elementary and Ravenswood Elementary students experiencing homelessness passed math tests at a rate similar to their housed peers. In other districts, however, students experiencing homelessness often scored substantially lower. School districts with the widest math testing gaps between the overall student body and students experiencing homelessness were San Mateo-Foster City and Millbrae Elementary, with a 41 percentage point gap and 42 percentage point gap, respectively.
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Figure V-20.

Students who Met or Exceeded Math Testing Standards, by Special Case and District, 2018-2019
Source: California Department of Education, California Assessment of Student Performance and Progress, and Root Policy Research School District
Unified School Districts
Cabrillo Unified 34% 4% 5% 4% 9%
La Honda-Pescadero 31% 4% (no data) (no data) 2%
South San Francisco 44% 20% 25% 4% 18%
High & Elementary School Districts
Jefferson Union High School 37% 5% (no data) (no data) 6% Bayshore Elementary 27% 11% (no data) (no data) 9%
Brisbane Elementary 54% 4% (no data) (no data) 12%
Jefferson Elementary 37% 15% 36% (no data) 11%
Pacifica 57% 22% (no data) (no data) 17%
San Mateo Union High School 50% 10% (no data) (no data) 13% Burlingame Elementary 78% 40% (no data) (no data) 29%
Hillsborough Elementary 85% (no data) (no data) (no data) 48% Millbrae Elementary 58% 26% 16% (no data) 25%
San Bruno Park Elementary 41% 12% (no data) (no data) 9% San Mateo-Foster City 56% 11% 15% (no data) 14%
Sequoia Union High School 50% 3% 33% (no data) 9%
Belmont-Redwood Shores 79% 42% (no data) (no data) 43%
Las Lomitas Elementary 82% 54% (no data) (no data) 28%
Menlo Park City Elementary 83% 31% (no data) (no data) 38% Portola Valley Elementary 83% 14% (no data) (no data) 39% Ravenswood City Elementary 15% 5% 11% (no data) 2%
Redwood City Elementary 46% 14% (no data) 29% 14%
San Carlos Elementary 75% 24% (no data) (no data) 21%
Woodside Elementary 84% 27% (no data) (no data) 41%
English
Learners
Experiencing
homelessness Migrant
With
Overall Disabilities
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Students with extenuating circumstances also consistently scored lower in English testing than the overall student body.

For instance, English learning students in San Mateo Union High School District, Hillsborough Elementary School District, Sequoia Union High School District, Menlo Park City Elementary School District, and Portola Valley Elementary School District met or exceeded English test standards at a rate at least 60 percentage points below the overall test rate in each district. Hillsborough Elementary had the largest gap at 85 percentage points. Las Lomitas Elementary had the highest success rate among English learners, where 50% met or exceeded English testing standards.

However, students with disabilities in Las Lomitas Elementary and San Carlos Elementary school districts met or exceeded English test standards at rate 55 and 51 percentage points below the overall test rate, respectively. These were the largest gaps in the county.

Students with disabilities at Woodside Elementary did the best on English testing, where 56% passed or exceeded standards.

Among students experiencing homelessness, those at Sequoia Union High School were most likely to meet English testing standards, with 42% meeting or exceeding standards.

The school district with the widest gap between overall English test scores and scores among students experiencing homelessness was Cabrillo Unified with a 34 percentage point gap.

Just three districts reported English testing scores among migrant students. Redwood City Elementary had the highest pass rate at 34% and Cabrillo Unified had the lowest at 16%. 1229 of 1863
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Figure V-21.

Students who Met or Exceeded English Testing Standards, by Special Case and District, 2018-2019
Source: California Department of Education, California Assessment of Student Performance and Progress, and Root Policy Research School District
Unified School Districts
Cabrillo Unified 48% 9% 14% 16% 12%
La Honda-Pescadero 43% 9% (no data) (no data) 9%
South San Francisco 52% 21% 35% 20% 18%
High & Elementary School Districts
Jefferson Union High School 57% 3% (no data) (no data) 19% Bayshore Elementary 27% 3% (no data) (no data) 4%
Brisbane Elementary 64% 21% (no data) (no data) 16%
Jefferson Elementary 48% 16% 30% (no data) 15%
Pacifica 60% 12% (no data) (no data) 15%
San Mateo Union High School 70% 11% (no data) (no data) 27% Burlingame Elementary 80% 33% (no data) (no data) 33%
Hillsborough Elementary 85% (no data) (no data) (no data) 47% Millbrae Elementary 63% 19% 34% (no data) 23%
San Bruno Park Elementary 50% 14% (no data) (no data) 12% San Mateo-Foster City 62% 9% 33% (no data) 15%
Sequoia Union High School 68% 8% 42% (no data) 27%
Belmont-Redwood Shores 82% 31% (no data) (no data) 45%
Las Lomitas Elementary 86% 51% (no data) (no data) 31%
Menlo Park City Elementary 84% 21% (no data) (no data) 42% Portola Valley Elementary 87% 17% (no data) (no data) 37% Ravenswood City Elementary 22% 6% 16% (no data) 5%
Redwood City Elementary 54% 13% (no data) 34% 16%
San Carlos Elementary 80% 29% (no data) (no data) 28%
Woodside Elementary 88% 18% (no data) (no data) 56%
English
Learners
Experiencing
homelessness Migrant
With
Overall Disabilities
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Students who met university requirements. Many high schoolers in the county met admission standards for a University of California (UC) or California State University (CSU) school. Figure V-22 illustrates the percentage of cohort graduates who met admission requirements for a CSU or UC school according to California Department of Education data.

Of the high school districts in San Mateo County, Sequoia Union had the highest rate of graduates who met such admission standards, at 69%. On the other end of the spectrum, Cabrillo Unified and South San Francisco Unified had the lowest rates at 41%.

Figure V-22.

Students Meeting
California University
Admission
Standards, 2019-
2020
Source:

California Department of Education
and Root Policy Research.

Cabrillo Unified and South San Francisco Unified have experienced a decrease in the share of graduates meeting CSU or UC admission standards in recent years. For instance, in 2016-2017, 57% of South San Francisco Unified graduates met these standards, but this decreased by 16 percentage points by 2019-2020. Cabrillo Unified experienced a less drastic decrease over the same period, but the rate still shrunk by two percentage points.

Jefferson Union High School District had the most drastic increase in the share of graduates meeting CSU or UC standards: just 21% of students met these standards in 2016-2017 compared to 48% of students in 2019-2020. La Honda-Pescadero Unified School District experienced a 10 percentage point increase in this success rate over the same period.

Sequoia Union and San Mateo Union experienced more modest increases, but remain the districts with the highest rates of students meeting CSU and UC standards. 1231 of 1863
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Figure V-23.

Students Meeting
University
Admission
Standards, 2016-
2017 and 2019-2020
Source:

California Department of Education
and Root Policy Research.

Rates at which students met CSU or UC admissions standards varied substantially by race and ethnicity in 2019-2020. In all high school districts in San Mateo County, White and Asian students meet CSU and UC admissions standards at higher rates than the overall student population.

The largest gap is in South San Francisco Unified, where just 41% of students meet CSU or UC admissions standards, but 73% of Asian students meet those standards—a 32 percentage point gap.

On the other end of the spectrum, Black/African American students typically met CSU or UC admissions standards at lower-than-average rates. The largest gap was in San Mateo Union, where just 29% of Black/African American students met CSU or UC standards compared to 68% of students in the district overall.

Filipino students typically met admissions standards at rates similar to the overall student body. For instance, in Jefferson Union, San Mateo Union, and South San Francisco Unified, Filipino students are slightly more likely to have meet CSU and UC standards than the overall student population. In Sequoia Union, they are slightly less likely to have met admission standards than the overall student population. 1232 of 1863
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In La Honda-Pescadero, Hispanic students are slightly more likely to have met CSU or UC standards than the overall student body. However, in all other school districts, Hispanic students are less likely to have met CSU and UC standards than the overall student body.

The largest disparity is in San Mateo Union, where just 46% of Hispanic students meet the university admissions standards compared to 68% of students overall.

Finally, Pacific Islander students in Jefferson Union were slightly more likely to have met California university admissions standards compared to the overall student body, but in Sequoia Union and San Mateo Union they were substantially less likely. 1233 of 1863
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Figure V-24.

Students Meeting University Admission Standards, by Race and Ethnicity, 2019-2020
Source: California Department of Education and Root Policy Research As expected, students with extenuating circumstances were less likely to meet CSU or UC admissions standards than students in the county overall. In all school districts where data are available, students with disabilities, students experiencing homelessness, English learners, foster youth, and migrant students met CSU or UC admission standards at lower rates than the overall student population.
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English learners in Sequoia Union and San Mateo Regional met CSU or UC admission standards at higher rates than their peers in other school districts. However, compared to the overall student body within their own school districts, they had a larger gap than other districts. Namely, in Sequoia Union, 69% of students met admissions standards compared to just 32% of students learning English— a 37 percentage point gap.

Similarly, students with disabilities in Sequoia Union had the highest rate of meeting admissions standards (31%) compared to peers with disabilities in other districts, but also had the largest gap (38 percentage points) compared to the district’s overall student body.

Migrant students met admission standards at the lowest rate in South San Francisco Unified (27%) and at the highest rate in Sequoia Union (45%). However, in Cabrillo Unified, their rates were only eight percentage points lower than that of the overall student body, the smallest gap in the county.

Approximately 36% of students experiencing homelessness in Sequoia Union met CSU or UC admission standards, which was higher than rates in San Mateo Union (21%) and Jefferson Union (21%).

Just San Mateo Union and Sequoia Union had enough foster youth to report their rate of meeting CSU or UC admission standards. In Sequoia Union, 29% met admissions standards and 22% in San Mateo Union met admissions standards.
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Figure V-25.

Students Meeting
University
Admission
Standards, 2019-
2020
Source:

California Department of Education
and Root Policy Research.

Notes; La-Honda Pescadero Unified
is excluded from these data as they
do not report admission standards
data for these special groups, likely
due to small sample size.

College-going rates. The college-going rate is defined as the percentage of public high school students who completed high school in a given year and subsequently enrolled in any public or private postsecondary institution (in-state or out-of-state) in the United States within 12 or 16 months of completing high school.

Most school districts in the county have a college-going rate at 70% or higher. San Mateo Union had the highest college-going rate at 77%. La Honda-Pescadero School District is the notable exception, with just 32% of graduates attending college within 12 or 16 months. 1236 of 1863
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Figure V-26.

College-Going
Rates, 2017-2018
Source:

California Department of Education
and Root Policy Research.

As shown in Figure V-27, La Honda-Pescadero School District previously had the highest college-going rate of all the county’s high school districts, with an 80% college-going rate in 2014-2015 and a 93% college-going rate in 2015-2016. The district experienced a rapid decline in college-going rates, starting in 2016-2017. However, La Honda-Pescadero has especially small sample sizes. For instance, the district had just 26 twelfth-graders in the 2017-2018 school year, meaning that just a couple students going to college (or not) drastically alters the college-going rate in La Honda-Pescadero. All other high school districts in the county have maintained relatively consistent college-going rates. 1237 of 1863
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Figure V-27.

College-Going
Rates, 2014-2015 to
2017-2018
Source:

California Department of Education
and Root Policy Research.

Within each of the high school districts, college-going rates vary by race and ethnicity.  In every district, White students have a higher college-going rate than Hispanic students, but the largest gaps are in South San Francisco United, where 91% of White students go to college compared to just 68% of Hispanic students, a 23 percentage point gap. Jefferson Union has the smallest gap between the two groups: 77% of White students go to college compared to 71% of Hispanic students.  Among Black/African American students, those at San Mateo Union have the highest college-going rate at 82%. Those at Jefferson Union have the lowest at just 53%, which is 24 percentage points lower than that of White students and 34 percentage points lower than that of Asian students.
 Overall, Asian students have among the highest college-going-rates in the county. The rate is especially high in South San Francisco Unified, where 92% go to college. The rate is lowest in Sequoia Union High School District, where 84% go to college. 1238 of 1863
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 Filipino students also have generally high rates of college-going. The highest collegegoing rate among Filipino students is in Sequoia Union (86%) and the lowest is in South San Francisco Unified (73%).
 College-going rates for Pacific Islander students vary substantially by district. For instance, in Sequoia Union 54% go to college, but in South San Francisco Unified 92% go to college.

Figure V-28.

College-going Rates by Race and Ethnicity, 2017-18
Note: Cabrillo Unified and La Honda- Pescadero Unified are not included here because they do not report the data, likely due to small sample sizes.
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Source: California Department of Education and Root Policy Research College-going rates are lower for students with disabilities and those learning English compared to the overall student population across the county.  For instance, the largest gap between overall college-going rates and English learners’ college-going rates is in South San Francisco Unified, where just 52% of English learning students go to college as opposed to 74% of the overall student population— a 22 percentage point gap. Among English learners, San Mateo Union High School District had the highest college-going rate, where 63% of English learners go to college.  Among students with disabilities, South San Francisco Unified also had the largest gap, where 59% of students with disabilities went to college compared to 74% of the overall student population — a 15 percentage point gap. Jefferson Union, on the other hand, had a relatively high college-going rate among students with disabilities that was not very different from the district’s overall college-going rate: 71% went to college which is just five percentage points lower than the district’s overall student population.

Figure V-29.

College-going Rates
for English Learners
and Students with
Disabilities, 2017-
2018
Note:

Cabrillo Unified and La HondaPescadero Unified are not included here because they do not report the
data, likely due to small sample
sizes.

Source:

California Department of Education
and Root Policy Research.

Gaps in college enrollment by race, ethnicity, disability status, or English learning have stark financial consequences for students in the long-term. Figure V-30 illustrates median annual earnings by educational attainment. College degrees are especially important in San Mateo County: those with a bachelor’s degree in the county earn 115% more than those with a high school diploma. This gap is wider in San Mateo County than in other parts of California and nationwide. The differences between high-school graduate earnings and bachelor's degree earnings are around 100% in California and 76% in the US overall. 1240 of 1863
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Figure V-30.

Median Annual Earnings by Educational Attainment, 2019
Source: 5-year 2019 American Community Surveys Data.

Unfortunately, the gap between high school graduates’ and college graduates’ earnings have been increasing in San Mateo County. As illustrated in Figure V-31, median earnings for high school graduates increased by just 15% over the last decade (from $31,816 to $36,747) while earnings for college graduates increased by 29% over the same period (from $61,485 to $79,080).
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Figure V-31.

Median Annual Earnings by Educational Attainment in San Mateo County, 2010 to 2019
Source: 5-year American Community Surveys Data.

Because income disparities between college graduates and high school graduates have been increasing, it is increasingly important that school districts in San Mateo County address differences in college-going rates stratified by race, ethnicity, and extenuating circumstances.

Barriers to Success
Many students are unable to achieve academic success because of barriers in home and school. This section explores the available indicators of barriers to success, including chronic absenteeism and dropout rates. It also describes inequities in discipline rates by 1242 of 1863
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race and ethnicity, which has been linked both to discrimination by education professionals as well as a major barrier to students’ future success.

Chronic absenteeism. Academic studies have found that if a student is chronically absent, it reduces their math and reading achievement outcomes, educational engagement, and social engagement.12 Chronic absenteeism also has spillover effects and negatively impacts students who themselves are not chronically absent. For instance, one study found that students suffer academically from having chronically absent classmates— as exhibited across both reading and math testing outcomes.13 Students are considered chronically absent if they were absent for 10% or more of the days during a school year. Note, however, students are exempt from chronic absenteeism calculations if they receive instruction through a home or hospital instructional setting, are attending community college full-time, or were not expected to attend more than 31 days.

In the county overall, 10% of students were chronically absent during the 2018-2019 school year.
14 This is a slight increase from the 2016-2017 school year, where just 9% of students overall were chronically absent.

Chronic absenteeism rates were higher in districts with a large number of students experiencing economic and housing precarity. For instance, Ravenswood Elementary, which has a 30% rate of homelessness among students, had one of the higher rates of chronic absenteeism at 16%. La Honda-Pescadero and Sequoia Union high school districts also had high rates of chronically absent students at 16% and 17%, respectively.

When disaggregating by race and ethnicity, just 3% of Asian students were chronically absent, and 7% of White and Filipino students were chronically absent. On the other end of the spectrum, Pacific Islander students (26%), Black/African American students (18%), and Hispanic students (15%) had notably higher rates of chronic absenteeism than the overall student population (10%). Chronic absenteeism among Pacific Islander students has increased in recent years, as illustrated in Figure V-32. 12 Gottfried, Michael A. "Chronic absenteeism and its effects on students’ academic and socioemotional outcomes." Journal of Education for Students Placed at Risk (JESPAR) 19.2 (2014): 53-75. 13 Gottfried, Michael A. "Chronic absenteeism in the classroom context: Effects on achievement." Urban Education 54.1 (2019): 3-34.
14 Because of the physical school closures during the COVID-19 pandemic, the California Department of Education determined that 2019–2020 absenteeism data are not valid, therefore, we present data from the 2018-2019 school year.
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Figure V-32.

Chronic
Absenteeism by
Race/Ethnicity,
2016-2017 to 2018-
2019
Source: California Department of
Education and Root Policy
Research
Chronic absenteeism among Pacific Islander students was especially pronounced in San Mateo-Foster City school district where there was a 26 percentage point gap between chronic absenteeism rates for Pacific Islander students (32%) and the overall student body (6%). Other districts had similarly large gaps, including San Bruno Park Elementary (20 percentage points) and South San Francisco Unified (18 percentage points).

Some districts had larger gaps in absenteeism rates between Black/African American students and the overall population. For instance, in San Carlos Elementary, 4% of the overall student body is chronically absent compared to 27% of Black/African American students— a 23 percentage point gap. Jefferson Elementary school district had a 17 percentage point gap between their overall chronic absenteeism rate (12%) and their chronic absenteeism rate among Black/African American students (28%).

Among White students, Bayshore Elementary School District was a major outlier, where 46% of White students were chronically absent compared to just 12% of the total student population. However, it is important to note that this represents a very small sample of White students: just 3% of students at Bayshore Elementary are White, one of lowest in the county.
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Figure V-33.

Chronic Absenteeism by District and Race/Ethnicity, 2018-2019 Source: California Department of Education and Root Policy Research In most districts, chronic absenteeism is higher among students with disabilities. In fact, only Bayshore Elementary’s students with disabilities had a lower rate of chronic absenteeism than the overall student body. In all other districts, students with disabilities were more likely to be chronically absent than the overall student population. This was particularly true in Sequoia Union High School District, Jefferson Union High School District, and San Mateo Union High School District, which had gaps between the overall School District
Unified School Districts
Cabrillo Unified 10% 5% (no data) 5% 11% (no data) 10%
La Honda-Pescadero 16% (no data) (no data) (no data) 14% (no data) 18% South San Francisco 13% 4% 16% 7% 17% 31% 12%
High & Elementary School Districts
Jefferson Union High School 15% 8% 22% 11% 22% 18% 15%
Bayshore Elementary 12% 5% 12% 0% 18% 19% 46%
Brisbane Elementary 12% 3% (no data) 12% 17% (no data) 17% Jefferson Elementary 12% 5% 28% 6% 13% 25% 23%
Pacifica 7% 4% 12% 6% 9% 21% 7%
San Mateo Union High School 10% 3% 18% 4% 17% 21% 9%
Burlingame Elementary 5% 2% 15% 5% 10% 20% 5%
Hillsborough Elementary 4% 1% (no data) 4% 4% (no data) 6% Millbrae Elementary 10% 3% 6% 17% 16% 26% 14%
San Bruno Park Elementary 12% 5% 10% 4% 14% 32% 9%
San Mateo-Foster City 6% 2% 9% 2% 10% 32% 4%
Sequoia Union High School 17% 6% 23% 8% 23% 33% 10%
Belmont-Redwood Shores 5% 3% 8% 5% 12% 17% 5%
Las Lomitas Elementary 4% 2% 0% (no data) 7% (no data) 3% Menlo Park City Elementary 3% 1% 8% 7% 5% 14% 3%
Portola Valley Elementary 4% 0% (no data) (no data) 6% (no data) 3% Ravenswood City Elementary 16% 0% 20% (no data) 15% 24% 21% Redwood City Elementary 10% 2% 19% 3% 12% 18% 4%
San Carlos Elementary 4% 2% 27% 8% 7% (no data) 3%
Woodside Elementary 8% 0% 0% (no data) 12% (no data) 7% Total 10% 3% 18% 7% 15% 26% 7%
Total Asian Black Filipino Hispanic
Pacific
Islander White
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absenteeism rate and the absenteeism rate among students with disabilities of 13, 12, and 11 percentage points, respectively.

Rates of chronic absenteeism were also higher among English learners than the general population in most districts (with the exception of Ravenswood City Elementary and Jefferson Elementary). Woodside Elementary and Sequoia Union High School districts both had 14 percentage point gaps between absenteeism rates of English learners and the overall student body.

In every school district where the data are available, foster youth had higher rates of chronic absenteeism than the overall population. This was especially true in Sequoia Union High School District, where 63% of foster youth were chronically absent compared to just 17% of the overall student body.

Similarly, in almost all districts with available data, students experiencing homelessness had higher rates of chronic absenteeism than the overall student body. The chronic absenteeism rate among students experiencing homelessness was highest in Burlingame Elementary at 64%.

Migrant students were chronically absent at rates similar to or lower than the total student body in all districts with reported data.
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Figure V-34.

Chronic Absenteeism by District and Extenuating Circumstance, 2018-2019 Source: California Department of Education and Root Policy Research Dropout rates. As previously indicated, workers without a high school degree have the lowest annual earnings compared to others at higher levels of educational attainment. In addition to the economic and housing precarity associated with low earnings, low earnings also often lead to increased incentives to participate in criminal activity. In fact, one study School District
Unified School Districts
Cabrillo Unified 10% 12% 23% 9% (no data) 18%
La Honda-Pescadero 16% 16% (no data) (no data) (no data) 22% South San Francisco 13% 14% 47% 13% 49% 18%
High & Elementary School Districts
Jefferson Union High School 15% 27% 33% (no data) 36% 28% Bayshore Elementary 12% 19% (no data) (no data) (no data) 11% Brisbane Elementary 12% 18% (no data) (no data) (no data) 18% Jefferson Elementary 12% 10% 21% (no data) 24% 16%
Pacifica 7% 11% (no data) (no data) (no data) 14%
San Mateo Union High School 10% 21% 50% (no data) 53% 21% Burlingame Elementary 5% 8% 64% (no data) (no data) 12% Hillsborough Elementary 4% 6% (no data) (no data) (no data) 8% Millbrae Elementary 10% 12% 5% (no data) (no data) 12%
San Bruno Park Elementary 12% 12% (no data) (no data) 18% 20% San Mateo-Foster City 6% 8% 15% (no data) 17% 13%
Sequoia Union High School 17% 31% 52% 16% 63% 29%
Belmont-Redwood Shores 5% 11% (no data) (no data) (no data) 10% Las Lomitas Elementary 4% 6% (no data) (no data) (no data) 5% Menlo Park City Elementary 3% 5% (no data) (no data) (no data) 9% Portola Valley Elementary 4% 3% (no data) (no data) (no data) 9% Ravenswood City Elementary 16% 16% 19% 17% 23% 21%
Redwood City Elementary 10% 12% 30% 6% 32% 16%
San Carlos Elementary 4% 8% 23% (no data) (no data) 11% Woodside Elementary 8% 22% (no data) (no data) (no data) 10% Total
English
Learners
Experiencing
homelessness Migrant
With
Disabilities
Foster
Youth
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suggest that high school dropouts are 3.5 times more likely than high school graduates to be imprisoned at some point during their lifetime.15 Another study found that raising the high school completion rate by one percent for all men ages 20 through 60 would save the US $1.4 billion annually in crime related costs.16 Dropping out of high school also has adverse health costs: for instance, research has shown that high school dropouts are more likely to smoke and have a marijuana disorder in adulthood.17 For these reasons, reducing high school dropout rates in San Mateo County is pivotal to the health and economic prosperity of the community.

In this report, dropout rates shown for high school districts with available data and are defined as the percentage of cohort students who did not graduate with a regular high school diploma, did not complete high school, and are not still enrolled as a "fifth year senior".

In the 2019-2020 academic year, dropout rates were highest in Sequoia Union High School District, where 10% of students dropped out. This is similar to South San Francisco Unified, where 9% of students dropped out. In both these districts, and in Cabrillo Unified, dropout rates have increased since 2016-2017.

Dropout rates have decreased by one percentage point over the same period in San Mateo Union High School District, from 5% to 4%. Jefferson Union had the lowest dropout rate in the county at just 3%, which after slightly higher rates in 2017-18 and 2018-19, is the same as its 2016-2017 rate.
15 Monrad, Maggie. "High School Dropout: A Quick Stats Fact Sheet." National High School Center (2007). 16 U.S. Department of Justice, Bureau of Justice Statistics. (2002). Correctional populations in the United States, 1998 (NCJ-192929). Washington: U.S. Government Printing Office. 17 Gonzalez, Jennifer M. Reingle, et al. "The long-term effects of school dropout and GED attainment on substance use disorders." Drug and alcohol dependence 158 (2016): 60-66. 1248 of 1863
ROOT POLICY RESEARCH SECTION V, PAGE 53
Figure V-35.

Dropout Rates by
District, 2016-2017 to
2019-2020
Note: La Honda-Pescadero Unified
School District is excluded
from these data.

Source: California Department of
Education and Root Policy
Research
In all school districts in the county, dropout rates are higher for boys than for girls.

Jefferson Union had the smallest gender gap, where 3% of girls dropped out and 4% of boys dropped out. Sequoia Union had the widest gender gap, where 13% of boys dropped out compared to just 7% of girls.

Figure V-36.

Dropout Rates by
Gender, 2019-2020
Note: La Honda-Pescadero Unified
School District is excluded
from these data.

Source: California Department of
Education and Root Policy
Research
Pacific Islander, Black/African American, and Hispanic students in the county often had higher dropout rates than those in other racial and ethnic groups. 1249 of 1863
ROOT POLICY RESEARCH SECTION V, PAGE 54
 In Sequoia Union High School District, dropout rates were highest among Pacific Islander students, where 20% dropped out in the 2019-2020 academic year. Dropout rates were also especially high among Hispanic and Black/African American students in Sequoia Union, at 16% and 12% respectively.
 In districts with lower dropout rates, for instance, Jefferson Union, the highest dropout rates still found among Black/African American (7%) and Hispanic students (6%).  Notably, however, in South San Francisco Unified, White students were more likely to drop out than any other racial or ethnic group. In fact, 12% of White students dropped out compared to 11% of Hispanic students, 5% of Filipino students, and 3% of Asian students. Data for Black/African American and Pacific Islander students were not available for South San Francisco Unified due to small sample sizes.

Figure V-37.

Dropout Rates by Race, 2019-2020
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ROOT POLICY RESEARCH SECTION V, PAGE 55
Source: California Department of Education and Root Policy Research In all school districts in the county, students with disabilities, students experiencing homelessness, foster youth, and students learning English had higher dropout rates than the overall population.
 Among students with disabilities, the highest dropout rate was in Sequoia Union, where 24% dropped out. The gap between overall dropout rates and dropout rates among students with disabilities was wide in Sequoia Union at 14 percentage points.  Cabrillo Unified, on the other hand, had less than a one percentage point gap between the dropout rate of overall students (6%) and students with disabilities (6%).  Among students learning English, Sequoia Union had the highest dropout rate at 27%, while Jefferson Union had the lowest dropout rate at 8%.  Sequoia Union also had the highest rate of dropout among students experiencing homelessness at 29% while Jefferson Union, again, had the lowest at 15%.  Foster Youth in Sequoia Union had an exceptionally high dropout rate a t 40%. San Mateo Union is the only other district in the county which reported these data in 2019- 2020, and found only 18% of foster youth dropped out.
 Migrant students at South San Francisco Unified actually dropped out at a rate slightly lower than the general student body: just 8% of migrant students dropped out compared to 9% of the overall student body. However, those in Cabrillo Unified were 11 percentage points more likely than the total student body to dropout. 1251 of 1863
ROOT POLICY RESEARCH SECTION V, PAGE 56
Figure V-38.

Dropout Rates by Extenuating Circumstance, 2019-2020
Source: California Department of Education and Root Policy Research Disproportionate discipline rates. Strict discipline policies may stigmatize suspended students and expose them to the criminal justice system at a young age, setting them up for limited economic and social success down the line. Research has found that suspensions not only negatively affect the suspended students, but also their peers. 1252 of 1863
ROOT POLICY RESEARCH SECTION V, PAGE 57
Students in schools with higher suspension rates are more likely to drop out or school and less likely to attend a four-year college.18
Other academic studies have found that students from African American and Latino families are more likely than their White peers to receive expulsion or out of school suspension as consequences for the same or similar problem behavior.19 This means that Black/African American and Hispanic students suffer more of the economic and social consequences than their White peers for the same behaviors.

Luckily, in every high school district in San Mateo County, suspension rates have decreased since 2011-2012. La Honda-Pescadero School District experienced the largest decrease: it was the district with the highest suspension rate in 2011-2012 at 10%, but now has the lowest suspension rate at just 1% in 2019-2020. San Mateo Union also experienced a rapid decrease in suspension rates over the same period, with a rate of 9% in 2011-2012 to a rate of 3% in 2019-2020.
18 Bacher-Hicks, Andrew, Stephen B. Billings, and David J. Deming. The school to prison pipeline: Long-run impacts of school suspensions on adult crime. No. w26257. National Bureau of Economic Research, 2019. 19 Skiba, Russell J., et al. "Race is not neutral: A national investigation of African American and Latino disproportionality in school discipline." School Psychology Review 40.1 (2011): 85-107. 1253 of 1863
ROOT POLICY RESEARCH SECTION V, PAGE 58
Figure V-39.

Suspension Rates, 2011-2012 to 2019-2020
Source: California Department of Education and Root Policy Research In many school districts across San Mateo County, Hispanic students are disciplined at disproportionately higher rates compared to their peers. Figure V-40 compares each racial/ethnic group’s share of suspensions to their share of the overall student population.  In all districts except for La Honda-Pescadero, Hispanic students make up a larger share of suspensions than their overall share of the student body. For instance, in San Mateo Union, 34% of students are Hispanic, but 66% of suspended students are Hispanic, making a 32 percentage point overrepresentation gap.  In most districts, Black and Pacific Islander students are also overrepresented in terms of suspension rates, but these rates are slight compared to those of Hispanic students.

For instance, in Sequoia Union, just 2% of the student body identified as Pacific Islander but 8% of suspended students were Pacific Islander.  Asian and Filipino students were underrepresented in terms of suspension rates. For example, in Jefferson Union High School District, 31% of students identified as Filipino but just 10% of suspended students were Filipino, a 21 percentage point gap. In San 1254 of 1863
ROOT POLICY RESEARCH SECTION V, PAGE 59
Mateo Union High School, 22% of students identified as Asian but just 5% of suspended students were Asian, a 17 percentage point gap.  White students were also underrepresented in discipline rates in most districts except for La Honda-Pescadero, where they were overrepresented by 30 percentage points.

They were substantially underrepresented in Cabrillo Unified (with a gap of 21 percentage points) and Sequoia Union (18 percentage points). 1255 of 1863
ROOT POLICY RESEARCH SECTION V, PAGE 60
Figure V-40.

Suspension Rates by Race and Ethnicity, 2019-2020
Notes: the percentage of suspensions and shares of racial groups do not sum to 100% because we exclude students with no reported race, with more than one reported race, where districts did not report racial/ethnic data due to small sample sizes. Gaps of 15 percentage points or more are highlighted.

Source: California Department of Education and Root Policy Research School District
Asian Students
Share of Student Body 1% 14% 22% 9% 13%
Share of Suspensions 1% 7% 5% 1% 3%
Gap 0% -7% -17% -8% -10%
Black Students
Share of Student Body 1% 1% 3% 1%
Share of Suspensions 5% 1% 6% 2%
Gap 4% 0% 3% 1%
Filipino Students
Share of Student Body 1% 31% 6% 2% 23%
Share of Suspensions 0% 10% 2% 0% 9%
Gap -1% -21% -4% -2% -14%
Hispanic Students
Share of Student Body 52% 32% 61% 34% 41% 48%
Share of Suspensions 79% 46% 33% 66% 62% 69%
Gap 27% 14% -28% 32% 21% 21%
Pacific Islander Students
Share of Student Body 1% 2% 2% 2%
Share of Suspensions 4% 4% 8% 3%
Gap 3% 2% 6% 1%
White Students
Share of Student Body 40% 14% 37% 26% 38% 7%
Share of Suspensions 19% 16% 67% 14% 20% 7%
Gap -21% 2% 30% -12% -18% 0%
Cabrillo
Unified
Jefferson
Union
High
La HondaPescadero
San
Mateo
Union
High
Sequoia
Union
High
South San
Francisco
Unified
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ROOT POLICY RESEARCH SECTION V, PAGE 61
Staff demographics. Diversity of school staff has been shown to improve outcomes for students of color. For instance, one recent study found that students are less likely to be removed from school as punishment when they and their teachers are the same race.

This effect is driven almost entirely by black students, especially black boys, who are markedly less likely to be subjected to exclusionary discipline when taught by black teachers. There is little evidence of any benefit for white students of being matched with white teachers.20 Other research in California has found that, when students have a teacher of their race, they are more likely to attend class, therefore reducing chronic absenteeism.21 Even more studies have found that having a teacher of a student’s own race substantially improves their math and reading achievement.22 In San Mateo County, the demographics of faculty and staff are fairly similar to that of its students. Figure V-41 illustrates the share of the county’s faculty and staff who are Asian, Black/African American, Hispanic, Filipino, Pacific Islander, and White, and compares those shares to the racial/ethnic breakdown of the county’s student body.

There is a slightly larger share of White and Black/African American staff than students, meaning that Black/African American and White student groups are more likely to interact with same-race staff and faculty than other racial groups. Asian students are less likely to interact with a same-race staff of faculty member: 17% of the student body is Asian compared to just 8% of staff and faculty.
20 Lindsay, Constance A., and Cassandra MD Hart. "Teacher race and school discipline: Are students suspended less often when they have a teacher of the same race?." Education Next 17.1 (2017): 72-79. 21 Gottfried, Michael, J. Jacob Kirksey, and Tina L. Fletcher. "Do High School Students With a Same-Race Teacher Attend Class More Often?." Educational Evaluation and Policy Analysis (2021): 01623737211032241. 22 Dee, T. S. (2004). Teachers, race, and student achievement in a randomized experiment. Review of economics and statistics, 86(1), 195-210.
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ROOT POLICY RESEARCH SECTION V, PAGE 62
Figure V-41.

Staff and Student
Demographics,
2020-2021
Notes: Percentages do not always
sum to 100% because we
do not show shares of staff
with no reported race, with
more than one reported
race, or Native American
staff.

Source: California Department of
Education and Root Policy
Research
Since 2011-2012, the county’s school districts have diversified in that there has been a 13 percentage point decrease in the share of White faculty and staff and a 10 percentage point increase in Hispanic faculty and staff. However, there has been a slight decrease (by two percentage points) in the share of faculty and staff who identify as Black/African American. There has been a two percentage point increase in the share of Asian and Filipino faculty and staff, and a one percent increase in the share of Pacific Islander faculty and staff.
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ROOT POLICY RESEARCH SECTION V, PAGE 63
Figure V-42.

Faculty and Staff Demographics, 2011-2012 to 2020-2021
Notes: Percentages do not always sum to 100% because we do not show shares of staff with no reported race, with more than one reported race, or Native American staff.

Source: California Department of Education and Root Policy Research Figure V-43 illustrates faculty and staff racial and ethnic diversity for the 2020-2021 school year by district.
 Portola Valley has the least diverse faculty and staff in the county, with 59% identifying as White.
 Ravenswood Elementary has the most diverse faculty and staff: the district has the highest share of Pacific Islander (5%), Black/African American (12%) and Hispanic (72%) faculty and staff.
 South San Francisco Unified School District has the highest share of Asian faculty and staff at 14%.
 Brisbane Elementary and Jefferson Elementary have the highest shares of Filipino faculty and staff at 28%.
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ROOT POLICY RESEARCH SECTION V, PAGE 64
Figure V-43.

Faculty and Staff Race/Ethnicity, by District, 2020-2021 Notes: Percentages do not always sum to 100% because we do not show shares of staff with no reported race, with more than one reported race, or Native American staff.

Source: California Department of Education and Root Policy Research School District
Unified School Districts
Cabrillo Unified 0% 1% 1% 46% 0% 51%
La Honda-Pescadero 0% 5% 5% 39% 0% 51%
South San Francisco 14% 3% 16% 34% 2% 28%
High & Elementary School Districts
Jefferson Union High School 3% 3% 13% 26% 1% 43%
Bayshore Elementary 13% 4% 17% 61% 0% 4%
Brisbane Elementary 7% 0% 28% 20% 4% 42%
Jefferson Elementary 13% 3% 28% 25% 0% 29%
Pacifica 7% 2% 8% 23% 2% 54%
San Mateo Union High School 11% 5% 6% 34% 3% 40%
Burlingame Elementary 8% 5% 11% 27% 3% 45%
Hillsborough Elementary 2% 1% 7% 20% 1% 55%
Millbrae Elementary 13% 3% 9% 25% 0% 48%
San Bruno Park Elementary 4% 2% 13% 26% 4% 48%
San Mateo-Foster City 13% 2% 7% 33% 3% 37%
Sequoia Union High School 2% 12% 2% 54% 4% 26%
Belmont-Redwood Shores 13% 2% 3% 39% 0% 42%
Las Lomitas Elementary 7% 7% 0% 42% 0% 42%
Menlo Park City Elementary 3% 1% 3% 28% 1% 40%
Portola Valley Elementary 4% 4% 0% 33% 0% 59%
Ravenswood City Elementary 2% 12% 1% 72% 5% 3%
Redwood City Elementary 4% 5% 2% 65% 1% 21%
San Carlos Elementary 8% 6% 3% 37% 1% 42%
Woodside Elementary 12% 8% 0% 30% 0% 49%
Total 8% 5% 8% 40% 2% 35%
Asian Black Filipino Hispanic White
Pacific
Islander
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ROOT POLICY RESEARCH SECTION V, PAGE 65
Figure V-44 illustrates the gap between faculty/staff representation and the student body.

For instance, at San Bruno Park Elementary, 15% of the students are White while 48% of the faculty/staff are White, leaving a 33 percentage point gap.

If schools are striving for a distribution of faculty/staff that reflects the racial and ethnic distribution of their student body, the closer to a 0 percentage point gap, the better.

Schools like San Bruno Park Elementary fall short of meeting this goal, in that there is a large overrepresentation of White faculty/staff compared to the student body. Many other districts have a large overrepresentation of White faculty/staff, including Millbrae Elementary (32 percentage point gap), Jefferson Union High School District (29 percentage point gap), and South San Francisco Unified School District (22 percentage points). There are just a few school districts where the share of White students is higher than the share of White faculty, particularly Woodside Elementary and Menlo Park City Elementary, both with a 15 percentage point gap.

Across most school districts, the share of Asian students is larger than the share of Asian faculty/staff. This suggests that Asian students are less likely than their peers to interact with a same-race teacher or staff member. The largest disparity is in Millbrae Elementary, where just 13% of the faculty identify as Asian compared to 46% of the student body, a 33 percentage point gap.

In many school districts, there is a dearth of Hispanic faculty and staff. For instance, in La Honda-Pescadero, 63% of students are Hispanic compared to 39% of faculty, a 24 percentage point gap. In other districts, however, there is a larger share of Hispanic faculty/staff than students. In Las Lomitas Elementary, for instance, 13% of students are Hispanic and 42% of faculty/staff are Hispanic. Recall that Las Lomitas Elementary commonly has high-performing English language learnings students. This may be partly due to the district’s large portion of Hispanic faculty/staff.

Though district wide there are approximately the same portions of Filipino students as there are faculty/staff, Jefferson Union High School stands out as a district where Filipino students are less likely to interact with a same-race teacher or staff member. In Jefferson Union, 29% of students are Filipino compared to just 13% of faculty/staff.

In all districts, there only very small gaps in the share of students that identify as Pacific Islander and the share of faculty/staff that identify as Pacific Islander. All in all, they are represented in approximately equal proportions.
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ROOT POLICY RESEARCH SECTION V, PAGE 66
Figure V-44.

Difference Between Staff and Student Populations, by District, 2020-2021 Notes: The figure shows percentage point gaps in student representation versus faculty/staff representation (calculated as the share of faculty/staff minus the share of students).

Source: California Department of Education and Root Policy Research School District
Unified School Districts
Cabrillo Unified -1% 1% 0% -6% 0% 11%
La Honda-Pescadero 0% 5% 4% -24% 0% 16%
South San Francisco 0% 2% -7% -14% 0% 22%
High & Elementary School Districts
Jefferson Union High School -12% 2% -16% -5% 0% 29%
Bayshore Elementary -6% 1% -4% 20% -4% 1%
Brisbane Elementary -13% -1% 16% -8% 4% 18%
Jefferson Elementary -6% 1% 3% -11% -1% 18%
Pacifica -1% 1% -1% -3% 2% 15%
San Mateo Union High School -12% 4% 1% 2% 1% 12%
Burlingame Elementary -19% 5% 8% 11% 3% 4%
Hillsborough Elementary -30% 1% 5% 15% 1% 7%
Millbrae Elementary -33% 2% 3% 5% -2% 32%
San Bruno Park Elementary -12% 1% 3% -15% -1% 33%
San Mateo-Foster City -13% 1% 4% -4% 1% 16%
Sequoia Union High School -7% 10% 1% 9% 2% -9%
Belmont-Redwood Shores -19% 1% 0% 27% -1% 8%
Las Lomitas Elementary -11% 6% -1% 29% 0% -11%
Menlo Park City Elementary -10% 0% 2% 11% 0% -15%
Portola Valley Elementary -2% 4% 0% 19% 0% -7%
Ravenswood City Elementary 2% 7% 1% -12% -2% 2%
Redwood City Elementary 0% 4% 1% -5% 0% 2%
San Carlos Elementary -10% 5% 2% 23% 1% -7%
Woodside Elementary 8% 6% 0% 14% -1% -15%
Total -9% 4% 0% 2% 0% 9%
Asian Black Filipino Hispanic
Pacific
Islander White
1262 of 1863
ROOT POLICY RESEARCH CA FAIR HOUSING LAWS, PAGE 1
Appendix I
State Fair Housing Laws and Regulations
This appendix summarizes key state laws and regulations related to mitigating housing discrimination and expanding housing choice.

California Fair Employment and Housing Act (FEHA) (Part 2.8 (commencing with Section 12900) of Division 3 of Title 2) is the state fair housing law that prohibits those engaged in the housing business—landlords, real estate agents, home sellers, builders, mortgage lenders, and others—from discriminating against tenants or homeowners.

California law protects individuals from illegal discrimination by housing providers based on:
➢ Race, color
➢ Ancestry, national origin
➢ Citizenship, immigration status
➢ Primary language
➢ Age
➢ Religion
➢ Disability, mental or physical
➢ Sex, gender
➢ Gender identity, gender expression
➢ Marital status
➢ Familial status
➢ Source of income
➢ Military or veteran status
Government Code section 65008. Covers actions of a city, county, city and county, or other local government agency, and makes those actions null and void if the action denies an individual or group of individuals the enjoyment of residence, landownership, tenancy, or other land use in the state because of membership in a protected class, the method of financing, and/or the intended occupancy.
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ROOT POLICY RESEARCH CA FAIR HOUSING LAWS, PAGE 2
 For example, a violation under Government Code section 65008 may occur if a jurisdiction applied more scrutiny to reviewing and approving an affordable development as compared to market-rate developments, or multifamily housing as compared to single family homes.
 Government Code section 65008, subdivision (e), authorizes preferential treatment of affordable housing
Government Code section 8899.50 requires all public agencies to administer programs and activities relating to housing and community development in a manner to affirmatively further fair housing and avoid any action that is materially inconsistent with its obligation to affirmatively further fair housing.

Government Code section 11135 et seq. requires full and equal access to all programs and activities operated, administered, or funded with financial assistance from the state, regardless of one’s membership or perceived membership in a protected class.

Density Bonus Law (Gov. Code, section 65915) requires California jurisdictions to adopt ordinances that specify how density bonuses will be offered to incentivize affordable housing. The state law contains the minimum specifications for density bonuses.

Housing Accountability Act (Gov. Code, section 65589.5) prohibits local agencies from disapproving housing developments, including farmworker housing and emergency shelters, or requiring conditions that make such housing infeasible except under certain conditions specified in the law.

No-Net-Loss Law (Gov. Code, section 65863) is meant to ensure that development opportunities remain available throughout a jurisdiction’s regional housing need allocation (RHNA) period, especially for low and moderate income households. It prohibits jurisdictions from lowering residential densities without substantial evidence.

Least Cost Zoning Law (Gov. Code, section 65913.1) requires jurisdictions to designate and zone sufficient vacant land for residential use with sufficient standards in relation to growth projections.

Excessive subdivision standards (Gov. Code, section 65913.2) prohibits jurisdictions from imposing design criteria that make residential development infeasible.

Limits on growth controls (Gov. Code, section 65302.8) describes how flood plains are used in comprehensive planning and zoning.

Housing Element Law (Gov. Code, section 65583, esp. subds. (c) (5), (c) (10) governs state-required housing elements.
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Appendix J
Summary of Public Engagement and
Community Correspondence
Included in Appendix J:
a. City of San Bruno Housing Element Workshop – April 8, 2021: Survey Responses b. City of San Bruno Housing Element Workshop

1. Workshop #1 White Board Exercise – May 4, 2022

2. Workshop #2 White Board Exercise – May 26, 2022
c. Survey Data from the City of San Bruno Housing Element Survey which was open from March 3, 2022 to June 24, 2022
d. 21 Elements Stakeholder Listening Sessions Summary
e. Community Correspondence received by the city as of June 24, 2022

1. Letter from YIMBY Law – Greenbelt Alliance dated April 21, 2022

2. Letter from San Francisco International Airport dated May 6, 2022

3. Letter from Housing Leadership Council dated June 24, 2022

4. Email from Paul Wapensky dated May 24, 2022
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Survey Responses - CCM2 (4.08.21)
Question
(x)
Overall,
how would
you rate
this virtual
meeting?
What did you like about the meeting? Is there anything we could improve?
4 - Very
Good
Good introduction to the subject;
seeing the current and expected RHNA
numbers was helpful.
4 - Very
Good
I loved that most people seemed focus
on equity and social justice, and
serving our lower-income community.

That's the whole reason I showed up,
I'm glad many others did too!
More time to discuss would have
been great, our group was still on
a roll when the breakout session
ended. Also, the 6-7:30 time is
very inconvenient for people with
young kids and no other
caretakers. Some meetings could
be held later to accommodate
parents who want to participate.
1 - Poor I though the whole point of
having various cities in each
meeting was to have a mix of
perspectives, socioeconomic
status, demographics, etc.

Breakout rooms for each city

COMPLETELY DEFEATED THE
PURPOSE.
x 4 - Very
Good
The overview was short and to the
point, which was good (not too
wonky); and the breakout session was
good in that Deanna allowed people to
ask questions and make comments
even though she wanted to get to the
questions. It turned out that the
questions/comments addressed two of
the three questions, and it was good to
hear what people needed to
understand. For example, how does
policy impact housing development?
Include some racial equity
analysis/framing, to explain how
policy forced and continues to
design for segregation (or could
lead to inclusion). Use an
example or two. % of Menlo Park
that is zoned for single family
homes and even SFH with
minimum lot sizes, for example.

Height and density limits in DSP,
as another example.
4 - Very
Good
Learning about the demographics of
Belmont, its relationship to the median
household income, and other
economic details about Belmont. I also
appreciated learning what Belmont
currently has in the housing pipeline
and the numbers the hope for in the
future.
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x 5 -
Excellent
folks brought a positive attitude I wonder whether actually doing some cross-community
conversations would be useful at
some point, as well as city
breakouts?
3 - Good a chance to hear from others in the
county
would like the breakouts to be a
mixture of cities so we can hear
others concerns
4 - Very
Good

N/A N/A
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May 4, 2022 HE Workshop
Whiteboard Activity
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Housing Element Survey #1
1 / 15

84.01% 373

1.58% 7

14.41% 64
Q1 Do you:

Answered: 444 Skipped: 3
TOTAL 444
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
Live in San
Bruno
Work in San
Bruno
Live and work
in San Bruno

ANSWER CHOICES RESPONSES
Live in San Bruno
Work in San Bruno
Live and work in San Bruno
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Housing Element Survey #1
2 / 15

91.69% 408

4.72% 21

2.25% 10

0.22% 1

0.67% 3

0.45% 2
Q2 Which best describes your current living situation?
Answered: 445 Skipped: 2
TOTAL 445
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
I live in a
single-famil...

I live in an
apartment
I live in a
condominium
I live in a
townhome
I live in an
accessory...

Other type of
housing not...

ANSWER CHOICES RESPONSES
I live in a single-family home
I live in an apartment
I live in a condominium
I live in a townhome
I live in an accessory dwelling unit (granny flat/ guest house) Other type of housing not listed
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Housing Element Survey #1
3 / 15

84.91% 377

12.61% 56

2.48% 11
Q3 Which best describes your current housing situation? Answered: 444 Skipped: 3
TOTAL 444
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
I live in a
place I own
I live in a
place I rent
I live with
friends/...

ANSWER CHOICES RESPONSES
I live in a place I own
I live in a place I rent
I live with friends/ family, and do not own or pay rent 1273 of 1863
Housing Element Survey #1
4 / 15
Q4 What types of housing does San Bruno need most? Please rank the following nine housing options in the order you feel is needed most, with #1 being the most needed:

Answered: 440 Skipped: 7
0 1 2 3 4 5 6 7 8 9 10
Single-family
homes
Condominiums
Townhomes
Apartments
with 6 units...

Apartments
with 7 units...

Accessory
dwelling uni...

Special needs
housing for...

Senior Housing
Interim/transit
ional housin...
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Housing Element Survey #1
5 / 15

53.44%
225

9.26%
39 5.46%
23 4.04%
17 4.99%
21 4.28%
18 4.28%
18 2.38%
10 11.88%
50 421 6.

5.35%
22 20.44%
84 25.55%
105

13.63%
56 10.95%
45 5.35%
22 6.81%
28 6.81%
28 5.11%
21 411 5.

5.56%
23 22.95%
95 25.85%
107

15.94%
66 7.73%
32 5.80%
24 5.07%
21 9.18%
38 1.93%
8 414 6.

6.11%
25 10.76%
44 7.58%
31 23.47%
96 20.29%
83 16.14%
66 7.82%
32 4.89%
20 2.93%
12 409 5.

9.76%
40 5.12%
21 6.59%
27 8.78%
36 12.68%
52 21.22%
87 15.12%
62 11.71%
48 9.02%
37 410 4.

4.91%
20 9.58%
39 6.88%
28 9.34%
38 16.46%
67 16.71%
68 15.48%
63 11.30%
46 9.34%
38 407 4.

5.83%
24 6.55%
27 7.52%
31 6.55%
27 10.68%
44 12.14%
50 24.03%
99 20.15%
83 6.55%
27 412 4.

8.65%
36 14.42%
60 12.26%
51 12.74%
53 10.10%
42 9.38%
39 12.02%
50 17.55%
73 2.88%
12 416 5.

4.89%
20 3.18%
13 3.91%
16 5.62%
23 4.89%
20 7.33%
30 7.09%
29 12.96%
53 50.12%
205 409 2.
1 2 3 4 5 6 7 8 9 TOTAL SCOR
Single-family
homes
Condominiums
Townhomes
Apartments with 6
units or less
Apartments with 7
units or more
Accessory
dwelling units
(granny flat/ guest
house)
Special needs
housing for
families and
individuals who
need supportive
services like jobs
training and social
services
Senior Housing
Interim/transitional
housing for people
looking to
transition from
homelessness
1275 of 1863
Housing Element Survey #1
6 / 15
Q5 Please rank the importance of current housing challenges in San Bruno by indicating whether the following are very important, somewhat important, not important or don’t know:

Answered: 445 Skipped: 2
To ensure that
teachers,...

To ensure that
youth who gr...

To ensure that
people who w...

To provide
housing for...
1276 of 1863
Housing Element Survey #1
7 / 15

61.12%
272

27.87%
124

8.76%
39 2.25%
10 445

48.31%
215

31.69%
141

18.88%
84 1.12%
5 445

28.99%
129

44.49%
198

24.04%
107

2.47%
11 445

19.10%
85 39.10%
174

37.98%
169

3.82%
17 445

52.58%
234

37.98%
169

7.19%
32 2.25%
10 445

39.14%
173

26.92%
119

28.73%
127

5.20%
23 442
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
Very Import… Somewhat I… Not Import… No Opinion
To provide
housing opti...

Should the
city improve...

VERY

IMPORTANT

SOMEWHAT

IMPORTANT
NOT

IMPORTANT
NO

OPINION
TOTAL
To ensure that teachers, police, fire, and related safety workers can afford to live in San Bruno
To ensure that youth who grow up in San Bruno can afford to live in San Bruno when they are adults
To ensure that people who work at downtown businesses can afford to live in San Bruno
To provide housing for professionals working in San Bruno office parks
To provide housing options for seniors who want to downsize while remaining in San Bruno
Should the city improve land use policies to allow for housing types in addition to single-family homes to be built
1277 of 1863
Housing Element Survey #1
8 / 15

29.41% 125

30.59% 130

7.53% 32

32.47% 138
Q6 Where should the city focus on increasing housing?
Answered: 425 Skipped: 22
TOTAL 425
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
In existing
commercial...

Along existing
major corrid...

In existing
single-famil...

Anywhere in
the city

ANSWER CHOICES RESPONSES
In existing commercial areas
Along existing major corridors (San Bruno Avenue, El Camino Real, San Mateo Avenue) In existing single-family areas
Anywhere in the city
1278 of 1863
Housing Element Survey #1
9 / 15
Q7 To meet the City’s long-term housing needs, the city will need to plan for more homes. This includes single-family homes as well as apartments, townhomes, Accessory Dwelling Units (ADU’s) and condominiums. Please indicate if you Highly Support, Support, Don’t Support housing in the following areas:

Answered: 447 Skipped: 0
Along El
Camino Real...

Along El
Camino Real...

Downtown,
along San Ma...
1279 of 1863
Housing Element Survey #1
10 / 15
Downtown, on
surface park...

On vacant
former schoo...

Along San
Bruno Avenue
Along Sneath
Lane between...

At Tanforan
Mall or...
1280 of 1863
Housing Element Survey #1
11 / 15

35.52%
157

41.18%
182

18.10%
80 5.20%
23 442 1.93

30.77%
136

37.56%
166

27.15%
120

4.52%
20 442 2.05

30.16%
133

39.00%
172

25.40%
112

5.44%
24 441 2.06

26.64%
118

35.67%
158

32.28%
143

5.42%
24 443 2.16

17.31%
76 23.69%
104

51.25%
225

7.74%
34 439 2.49

34.31%
152

37.47%
166

23.93%
106

4.29%
19 443 1.98

18.91%
83 34.85%
153

41.00%
180

5.24%
23 439 2.33

25.23%
111

37.50%
165

32.73%
144

4.55%
20 440 2.17

40.67%
181

34.16%
152

21.57%
96 3.60%
16 445 1.88

25.68%
114

28.60%
127

35.81%
159

9.91%
44 444 2.30
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
Highly Supp… Support Don't Supp… No Opinion
By the
addition of...

HIGHLY

SUPPORT

SUPPORT DON'T

SUPPORT
NO

OPINION

TOTAL WEIGHTED

AVERAGE
Along El Camino Real from Highway 380 north to
South San Francisco
Along El Camino Real between Highway 380
extending south to San Mateo Avenue
Along El Camino Real extending south between San
Mateo Avenue to the Millbrae Border
Downtown, along San Mateo Avenue
Downtown, on surface parking lots
On vacant former school sites
Along San Bruno Avenue
Along Sneath Lane between Interstate 280 and El
Camino Real
At Tanforan Mall or portions of Towne Center
By the addition of Accessory Dwelling Units (ADU’s)
in Single-Family neighborhoods
1281 of 1863
Housing Element Survey #1
12 / 15

0.00% 0

62.16% 276

19.37% 86

8.33% 37

7.43% 33

1.80% 8

0.90% 4
Q8 About You. The following questions are optional, but will assist the city greatly in understanding respondents to this survey. Responses are confidential and will only be presented in tabulated form:

Answered: 444 Skipped: 3
TOTAL 444
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
How long have
you lived in...
21+ years
11-20 years
6-10 years
1-5 years
less than 1
year
I do not live
in San Bruno

ANSWER CHOICES RESPONSES
How long have you lived in San Bruno?
21+ years
11-20 years
6-10 years
1-5 years
less than 1 year
I do not live in San Bruno
1282 of 1863
Housing Element Survey #1
13 / 15

41.10% 180

48.40% 212

10.50% 46
Q9 Please indicate your gender.

Answered: 438 Skipped: 9
TOTAL 438
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
Male
Female
Prefer not to
say

ANSWER CHOICES RESPONSES
Male
Female
Prefer not to say
1283 of 1863
Housing Element Survey #1
14 / 15

52.83% 233

15.65% 69

12.24% 54

0.68% 3

0.23% 1

18.37% 81
Q10 How do you identify yourself? (Select all that apply) Answered: 441 Skipped: 6
TOTAL 441
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
White
non-Hispanic
Asian or Asian
American
Hispanic
African
American
Native
American
Prefer not to
say

ANSWER CHOICES RESPONSES
White non-Hispanic
Asian or Asian American
Hispanic
African American
Native American
Prefer not to say
1284 of 1863
Housing Element Survey #1
15 / 15

0.23% 1

2.73% 12

25.06% 110

35.99% 158

35.99% 158
Q11 What is your age group?
Answered: 439 Skipped: 8
TOTAL 439
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
5-18
19-29
30-49
50-64
65+

ANSWER CHOICES RESPONSES
5-18
19-29
30-49
50-64
65+
1285 of 1863
1 MEETING SUMMARY A
Countywide Stakeholder Listening Session #1
Fair Housing
9/27/2021, 1-2:30 pm on Zoom
Executive Summary
On September 27, 2021, 21 Elements hosted a housing element stakeholder listening session with organizations focused on fair housing issues, including:
• the Center for Independence of Individuals with Disabilities, • Community Legal Services of East Palo Alto,
• the Housing Equality Law Project,
• Legal Aid for San Mateo County, and
• Project Sentinel.

Detailed information about speakers and attending jurisdictions is below. 21 Elements’ AFFH (Affirmatively Furthering Fair Housing) consultant, Heidi Aggeler from Root Policy, also made some opening remarks and participated in the discussion.

Key themes included:
• Concern about the upcoming end of the eviction moratorium, • The importance of transit-oriented affordable housing and stronger anti-displacement policies, • The need for more education around accessibility regulations and reasonable accommodation, and
• The ability of jurisdictions to use their platform (including jurisdiction websites) to promote education and resources for tenants and landlords.

Stakeholder Presenters & Additional Resources
Center for Independence of Individuals with Disabilities (https://www.cidsanmateo.org/) Benjamin McMullan, Systems Change Advocate, [email protected] Community Legal Services of East Palo Alto (CLSEPA) (https://clsepa.org/) Michelle Trejo-Saldivar, Law Fellow, Housing Program, [email protected] CLSEPA’s COVID assistance website: https://www.youarecommunity.org/ 1286 of 1863
2 Housing Equality Law Project (http://www.housingequality.org/) Mary Prem, Executive Director, [email protected] Legal Aid for San Mateo County (https://www.legalaidsmc.org/) Shirley Gibson, Directing Attorney, [email protected] Project Sentinel (www.housing.org)
Ann Marquart, Executive Director, [email protected] Housing Choices (presented at a prior meeting) (http://www.housingchoices.org/) Jan Stokley, Executive Director, [email protected] Kalisha Webster, Housing Advocate, [email protected] Public Interest Law Project (unable to attend) (http://www.pilpca.org/) Michael Rawson, Director, [email protected]
Root Policy Research (AFFH consultant to 21 Elements) (www.rootpolicy.com) Heidi Aggeler, Managing Director, [email protected]
Jurisdictions in attendance:

Belmont Millbrae San Mateo (County)
Brisbane Pacifica South San Francisco
Burlingame Portola Valley Woodside
Daly City Redwood City
East Palo Alto San Bruno + California Department of
Half Moon Bay San Carlos Housing and Community
Menlo Park San Mateo (City) Development (HCD)
Key Themes and Actions
• Eviction Moratorium: There was widespread concern about what will happen when the California eviction moratorium ends on October 1, 2021. Just Cause eviction ordinances and Covid rent relief (especially for back rent) have been important to keep people in their homes.

CLSEPA shared a flyer after the session with a summary of renters’ rights and resources. • Vulnerable Populations: The stakeholder groups shared several details about the housing needs of the most vulnerable populations.
1287 of 1863
3 o People with disabilities experience the most housing discrimination. Legal assistance organizations get the most calls regarding discrimination against people with and find it is the most misunderstood category.
o Displacement disproportionately affects Latinx, African American/Black households and families with children.
o Many or most evictions are no-fault evictions, not evictions resulting from a failure to pay rent.
• Anti-Displacement Policies: Jurisdictions were curious about which anti-displacement policies were favored by the stakeholder groups.
o Affordable housing: More subsidized affordable housing is needed. Stakeholders noted that it is key to locate affordable housing in places located on transit or with good access to transit.
o Just Cause protections, rent stabilization: While there are some baseline protections at the state level, they need to be strengthened. The rent gauging gap does not go far enough to protect lower-income households.
o TOPA and COPA: Currently, there is significant interest in Tenant and Community Opportunity to Purchase Act policies that give tenants and nonprofits a first right to purchase or a right of first refusal when a property goes on the market. o Rent registries: Stakeholders noted that a rental registry is important in order to obtain data that can be used to inform anti-displacement policies, but it is not an antidisplacement policy on its own. o Section 8 vouchers: Stakeholders noted that while vouchers can provide opportunities for lower-income households to live or remain in the county, there are not enough vouchers to meet the need. In addition, vouchers have resulted in some concentration of low-income households in areas with less economic and educational opportunity. o Accessory dwelling units: ADUs are a great housing solution in the suburbs, as they provide suburb-appropriate density along with a good quality of life and provide more affordable options without requiring subsidy.
• Accessibility: Cities’ housing elements typically only have the minimum standard/generic language for accessibility. Some of the participating jurisdictions indicated an interest in doing more and are looking for examples of cities going beyond what is required. o Cities should be prominently promoting organizations working with tenants. City websites get the most visibility out of any form of advertisement/media o Jurisdictions were very interested in data that quantifies the existing supply of accessible housing and the demand for accessible housing. o Stakeholders suggested that affordability and accessibility issues must be considered together.
o Transit-friendly locations are key for people with disabilities. 1288 of 1863
4 o Stakeholders noted that “visitability” policies – making sure homes allow for access to those who are visiting – are less common today and should be considered. Consider requiring some degree of accessibility and visitability in new homes. o Accessibility requirements (or lack thereof) for new townhomes were a point of concern for stakeholders.
• Reasonable Accommodation: The speakers indicated that there is widespread confusion about the meaning of reasonable accommodation. They shared ideas that could help educate residents and landlords.
o Building departments should be posting reasonable accommodations policies. o Education for and outreach to apartment managers, property owners and homeowner associations is needed.
• Ideas for Action:
o Hire someone to do an audit of each jurisdiction’s website for reasonable accommodation policies.
o Improve jurisdiction websites to give a more prominent platform to organizations that work with tenants on fair housing issues.
o Create a program to rent ADUs to people who really need housing (maybe run by HIP Housing).
o Look at SB 9 and how it may impact the creation of duplexes that may or may not be accessible.
o Identify examples where cities go beyond the standard accessibility language in housing elements.
o Find data that quantifies the need for accessible housing (and the existing supply). 1289 of 1863
5 Appendix: Raw Notes
Room 1 (Josh) Notes:

Ben McMullan – CIID

1. Areas that can use work

2. Inaccessible new house – Many are built in town homes. There is a lack of visibility. No ground floor restroom. One bedroom on ground floor.
a. Restroom on ground floor
b. Access to kitchen

3. All new construction be accessible and visitable

4. Encourage more ADUs

5. Funding for home repairs for people with disability

6. Affordability

7. Mary to circle back with best practices for policies a. Report on where there are systemic violations

8. Education on reasonable accommodation for cities and apartment managers a. Require they take localized training
Ann Marquart – Project Sentinel

1. Tenant landlord

2. Mediation

3. Special emphasis

4. More visibility for fair housing

5. Make it clear how to make it more visible

6. Post reasonable accommodation

7. Most complaints about discrimination of disability

8. Reforms coming to service/companion animals rules

9. Companion animals have same civil rights protections

10. Many property owners do not understand laws

11. The lack of affordable housing

12. People are very worried about Oct 1 and after emergency rental restrictions end

13. Biggest issue with reasonable accommodation - landlords Shirley – Legal Aid

1. Eviction data from Legal Aid and EPA Legal Aid are based on that data

2. Black, Hispanic and families with children are the most hard-hit

3. It’s not a crisis of nonpayment, it is many no-fault evictions a. Even more disproportionately hitting black, Hispanic and children

4. Had the benefit of expanded just cause for 18 months. Been helpful. 1290 of 1863
6 5. Goals – strengthen no fault protections

6. “We don’t need data to figure out if there is a problem. We know there is a problem”

7. Rent registry does not prevent displacement, but data is useful, and as part of that lets get data about displacement

8. Covid rules did not cause the sky to fall

9. There are hotspots about how to use vouchers, there has been limited areas where vouchers getting used
a. But many of these are not in areas of opportunities

10. Time limited vouchers less useful

11. Make sure there are not group home discrimination

12. Post reasonable accommodation clearly
Michele – CLESPA

1. Just cause protections. They help tenants and inform tenants

2. Better rent stabilization

3. COPA/TOPA – Help displacement
Room 2 (Kristy) Notes:
• Ben McMullan - Center for Independence of Individuals with Disabilities o Advocate with housing, also look at transportation and health care issues o Biggest issues: Lack of affordable, accessible housing o Like to encourage affordable housing
o On transit lines, near transit
o Q from Nancy - with more power shutoffs, fire evacuation, etc. happening these days, for units not on the 1st floor, how is that being addressed? § PSPS (Public Safety Power Shutoff) program where help distribute backup power packs for people dependent on power
• Ann Marquart - Project Sentinel
o More affordable housing
o Disability is the protected category that they get the most calls about, and is the most misunderstood
o Want housing next to transportation
o Protected categories
§ Race
§ National origin
§ Gender
§ Families
§ Section 8 (NEW)
§ There is now fair housing protection for Section 8
§ But concern is that there are not enough certificates to go around, years of waiting lists, etc.
1291 of 1863
7 § Criminal history (is a little different)
o Q from Jennifer Rose: would be beneficial to all of the cities if you came up with collective wish-list of actions! Funding, help with promotion, policies, etc. § Ann: Promote fair housing groups in big letters on a lot of city websites, give agencies a bigger platform
§ For example, for first-time homebuyer training in San Jose, the only promotion was a notice on the city’s website, and it became clear that people go to city websites for information! Distributing flyers, holding zoom workshops - can only go so far, reach some people. § Suggestion: “How can we promote project sentinel”
§ HIP housing helped write language in last housing element (?) • Mary Prem - Housing Equality Law Project
o Full service
§ Focused on unserved or underserved areas
§ Investigate complaints
§ Counsel tenants
o Accessible housing
§ Not just accessibility but visitability
§ New construction (townhomes)
o Housing solutions for people seeking reentry
§ Worked with SF city and human rights commission on “unchecking the box” o Add more ADUs
§ housing is such a scarcity
§ More affordable solution
§ Greater life experience for people living in suburbs, not as dense o Really important that accessible housing is located near transit • MIchelle Trejo-Saldivar - Community Legal Services of East Palo Alto (CLSEPA) o San Mateo County, plus Mountain View
o Especially serve low income, very low income, LatinX
o Housing needs: stronger rent stabilization policies, just cause protections § There is a state just cause and rent control, but there is a need for stronger policies
§ TOPA and COPA policies, other anti-displacement policies o Low income populations know where they will find affordable housing and where they will not: Recommendation jurisdictions take a look at where LI and VLI people live - they should only be paying 30% of income - where should we be pushing more affordable housing development
• Shirley GIbson - Legal Aid of San Mateo County
o Similar mission and population served as CLSEPA
§ But only San Mateo County
§ The 2 organizations share information across 2 organizations (Tableau), lots of data at fingertips
1292 of 1863
8 o Why are these policies necessary from fair housing standpoint § Displacement falls squarely and disproportionately on Black and Latinx households, households with children
§ Disproportionality is even bigger when you look at no-fault termination evictions (not failure to pay rent)
o Biggest barriers to housing choice?
§ We heavily rely on housing choice vouchers - unfortunately have managed to isolate and concentrate those tenants in areas of low economic and educational opportunity
§ We must take take areality check: time-limited vouchers that transition people from homelessness to permanent opportunity are not working. It’s a revolving door because there isn’t enough time to stabilize households § Look at how housing vouchers are administered and distributed o Note that while a rent registry is an interesting source of data, and it is great to have more info, it is NOT a anti-displacement policy in itself. Can use the data (which is better if you require data from landlords) to inform and structure more robust antidisplacement policies: looking at turnover, tenancy, how often, why Room 3 (Vu-Bang) Notes:
• Mary Prem, Housing Equality Law Project
o Visitable housing units with accessibility on the ground floor unless there’s an elevator to other floors
o Serve areas that are deemed unserved, areas not covered by fair housing o Investigate fair housing complaints
o Training housing providers for more affordable housing o Collaborate with UC Berkeley - race studies in high school o City of SF- unchecking the box - re-entry housing programs, previously incardinated o Reasonable accommodations denial and other accessibility issues are most common work
o New construction, esp around transportation hub - housing that’s in townhome and not “visitable” (no toilet in common area, no elevators)
o Affordability and availability biggest concern - ADU units encouraged o Topic brought up with jurisdictions but haven’t seen adopted o Affordability and availability for housing
o Congestion on highways and accessibility in hubs
• Michelle Trejo-Salvidar
o Just Cause protections - provide tenants with their rights when tenant gets notice • Shirley Gibson
o Be wary of full scale models of Just Cause - can pick and choose from model ordinances to shore up the weak Just Cause ordinances
• Ann Marquart, Project Sentinel
1293 of 1863
9 o Disability and familial status got the most complaints - reasonable modifications, can go to CID to pay for modifications, VA will pay for some of those repairs. Reasonable Accommodations - companion/service animals (anyone giving the certificate now has to note how many hours of therapy), different parking space, reminder to pay the rent, o Policies: wishlist - something to project tenants after the moratoriums and now focused on back rents
o Something (not rent control) - new housing near transportation o Education - getting word out to housing providers, raise Project Sentinel to larger visibility so people can find them
o What cities have the best visibility to Project Sentinel - will follow up. o Section 8 renters - no discrimination
o Landlord should not evict everyone in the household after domestic disturbances • Ben Mcmullan
o Systems change for Center for Independence of Individuals with Disabilities o San Bruno, SSF, County offices
o Visitability - wheelchair and mobility devices can adequately visit. Not many obstacles on different levels - Home Modification Program that people can take advantage of.

Having new housing be accessible from the get-go
o Plug for transit oriented housing - people with disabilities face needing housing and transit.
o Explore transit oriented housing - vastly great step forward o Paratransit coordinating chair on SamTrans and CalTrain accessibility advisory committee
o Biggest barriers to housing for vulnerable households - affordable and accessible housing. If it's affordable and not accessible, it only goes so far, and vice versa. • Burlingame - has standard language on accessibility - want to know what language to use to go above and beyond. Townhouse units esp have concerns with. Set up well for TOD, but linking TOD + Accessibility + Affordability . SB9 - two flats or 2 townhouses preferred when it comes to accessibility.
• Hillsborough – language is generic, actual implementation only on ADUs, but predominantly single family housing. Transportation corridor only on El Camino Real and ½ mile from Burlingame Caltrain station.
• Jan (HCC): Physical accessibility is not the only type of accessibility barrier--I am thinking of people with cognitive disabilities--they shouldn't be left out of the discussion. 1294 of 1863
1 MEETING SUMMARY A
Countywide Stakeholder Listening Session #2: Housing Advocates 10/18/2021, 1-2:30 pm on Zoom
Overview
On October 18, 2021, 21 Elements hosted the second of four housing element stakeholder listening sessions with housing advocacy organizations. A majority of 21 E jurisdictions attended the listening session. Five stakeholder advocate groups introduced themselves and spoke about their group’s interest in the Housing Element process. Detailed information about speakers and attending jurisdictions is below and in the appendix.

Key themes included:
• Ongoing outreach needed to underserved and diverse communities • Production of new housing is critical to the SMC workforce o Greatest need for deeply affordable housing, dense, infill • Connecting labor, environment and equity to housing
• Rent increases are a primary concern
• Protecting vulnerable renting populations with assistance from the governments Policies & Programs to consider:
• Additional funding for affordable housing through commercial linkage fees, inclusionary zoning, vacancy tax, sales tax, etc.
• Protections: eviction assistance, anti-harassment measures, stronger just cause, tenant right-to return, relocation assistance, improvements to the building inspection process, rental registries as a tool
• Production: Increase density within existing communities in non-high fire severity zones, eliminating harmful restrictions on density, eliminating parking minimums, streamlining housing building process, fair and inclusive zoning policies
• Prioritize BIPOC families in housing policies, outreach and practice (all stages of the practices) • Manage the threat of climate risk by adding green infrastructure. 1295 of 1863
2 Stakeholder Presenters & Additional Resources
Organization Speaker Name Contact
Housing Leadership Council Angela Solis [email protected] Faith in Action Nani Friedman [email protected]
Greenbelt Alliance Zoe Siegel [email protected]
San Mateo County Central
Labor Council
Rich Hedges [email protected]
Peninsula for Everyone Jordan Grimes [email protected] San Mateo County Association
of Realtors
Gina Zari (invited, unable to
attend)
[email protected]
Learn more about Greenbelt Alliance’s endorsement program: https://www.greenbelt.org/climatesmart-development-endorsement-program/ Learn more about Greenbelt Alliance’s Resilience Playbook: https://www.greenbelt.org/resilienceplaybook/ Full list of Greenbelt Climate Policies can be found in the draft housing element playbook (under policies tab) https://coda.io/@gazoe-siegel/housing-element-toolkit For those who wish to learn more about the focus groups in Redwood City that Trinidad from Faith in Action mentioned,, you can read the report here (posted on the City of Redwood City website):
https://www.redwoodcity.org/home/showpublisheddocument/23755/637623096709130000 Faith in Action supported with two other reports (tenant protections and preservation), found here:
https://www.redwoodcity.org/departments/city-manager/housing-services/housing-policies/antidisplacement-strategic-plan Note Faith in Action works mostly with renter leaders in Daly City, San Mateo and Redwood City, but they have a presence in several other cities in the county as well.

Jurisdictions in Attendance:

Atherton Half Moon Bay San Mateo (City)
Brisbane Menlo Park San Mateo (County)
Burlingame Millbrae South San Francisco
Daly City Pacifica Woodside
East Palo Alto Redwood City
Foster City San Bruno +HCD
1296 of 1863
3 Key Themes and Actions:

Themes
• Ongoing outreach needed to underserved and diverse communities • Production of new housing is critical to the SMC workforce o Greatest need for deeply affordable housing, dense, infill • Connecting labor, environment and equity to housing
• Rent increases is a primary concern
• Protecting vulnerable renting populations with assistance from the governments o Rental registries, eviction assistance, section 8 availability, anti-harassment measures.

Questions/Discussion
• How do you best balance providing adequate living wages for construction workers with keeping housing units affordable?
o Fair labor is critical to the building process
• Who should operate rental registries (city, county, nonprofit?) o Administered by RWC city staff
• Potential policies prioritizing BIPOC
o Understand needs of BIPOC communities throughout the process o Understand displacement policies
o More housing in transit rich corridors
• Section 8 Vouchers
o How to increase the availability
• Housing as a benefit to the community/not extracting from it 1297 of 1863
4 Appendix: Additional Stakeholder Information & Input
o Housing Leadership Council: Angela Solis
§ Network of organizers to support affordable housing
§ Advocating for and preserving affordable housing
§ Greatest need:
§ Deeply affordable homes
§ Focused on funding for affordable homes with example policies:
§ Commercial linkage fees
§ IZ, vacancy tax, sales tax, etc.
§ Seeking greater outreach from jxs for Housing Element process- window into populations
o Faith in Action Bay Area: Trinidad Villagomez
§ Focus in Redwood City
§ Community organizers, leaders working in congregations schools, neighborhoods and apartments across SMC to uphold dignity of all people § Listening to community experiences with housing (phone calls, door knocking, church involvement, people at food distribution sites)
§ What the group heard from the community:
• Poor building conditions, harassment, discimination, rent increases, fear to speak to authorities, difficulty relocated, evictions for renovations and owner move in, unclear how to enforce existing rental rights, pandemic insecurity, rental debt, financial hardship, credit limitations, application fees
§ From focus groups:
• Rent increase is the majority primary issue
§ Vision:
• Regulations on eviction due to renovations
• Preventing harassment of tenants
• Partnership with city to work with tenants and landlords as a mediator o City to inspect buildings
o Rental assistance
o Process relocation assistance
o Report rent increases, eviction notices, their business license and taxes
o Education for tenant about rights
§ Policies:
• Stronger just cause policy (define substantial renovation) and give tenants right to return (right of first refusal)
• Stronger relocation assistance administered by the city • Improvements to the building inspection process, with greater confidentiality with the tenant
• Rental registry program by city-tenant/landlord office • Anti-harassment policy
1298 of 1863
5 § More information:
https://www.redwoodcity.org/home/showpublisheddocument/23755/6376230 96709130000
o Greenbelt Alliance: Zoe Siegel
§ Inclusive, climate resilient communities for all to thrive § Housing and climate are linked
§ Advocating for climate smart development
o SMART: Sustainable, Mixed, Affordable, Resilient, TransitOriented development • Resilience Playbook
o Resources for local decision-makers and community leaders with policies, model ordinances, etc.
§ Ensure fair and inclusive zoning policies that makes housing accessible to everyone
• Prioritize BIPOC families in housing policies, outreach and practice (all stages of the practices)
• Advance racial and social equity in process
§ Increase density within existing communities in non-high fire severity zones § Manage the threat of climate risk by adding green infrastructure. • Prepare for climate impacts, require nature-based solutions for climate resilience
o San Mateo County Labor Council: Richard Hedges
§ Advocate for increased outreach
§ Increases for min. wage, building of housing for all workers (safe and affordable) § Builders: getting the work/pay required to live in San Mateo County (can afford to rent/own home)
• Service workers are struggling to live in SMC (especially retail pay) § Advocated for housing built at Bay Meadows, advocated for 10% inclusive § State law to allow for more density for affordable housing § Qualified workforce is critical
§ Removing barriers for Section 8 voucher holders
o Peninsula for Everyone: Jordan Grimes
§ Frustration with lack of dense infill housing in SMC
§ Member engage in local project advocacy, and planning meetings and are politically active at the local and state level
§ Huge housing shortage in the county, decades of underbuilding § Focus on as much being built as quickly as possible
§ 3 Ps of housing policy, preservation, production, protection (interested in rental registries, want more rent data)
• Protection: Rent control, right to counsel with the eviction process • Production: eliminating harmful restriction on density, parking min, streamlining housing building process
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1 MEETING SUMMARY A
Countywide Stakeholder Listening Session #3: Builders/Developers 11/1/2021, 1-2:30 pm on Zoom
Overview
On September 27, 2021, 21 Elements hosted the third of four housing element stakeholder listening sessions with housing developers and builders, including both affordable housing developers and market-rate housing developers. Detailed information about speakers and attending jurisdictions is below.

Key themes for affordable housing development included:
• Primary constraints to affordable housing include: the limits of local funding, tax credit availability (the county’s pool is small, limiting the size of a development that could get an award), appropriate sites
• Key policies and programs: sufficient and flexible local funding; either public land or land that is eligible for SB 35; streamlined process and alignment across city departments • Local governments should be aware of state and tax credit policies/requirements; be cognizant of the cumulative impacts of multiple layers of funding requirements; be prepared for community pushback now that high-resource areas are being targeted Key themes for market-rate housing development included:
• Primary constraints include competition for sites (with other uses) which drives up land costs; construction costs; city process and zoning; all the “easy” sites have already been developed, leaving sites with environmental or political (close to single-family homes) or other sensitivities • Key policies and programs: Specific plans and master plans and form-based zoning have been successful; removing CEQA from the equation is helpful; seek a balance of flexibility and predictability
• Localities should exercise caution with parking and ground-floor commercial requirements • Property tax exemption is likely best tool for encouraging moderate/middle income housing created by the market
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2 Stakeholder Presenters & Additional Resources
Organization Speaker Name Contact
MidPen Housing
(Affordable)
Abby Goldware Potluri [email protected]
HIP Housing
(Affordable)
Kate Comfort [email protected]
BRIDGE Housing
(Affordable)
Brad Wiblin [email protected]
Mercy Housing
(Affordable)
William Ho [email protected]
Habitat for Humanity—
Greater SF
(Affordable)
Maureen Sedonaen [email protected]
Eden Housing
(Affordable)
Ellen Morris [email protected]
Affirmed Housing
(Affordable)
Rob Wilkins [email protected]
The Core Companies
(Affordable, Market
Rate)
Chris Neale [email protected]
Sand Hill Property
Company (Affordable,
Market Rate)
Candice Gonzalez (invited,
unable to attend)
[email protected]
Sares | Regis
(Market Rate)
Andrew Hudacek (invited,
unable to attend)
[email protected]
Summerhill Apartment
Communities
(Market Rate)
Elaine Breeze [email protected]
Greystar
(Market Rate)
Jonathan Fearn [email protected]
Jurisdictions in attendance:

Belmont Half Moon Bay San Bruno
Burlingame Menlo Park San Mateo (City)
Daly City Pacifica San Mateo (County)
East Palo Alto Portola Valley South San Francisco
Foster City Redwood City Woodside
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3 Roundtable Discussion Questions/Answers
Affordable Housing Developers

1. What do you perceive are the primary constraints on affordable housing development? o Local funding – esp since state housing laws have helped on the land use side o Having funding programs that actually match the supply side/building of the homes o Local Funding and Operating Subsidy
o Current cap in the 9% tax credit round (in last several rounds, not many projects going in because not enough credits in the region) – only projects with fewer than 60 units, plus high costs
o On preservation side – have to be agile and fast, if cities want to do this, they need to have systems to deal with tight escrow periods
o Appropriate sites

2. Are long lead (escrow) times possible in the property market today? o Sellers are amenable to longer lead times than pre-covid, though Peninsula is still tight o What’s key is having a good read on public partners’ funding commitment o For every site where factors line up, you lose a site because other things don’t line up o You can tie it up to close upon entitlements, but carrying cost adds up, so if public commitment can come in earlier that helps reduce cost

3. What are new policies or improved policies that you think would go farthest to making it easier to develop affordable housing?
o Local Funding and Operating Subsidy, esp flexible funding o 20% setaside dedicated to homeownership programso Fee waivers o Streamlined project timelines on the city’s side
o Consistent, regular NOFA timelines
o Having all departments aligned on goals
o Not having extra requirements/costs for affordable housing developments o Affordable housing should not bear burden for infrastructure costs o Remove restrictive racial covenants
o More policies like SB 9 and 10
o Update zoning of sites that were zoned in the 1960s
o Resources for site analysis, more points awarded when possible to incentivize and also help with by right potentially

4. What would you say are the 3 most important things that jurisdictions can provide in order to facilitate affordable housing development in their jurisdiction? o Local Funding and Operating Subsidy
- Shift unused resources (downpayment assistance for example) to production allocation for more housing or land purchases
- Nimble funding sources
- Affordable homeownership
o Land with appropriate zoning
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4 - Public land, esp in high resource areas (https://belonging.berkeley.edu/2021- tcac-opportunity-map)
- Making more land available with by right zoning or SB35 - Or priority zoning for affordable – San Jose allowing affordable housing to convert industrially zoned land
o Process
- Streamlining and alignment across city Departments
- Dedicated planner to shepherd affordable housing projects o I’d like to encourage jurisdictions to think outside the box and find ways to encourage partnerships between for and nonprofit developers. HIP Housing has had several great experience on projects using diverted impact fees and limited partnerships.

5. What should jurisdictions be aware of as they designate sites for affordable housing? o Think about how state funding sources/developers are looking at sites. “Vanilla” Aff family is gone unless in high resource areas so need operating subsidy. Sites need to be in amenity rich area (put site through amenity scoring lens) o Operating subsidies needed to support the deeper affordability that is sought today o Layering of requirements and compatibility of different populations o Think about not just # of units but also # of people being served o A comprehensive view of constraints, impacts of delays on developers o Be prepared for pushback in high resource areas
o We need more ownership, multifamily sites should be funded and counted by # of people served, not just # of doors; make residential "only" or limit commercial so can residential compete

6. Most of the Cities I consult for are small and do not have the capacity or expertise to shepherd affordable projects. What can you recommend otherwise?
o Important who the city chooses to partner with. Experienced developers can do some education on that. Hire a consultant or someone who can help to navigate the process o Small cities are sometimes great because they don’t have as much bureaucracy and can get things done more quickly
o Smaller cities could look to partner with Developers who build under 20 units (like Habitat and others on this call) and we welcome the opportunity to learn together. P.S.

It's hard to make it work financially if there are under 6 units however:)

7. What is your experience with rolling NOFAs (no deadline) versus NOFAs that have a fixed deadline for responses? Are there particular advantages or disadvantages to either one of these?
o Affordable developers rely on consistent, regular process o Don’t create a land rush and have affordable developers bid up land o Like rolling deadlines, since in the preservation world, can’t wait until a NOFA o No deadlines better align with development
o Rolling NOFA's are good, allow for flexibility to be responsive o If you really need to schedule it, make sure NOFA schedules coincide with other funding sources
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5 8. Would you have advice for jurisdictions with a lot of environmental constraints that can make housing expensive--faults, steep slopes, limited sewer, fire hazard, etc.? o Often they aren’t as bad as you might initially think. A second look can make something workable
o All the easy land has been developed on already! So don’t hold back, this is the norm, not the exception
o There are sometimes sources for brownfield funding

9. What is the densities that are working best for 100% affordable projects that cities should be planning for in the Housing Element process?
o Anything over 20 duac but 30-50 is better, gives more flexibility

10. What site criteria make a site feasible for securing tax credits? o High resource area (amenity rich)
o Site logistics (e.g. flat site, sufficient size)
o No need to build out infrastructure

11. Do you have a "rule of thumb" for how much local subsidy you are looking for in order to make an affordable housing development "pencil"? Do you typically need to secure County funds for the project as well as city funds and/ or land?
o 100-300K per home
o 30% local subsidy. Typically need county, city funding and land but depends on project specifics

12. Do you have any advice as jurisdictions release NOFAs/prioritize their affordable housing trust funds?
o Put more money in production! Support ownership programs, modify program to accommodate and understand their impacts
o Family housing that can compete (e.g. high resource area) o Senior housing at lower AMI's
o Operating Subsidies that aren't a COSR (e.g. LOSP) to serve homeless/ELI

13. From your experience in responding to site-specific RFPs, what would you say makes for a good RFP that you would be super excited to respond to?
o Large sites
o Sites with good logistics
o Consider RFQ's instead of RFP's
Market-Rate Housing Developers

1. What do you perceive are the primary constraints on market-rate housing development? o Competing with other land uses in acquisitions - life science and industrial and certain commercial driving more value
o City constraints
o Construction costs
o All the easy sites are gone. Now they’re politically sensitive, closer to single-family neighborhoods
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6 2. What are new policies or improved policies that you think would go farthest to making it easier to develop infill housing?
o Clear paths to entitlements would help
o Specific plans and master plans are great, CEQA document, design standards o Other paths that remove CEQA from the equation
o Would be a mistake to only think about high density residential, need to think about housing of all shapes and sizes (SB 9, ADUs, duplexes)

3. Which jurisdictions are doing a good job? (Answers were mostly about specific plans) o Redwood City
o Milpitas
o Santa Clara County
o City of Santa Clara
o Oakland – 4 specific plans
o Burlingame’s general plan
o Caution that specific plan does take time, often falls behind schedule o San Mateo County’s transit has a lot of potential

4. Conversely, what are some cities that took approaches you think didn't work out well and why? o A city that got very detailed in a specific plan, and it wasn’t relevant to the market, so it sat for a very long time before the city realized they needed to adjust the specific plan

5. What would you say are the 3 most important things that jurisdictions can provide to facilitate more housing development in their jurisdiction?
o Flexibility is key, but balance with predictability and consistent standards o Form-based zoning allows for evolution of details – we talk in terms of density, but form-based zoning images make more sense to people
o Resources
o Streamlined processes
o Restrictions on other competing uses
o Partnerships with city departments that streamline and adhere to code standards and other standards

6. What should jurisdictions be aware of as they designate sites for multifamily housing? o Anticipate objections and set up ways to mitigate them

7. Is there a range of project densities or size that is your sweet spot? o Depends on location
o Depends on rents
o Summerhill - Type III over Type I garage, (5 stories wood over 2 stories concrete), 20-22 units to the acre – 3 story resioential density
o Densities are going down, because unit mix is changing, putting bigger units in them.

Used to have a lot of studios and 1BRs, now making 2BRs and larger 1BRs

8. Questions on parking. Are you finding car stackers practical for your developments? o Yes starting to do this in the right locations (Core, Summerhill) o Not necessarily cheaper but allows you to use land more efficiently and not go underground
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7 o Hard parking minimums can be problematic when it comes to site planning, so some flexibility on parking is key
o 1:1 parking ratio works near transit

9. Does this group see a lot of potential in SB 10? -- urban infill for up to 10 unit multi-family projects -- exempt from CEQA
o Fan, there are possibilities, but we’ll see how much it actually gets implemented o What’s missing is the small scale developer (they’ve been zoned out), if SB 9 and 10 can spawn that ecosystem, it can make a difference. Right now the pool isn’t deep enough, not enough to sustain a business. If a community wants them, they will need to cultivate these types of development and developers

10. How does developing mixed use developments affect housing? How does it affect competing land uses?
• Summerhill has mixed-use projects with ground floor commercial that is not leased • What makes good retail is sometimes at direct odds with what makes for good unit plans above. Depth of retail etc. It is a challenge
• Amount of retail, needs foot traffic, really depends on location. Only so much retail to go around

11. What are ways that you think jurisdictions could facilitate the development of moderate and middle income housing?
o Projects with JPA programs
o Property tax relief for moderate-income units
o Once upon a time, market-rate housing delivered housing for middle income households, we just don’t have a lot of housing opportunities. Restricting supply doesn’t restrict demand. Allow more housing generally
o Access to specialized loan products and property tax incentives would help with middle income housing
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1 MEETING SUMMARY A
Countywide Stakeholder Listening Session #4: Service Providers 11/15/2021, 1-2:30 pm on Zoom
Overview
On November 15, 2021, 21 Elements hosted the fourth of four housing element stakeholder listening sessions with San Mateo County service providers. Detailed information about speakers (see appendix for organizational information) and attending jurisdictions is below.

Key themes included:
• Key location characteristics were similar for most groups: access to transit, groceries, medical services, pharmacy, schools/parks/community centers/senior centers, jobs and job training. • Most of these stakeholder groups serve people with a range of incomes – focused primarily at the low end of the income spectrum but also into moderate levels. • Need affordable housing (or access to vouchers/subsidies that help with access to market-rate housing) of all shapes and sizes: mostly smaller units (studios to 2BR) but there is a need for larger units. It is hard for larger families (5-8 people) to find appropriately sized housing. Space, closets and storage, design for people with disabilities. See below for details. • Some people need onsite supportive services; others just need to be able to easily access services, whether by transit or if it can come to them. • Work with service providers and people experiencing issues firsthand before creating programs. • Use your networks and power to encourage business/tech/philanthropy to support service providers
Policies & Programs to consider:
• Actively partner with affordable housing developers to streamline and facilitate development • Stabilize market rents
• Use public land for affordable housing
• Create more workforce housing.
• Increase inclusionary housing
• Encourage and facilitate more homesharing
• Educate landlords on their rights so they are more willing to partner with Housing First service providers
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2 Stakeholder Presenters & Additional Resources
Organization Speaker Name Contact
Daly City Partnership
(one of San Mateo
County’s Core Agencies)
Marya Ouro-Gbeleou [email protected]
HIP Housing Laura Moya [email protected]
LifeMoves Jacob Stone [email protected]
Mental Health
Association of San
Mateo County
Melissa Platte [email protected]
National Alliance on
Mental Illness
Michael Lim [email protected]
Ombudsman of San
Mateo County
Bernadette Mellott [email protected]
Samaritan House San
Mateo (one of San
Mateo County’s Core
Agencies)
C. LaTrice Taylor [email protected]
Youth Leadership
Institute
Alheli Cuenca [email protected]
Abode Services Jeremiah Williams (unable to
participate live, interviewed)
[email protected]
El Concilio Gloria Flores-Garcia (unable to
participate live)
[email protected]
Roundtable Discussion Questions/Answers

1. We assume that transit-oriented or transit accessible housing is important. Are there any other location characteristics that you would highlight are important for the people you serve? o Mental Health Association – access to transit, medical care, grocery stores, pharmacy o Daly City Partnership – in Daly city all services are sited in the govt center by design, so housing should either be close to it or have direct transit access o Youth Leadership Institute – parks within or near housing developments are important to young people, new community centers or access to existing ones, high walkability o HIP Housing – agree with all mentioned, near schools for family housing, senior centers for senior housing
o National Alliance on Mental Illness – justice-informed community (people who have experience with law enforcement, ranging from a 5150 call or involuntary hold to being incarcerated in jail or prison system) need access to services 1308 of 1863
3 o Abode – varies. Have some unique programs, sometimes relocate people out of the county. Medical, schools, childcare, transportation. Access to jobs/job training

2. What is the range of income levels of the population you serve? o Mental Health Association - 0 to 15%
o LifeMoves – range from 0 to 100%
o Daly City Partnership – weighted to the lower end 0 to 30, 0 to 50%, a lot at 80% too but not as many
o National Alliance on Mental Illness – lower end, but mental illness spans people across the whole income spectrum
o Abode – serve the lowest incomes

3. What role does market-rate housing play for the people you serve? Are vouchers helping? o Mental Health Association – for most clients, market-rate housing is out of reach, even affordable is also often out of reach (since it serves 40% to 120% AMI) o Ombudsman – her clients in assisted living get a $1500 check, rent is $5000+, sometimes families or retirement funds make it work. Now facing a number of families who cannot help anymore because of lost jobs during the pandemic. 15 people on evictions list right now, many are 85+ years. If they are evicted they will end up on the streets. Looking for solutions for them. They don’t take transportation, they can’t o HIP Housing – 95% of clients in homesharing program are at or below 80% of AMI, sometimes not low enough to access affordable housing. And some are on fixed income and don’t qualify for affordable housing and don’t make enough to access homesharing program. Waiting lists are way too long
o Daly City Partnership – see a lot of same types of people that Ombudsman sees, just a few years earlier, before they need assisted living. It’s a tough spot to be aging in San Mateo County, unless you’re healthy or living with your adult children. Think about dignity for our older folks. We need to care for our elders. o Abode – do master leases, use vouchers, so existing and new market-rate housing plays an important role. Develop relationships with landlords that accept vouchers (provide case mgt/contact for landlords, help to avoid evictions). Important to educate landlords around their rights, not a lot of legal services available to them. Work with a range of landlord and building types.

4. Do affordable units need to be designed in a certain way or certain size to meet the needs of the people you serve?
o Mental Health Association – definitely need more units that are available for people with physical disabilities. Serve people with serious mental illness, HIV/AIDS debilitating conditions, etc. It used to be that they would die far younger than most, but now people are now living into 60s-70s-80s. This is great but long-term effects of medications have impact on their bodies, put them at greater risk for falls, etc. Mostly studios and 1BRs (preferred), closets and storage in the unit are critical o Youth Leadership Institute – serve young people – in Half Moon Bay they are seeing 3 HH living in one unit, looking to advocate for pathway to homeownership, also single family housing (3BR/2BA). Want as much space as possible, spacious living areas. 1309 of 1863
4 During pandemic school from home was incredibly challenging esp when community centers weren’t open or limited. Also like ADA accessible, parking spaces, access to community parks, trails, since there are not a lot of things for young people to do; storage units and closets, public bathrooms in developments o HIP Housing – serve single individuals, families and seniors. Larger families get missed, families of 5-8 or larger can’t find any affordable housing options. Some seniors would benefit from onsite services, during pandemic especially suffered from isolation o LifeMoves – serving more seniors every year, medically fragile folks – in terms of families serve primarily smaller households of 2-3, but do have a few large HH too o National Alliance on Mental Illness – agree with many things mentioned above, add better noise insulation since clients may have experienced trauma and loud levels of noise can trigger them to the next episode
o Abode – need all types of units

5. For the population you serve, if the cities were able to encourage a set-aside within affordable housing for special needs, who needs onsite supportive services? Who can live in general affordable housing (assuming deeper levels of affordability)? o Mental Health Association – only 30% of people we serve need to have site-based services onsite, but 100% of clients need access to support services. Deep affordability/subsidies/vouchers can work as long as there are services that can be brought in to work with them
o National Alliance on Mental Illness – some of our clients may lose custody of their children or have shared custody. Studio will suffice for most but for some who are working to get their life back in order, helps to have a little bit more space when they have their children visit
o Daly City Partnership – Was able to tour Sweeney Lane (MidPen Housing) in Daly City – wonderful onsite services. Was moved, this is what our people need, it’s a shame that it is so small. Excellent example of good practice of surveying residents about their needs and evolved services as needed. Many clients don’t need that level though. Echo importance of evolving services over time. Midway Village in Daly City – for several years there weren’t onsite services, people there for generations, underserved population historically. Some of the seniors today moved there when they were young – we need to think about aging in place, be thoughtful over the long term about evolving resident needs. There is a need for large units (4 children) in the market even though the smaller households are most common. # of kids is a limiting factor on affordable applications
o Ombudsman – there is no affordable assisted living. Pipe dream is that some people might be able to live in affordable housing with their families if they had some onsite services. Some need their medications to be given to them. Physical therapy is provided in nursing homes. Cheapest assisted living is $4500, ranges up to $10K/mo. Seniors need the same basic services no matter their income. Also serve mentally and physically disabled in residential homes. Nobody wants them, which is very sad.

6. Aside from more money, what can jurisdictions do to be helpful? Future programs and policies not just about the direct allocation of money
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5 o Daly City Partnership – Sweeney Lane is an example of the city getting behind a development and working collaboratively to get everything together – zoning, permitting, convincing adjoining land owner with lot to sell the lot. Worked to move things as quickly as possible. It takes such a long time to make these projects happen, which is a problem when people are homeless *today*
o HIP Housing – one of the things jurisdictions can do is encourage and support affordable and accessible prices in the overall housing market. More supportive services for mental health issues, esp at earlier stages. More supportive services to people on fixed income, make sure they don’t lose fixed income if they get access to new resources. Jurisdictions may not recognize homesharing as a solution, but they should consider it, it is readily available, no cost, can help fill in the gaps o Mental Health Association – agree with everything that has been said. Use city and county owned property for low income housing. Support developers that include extremely low income units, that provide support services onsite or accessible. There’s a lot of talk about teacher housing – nonprofit staff need affordable housing too. Would help to recruit and retain employees, who we are losing every day. If we can’t hire staff, we will not be able to serve
o Ombudsman – all the market-rate developers who are building these beautiful residential buildings, but only put 3 low income units in 25 unit building. We should incentivize them to add more low-income units. Give the developer a tax credit to incentivize them to increase the # of low income units. Get more people off the streets and into nice apartments.
o National Alliance on Mental Illness – incentives to builders is great. Also think about how to halt the exchange of ownership on property. Every time land is sold and changes hands, it becomes more expensive. Think more creatively about ownership of land o Abode – Besides more money, we need more vouchers, more staff. More project-based housing. Education for landlords on their rights will help more landlords be willing to take vouchers, sign master leases. Rapid rehousing is needed but it doesn’t work for everyone; we need more permanent supportive housing. Jurisdictions should reach out to people at ground level for input before creating programs.

7. Are there options for people that have animals?
o Mental Health Association - Most of our clients can have an animal as long as we work with them to request a reasonable accommodation. 100% of our units can and will make the accommodation.
o National Alliance on Mental Illness – pets are huge thing for our clients, not only with soothing them but also creating a sense of responsibility, gives them second thoughts when they are thinking of ending their lives
o HIP Housing – it is still a big barrier in affordable housing when their pet is not a service or supportive animal. Many people have more than one pet which is also a barrier. 1311 of 1863
6 8. How much have the large companies--Apple, Facebook, YouTube, etc--stepped up to help provide money for these services and housing units?
o Mental Health Association - To our knowledge, not much. o Ombudsman – got turned down for grants from FB, Google, Genentech o Samaritan House – they do fund some things, some of the folks here do have funding, depends on the focus, housing, food, youth has been big. Need to understand what is it that they really want to fund and tailor what you’re doing to what they’re asking for o Daly City Partnership – CZI is funding all of the Core Agencies in SMC, doing a lot of work around free, high-quality training for their grantees and others. They are at the forefront. Key to support for Core Agencies: someone at County advocated for the Core Agencies. Jurisdictions, use your network and political power to help orgs o HIP Housing – has benefited from CZI as well

9. Additional comments
o Samaritan House – article came out today about most expensive zip codes in the country. For the 5
th year in a row: Atherton. In the Bay Area we have 47 out of 100 zip codes that are among the highest in the country. In SMC, 10 of the 47. Somehow, some way we need to figure out how to solve this with partners, with developers (who have codes to follow, does tax credit offset how much they can make, when it’s more about the money and those who can afford it vs. police, firemen, nonprofit workers). We are fast approaching that cliff where we’re not only pricing out our clients but also the middle class. We need to do something, not sure what it is. We’ve got a fire. Where are the hoses, where is the water, where are the fire trucks? Tech companies should be a part of this process. We need the people with the money at the table. The tech companies are contracting with people so they don’t have to pay benefits. People are working from other parts of the state/country because their money doesn’t go as far in the Bay Area. $140K income for a family of 4 only covers the basics. I know the people who are here know that. But who else do we need at the table to know it too. o Daly City Partnership - One of my favorite quotes, "Tell the rich of the midnight sighing of the poor." We need to educate the upper-class and business folks - appeal to their conscience. But that is my own personal view. LaTrice (Samaritan House) is so right. o National Alliance on Mental Illness – Need to look at transportation, exploring localities that are hubs. In a few years (or even now) we are facing the challenges of our own existence. NAMI San Mateo had to give up its permanent site and move offsite. Current location is not ideal, not close to any public transportation system. El Camino is going to look like two walls of buildings with homes. Is that what we want or do we want to add transit to allow people access to services. Jurisdictions should start thinking about transportation hubs. Think about housing density and building up because limited land, is precious. Need to think about it now since it takes time to build infrastructure 1312 of 1863
7 Appendix: Additional Stakeholder Information
Human Investment Project (HIP Housing)
• Mission: HIP Housing’s Mission is to invest in human potential by improving the housing and lives of people in our community. HIP Housing enables people with special needs, either from income or circumstance, to live independent, self-sufficient lives in decent, safe, low-cost homes. To achieve our mission, HIP Housing provides Home Sharing, Self-Sufficiency, and Property Development.
• Where you operate: All cities in San Mateo County
• Whom you serve: Families and Individuals who live, work, go to school or have a housing voucher in San Mateo County.

LifeMoves
• Mission: To provide interim housing and supportive services for homeless families, couples and individuals to rapidly return to stable housing and achieve long-term self-sufficiency. • Where you operate: Countywide, Daly City to East Palo Alto and Half Moon Bay on the coast • Whom you serve: families, couples and individuals experiencing homelessness Mental Health Association of San Mateo County
• Mission: Mental Health Association of San Mateo County is dedicated to improving and enriching the quality of life for individuals in our community who have a mental illness, HIV or AIDS or a co-occuring disorder by providing stable housing and supportive services. • Where you operate: San Mateo County
• Whom you serve: Individual adults, transition age youth, and families.

Samaritan House
• Mission: Fighting Poverty, Lifting Lives
• Where we operate:
o San Mateo Office: Belmont, Burlingame, Foster City, Hillsborough, Millbrae, San Carlos, San Mateo
o E. Palo Alto Office: E. Palo Alto, Menlo Park
• Whom we serve: residents in need, including families with children, seniors, persons living with disabilities, veterans, and unhoused individuals
Daly City Partnership
• Mission: Working together to enrich life in our community • Where you operate: Daly City, Colma, Broadmoor residents primarily. San Mateo County residents.
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8 • Whom you serve: Residents in need, including families with children, seniors, persons living with disabilities, veterans, and unhoused individuals and families. Services for all ages and stages.

Youth Leadership Institute
• Mission: yli builds communities where young people and their adult allies come together to create positive social change. We achieve this in two key ways: providing training, tools and resources for effective youth advocacy, and by leveraging the experience and savvy of adult allies.
• Where you operate: Half Moon Bay, Daly City, & greater San Mateo County • Whom you serve: Low income and BIPOC youth
Ombudsman Services of San Mateo County
• Mission: The residents of Long Term care Facilities are often the most vulnerable in society.

OSSMC works to ensure the protection of these residents through advocacy, direct intervention and collaboration with service providers.
• Where you operate: OSSMC provides services to all licensed LTC facilities in San Mateo County. • Whom you serve: We service all residents in licensed LTC facilities in SMC. We presently serve 442 facilities with a total of 9278 residents
El Concilio of San Mateo County
• Mission: ECSMC is committed to increasing education, employment and access to quality of life services to underserved communities in San Mateo County • Where you operate: County wide, East Palo Alto, Menlo Park, North Fair Oaks/Redwood City • Whom you serve: Low Income, non/limited English speaking and non/limited literacy residents Abode Services
• Mission: Abode Services' mission is to end homelessness by assisting low-income, un-housed people, including those with special needs, to secure stable, supportive housing; and to be advocates for the removal of the causes of homelessness. • Where you operate: Alameda, Santa Clara, San Francisco, Santa Cruz, San Mateo, and Napa counties.
• Whom you serve: People identified as homeless or at risk of becoming homeless 1314 of 1863
April 21, 2022
Dear San Bruno City Council:

We are writing on behalf of YIMBY Law and Greenbelt Alliance regarding San Bruno’s 6th Cycle Housing Element Update. YIMBY Law is a legal nonprofit working to make housing in California more accessible and affordable through enforcement of state law. Greenbelt Alliance is an environmental nonprofit working to en‐ sure that the Bay Area’s lands and communities are resilient to a changing climate.

We are writing to remind you of San Bruno's obligation to include sufficient sites in your upcoming Housing Element to accommodate your Regional Housing Needs Allocation (RHNA) of 3,165 units.

In the Annual Progress Reports that San Bruno submitted to HCD, we observe the following trend of housing units permitted in the last four years:

Year Housing units permitted
2018 6
2019 135
2020 48
2021 83
Average, 2018-2021 68
To meet the 6th cycle RHNA target, the rate of new housing permits in San Bruno would need to increase from 68 units per year in 2018-2021 to 396 units per year in the next 8 years. This is a 482% increase from re‐ cent years. If the current pace were to continue, San Bruno would meet only 17% of its new housing target.

Based on these trends, it is unlikely that San Bruno’s existing realistic zoning capacity is sufficient to meet its 6th cycle RHNA target. According to HCD’s Housing Element Site Inventory Guidebook, housing elements must analyze the realistic capacity of their sites, which may include considerations of “[l]ocal or regional track records”, “past production trends”, and “the rate at which similar parcels were developed during the previous planning period”. A housing element that does not include a significant rezoning component is therefore un‐ likely to be compliant with state law.

We urge San Bruno to include a major rezoning component in its Housing Element—a rezoning large enough to close the gap between recent housing production trends and the RHNA target. The rezoning should be within existing communities and should comply with the city’s obligation to Affirmatively Further Fair Hous‐ ing. We also urge San Bruno to ease any other constraints, such as discretionary approval processes or impact fees, that may impede the rate of development on your city's housing sites.

Thank you,
Sid Kapur, East Bay YIMBY ([email protected])
Rafa Sonnenfeld, YIMBY Law ([email protected])
Zoe Siegel, Greenbelt Alliance ([email protected])
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City of San Bruno
567 El Camino Real
San Bruno, CA 94066
RE: Housing Element Public Comment
To the honorable San Bruno City Council,
The Housing Leadership Council (HLC) appreciates this opportunity to comment on the city of San Bruno’s housing element. HLC works with communities and their leaders to create and preserve quality affordable homes. We were founded by service providers and affordable housing professionals over 20 years ago to change the policies at the root cause of our housing shortage.

In recent years, San Bruno has implemented ambitious new policies to facilitate housing development. In particular, the San Bruno city council’s leadership on Measure N in 2014–and the community’s widespread embrace of the measure–creates potential for significant new housing production along the city’s primary transit and commercial corridors. Ordinance 1898, passed in 2021, has significantly increased ADU production by allowing ministerial approval; the city’s internal efforts to simplify the review process for ADUs further facilitate production. These policies and many others set San Bruno apart from other cities in the county, demonstrating the city’s commitment to promoting housing production.

San Bruno’s draft housing element continues this trend, with strong commitments to introduce important policies and programs. Nonetheless, San Bruno faces new challenges in the 6th RHNA cycle as the city plans for more than 3,000 new homes by 2031.

This letter provides proposals for changes and additions that will enable San Bruno to meet its housing obligations for all residents regardless of income. The first part of this letter examines San Bruno’s needs, constraints, and AFFH analyses. The second part evaluates San Bruno’s site inventory. In conclusion, we propose specific policy recommendations San Bruno can implement to increase likelihood of development on its opportunity sites, affirmatively further fair housing, and otherwise promote housing.

Needs, Constraints, and AFFH Analyses
State law requires housing elements to have several technical analyses, including an analysis of housing needs within the jurisdiction, an analysis of the governmental and nongovernmental constraints to meeting those housing needs, and an analysis of fair housing patterns in the city. 1340 of 1863
Each of these analyses must connect directly to the site inventory and the goals, policies, and programs of the housing element.

Of the three analyses, San Bruno’s draft AFFH analysis is exemplary for San Mateo County.

The draft housing element considers distribution of units by census tract, evaluates concentration and segregation, and proposes specific policies to further fair housing goals.

These proposals are informed by a fair housing survey with diverse respondents, which garnered feedback from a significant number of renters, households with disabled residents, and single-parent households.
1 Though still stronger than most other San Mateo County jurisdictions, San Bruno’s draft needs and constraints analyses would benefit from further improvements. The needs analysis in particular reads like a list of statistics, without significant effort to describe the housing needs indicated by the data. This disconnect between evidence and identified housing needs results in discrepancies between the needs analysis and the goals, policies, and programs.

For example, the city recognizes 8% of residents have a disability, and that “There is a limited supply of handicap accessible, affordable housing generally, and the supply is especially tight near transit.”
2 Yet the city then proposes vague programs (Programs 2-F, 4-G), with quantified metrics to produce 5 units of handicap accessible housing over the next RHNA cycle–an objective that seems somewhat divorced from the identified need and the city’s capacity to meet it by providing incentives for more handicap-accessible housing. (See the Goals, Policies, and Programs section of this letter for amendments and additional policy proposals.) The needs analysis also does not connect its data to the need for very low- and extremely low-income housing, though several data points indicate such need. 63% of jobs in San Mateo pay less than $75,000. Less than 15% of San Bruno’s housing is available at rents of $1,500 or below, compared to almost 20% in San Mateo County and 35% in the Bay Area region. Yet the city does not consider how this difference indicates a lack of housing in the San Bruno community for the highest need residents.
3 One table lists households by income buckets;
approximately 3,500 households make less than 50% of AMI in San Bruno, comprising more than 20% of the town’s population.
4 More than 60% of those renters are cost burdened.

Explicitly recognizing the housing needs demonstrated by this data will ensure the city implements adequate policies to promote deeply affordable homes.

On the other hand, the city’s constraints analysis makes a strong argument that the height limits imposed on San Bruno by Ordinance 1284 do not pose a constraint to housing because of Measure N.
5 HLC has reviewed a number of housing elements for cities with strict height limits, none of which have taken the steps that San Bruno has to promote denser housing 5 Draft housing element, p. 106
4 Draft housing element, p. 58
3 Draft housing element, p. 51
2 Draft housing element, p. 86
1 Draft housing element, p. 133
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development. The city also analyzes the constraints posed by its minimum lot size requirements, and takes significant action to address them in R-2 zones (Program 2-D).

A few constraints could be further analyzed, with stronger policies implemented to address them. The city does not adequately consider the extent to which its floor-area ratio (FAR) requirements affect feasibility of housing development. In particular, FARs of 3.0 in the Central Business District, 2.0 for parcels smaller than 20,000 square feet in the TOD districts, and similarly low FARs in the Multi Use-Residential Focus zones. Several small non-vacant opportunity sites have a negligible likelihood of development without implementation of new policies that exempt them from FAR requirements.

The constraints analysis would also benefit from a more robust analysis of fees. San Bruno’s fees on large multi-unit projects are above average for the county, at $39,412 per unit. 6 The city
claims its fees are “a small portion of overall housing development costs,” when, according to data provided to the city by the 21 Elements consulting team, fees make up 5% of the total cost of large multi-unit projects–a significant portion that often makes the difference between a project being financially viable or not. In its AFFH analysis, the draft housing element bizarrely classifies Housing Development Impact Fee as a policy in place that encourages housing production,
7 when fees are by definition a disincentive on production. Alternatively, HLC proposes several fee waivers for different kinds of housing in the Goals, Policies, and Programs portion of this letter (Programs 4-G and 4-L in particular).

In some cases, the constraints analysis recognizes important barriers to housing development that then go unaddressed in the rest of the draft housing element. Most importantly, the city says that its parking requirements “could still be considered a barrier to the development of affordable housing. Recent development applications and inquiries indicate that developers prefer housing developments with fewer parking spaces than the city’s revised parking requirements require.” 8 However, none of the draft housing element’s policies or programs address parking minimums as a constraint on housing, especially for affordable housing or housing serving populations with special housing needs, such as disabled groups.

Fully analyzing the housing needs present in San Bruno and the governmental constraints to meeting those needs will help the city implement the necessary policies and programs to make its site inventory viable.

Site Inventory
San Bruno’s Regional Housing Needs Allocation requires the city to plan for 3,165 units at the affordability levels described in the “San Bruno’s RHNA Allocation” table as listed below. The site inventory requires cities to demonstrate that they have adequate locations with the necessary policies in place to produce the RHNA allocations. 8 Draft housing element, p. 98
7 Draft housing element, p. 127
6 Draft housing element, p. 111
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Recent changes to state law require cities to meet a higher burden of proof for affordable housing in their site inventories. In particular, sites projected for lower-income housing must meet higher standards than in prior cycles, particularly if more than 50% of sites are non-vacant–as is the case in San Bruno.
9 HLC’s proposals in this section are intended to help
the city comply with state law and create the best possible plan for new housing.

Table I: San Bruno’s Regional Housing Needs Allocation
10 Very Low
Income
Low Income Moderate
Income
Above
Moderate
Income
Total
San Bruno’s
RHNA
Allocation
704 405 573 1,483 3,165
San Bruno’s
Site Inventory
According to
Draft HE
684 468 580 2,002 3,723
In order to demonstrate capacity for enough housing units, San Bruno’s housing element first demonstrates that the city has 670 units in the pipeline. HLC applauds the city’s demonstrated success promoting housing in recent years, and we believe the pipeline count to be accurate.

Next, the city assumes 345 ADUs will be built in the next eight years, a rate of just over 43 ADUs per year–nearly tripling ADU production from the past cycle, with 121 ADUs permitted from 2015-2021. In order to generate this assumption, the city notes that it updated its ADU regulations to comply with state law and streamlined the approval process in 2021, resulting in 68 building permits for ADUs in 2021. However, the city only issued 7 building permits in 2020, despite issuing 51 project approvals, meaning that a large portion of the ADU building permits issued in 2021 were a result of rollover from the prior year. Though HLC applauds San Bruno’s recent ADU production, San Bruno’s assumptions are more generous than HCD’s standard methodology for calculating ADU counts.
11 The city should either provide stronger justification for its assumption of 43 ADUs per year or recalculate the number using data from 2018-2021.

The rest of San Bruno’s housing element relies on projected development from opportunity sites. Though the city provides limited justification for its assumption that all sites will have a 11 HCD’s Site Inventory Guidebook, p. 31, “Use the trends in ADU construction since January 2018 to estimate new production.”
10 The city did not aggregate this information on its own, so I did by adding up the draft housing element’s counts for ADUs, pipeline units, and expected units from opportunity sites. In its housing element, San Bruno claims it has capacity for 3,640 dwelling units (see top of page 165 of the Draft Housing Element); this appears to be a slight miscount based on data available in San Bruno’s draft housing element. 9 HCD’s Site Inventory Guidebook, p. 27
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100% realistic capacity,
12 HLC believes adequate evidence exists for this assumption based on recent development on San Bruno’s high-density corridors. We recommend the city provide more data to justify this assumption to HCD, but we support its inclusion for sites located in San Bruno’s TOD-1 TOD-2, C-N, and P-D zoning districts–the majority of sites.

Though HLC supports San Bruno’s use of 100% realistic capacity, the city assumes inconsistent, unreasonably high unit yields for a number of sites. In the TOD zones, assumed densities range from 76 du/ac (Site #20, 104 San Bruno Ave W) to 200 du/ac (Site #23, 401 San Mateo Ave). The city provides no justification for this massive variation in assumed density within the same zoning district.

Below, the “Small Opportunity Sites with Limiting FAR in TOD Zones” table lists four sites that are smaller than 20,000 square feet, meaning they would be limited by a FAR of 2 based on the restrictions of San Bruno’s TOD zone.
13 Yet the city inexplicably assumes these sites will be developed at densities ranging from 144 du/ac to 200 du/ac. Several sites have active businesses. Limited to a FAR of 2, with parking requirements of at least 1 car per unit, these sites have a very low likelihood of development over the next RHNA cycle. Under current city policies, they should be struck from the inventory.

Table II: Small Opportunity Sites with Limiting FAR in TOD Zones Site Number Site Address Lot Size (acres) Implicit
Assumed
Density (du/ac)
Projected Unit
Count
15 170 San Bruno
Ave W

0.29 144 42
21 104 San Bruno
Ave W

0.17 147 25
22 426 El Camino
Real
.30 166 50
23 401 San Mateo
Ave
.20 200 40
Unit Total 157
In order to justify inclusion of these sites in the inventory, the draft housing element must:

1. Standardize assumed density for sites located within the same zoning district or demonstrate why different densities are appropriate. HLC proposes the city use the 13 The city’s TOD zones limits FAR to 2 on sites smaller than 20,000 square feet. 12 Draft housing element, p. 174, “The calculations used to estimate realistic development capacity along the transit corridors assume complete redevelopment of each site primarily based on conversations with developers and based on the density of similar housing developments that were approved or proposed nearby.”
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conservative assumption of 100 du/ac in its TOD zoning districts absent substantial policy changes.

2. Remove FAR limits for all sites in TOD zones regardless of lot size and decrease parking requirements by 50% for sites smaller than 1 acre (See proposed Program 2-L). This program should have been in place anyway, since the city’s constraints analysis explicitly recognizes the FAR and parking requirements as barriers to housing development.

Furthermore, some large non-vacant opportunity sites do not have adequate evidence to justify their inclusion in the site inventory. In particular, San Bruno’s draft housing element relies on the Tanforan shopping center for 1,000 units of housing, which would be an excellent location for new housing if feasible. Though the shops at Tanforan are closing, the site was recently bought by a commercial real estate developer.
14 Though the Tanforan sites would be an excellent
location for new housing, the city does not have policies in place that make it likely to expect any housing development there. HLC would support inclusion of this site in the inventory at the assumed density if the draft housing element presented evidence that the developer had made some commitment to pursue at least 1,000 units of housing on the site; absent such evidence, housing development at this location is highly uncertain.

In order to promote development of housing at the Tanforan sites, San Bruno’s city council has adopted a nonbinding Land Use Fact Sheet.
15 With program 2-F of the draft housing element,
the city promises to “Meet with the developer of the Tanforan site to … emphasize the need of including a minimum of 1,000 housing units onsite.” HLC believes the city must make significantly stronger commitments to incentivize housing at Tanforan in order to justify inclusion of the site in its housing element. Absent commitment to substantial policy changes–or credible evidence from the city that they have a commitment from the new Tanforan owner to build at least 1,000 units of housing–the Tanforan sites must be removed from the inventory. In the next section, we recommend policies that would validate inclusion of Tanforan as an opportunity site.

Similarly, the city has not demonstrated a high likelihood of development at other non-vacant sites, such as the Bayhill Shopping Center and 2101 Sneath Ln, a current golf driving range.

The city provides no specific incentives for housing development at these sites; in fact, the city explicitly recognizes that Bayhill remains a viable shopping center. In order to ensure compliance with state law, HLC recommends the city remove these sites entirely as well, or implement specific policies as described in the following section to facilitate new development.

Table III: San Bruno’s Site Inventory with Removal of Sites 3, 6, 14, 15, 21-23 Very Low
Income
Low Income Moderate
Income
Above
Moderate
Income
Total
380 388 320 1,261 2,238
15 Reimaging Tanforan: Land Use Fact Sheet
14 SF Gate, Bay Area mall The Shops at Tanforan will be razed for a massive biotech campus 1345 of 1863
This total would be further reduced if the city accounted for several other non-vacant sites with pre-existing uses that could further impede housing development. For example, the draft housing element assumes housing will be built on school district sites, without providing any justification for inclusion of these sites in the inventory. We also do not make adjustments to the city’s ADU counts or to the unexplained variation of projected density in TOD zones.

As demonstrated above, San Bruno must identify new sites or implement new strategies to create the necessary capacity for its site inventory. Fortunately, the city’s goals, policies, and programs already have a number of strong policies to incentivize development, and the city can easily implement new policies that will spur housing development further on key sites.

Though our analysis may seem overly conservative, HLC believes all of the sites we have removed from the site inventory can be justified for inclusion if San Bruno implements new policies increasing the likelihood of housing development on those sites.

Goals, Policies, and Programs
In the following section, HLC describes how San Bruno can strengthen its Goals, Policies, and Programs to more effectively promote low- and very low-income housing as needed to create a viable site inventory. With its explicit action items, discrete timelines, and quantified objectives, San Bruno’s draft goals, policies, and programs are significantly better than any HLC has yet seen in San Mateo County. Still, the programs in particular must be strengthened to remove constraints to housing needs and demonstrate high likelihood of development on opportunity sites.

Similarly to the site inventory, new state laws have added new requirements to the goals, policies, and programs section of a housing element. Passed in 2018, AB 1397 requires cities to directly connect policies and programs to the identified needs, governmental constraints, and site inventory, among other analyses.
16 Another 2018 law, AB 686, implemented Affirmatively
Furthering Fair Housing mandates, specifically requiring cities to consider how their goals, policies, and programs can better advance fair housing goals, especially the production of lowand very low-income housing. The specific programs cities implement must include “concrete steps, timelines and measurable outcomes.”
17 HLC recognizes that San Bruno has many goals, policies, and programs that have these characteristics. All of the programs under Goal 1, “Improve the development review and approval process to reduce processing times and simplify administration,” are exemplary.

Others, such as Programs 2-A and 2-B, set the city up for success in the next RHNA cycle by committing to consider ambitious new policies on a reasonable timeframe. Program 2-D, “Amend the R-2 zoning district to not allow new SFDs on vacant sites and allow two dwellings 17 HCD’s Affirmatively Furthering Fair Housing Guidebook, p. 55 16 See, e.g., Gov. Code, § 65583, subds. (b), (c); HCD, Building Blocks, at https://www.hcd.ca.gov/community-development/building-blocks/ index.shtml 1346 of 1863
per lot regardless of lot size,” is the strongest program to increase missing middle density yet proposed in San Mateo County for this RHNA cycle (as of the date the city receives this letter).

However, some programs do not meet the standards of AB 1397 or AB 686, and others must be strengthened in order to justify inclusion of several significant proposed opportunity sites in the site inventory. The city must also introduce new policies to remove constraints to and implement new incentives for housing development.

Below, HLC proposes specific policies recommended by affordable housing developers and service providers to encourage affordable housing, as well as specific policy proposals to help San Bruno generate a viable site inventory.

New Policies to Promote Housing Opportunity
Proposed
Policy or
Program
Proposed
Measure(s)
Actions and Justification
Amend
Program 2-B
Put Forward a
Ballot
Measure to
Increase
Building
Heights and
Floor
Numbers
Along the El
Camino Real
Corridor
Unclear language like “Evaluate the possibility of putting forth a ballot initiative” (the current draft program’s text) undermines this program. Making a firmer commitment to pursue a ballot measure to increase allowable heights and floors along
Camino Real may be necessary to demonstrate that the sites along Camino Real outside of the current TOD zones qualify as opportunity sites.

Amend
Program 2-F
Incentivize
Housing
Development
at Tanforan
In order to justify inclusion of the Tanforan sites in its site inventory, San Bruno must either present evidence
demonstrating commitment from the property owner to build 1,000 homes or implement specific policies incentivizing housing on this site, especially affordable housing. These policies could include but are not limited to:
- 50% parking reduction for all housing units
- Impact fee waiver for very low- and extremely
low-income units
- City-funded subsidies for stand-alone affordable
housing development built in partnership with a
nonprofit developer
Amend
Program 2-H
Identify
Publicly
Owned Sites
for Affordable
Housing
In addition to commissioning a study for housing development analysis on publicly owned sites, HLC recommends San
Bruno also consider sites owned by religious organizations and nonprofits.
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Program 2-I Allow
Pre-Approved
ADU Designs
with
Expedited
Permitting
Cities can incentivize ADU development by lowering costs.

Pre-approved ADU designs have successfully spurred ADU
production in a number of cities, from big cities such as San Jose to smaller ones like Encinitas.

Program 2-J Waive Impact
Fees for
ADUs With
Low- or Very
Low-Income
Deed
Restrictions
Lowering costs for deed-restricted affordable ADUs in
particular will incentivize production of the lower-income ADUs that San Bruno needs in order to meet the needs of all
residents and create a compliant site inventory.

Program 2-K Partner With
Nonprofit
Property
Management
to Incentivize
Property
Owners to
Rent Their
ADUs at
Affordable
Rates
Nonprofit property management organizations such as Hello Housing or HIP Housing can provide low-cost property
management services to help households rent ADUs out at affordable rates. The city can actively partner with these providers and promote their services to encourage ADU
affordability.

Program 2-L Facilitate
Housing on
Small
High-Density
TOD Parcels
- Allow unlimited FAR for all parcels in TOD-1 and
TOD-2 districts regardless of lot size.
- Reduce parking requirements by 50% for all sites
smaller than 1 acre expected in TOD-1 and TOD-2
zones.
-
Program 3-C Rental
Registry
Create a rental registry listing all properties available for rent in the city, especially affordable rentals and those accessible to people with disabilities.

Program 3-D Emergency
Rental
Assistance
Work with organizations to increase funding available to tenants at risk of not making rent.

Program 3-E Improved Just
Cause
Eviction
Ordinance
Commit to a local ordinance that protects more renters from unreasonable and unfair evictions.

Program 3-F Relocation
Benefits and
First Right of
Commit to passing an ordinance that requires landlords to provide tenants with money to cover moving costs and finding a new rental when evictions are the result of not maintaining 1348 of 1863
Return the health and safety of the building. Require that a tenant be reserved a new unit at the prior level of affordability in the case they are displaced during redevelopment.

Amend
Program 4-G
Create 25
Housing Units
For
Development
ally Disabled
Community
During
Planning
Period
As currently written in the draft housing element, Program 4G’s commitment to create 5 ADA-accessible units over the planning period does not reflect the identified need for housing for those with disabilities in the city’s needs analysis. HLC proposes the city set a higher goal, and then make specific commitments to implement new policies, including but not limited to:
- Waive parking requirements for units geared toward
the disabled.
- Waive impact fees.
- Allow extra density bonus for projects with more units accessible to disabled communities.
- Provide expedited by-right approval for projects that have facilities for special needs populations.

Program 4-J Fee
Exemptions
for 100%
Affordable
Housing
Projects
According to the 21 Elements Fee Survey, San Bruno’s fees for large multi-family housing projects cost an average of 5% of the total development costs. These fees can make many affordable housing projects, which rely on public subsidy, infeasible. Waiving or lowering fees for 100% affordable housing projects can promote the production of more
affordable housing across a spectrum of income levels.

Program 4-K Expand
Sources of
Funds for the
City
Affordable
Housing
Fund.

In order to raise reliable revenue, the city would benefit from internal revenue-raising proposals, such as:
1) Vacancy Tax - Parcel taxes in the form of a
vacant property tax have been used by cities
(VPT, Oakland) to fund affordable housing and
homeless services; as well as to entice owners
of undeveloped sites to either sell or build
homes on their parcels.
2) Transfer Tax - A one-time tax payment that is
levied by a government on the transfer of
ownership to property (i.e. sale of a home) from
one individual or entity
HLC recommends that the city commit to dedicating staff time and arranging a range of public meetings to discuss
opportunities to raise revenue from local sources to subsidize affordable housing.
4-L Promoting
very low- and
extremely
- Allow flexible inclusionary housing ordinance, with a lower proportion of BMR units if they are more deeply
affordable
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low-income
housing
- Waive parking requirements for units geared toward
the disabled.
- Waive impact fees.
- Allow extra density bonus for projects with more units accessible to disabled communities.
- Provide expedited by-right approval for projects that have facilities for special needs populations.
4-M Upzone
HLC wants to be a partner to the city, sharing our collective knowledge of state law and best practices to facilitate fair housing. Please contact me or other HLC staff if you would like to talk further about how San Bruno can identify and implement policies that will best meet the community’s needs.

Thank you for your consideration,
Jeremy Levine
Policy Manager, Housing Leadership Council of San Mateo County Alex Melendrez,
Organizing Manager, Peninsula For Everyone/YIMBY Action 1350 of 1863
From: Paul J Wapensky
Sent: Tuesday, May 24, 2022 7:56 PM
To: Michael Smith
Subject: Housing Element Comments
We are increasing the Cities housing by 3600 units. Where is all the water to support these units going to come from?
Paul Wapensky
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Appendix K
Complete Site Inventory
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RHNA distribution of units for Density > 30 City Inclusionary Policy

VL L M AM VL L M AM
HCD Assumption 22% 13% 18% 47% Rental 5% 5% 5% 85%
For Sale 0% 5% 10% 85%
Tanforan Total
Key Vacant/Nonvacant Site (sites where you think residential development/redevelopment will occur in the 6th cycle) 222 128 181 469 1000 Site Name Description Address APN(s) Sq ft. Est. Acreage Est. number of units Density (DUA) Very Low Low Moderate Above Moderate Total (should match col H) Notes (optional) Rationale (optional) Column1 Column2 Tanforan 0.0
70dba Seritage Regional Shopping Center - Included in Tanforan 1150 El Camino Real 014-316-330 513572 11.8 100 22 22 13 18 47 100 1000 total Tanforan Mall, developer interest 70dba Tanforan Regional Shopping Center - Included in Tanforan 1150 El Camino Real 014-316-360 521631 12.0 250 21 56 32 45 117 250 Tanforan Mall, developer interest Tan = rezoneJCsite Penny 1 Regional Shopping Center - Included in Tanforan 1122 El Camino Real 014-316-300 680158 15.6 250 16 56 32 45 117 250 Tanforan Mall, developer interest Tanforan Regional Shopping Center - Included in Tanforan 1122 El Camino Real 014-316-240 667731 15.3 300 20 67 38 54 141 300 Tanforan Mall, developer interest Parking Lot for Seasonal Sales overflow mall parking lot 1292 Huntington Ave. 014-311-060 61083 1.4 100 71 22 13 18 47 100 Tanforan Mall, developer interest Total 56.1 1000 18
Walgreens retail store 333 El Camino Real 020-293-030 57328 1.3 150 114 33.36 19.19 27.16 70.28 150 developer interest x AT&T Building office building 840 San Bruno Avenue 020-071-050 68446 1.6 320 204 71 41 58 150 320 Preliminary plans/site for sale x Melody Toyota Showroom vehicle sales showroom building 750 El Camino Real 020-126-200 11926 0.3 32 117 7 4 6 15 32 developer interest x Melody Toyota Lot vehicle sales lot 750 El Camino Real 020-126-050 2919 0.1 7 104 2 1 1 3 7 developer interest x Melody Toyota Lot vehicle sales lot 750 El Camino Real 020-126-140 14205 0.3 34 104 8 4 6 16 34 developer interest x Car sales Lot vacant site 529 El Camino Real 020-256-090 4596 0.1 5 47 1 1 1 2 5 x Car sales Lot vacant site 529 El Camino Real 020-256-100 3000 0.1 3 44 1 0 1 1 3 x Car sales Lot vacant site 529 El Camino Real 020-256-130 5000 0.1 6 52 1 1 1 3 6 x Car sales Lot vacant site 529 El Camino Real 020-256-140 5000 0.1 6 52 1 1 1 3 6 x Car sales Lot vacant site 529 El Camino Real 020-256-150 7500 0.2 9 52 2 1 2 4 9 x Car sales Lot vacant site 529 El Camino Real 020-256-160 2500 0.1 3 52 1 0 1 1 3 x Car sales Lot vacant site 529 El Camino Real 020-256-170 2500 0.1 3 52 1 0 1 1 3 x Car sales Lot vacant site 529 El Camino Real 020-256-180 2500 0.1 3 52 1 0 1 1 3 x Car sales Lot vacant site 529 El Camino Real 020-256-190 2500 0.1 3 52 1 0 1 1 3 x Car sales Lot vacant site 529 El Camino Real 020-256-250 1617 0.0 2 54 0 0 0 1 2 x Car sales Lot vacant site 529 El Camino Real 020-256-260 4761 0.1 5 46 1 1 1 2 5 x Car sales Lot vacant site 529 El Camino Real 020-256-270 6307 0.1 7 48 2 1 1 3 7 x Car sales Lot vacant site 529 El Camino Real 020-256-280 3234 0.1 4 54 1 1 1 2 4 x Car sales Lot vacant site 529 El Camino Real 020-256-320 6186 0.1 7 49 2 1 1 3 7 x Car sales Lot vacant site 529 El Camino Real 020-256-340 2483 0.1 3 53 1 0 1 1 3 x Car sales Lot vacant site 529 El Camino Real 020-256-350 2483 0.1 3 53 1 0 1 1 3 x vacant vacant site 170 San Bruno Ave. 020-111-160 12500 0.3 42 146 9 5 8 20 42 development application submitted x former Budget Motel vacant site 850 El Camino Real 020-116-310 27442 0.6 60 95 13 8 11 28 60 x IHOP restaurant and parking lot 590 El Camino Real 020-145-020 3332 0.1 7 92 2 1 1 3 7 vacant x IHOP restaurant and parking lot 590 El Camino Real 020-145-030 3334 0.1 7 91 2 1 1 3 7 vacant/city owned IHOP restaurant and parking lot 590 El Camino Real 020-145-010 4535 0.1 8 77 2 1 1 4 8 IHOP restaurant and parking lot 590 El Camino Real 020-145-470 11498 0.3 20 76 4 3 4 9 20 vacant vacant site 104 San Bruno Ave. 020-111-150 7525 0.2 25 145 6 3 5 12 25 density est based on adjacent site Russo Dental medical office 1101 El Camino Real 020-013-200 5214 0.1 15 125 3 2 3 7 15 San Bruno Pet Hospital veterinary office 1151 El Camino Real 020-013-100 24608 0.6 60 106 13 8 11 28 60 0 0
Bank of America Bank/Parking 465 San Mateo Avenue 020-362-180 22900 0.5 45 86 10 6 8 21 45 underutilized Citibank Bank/Parking 475 San Mateo Avenue 020-361-240 31500 0.7 60 83 13 8 11 28 60 underutilized Chilis Restaurant 899 El Camino Real 020-019-080 57069 1.3 100 76 22 13 18 47 100 Bedroom Express retail store 426 El Camino Real 020-362-240 14744 0.3 50 148 11 6 9 23 50 San Bruno Gas gas station 401 San Mateo Avenue 020-362-210 10854 0.2 40 161 9 5 7 19 40 Below 30 DUA
large site with one house (R-2) underutilized site 117 San Juan Avenue 021-172-130 9920 0.2 2 9 0 0 0 2 2 Owner interest. Zoning allows for 2 more units Vacant site vacant site 116 San Marco Avenue 021-172-130 5350 0.1 2 16 0 0 0 2 2 Owner interest. Zoning allows for 2 units Vacant site vacant site xxx San Marco Avenue 021-172-120 5350 0.1 2 16 0 0 0 2 2 Owner interest. Zoning allows for 2 units Engvall MS golf driving range 2101 Sneath Ln. 019-270-270 435600 10.0 58 6 0 3 6 49 58 development application submitted Engvall MS golf driving range 2101 Sneath Ln. 019-270-260 483951 11.1 60 5 0 3 6 51 60 development application submitted Bayhill Sites (Specific Plan) 0.0
Bayhill Shopping Center shopping center 851 Cherry Avenue 020-012-190 401192 9.2 210 23 47 27 38 98 210 BHSP housing option per plan Office Building office building 801 - 851 Traeger Avenue 020-017-020 264360 6.1 205 34 46 26 37 96 205 BHSP housing option per plan Key Single-Family Sites
former Edgemont ES school district offices 500 Acacia Ave. 020-253-050 94888 2.2 15 7 0 0.75 1.50 12.75 15 district diposition of site TOTAL 2708 571 335 479 1323 2709
Total
1708
Appendix L
Housing Trust Fund Memo for San Bruno
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Memorandum
To: City of San Bruno
From: 21 Elements, Janet Stone consultant
Date: 11/10/2021
Subject: Housing Trust Fund Memo
Table of Contents
I. Executive Summary and Action Checklist ...............................................................................1 II. Introduction ............................................................................................................................2 III. Purpose................................................................................................................................2 IV. Options to Facilitate HTF Program/Policy Development and Ongoing Implementation.....3 V. Deploying Housing Trust Fund Resources...............................................................................7 VI. Using Public or Institutional Sites for Affordable Housing.................................................14 VII. Summary of Suggested Housing Element Policies & Programs.........................................19 VIII. List of Attachments - Included as Separate Documents....................................................21 I. Executive Summary and Action Checklist
This memo was prepared by the 21 Elements team to help the City of San Bruno efficiently and effectively deploy the City’s BMR In-Lieu Fee Fund and Commercial Linkage fees, collectively referred to as the City’s housing trust fund (HTF). It aims to provide general guidance and options to consider. The project team has also included suggested Implementation Program language to consider for the City’s upcoming Housing Element update.

Here's a quick ‘checklist” for using the memo:
(1) Skim the memo - to get an overall picture of what’s presented (2) Think about which suggested policies and programs are most relevant to your city (3) Use the suggested Housing Element policy & program language as a place to start and tailor to your own situation
(4) Reach out to Janet Stone ([email protected]) for questions or further assistance (5) Finish drafting your Housing Trust Fund-related policies and programs for your Housing Element update
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2 II. Introduction
The City of San Bruno is one of several jurisdictions that submitted a response to a 21 Elements survey on Housing Trust Funds (HTF) sent to all jurisdictions in late August 2021. San Bruno’s response indicated that staff was seeking additional guidance in deploying the City’s HTF. On 10/12/21 Janet Stone, consultant with 21 Elements, held an hour-long scoping session zoom call with staff members Michael Laughlin and Michael Smith. The purpose was to review San Bruno’s HTF program and identify specific areas where staff felt additional assistance was needed to better deploy the jurisdiction’s housing trust funds. For San Bruno, the areas needing additional assistance included:
o Insight into what to spend the HTF on
o Guidance on a policy framework / Steps for putting together a policy framework for cities just starting out that answers key questions, such as what can the HTF funds be used for (e.g. rent subsidy, creation of affordable housing, preservation of units at risk of losing their affordable deed restrictions)
o Dedicated staffing / Currently there is no dedicated staffing for the HTF policy and program work – need to determine how to staff and what resources will be used to pay for this work
o Sample language staff can put in their Housing Element update referring to whatever actions they will be taking on deploying their HTFs
III. Purpose
This memo was developed in response to San Bruno’s HTF survey and information shared during the scoping session. The project team also reviewed relevant sections of San Bruno’s current Housing Element and the 2020 Housing Element Annual Progress Report (2020 APR).

Also provided with this memo (and referenced within) are additional resources that may prove helpful, such as information on preservation and examples of professional services RFQs (Request for Qualifications), Housing Trust Fund NOFAs (Notice of Funding Availability), and RFQs/RFPs (Request for Qualifications/ Proposals) for site-specific affordable housing. 1356 of 1863
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3 The purpose of this memo is to provide:
o General guidance and options to consider to help the City effectively deploy the Commercial impact in-lieu fees and Residential in-lieu fees that comprise the HTF o Suggested Implementation Program language for San Bruno’s upcoming Housing Element update
o Ideas for initial steps the City may wish to consider to get started This memo is not intended to provide detailed policy analysis, site identification assistance, or funding recommendations, as these deliverables are beyond the scope of this 21 Elements Housing Trust Fund initiative.

IV. Options to Facilitate HTF Program/Policy Development and Ongoing Implementation
A. Consider using some HTF resources to support City staffing and/or outside consultants to administer and deploy HTF resources
How to Implement
How to Implement
According to staff, San Bruno currently has a balance of around $3,900,000 in its housing trust fund and is anticipating receiving in the neighborhood of $10.7M within the next year.

Currently, none of the HTF balance has been encumbered (committed) for any specific use, although staff indicated they are “in conversation” with an affordable housing developer to use the funds currently available.

The City may want to consider using a relatively small portion of its current HTF balance (e.g., up to around $50,000, but likely far less) to contract with an experienced affordable housing consultant or consultants for assistance with “start-up” tasks necessary to structure the City’s HTF allocation and disbursement program. According to the 2020 APR, the City Council in 2019 Key Idea: Use a small portion of current HTF balance to fund staff support or a consultant to help with “start-up” tasks necessary to structure the City’s HTF allocation and disbursement program.

Key Idea: Use around 1% - 2% of the HTF balance annually to fund staff support or a consultant to help with ongoing HTF administration (NOFA implementation, RFQs or RFPs, loan administration, etc.)
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4 authorized funding to retain a professional consultant to administer the City’s Affordable Housing Program. However, due to the pandemic, staff was unable to complete the research regarding such consultant. 21 Elements has compiled a list of some experienced affordable housing consultants working in the Bay Area who are able to provide these types of services [see attached list]. Initial tasks could include assisting with development of the HTF’s funding priorities, establishing HTF loan criteria, and drafting the initial Housing Trust Fund NOFA.

Ideally, these tasks could be accomplished within about 6-8 months.

This initial period of time would also provide the city with an opportunity to explore the feasibility of offering a city-owned site that could meet tax credit funding criteria, or even an underutilized portion of a site owned by another public agency or a large institution willing to consider repurposing such area. Staff indicated during the scoping session that there are a number of city-owned parking lots in the downtown area that potentially could be used for affordable housing. An experienced affordable housing consultant could also assist with this task of identifying publicly-owned sites, or portions of sites, that might be redeveloped.

After this initial start-up work, the City may want to consider using at least 1%-2% of the HTF balance annually to engage a consultant who can assist with publishing an initial (and potentially, ongoing) NOFA, evaluating NOFA responses and making awards. Following an award of HTF funds, staff may need assistance with other tasks such as loan document preparation and loan monitoring, etc. An experienced affordable housing consultant can also help prepare and implement an RFQ or RFP if one or more new public or institutional sites have been identified for affordable housing development. Using a small percentage of the HTF annually to support deployment of HTF funds seems reasonable given that the current HTF balance is around $4 million and the staff’s revenue forecast is for another approximately $10.7M to be added in 2022.

Staff will want to consult with the appropriate city departments and officials, including the City Attorney and City Manager, about any legal considerations as well as the question of whether it may be best to add part-time/full-time staff or hire contractors to carry out the types of tasks indicated above.

Why Implement
There is ample precedent for charging a fee or using a portion of loan funds for program development and administration:
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5 § Cities receiving CDBG and HOME funds are allowed to charge a portion of their allocated funding for administration costs – eligible tasks include developing funding priorities, issuing NOFAs, evaluation of NOFA responses, loan documentation, loan monitoring, etc. § Jurisdictions that formerly had RDAs (Redevelopment Agencies) used a portion of their RDA funds to cover administrative expenses; successor agencies are allowed to take an administrative cost allowance
§ In scoping sessions with a number of jurisdictions, staff reported feeling stretched, often beyond capacity, by additional work related to the new funding programs and/or the modification of existing Inclusionary and Commercial Linkage fee programs § Figuring out how to use HTF resources calls for affordable housing policy and program expertise that is often beyond the capacity of many smaller jurisdictions § Several years ago, San Mateo County Department of Housing began using a small percentage of the Affordable Housing Trust Fund (AHF) to support HCD staffing time involved in administering the AFH
o The Department charges a 1.5% loan fee when a loan is committed to an affordable housing development
o Each year, approximately $250,000 in AHF loan fees is collected and used for administration of the AHF, including accounting and fiscal services, staff project management time, loan administration, and activities to carry out the NOFA process (e.g., developing NOFA funding guidelines, drafting the NOFA, evaluating responses including due diligence reviews, selection of awardees, etc.) § The County’s method of applying a service fee to AHF loans is just one possible way of structuring such administration fee; there may be other equally useful approaches Suggested HE Update Implementation Program language: Use* a relatively small portion of the current Housing Trust Fund balance (e.g., up to around $50,000) to contract with an experienced affordable housing consultant or consultants for assistance with “start-up” tasks necessary to structure the City’s HTF allocation and disbursement program. Such tasks will include assisting with development of the HTF’s funding priorities, establishing HTF loan criteria, and drafting the initial Housing Trust Fund NOFA.

B. Consider charging a modest monitoring fee for Inclusionary Housing units How to Implement
For the same reason that it may be appropriate to consider using a small percentage of San Bruno’s HTF to support implementation of HTF activities, the City may also want to consider charging a modest annual per-unit monitoring fee for approved projects that create inclusionary (BMR) units. The project team noted in the 2020 APR that staff annually monitors the 325 affordable deed-restricted units at the Crossing. However, there was no indication that BMR units are monitored for compliance. The per-unit fee can be set at a level that does not impact the market rate project’s operational budget to any significant degree. A monitoring fees program can also be used to support the proper documentation, through a deed restriction and well-designed BMR agreement between the owner and the City, of all of the conditions and requirements related to the BMR units. Such BMR agreements then become the basis for the monitoring activities with which the owner has agreed to cooperate.

Why Implement
§ Without appropriate BMR agreements and monitoring of compliance with BMR rent/sale and income restrictions, many affordable units – both homeownership and rental – will inevitably be lost over time
§ Units may revert to market-rate housing due to lack of awareness on the part of owners or residents, negligence, or intentional noncompliance
§ Simple ongoing monitoring efforts costing a relatively modest per-unit amount can go a long way to ensure that such loss of valuable community assets, worth many millions of dollars to replace, does not happen
Key Idea: Charge a modest annual per-unit monitoring fee for projects with inclusionary (BMR) units. Use the fees to support annual monitoring and to create a deed restriction for each property and a legal agreement laying out all the conditions and requirements related to a project’s BMR units.
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7 Suggested HE Update Implementation Program language: Consider charging a modest per-unit monitoring fee for approved projects creating inclusionary units in order to support ongoing monitoring of the BMR units according to the project’s BMR agreement.

V. Deploying Housing Trust Fund Resources
A. Identify the City’s funding priorities for allocating HTF resources B.

How to Implement
As mentioned earlier, an important initial step is to identify funding priorities for the HTF. The City Council will most likely look to the City’s Housing / Community Development staff to make recommendations for the Council’s or HTF oversight board’s consideration. The following types of funding priorities have been identified by a number of jurisdictions in the bay area and will be further discussed below:
§ Creation of new affordable housing units, serving a range of household incomes and a diverse set of populations (including supportive housing), with an emphasis on Very Low- and Extremely-Low Income units -- income ranges that are currently underserved § Preservation of deed-restricted affordable housing
§ Preservation of “naturally-occurring” affordable housing § Rental assistance for lower-income households
§ First-time Home Buyer assistance for income-qualifying homebuyers § Assistance with rehabilitation and repair for income-qualifying homeowners § Support for programs providing shelter, transitional housing, supportive housing, etc.

Note: not all potential funding priorities may apply to San Bruno: for example, as discussed below, it appears the City does not have any existing deed-restricted affordable housing properties that are “at-risk” of conversion to market rate due to expiring use restrictions.

Key Idea: Identify funding priorities for the HTF.
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8 Why Implement
§ Before RDAs were dissolved, there were funding guidelines for “set-aside” funds for affordable housing; HOME funds also have explicit funding guidelines § Newer sources of affordable housing funds, such as BMR in-lieu fees and Commercial linkage fees, generally have been adopted with little guidance about specific affordable housing purposes for which they may be used
§ Before issuing NOFAs or allocating HTF resources, it would be prudent for cities to identify funding priorities for these funds – which may, of course, change over time Examples of Affordable Housing funding Priorities:

Funding Priority Example: Production of New Affordable Housing Units Typically, jurisdictions in San Mateo County place a high priority on the creation of new affordable housing units that serve a range of needs. Some jurisdictions, including the County, place a very high priority for their HTFs on the development of affordable housing units serving Very Low-Income (VLI) and Extremely Low-Income (ELI) households, while still allowing projects receiving HTFs to target a certain portion of the units as “workforce” or Low-Income units serving households up to 80% of Area Median Income (AMI), currently the upper allowable AMI for tax-credit projects. We noted in the City’s 2020 APR that no ELI or VLI units have been built to date in the current Housing Element period, although 26 VLI units were approved in August 2020 as part of the Mills Park Center mixed-use project.

Because nearly all new affordable housing developments are funded with tax credits, and a growing number are funded with State HCD program funds as well, it would be prudent to refer to tax credit guidelines and State HCD program guidelines when developing the City’s guidelines for new affordable housing developments. Aligning guidelines with existing State and Federal programs will ensure that the projects your city encourages are feasible.

The City may decide to encourage some affordable developments, or at least a portion of the units in a development, to address particular housing-related needs identified in San Bruno’s Housing Element, such as low-income large households, low-income seniors, and low-income persons with disabilities (who may require supportive housing services). One factor to keep in mind is that some areas within San Bruno have been designated “High Resource” areas under current tax credit regulations, which means that “large-family” new construction tax credit 1362 of 1863
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9 projects in these areas would be very competitive under the 9% tax credit program. Projects winning 9% tax credits receive a much greater amount of funding than those receiving funding under the 4% program, which translates to more capital available for the project and the ability to more deeply target units to serve Extremely Low- and Very Low-Income households.

The specific location and size of a potential affordable housing site will also influence the type of housing (e.g., senior, family, supportive housing) that is most appropriate to build on that site, although many potential populations can often be accommodated on well-located sites near transportation and services. A growing trend is to serve more than one population within an affordable housing development, while ensuring that the specific combination of resident populations is carefully planned and there are adequate services provided for the residents In certain cases, the City may also wish to encourage affordable housing developments to provide neighborhood-serving amenities or a mix of uses where such mixed-use development is both feasible and appropriate.

In addition to the location and populations served by an affordable housing development, it is important to carefully consider the selection of the developer partner. The guiding consideration for jurisdictions when selecting which affordable housing developers to work with should be choosing those that meet the highest standards: i.e., they are large, missiondriven affordable housing developers; they will work with the City to expertly address identified affordable housing needs; they will work diligently to secure additional types of subsidy to supplement local funding and tax-credit financing, helping them achieve deeper-income targeting for ELI and special needs populations; and they also have the experience and commitment to provide (and have consistently provided) high quality, well designed, cost effective and expertly managed developments that continue to meet residents’ needs over the long-term.

Funding Priority Example: Preservation of Deed-Restricted Affordable Housing Another important priority for a jurisdiction may be the preservation of deed-restricted affordable housing. Some jurisdictions have existing deed-restricted affordable housing projects at “high” or “very high” risk of being lost to the affordable housing stock in the near future because of expiring use restrictions and owners who are contemplating or intending to sell. We consulted with California Housing Partnership Corp (CHPC) to find out whether San Bruno has any affordable projects at “high” or “very high” risk of conversion to market-rate over the next 1363 of 1863
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10 10 years. It appears San Bruno does not have such at-risk developments with use restrictions expiring over the next decade. CHPC has also shared this information with city staff.

Funding Priority Example: Preservation of “Naturally Occurring” Affordable Housing (NOAH) Another preservation funding priority the City may wish to consider is the preservation of socalled “naturally occurring” affordable housing (NOAH), which means existing rental housing that is not rent-restricted but is serving lower-income households at affordable rents.

CHPC recently released several publications on local preservation strategies, including a 2-page brief for local governments [see attached CHPC policy brief on “Best Practices in Local Government Preservation Strategies”]. One strategy presented is the preservation of NOAH in areas that have recently gentrified, are near high quality transit and are in higher opportunity areas. CHPC suggests that jurisdictions can consider using a portion of their housing trust funds for preservation of this type of affordable housing.

There is limited experience to date with the preservation of NOAH in San Mateo County. The County Department of Housing assisted several such projects in the last few years, funding a portion of the acquisition cost and rehab work for several smaller apartment properties scattered throughout the county and a 55-unit apartment complex in Redwood City occupied primarily by persons receiving supportive housing assistance. These apartment complexes now have deed restrictions that will keep them affordable over time.

The County has found these type of preservation projects to be extremely costly, requiring a high level of local subsidies. Each project also required a hefty commitment of developer time and staffing. Smaller apartment complexes may be too small to receive acquisition/ rehabilitation tax credits, and larger ones may not have the degree of rehabilitation needed to secure such tax credits. Perhaps the biggest barrier to using tax credits is a LIHTC provision referred to as the “10 year hold” rule, which dramatically limits when tax credits can be used for these types of acquisitions, thus leaving local jurisdictions entirely on their own in financing the acquisition beyond a (likely very small) bank loan. In contrast to this poor leveraging, new construction can utilize tax credits, tax exempt bonds, and a range of other state and federal that only have new construction as eligible projects types.

Another issue for these types of projects is the possibility of abuse by less-than-scrupulous actors. This may happen when a city with limited staff capacity fails to carry out the required 1364 of 1863
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11 due diligence necessary to evaluate the long-term health of the asset or the acquisition terms.

The County’s Department of Housing has become aware of situations in which parties have acquired NOAH buildings with city support and then either flipped them to REITs or convinced a legitimate nonprofit to acquire the building afterward, while also taking some cash out of the sale. Some have told the city the building is in good shape when in reality it is not, leaving the city on the hook to put in additional money some years down the road when the new owner comes back looking for assistance. At that point a city may have little recourse since the project is already deed-restricted and occupied with residents who need the affordable housing. We are providing this “heads-up” in order to help cities avoid these types of potential problems. If San Bruno is considering undertaking a NOAH project, we encourage staff to consult a technical expert such as California Housing Partnership Corporation (CHPC) or similar firm with extensive affordable housing financial expertise.

While the County Department of Housing has not ruled out assisting such acquisition of NOAH in the future, any such projects will need to be carefully considered and meet reasonable funding criteria.

Funding Priority Example: Rental Assistance for Lower-Income Households At the present time, Covid-related rental assistance is still available to landlords and eligible residents in San Mateo County. This assistance is provided through the California State Rent Relief Program / Housing is Key. When this assistance is no longer available, jurisdictions may wish to consider providing some amount of programmatic support for existing nonprofits that help lower-income residents with emergency housing assistance.

Funding Priority Example: First-Time Home Buyer Assistance for Income-Qualifying Homebuyers A jurisdiction may wish to provide assistance to help families with different incomes and housing needs become homeowners. For example, the City of San Mateo sponsors a variety of loan programs to help households purchase condominiums and townhouses within San Mateo City limits. Applicants who live or work in the City of San Mateo receive priority over those who do not. The Housing Endowment and Regional Trust (HEART) of San Mateo County also offers down-payment assistance loans for first-time home buyers in the county.

Funding Priority Example: Assistance with Rehabilitation and Repair for Income-Qualifying Homeowners
Program 1-D of San Bruno’s current Housing Element calls for “exploring opportunities to create a city-sponsored program to assist homeowners with rehabilitation and preventative 1365 of 1863
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12 maintenance, including potential funding from the City’s BMR Housing In-Lieu Fund.” Should San Bruno decide to use HTF resources for this type of program, it could limit the program to lower-income homeowners to be consistent with the purposes of the HTF sources of funding.

Funding Priority Example: Support for Programs Providing Shelter, Transitional Housing, Supportive Housing, etc.

Currently a number of jurisdictions provide city funding to support nonprofits providing shelter, transitional housing, supportive housing, and shared housing. The city could consider using some HTF resources to support these types of programs on an annual basis.

Suggested HE Update Implementation Program language: The City will identify funding priorities for affordable housing projects and programs funded by the City’s Housing Trust Fund.

B. Developing “Notices of Funding Availability” (NOFA)
How to Implement
Housing Trust funds for affordable housing production, rehabilitation and preservation are best deployed through a competitive process, using NOFAs. A jurisdiction may also decide to use some of its HTF to assist with the provision of housing-related services for low-income populations. If this is the case, the jurisdiction may want to use a competitive process to award these funds as well, by including the services-related funds in the larger HTF NOFA or using a separate competitive funding process.

Compatibility of HTF Funding Criteria with Other Funding Sources The vast majority of subsidized affordable housing that has been developed in San Mateo County has received part of its funding from the County. Therefore, in addition to aligning the City’s HTF funding criteria with tax credit and state funding criteria, an equally important factor contributing to the successful development of affordable housing will be the consistency or compatibility of the City’s HTF funding criteria for affordable housing production and Key Idea: Use a NOFA process to deploy funds for affordable housing production, rehabilitation, and preservation. NOFAs can be “rolling” with no fixed deadline for responses or they can have a fixed deadline for submittals.

Key Idea: If using the HTF to assist with housing-related services, consider also using a competitive process to award these funds.
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13 preservation with those of the County’s Department of Housing, maximizing the ability of an affordable housing developer to secure tax credits, a city’s local funding, and funding from the County.

NOFAs with Submittal Deadlines vs “Rolling” NOFAs
There are several considerations when deciding whether to issue NOFAs with submittal deadlines versus those that are “rolling” or open-ended. For large jurisdictions with very large pots of money that could support several funding awards, there likely would be a high degree of interest from affordable housing developers. A fixed deadline for submission allows multiple proposals targeting different sites to compete for the available funding. Proposals can then be compared and evaluated against the NOFA criteria, with several superior proposals typically selected for funding. However, there can be some significant drawbacks to fixed-deadline NOFAs, particularly when issued by a single jurisdiction (as opposed to the Countywide AHF NOFA).

When faced with a fixed-deadline NOFA, affordable developers looking for sites have to scramble to identify interested sellers, potentially bidding up the price for the few cityidentified priority sites that are also available and developable. Additionally, some jurisdictions are only gradually accumulating HTF money and it could take several years to accumulate enough funds to support more than one project. Given these considerations, it may be more advantageous to issue a rolling NOFA – using objective criteria to award some or all of the available funds. Rolling NOFAs encourage affordable housing developers to explore site acquisition opportunities and consult with city staff about potential development concepts for a site or sites. When an interested and qualified developer has satisfied all the funding criteria and has achieved site control, a funding commitment can go to Council for approval. This process provides greater certainty for the developer; further, affordable housing developers will see that the City is interested in creating a “pipeline” for considering new proposals and using their HTF resources as these accumulate.

Site-specific developer RFQs or RFPs for public land, on the other hand, almost always use a fixed-deadline competitive process in order to generate multiple responses that can be compared and evaluated at the same time.
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14 Timing of NOFA / RFP
Another item to consider is the timing for a HTF NOFA and/or any site-specific RFQ/RFP. Should San Bruno decide to use a fixed-submittal-date NOFA or RFQ/RFP process, it ideally should be completed at least a month or two prior to the issuance of the County’s AHF annual NOFA funding cycle. That way, an affordable housing developer who has secured a San Bruno commitment (even a preliminary commitment) of funding and/or site control will have a much greater likelihood of competing successfully to secure additional funding needed for the project from the County AHF trust funds. This type of “piggybacking” of local subsidy commitments will also positively impact the developer’s timetable for securing all the needed sources of the project’s financing, facilitating a shorter time period between when local subsidies have been secured and the start of construction.

Why Implement
§ Local HTFs accumulate funds over time and cities allocate these for public purposes § Jurisdictions must be transparent about the use of such funds and keep the public informed about policies, allocation rounds and funding decisions § Affordable housing developers also benefit from understanding the City’s funding priorities and policies
Suggested HE Update Implementation Program language: The City will issue an initial Housing Trust Fund “Notice of Funding Availability” (NOFA) for affordable housing production, rehabilitation, and/or preservation when the HTF has built up a balance of between $2- $3 million, unless the City identifies a priority that requires a larger balance. The City will also consider using a portion of the HTF, through a competitive process, to support housing-related programs and services provided by nonprofit organizations.

VI. Using Public or Institutional Sites for Affordable Housing In addition to providing financial resources through the HTF, jurisdictions can identify publiclyowned or other institutional sites that might be made available for affordable housing.

A. Consider contributing city-owned land
Key Idea: Identify and facilitate affordable housing development on city-owned land. 1368 of 1863
Housing Trust Fund Memo – City of San Bruno
November 10, 2021
15 How to Implement
In December 2020 San Bruno identified a city-owned property, Admiral Court, as a locallyowned surplus site and is trying to facilitate housing development there (at this time, the project team is not aware of the status of this initiative). The city has also implemented, or is in the process of implementing, various Housing Element programs designed to encourage and incentivize affordable housing development in the TCP area, El Camino Real corridor, and downtown. These are all very positive steps that will facilitate the provision of affordable housing over time.

Jurisdictions typically solicit developer interest in building affordable housing on city-owned land through issuing either a Request for Qualifications or site-specific Request for Proposals [see attached examples of Developer RFQs and Developer RFPs]. Following selection of a single developer or development team, a site is typically conveyed either through the transfer of ownership to the developer (or an affiliated entity) for a nominal amount, or through means of a long-term ground lease. If a site is to be ground-leased rather than having ownership transferred to the developer, it would be reasonable (and the developers would expect) to negotiate a ground lease requiring an initial lump-sum payment or regular ground lease payments.

Building on efforts to date, the City could continue to work on the following:
o Identifying additional city-owned land having the potential for affordable housing development and located in Priority Development Areas, other areas zoned for mixeduse, and other appropriate areas o Applying various policies and regulatory incentives to the development of these sites (e.g. fee waivers, reduced parking requirements, increased height limits, flexible setback requirements, etc.) to allow for the densities and other development conditions necessary to make affordable housing development feasible o Considering using outside consultants with expertise in Low-Income Housing tax credits and affordable housing production to help evaluate potential sites for feasibility of securing tax credits, state affordable housing program funds, and other types of financing
o If a city-owned site is approved for affordable housing development, preparing an RFQ to solicit qualified developers or an RFP to solicit conceptual development proposals 1369 of 1863
Housing Trust Fund Memo – City of San Bruno
November 10, 2021
16 Why Implement
§ Given the high cost of developing affordable housing in the Bay Area, affordable housing developers look to local jurisdictions to provide a significant amount of subsidy – in the form of land contribution, housing trust funds or other local funds, fee waivers/reductions, parking requirement reductions, etc. – that make projects “pencil” § Local subsidy is needed because non-local financing sources such as tax credits, state funding, and a commercial mortgage typically do not cover all of the development costs § According to data from the County’s Dept of Housing, city and county support – in the form of land contribution and financial subsidies – typically provides anywhere from 10% - 30% of the cost of an affordable development
§ Often there are few available sites, or available at a price that is feasible for an affordable housing development, in areas most advantageous for affordable housing development § Developers of affordable housing will be highly incentivized to deploy their limited staffing resources to develop affordable housing in jurisdictions where low- or zero-cost land is ready to be contributed for affordable housing production -- particularly if the available land is already zoned for higher-density residential development and the City has adopted other measures such as fee waivers, reduced parking requirements, density bonuses, etc. to incentivize affordable housing development and make it more financially feasible to build § Making additional subsidies available to such developments with deeper income targeting (ELI and VLI) and/or supportive-housing, will be an additional incentive for developers of affordable housing
Suggested HE Update Implementation Program language: To expand the stock of affordable housing, the City will continue to identify and evaluate city-owned land that could be developed with affordable housing. Should an appropriate site or sites be identified and selected for disposition, the City will apply regulatory and zoning incentives necessary to make affordable housing development feasible on the site(s) and will issue at least one RFQ/RFP to solicit qualified affordable housing developers within ___ years of adoption of the Housing Element.

B. Explore potential affordable housing opportunities with public agencies, health care institutions, and school districts
C.Key Idea: Approach public agencies, health care institutions, and school districts to assess interest in creating affordable housing on some of their underutilized or vacant properties or portions of sites; if there is interest, use zoning and regulatory incentives to facilitate such affordable housing development.
1370 of 1863
Housing Trust Fund Memo – City of San Bruno
November 10, 2021
17 How to Implement
According to the 2020 APR, the city is working with private developers to develop housing at the former Crestmoor High School and Engvall School sites, two former surplus school sites. The project team is unaware of the nature of the housing contemplated for these surplus sites (e.g. whether it would be 100% affordable). In addition to sites that have been declared surplus, there may be cases where a property – or portion of a property – is owned by a public agency, institution, school district, or other semi-public organization and is underutilized or currently vacant but has not been formally declared surplus. In such cases, it would be worthwhile to approach these property owners to assess interest in further exploring affordable housing development opportunities.

Why Implement
§ Agencies and institutions are increasingly aware that lack of affordable housing negatively impacts their workforces and threatens the overall economy § Some are re-examining their own properties for affordable housing possibilities § Recent examples in San Mateo County indicate interest in these types of initiatives:
o A 122-unit workforce housing complex currently under construction on the Jefferson Union High School District’s property in Daly City, which will serve the School District o A supportive housing development serving homeless and at-risk Veterans completed in 2015 on an underutilized area of the Menlo VA campus in Menlo Park Suggested HE Update Implementation Program language: To expand the stock of affordable housing, the City will work with public agencies, health care institutions and school districts to help identify potential sites or portions of sites that could be developed with affordable housing.

If there is interest from an owner entity in potentially developing affordable housing on a site or sites, the City will apply various regulatory and zoning incentives necessary to make affordable housing development feasible on such sites.

C. Explore potential affordable housing opportunities with faith-based institutions
D.

Key Idea: Do preliminary outreach to faith-based congregations to assess interest in exploring the idea of developing affordable housing on a portion 1371 of 1863
Housing Trust Fund Memo – City of San Bruno
November 10, 2021
18 How to Implement
A number of jurisdictions have begun to explore other innovative opportunities for developing affordable housing. One promising avenue has involved faith-based institutions. San Bruno could consider doing some preliminary outreach to faith-based congregations to assess interest in exploring potential creation of affordable housing on a portion of their property. Should any religious organizations express initial interest, the City could host a meeting and invite several affordable housing developers to be available to answer questions. The City could also provide a list of experienced affordable housing developers and encourage any interested faith-based institution to reach out for more information and assistance.

Why Implement
Faith-based organizations may be interested in developing affordable housing because:
§ Their values are often aligned with the idea of facilitating affordable housing § They may have excess or underutilized land that potentially could be developed into affordable housing
§ They may have declining revenues and are looking for a one-time payment or revenue stream to help support ongoing operational expenses
Below are two recent examples of projects under development on a portion of properties owned by faith-based organizations:

E.Jordan Court, now nearing completion, is located on the All Souls Episcopal Parish property in Berkeley. It will provide 34 affordable studio apartments for low-income seniors with incomes between 20% and 60% AMI; 12 of the apartments will be set aside through support from the state’s No Place Like Home program for formerly homeless seniors with serious mental illness. It will include new administrative offices for the clergy, as well as two residences for church staff. The $25 million project, the first affordable housing project in north Berkeley in 30 years, is being developed by SAHA and received funding from six different sources including the City of Berkeley, Alameda County, Housing Trust of Silicon Valley, Federal Home Loan Bank’s Affordable Housing Program, the state’s HCD, LowIncome Housing tax credits, and a bank mortgage. 1372 of 1863
Housing Trust Fund Memo – City of San Bruno
November 10, 2021
19 Suggested HE Update Implementation Program language: The City will engage in outreach to faith-based congregations to assess interest in exploring the concept of using a portion of their properties to develop affordable housing and facilitate a discussion between any interested parties and local affordable housing providers.

VII. Summary of Suggested Housing Element Policies & Programs For ease of reference, all of the suggested Housing Element policies and programs in the memo are listed below:

Policy: Consider using some of the HTF resources to support City staffing and/or outside consultants to administer the HTF and deploy HTF resources Suggested HE Update Implementation Program language: Use* a relatively small portion of the current Housing Trust Fund balance (e.g., up to about $50,000) to contract with an experienced affordable housing consultant or consultants for assistance with “start-up” tasks necessary to structure the City’s HTF allocation and disbursement program. Such tasks will include assisting with development of the HTF’s funding priorities, establishing HTF loan criteria, and drafting the initial Housing Trust Fund NOFA.

Suggested HE Update Implementation Program language: Use* a small percentage of Housing Trust Funds on an annual basis to support city staffing and/or outside consultants who will administer and deploy these funds in a timely, efficient, and productive manner. Such tasks may include accounting and fiscal services, interfacing with housing developers, development of Immanuel-Sobrato Community in San Jose just had its groundbreaking in September of 2021. It will provide 108 permanent supportive affordable apartment homes for chronically homeless residents (the church requested a 100% supportive housing project). This is San Jose’s first redevelopment of a place of worship to include supportive housing. The project is a unique private-public partnership between the City of San Jose, MidPen Housing, John Sobrato, the Housing Authority, and the Immanuel Evangelical Lutheran Church of San Jose. Eleven sources of financing were used. The development is near VTA transit, stores, healthcare and San Jose City College and will include a four-story building with 106 studios and 2 onsite manager units. Amenities include a secured lobby, dog run, 36 parking spaces, large common space, bicycle storage, community room with kitchen, courtyard with outdoor seating, exercise area, computer lab and laundry room. MidPen Housing is paying the church a lump-sum ground lease payment, which will significantly help the congregation financially.
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Housing Trust Fund Memo – City of San Bruno
November 10, 2021
20 funding NOFAs, evaluation of proposals and selection of awardees, loan document drafting, and evaluation of public, agency and institutional properties for potential affordable housing use. *These programs could use more conditional language, i.e., “Consider using”, if the City prefers.

Policy: Consider charging a modest monitoring fee for Inclusionary Housing units Suggested HE Update Implementation Program language: Consider charging a modest per-unit monitoring fee for approved projects creating inclusionary units in order to support ongoing monitoring of the BMR units according to the project’s BMR agreement.

Policy: Identify the City’s funding priorities for allocating HTF resources Suggested HE Update Implementation Program language: The City will identify funding priorities for affordable housing projects and programs funded by the City’s Housing Trust Fund.

Policy: Develop a “Notice of Funding Availability” (NOFA) Suggested HE Update Implementation Program language: The City will issue an initial Housing Trust Fund “Notice of Funding Availability” (NOFA) for affordable housing production, rehabilitation, and/or preservation when the HTF has built up a balance of between $2- $3 million, unless the City identifies a priority that requires a larger balance. The City will also consider using a portion of the HTF, through a competitive process, to support housing-related programs and services provided by nonprofit organizations.

Policy: Consider contributing City-owned land
Suggested HE Update Implementation Program language: To expand the stock of affordable housing, the City will continue to identify and evaluate city-owned land that could be developed with affordable housing. Should an appropriate site or sites be identified and selected for disposition, the City will apply regulatory and zoning incentives necessary to make affordable housing development feasible on the site(s) and will issue at least one RFQ or RFP to solicit qualified affordable housing developers within ___ years of adoption of the Housing Element.

Policy: Explore potential affordable housing opportunities with public agencies, health care institutions, and school districts
Suggested HE Update Implementation Program language: To expand the stock of affordable housing, the City will work with public agencies, health care institutions and school districts to help identify potential sites or portions of sites that could be developed with affordable housing.

If there is interest from an owner entity in potentially developing affordable housing on a site or 1374 of 1863
Housing Trust Fund Memo – City of San Bruno
November 10, 2021
21 sites, the City will apply various regulatory and zoning incentives necessary to make affordable housing development feasible on such sites.

Policy: Consider potential affordable housing opportunities with faith-based institutions Suggested HE Update Implementation Program language: The City will engage in outreach to faith-based congregations to assess interest in exploring the concept of using a portion of their properties to develop affordable housing and facilitate a discussion between any interested parties and local affordable housing providers.

VIII. List of Attachments - Included as Separate Documents RFQ examples
§ RFQ – Affordable Housing Financial Consultant (County Dept of Housing, 2021) § RFQ – Affordable Housing Financial Consultant – Q&A (County Dept of Housing, 2021) § RFQ – Affordable Housing/Homeless Services Consultants (County of Alameda, 2020) § RFQ – Qualified Development Partners for Project Homekey (County Dept of Housing, 2021) § RFQ – Qualified Developers for Multiple Development Opportunity Sites (Daly City, 2017) § RFQ – Qualified Developers – Bay Meadows Site (City of San Mateo, 2016) RFP examples
§ RFP – Developer - Middlefield Junction – Parcel A (County Dept of Housing, 2018) § RFP – Developer - Midway/Bayshore Redevelopment Project (County Dept of Housing, 2017) § RFP – Developer – Bradford Affordable Housing (Redwood City, 2015) Other resources
§ County Department of Housing Loan Policies – June 2020 § CHPC – Best Practices in Local Government Preservation Strategies (2019) § Jordan Court Affordable Housing (Faith-Based) – Berkeley (2020) § Immanuel-Sobrato Affordable Housing (Faith-Based) – San Jose (2021) § (Partial) List of Affordable Housing consultants who provide assistance to Local Governments 1375 of 1863
Appendix M
Policies Applicable to the Development of
Sites in the Inventory
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The proposed 2023-2031 Housing Element will replace the existing 2015-2023 Housing Element and serve as the City of San Bruno’s guiding policy document for meeting the City’s future housing needs at all economic levels. As a policy document, the Housing Element does not result in direct physical changes to the environment but would indirectly lead to physical environmental changes by enabling the development of approximately 3,618 additional housing units within the City’s jurisdiction. To reduce all potentially significant effects of developing the properties in the site inventory to a less than significant level, the City of San Bruno hereby adopts the following policies which are applicable to sites in the inventory listed in Chapter 6. 1) Future development at all Housing Opportunity Sites shall implement the following measures during demolition and construction:
a) Use Tier 4 engines for all off-road equipment greater than 50 horsepower (hp) and operating for more than 20 total hours over the entire duration of construction activities. b) Use diesel trucks with 2010 or later compliant model year engines during construction. c) Use renewable diesel during construction.
d) Use low-VOC coatings during construction.
e) Implement BAAQMD best management practices and if necessary, enhanced measures recommended by BAAQMD.
f) Use portable electrical equipment where commercially available and practicable to complete construction. Construction contractors shall utilize electrical grid power instead of diesel generators when (1) grid power is available at the construction site; (2) when construction of temporary power lines are not necessary in order to provide power to portions of the site distant from existing utility lines; (3) when use of portable extension lines is practicable given construction safety and operational limitations; and (4) when use of electrical grid power does not compromise construction schedules. 2) Future development at all Housing Opportunity Sites shall conduct a construction and operational health risk assessment (HRA) prior to the issuance of discretionary permits that would allow
demolition or construction activities to take place (whichever occurs first). If the HRA demonstrates, to the satisfaction of the City, that the health risk exposures for adjacent receptors will be less than BAAQMD project-level thresholds, then additional mitigation would be unnecessary. However, if the HRA demonstrates that health risks would exceed BAAQMD project level thresholds, additional feasible on- and off-site mitigation shall be analyzed to further reduce risks to the greatest extent practicable. 3) Future development at Housing Opportunity Sites shall comply with the following measures:
a) Demolition and nesting substrate (e.g., trees, bushes, grasses, and other vegetation) removal activities shall be scheduled to avoid nesting season (February 1 to August 31). To the extent feasible, construction activities shall be scheduled to occur during the nonnesting season (September 1 through January 31). b) Prior to issuance of any discretionary permits that would allow construction activities during the nesting season, a qualified biologist shall complete pre-construction surveys for active nests within 14 days of work commencing. The survey area must include the proposed development area and all areas within 300 feet of the development area boundary (“zone of influence”). If active nest, roost, or burrow sites are identified within the zone of 1377 of 1863
influence, a no-disturbance buffer shall be established for all active nest sites prior to commencement of any proposed construction-related activities to avoid disturbances to migratory bird nesting activities. A nodisturbance buffer constitutes a zone in which construction activities cannot occur. The sizes of the buffers shall be determined by a qualified biologist based on the species, activities proposed near the nest, and topographic and other visual barriers. Buffers shall remain in place until the young have departed the area or fledged and/or the nest is inactive, as determined by the qualified biologist. c) If work is necessary within a buffer zone of an active bird nest, work may occur under the supervision of a qualified avian biologist. The qualified avian biologist monitoring the construction work shall have the authority to stop work and adjust buffers if any disturbance to nesting activity is observed.
4) Future development at Housing Opportunity Site 14 shall comply with the following measures:
a) Removal or alteration of the commemorative features of California Historic Landmark #934 shall be prohibited, and must be incorporated into any future development proposals for Site 14.
b) As part of the future project-level CEQA analysis of any discretionary permit that would allow the demolition of the existing buildings located at Site 14, a Historic Resource Evaluation (HRE) shall be prepared by a qualified architect or architectural historian approved by the City and meeting the Secretary of the Interior's Professional Qualifications Standards published in the Code of Federal Regulations (36 CFR part 61). The HRE shall evaluate whether any of the existing buildings meet the definition of a historic resource pursuant to CEQA Guidelines Section 15064.5. If the existing buildings do not meet the definition of a historic resource, demolition may proceed. If the HRE finds that any of the existing buildings at Site 14 meet the definition of a historic resource, demolition of buildings eligible for listing as a historic resource shall be prohibited. c) In the event that any buildings meeting the definition of a historic resource pursuant to CEQA Guidelines Section 15064.5 are identified, future development proposals for Site 14 shall be reviewed for compliance by a qualified architect or architectural historian approved by the City and meeting the Secretary of the Interior's Professional Qualifications Standards published in the Code of Federal Regulations (36 CFR part 61) with one or both of the following standards prior to issuance of any discretionary permits that would allow modifications to the existing buildings or new construction on Site 14:
• Secretary of Interior's Standards for the Treatment of Historic Properties with Guidelines for Preserving,
Rehabilitating, Restoring, and Reconstructing Historic
Buildings; or
• Secretary of Interior's Standards for Rehabilitation and Guidelines for Rehabilitating Historic Buildings
(1995), Weeks and Grimmer.
5) Future development at Housing Opportunity Sites 6, 8, 10, 16, 18, and 19 shall comply with the following measures:
a) If evidence of an archaeological site or other suspected cultural resource as defined by CEQA Guideline Section 15064.5, including darkened soil representing past human activity (“midden”), that could conceal material remains (e.g., worked stone, worked bone, fired 1378 of 1863
clay vessels, faunal bone, hearths, storage pits, or burials) is discovered during construction related earth-moving activities, all ground-disturbing activity within 100 feet of the resources shall be halted and the City Planning Manager shall be notified. The project sponsor shall hire a qualified archaeologist to conduct a field investigation. The City’s Planning Manager shall consult with the archaeologist to assess the significance of the find.

Impacts to any significant resources shall be mitigated to a less-than significant level through data recovery or other methods determined adequate by a qualified archaeologist and that are consistent with the Secretary of the Interior’s Standards for Archaeological documentation. Any identified cultural resources shall be recorded on the appropriate DPR 523 (A-J) form and filed with the NWIC.
b) Prior to the initiation of any site preparation and/or the start of construction, the project sponsor shall ensure that all construction workers receive training overseen by a qualified professional archaeologist who is experienced in teaching nonspecialists, to ensure that contractors can recognize archaeological resources in the event that any are discovered during construction.
6) Future development at Housing Opportunity Site 14 shall comply with the following measures:
a) As part of the future project-level CEQA analysis of any discretionary permits that would allow ground-disturbing activities (e.g., grading, trenching, excavation, etc.) in the archaeological sensitive areas shown on Figure 4.5 1, exploratory trenching shall be conducted by a qualified archaeologist trained in both local prehistoric and historical archaeology within the proposed area of effect to determine if prehistoric- or historic-era archaeological resources are present. Explorations shall consist of at least one mechanically dug trench with excavation depths commensurate with the depth of proposed grounddisturbing activities. If any archaeological resources are exposed, these should be briefly documented, tarped for protection, and left in place. The results of the exploratory trenching shall be submitted to the Director of Community and Economic Development or the Director’s designee. If it is determined by the project archaeologist that the proposed activities could damage an archaeological resource or that indications of other suspected archaeological resources are present (i.e., darkened soil “midden” representing past human activity), an Archaeological Resources Treatment Plan shall be prepared as described in MM CUL-2.1b below.
b) If recommended by the project archaeologist, an Archaeological Resources Treatment Plan shall be prepared by the project archaeologist that contains, at minimum:
• Identification of the scope of work and range of subsurface effects (including location map and development plan), including requirements for preliminary field investigations.
• Description of the environmental setting (past and present) and the historic/prehistoric background of the parcel (potential range of what might be found).
• Monitoring schedules and individuals
• Development of research questions and goals to be addressed by the investigation (what is significant vs. what is redundant information). • Detailed field strategy to record, recover, or avoid the finds and address research goals.
• Analytical methods. Report structure and outline of document contents. 1379 of 1863
• Disposition of the artifacts.
• Security approaches or protocols for finds.
• Appendices: all site records, correspondence, and consultation with Native Americans, etc. Implementation of the treatment plan by the project archaeologist shall be required prior to the issuance of any permits related to ground-disturbing activities. The treatment plan shall utilize data recovery methods to reduce impacts on subsurface resources. The treatment plan shall be submitted to the Director of Community and Economic Development or the Director’s designee, along with a summary of the outcomes of the treatment plan and all associated documentation and recordation.
7) Future development at Housing Opportunity Site 14 shall comply with the following measures:
a) Prior to the issuance of any discretionary permits that would allow ground-disturbing activities (e.g., grading, trenching, excavation, etc.) within the non-sensitive areas mapped on Figure 4.5 1, the project applicant shall hire a qualified archaeologist to develop a Worker’s Environmental Awareness Program (WEAP) to train the construction crew on the legal requirements for the treatment of cultural resources as well as procedures to follow in the event of a cultural resources discovery. This training program shall be given to the crew before ground disturbing work commences and shall include handouts to be given to new workers.
b) The applicant shall note on all construction plans that require ground disturbing activities that there is a potential for exposing buried cultural resources including prehistoric Native American burials.
c) In the event that potentially significant archaeological resources are encountered during ground-disturbing activities occurring at Site 14, all activity within a 50-foot radius of the find shall be stopped, the Director of Community and Economic Development or the Director's designee shall be notified, and the project archaeologist shall examine the find.

The project archaeologist shall (1) evaluate the find(s) to determine if they meet the definition of an archaeological resource; and (2) make appropriate recommendations regarding the disposition of such finds prior to issuance of building permits.

Recommendations could include collection, recordation, and analysis of any significant cultural materials. A report of findings documenting any data recovery shall be submitted to the Director of Community and Economic Development or the Director's designee and the Northwest Information Center (if applicable).
8) Future development at Housing Opportunity Sites 1, 2, 4, 5, 6, 7, 8, 9, 10, 11, 12, 14, 15, 16, 17, 20, 22 and 23 shall comply with the following measures:
a) If human remains are discovered at any project construction site during any phase of construction, all ground-disturbing activity within 100 feet of the resources shall be halted and the City’s Planning Manager and the San Mateo County Coroner shall be notified immediately, according to Section 5097.98 of the State Public Resources Code and Section 7050.5 of California’s Health and Safety Code. If the remains are determined by the County coroner to be Native American, the Native American Heritage Commission (NAHC) shall be notified within 24 hours, and the guidelines of the NAHC shall be adhered to in the treatment and disposition of the remains. The project sponsor shall also retain a professional archaeologist with Native American burial experience to conduct a field 1380 of 1863
investigation of the specific site and consult with the Most Likely Descendant, if any, identified by the NAHC. As necessary, the archaeologist may provide professional assistance to the Most Likely Descendant, including the excavation and removal of the human remains.

The City of San Bruno shall be responsible for approval of recommended mitigation as it deems appropriate, taking account of the provisions of State law, as set forth in CEQA Guidelines section 15064.5(e) and Public Resources Code section 5097.98. The project sponsor shall implement approved mitigation, to be verified by the City of San Bruno, before the resumption of ground-disturbing activities within 100 feet of where the remains were discovered.
9) All applicants and their contractors for projects on the Sites Inventory site must implement the following measures prior to and during construction:
a) Prior to issuance of any discretionary permits that would allow demolition or construction (grading, excavation, building, etc.) activities at the Housing Opportunity Sites, the applicant shall submit a construction management plan that demonstrates that:
• Alternative fueled (e.g. biodiesel, electric) construction vehicles/equipment shall make up at least 15 percent of the fleet;
• Buildings shall be constructed with local building materials of at least 10 percent (sourced from within 100 miles of the City limits); and • Contractors shall recycle and reuse at least 50 percent of construction waste or demolition materials.
10) Future development at all Housing Opportunity Sites must demonstrate adherence with the following design measures prior to issuance of any discretionary permits that would allow construction of residential units:
a) Construction of natural gas infrastructure and the use of natural gas appliances shall be prohibited;
b) Future developments shall include all electric appliances; c) At a minimum, future development shall comply with offstreet electric vehicle requirements in the most recently adopted version of CALGreen Tier 2 requirements. 11) Future development at Housing Opportunity Sites 6, 8, 10, 16, 18, and 19 shall comply with the following measure:
a) The City shall require a Phase I Environmental Site Assessment (Phase I ESA) prior to issuance of any discretionary permits that would allow ground-disturbing activities, with a Phase II ESA also required if the Phase I ESA indicates evidence of potential site contamination. The City shall also require compliance with the site assessment(s) and any remediation, removal, and disposal requirements for soil, surface water, and/or groundwater contamination enforced by the Department of Toxic Substances Control (DTSC), Regional Water Quality Control Board (RWQCB), San Mateo County Department of Environmental Health (SMCEHS), California Division of Occupational Safety and Health (CalOSHA), U.S. Environmental Protection Agency (EPA), and other jurisdictional agencies. 12) Future development at Housing Opportunity Site 14 shall comply with the following measures:
a) Prior to the issuance of any discretionary permits that would allow ground-disturbing activities on Site 14 (outside of the area shown on Figure 4.9 1), the project proponent shall obtain a Phase I Environmental Site Assessment (ESA). The Phase I ESA shall be conducted in 1381 of 1863
accordance with the United States Environmental Protection Agency’s All Appropriate Inquiries (AAI) Rule and the latest American Society for Testing and Materials (ASTM International) guidelines, and identify all potential subsurface contaminants warranting further investigation.
b) If the Phase I ESA identifies any potential contaminants warranting further investigation, a Phase II ESA shall be prepared in accordance with the United States Environmental Protection Agency’s AAI Rule and the latest ASTM International guidelines. As part of the Phase II, a qualified environmental professional (as defined in Title 40 of the California Code of Regulations) shall take soil, soil vapor, and groundwater samples as determined necessary by the environmental professional in the area of proposed disturbance at 0.5 feet below ground surface (bgs) to the maximum proposed depth of disturbance. Collected soil samples shall be tested for all potential contaminants identified in the Phase I ESA to determine if contaminants exceed California Division of Occupational Safety and Health (Cal/OSHA) exposure limits or San Mateo County Environmental Health Services (SMCEHS) environmental screening levels for residential uses.
c) The results of the Phase II ESA shall be provided SMCEHS department. If determined necessary by the SMCEHS, a Redevelopment Management Plan (RMP) or equivalent shall be prepared and submitted to the SMCEHS and the Director of Community and Economic Development or the Director’s designee that includes 1) an evaluation of whether redevelopment activities will create new exposure pathways to human health and the environment that pose unacceptable risks, and, if so, how those risks will be mitigated, and 2) a discussion of how contaminated media will be handled and disposed during construction activities. Once approved by the SMCEHS and Community and Economic Development Department, the RMP or equivalent shall be implemented by a qualified environmental professional. The results of the RMP or equivalent shall be submitted to the SMCEHS and the Director of Community and Economic Development or the Director’s designee prior to the issuance of any issuance of any discretionary permits (e.g., grading, construction, occupancy, whichever occurs first).
13) Future development at Housing Opportunity Site 14 shall comply with the following measures:
a) Prior to the issuance of any construction or building permits, the applicant shall submit a plan with a list of equipment to be used during construction that includes their height and proposed area of operation to the Director of Community and Economic Development or the Director’s designee. The use of equipment in locations where it would penetrate critical aeronautical surfaces shall be expressly prohibited by any construction or building permits issued. The plan sets shall include a page depicting the critical aeronautical surfaces onsite, a list of all equipment with heights of 55 feet or greater and their respective heights, and informs construction workers that the use of equipment with heights that would penetrate critical aeronautical surfaces is prohibited.
b) Future development at Housing Opportunity Site 14 shall comply with Policy AP-3 of the Comprehensive Airport Land Use Compatibility Plan for the Environs of San Francisco International Airport (ALUCP). Buildings with heights in excess of the applicable critical aeronautical surface as shown in Exhibit IV-17 at Housing Opportunity Site 14 shall be prohibited unless the Federal Aviation Administration determines the proposed building height is not a hazard to air navigation in an aeronautical study prepared pursuant to the filing of Form 7460-1. Proof of compliance with Policy AP-3 of the ALUCP shall be provided 1382 of 1863
to the Director of Community and Economic Development or the Director’s designee prior to issuance of any construction or building permits.
14) Future development at all Housing Opportunity Sites shall implement the following measures during demolition and construction:
• Groundborne vibration studies shall be prepared by qualified professionals in accordance with industry-accepted methodology where heavy construction activities involving significant site grading, underground, or foundation work will occur within 25 feet of residential or other vibration sensitive uses. The industry accepted methodologies include the recommended vibration assessment procedure and thresholds provided by public agencies such as Caltrans or the Federal Highway Administration. The studies should identify necessary construction vibration controls to reduce both human annoyance and the possibility of cosmetic damage. Controls shall include, but not be limited to, the following measures:
o A list of all heavy construction equipment to be used for this project known to produce high vibration levels (tracked vehicles, vibratory compaction,
jackhammers, hoe rams, etc.) shall be submitted to the
City by the contractor. This list shall be used to
identify equipment and activities that would
potentially generate substantial vibration and to define the level of effort for reducing vibration levels below the thresholds.
o Place operating equipment on the construction site as far as possible from vibration-sensitive receptors.
o Use smaller equipment to minimize vibration levels
below the limits.
o Avoid using vibratory rollers and tampers near
sensitive areas.
o Select demolition methods not involving impact tools. o Modify/design or identify alternative construction
methods to reduce vibration levels below the limits.
o Avoid dropping heavy objects or materials.
1383 of 1863
Site Inventory
# Site Address # of Units Plan Area Rezone Status
1 AT&T Building 840 San Bruno Ave. 320 TCP No vacant
2 Bank of America 465 San Mateo Ave. 45 TCP No active
3 Bayhill Shopping Center 851 Cherry Ave. 210 BHSP No active 4 Mike’s Auto 529 El Camino Real 72 TCP No vacant
5 Citibank 475 San Mateo Ave. 60 TCP No active
6 Engvall School 2101 Sneath Ln. 118 none No vacant
7 Budget Motel (vacant) 850 El Camino Real 60 TCP No vacant 8 Edgemont School 500 Acacia Ave. 16 none No active
9 IHOP 590 El Camino Real 42 TCP No active
10 Underutilized site 116 San Marco Ave. 2 None No vacant 11 Melody Toyota Showroom 750 El Camino Real 34 TCP No vacant 12 Melody Toyota Lot 750 El Camino Real 41 TCP No vacant 13 Office Building 801-851 Traeger Dr. 205 BHSP No active 14 Tanforan 1150 El Camino Real 1,000 None Yes active
15 (vacant) 170 San Bruno Ave. 42 TCP No vacant
16 (vacant) San Marco 2 none No vacant
17 Walgreens 333 El Camino Real 150 TCP No active
18 Russo Dental 1101 El Camino Real 15 None Yes active
19 San Bruno Pet Hospital 1111 El Camino Real 60 none Yes active 20 Chili’s Restaurant 899 El Camino Real 100 TCP No active 21 (vacant) 104 San Bruno Ave. 25 TCP No vacant
22 Bedroom Express 426 El Camino Real 50 TCP No active
23 San Bruno Gas 401 San Mateo Ave. 40 TCP No active
Total 2,709
1384 of 1863
Exhibit B

EVIDENCE IN SUPPORT OF FINDINGS OF

SUBSTANTIAL COMPLIANCE

WITH THE REQUIREMENTS OF

STATE HOUSING ELEMENT LAW
1385 of 1863
Column 1 of the table below is populated with sections of the Govt. Code applicable to Housing Element Law, Article 10.6 [65580 – 65589.11]. Column 2 of the table below indicates the section and page number within the San Bruno’s 2023-2031 Housing Element update where the information can be found.

GOVERNMENT CODE PROVISION HOUSING ELEMENT COMPLIANCE
Section 65583
The housing element shall consist of an
identification and analysis of existing and
projected housing needs and a statement of
goals, policies, quantified objectives, financial
resources, and scheduled programs for the
preservation, improvement, and development of
housing.
• Chapter 1
o page 3
o page 3-4
• Chapter 7
o pages 1-2
o pages 3-32
The housing element shall identify adequate sites
for housing, including rental housing, factorybuilt housing, mobile-homes, and emergency shelters, and shall make adequate provision for
the existing and projected needs of all economic
segments of the community.
• Chapter 3 pages 15-16
• Chapter 6
o pages 13-16
o pages 18-22
The element shall contain all of the following:
(a) An assessment of housing needs and an
inventory of resources and constraints relevant
to the meeting of these needs. The assessment
and inventory shall include all of the following:
• Chapter 3
o pages 1-30, 35-37
o pages 30-35
(a)(1) An analysis of population and employment
trends and documentation of projections
• Chapter 2
o pages 1-12
o pages 17-26
o pages 37-39
• Appendix E
(a)(1) A quantification of the locality’s existing
and projected housing needs for all income
levels, including extremely low-income
households, as defined in subdivision (b) of
Section 50105 and Section 50106 of the Health
and Safety Code. These existing and projected
needs shall include the locality’s share of the
regional housing need in accordance with Section
65584. Local agencies shall calculate the subset
of very -low-income households allotted under
Section 65584 that qualify as extremely lowincome households. The local agency may either use available census data to calculate the
percentage of very low-income households that
qualify as extremely low-income households or
• Chapter 1 pages 3-4
• Chapter 2
o pages 5-7
o page 46
• Chapter 6
o pages 1-5
o pages 23-24
1386 of 1863
presume that 50 percent of the very low-income
households qualify as extremely low-income
households. The number of extremely lowincome households and very low-income households shall equal the jurisdiction’s
allocation of very low-income households
pursuant to Section 65584.
(a)(2) An analysis and documentation of
household characteristics, including level of
payment compared to ability to pay,
• Chapter 2
o pages 12-16, 23-28, 34-59
o pages 28-32
(a)(2) housing characteristics, including
overcrowding, and
• Chapter 2 pages 32-34
• Appendix G pages 5-7,
(a)(2) housing stock condition. • Chapter 2 pages 37-38 (a)(3) An inventory of land suitable and available
for residential development, including vacant
sites and sites having realistic and demonstrated
potential for redevelopment during the planning
period to meet the locality’s housing need for a
designated income level, and an analysis of the
relationship of zoning and public facilities and
services to these sites, and an analysis of the
relationship of the sites identified in the land
inventory to the jurisdiction’s duty to
affirmatively further fair housing. Note: Please
see Section 65583.2 regarding the land
inventory.
• Chapter 3 pages 26-29
• Chapter 4 pages 52-55
• Chapter 6 pages 2-24
[Note that AB 2339 (Chapter 654, Statutes of
2022) amended Section 65583(a)(4). It does not
apply to ABAG-area housing elements unless
the first draft of the housing element is
submitted to ABAG after January 31, 2023, or a
draft is submitted after April 1, 2023. Therefore,
the sections below include the statutory
provisions of Section 65583(a)(4) effective in
2022. Jurisdictions adopting their housing
element after January 1, 2023, should describe
why AB 2339 is not applicable to them.]
• AB 2339 does not apply because the City
submitted its first draft Housing Element
to HCD on July 8, 2022.
(a)(4)(A) The identification of a zone or zones
where emergency shelters are allowed as a
permitted use without a conditional use or other
discretionary permit. The identified zone or
zones shall include sufficient capacity to
accommodate the need for emergency shelter
identified in paragraph (7), except that each local
government shall identify a zone or zones that
can accommodate at least one year-round
emergency shelter.
• Chapter 3 pages 15-16
1387 of 1863
(a)(4)(A) If the local government cannot identify a
zone or zones with sufficient capacity, the local
government shall include a program to amend its
zoning ordinance to meet the requirements of
this paragraph within one year of the adoption of
the housing element. The local government may
identify additional zones where emergency
shelters are permitted with a conditional use
permit.
• Chapter 3 pages 15-16
(a)(4)(A) The local government shall also
demonstrate that existing or proposed permit
processing, development, and management
standards are objective and encourage and
facilitate the development of, or conversion to,
emergency shelters.
• Chapter 3 pages 15-16
(a)(4)(A) Emergency shelters may only be subject
to those development and management
standards that apply to residential or commercial
development within the same zone except that a
local government may apply written, objective
standards that include all of the following:
(i) The maximum number of beds or persons
permitted to be served nightly by the facility.
(ii) Sufficient parking to accommodate all staff
working in the emergency shelter, provided that
the standards do not require more parking for
emergency shelters than other residential or
commercial uses within the same zone.
(iii) The size and location of exterior and interior
onsite waiting and client intake areas.
(iv) The provision of onsite management.
(v) The proximity to other emergency shelters,
provided that emergency shelters are not
required to be more than 300 feet apart.
(vi) The length of stay.
(vii) Lighting.
(viii) Security during hours that the emergency
shelter is in operation.
• Chapter 3 pages 15-16
(a)(4)(B) The permit processing, development,
and management standards applied under this
paragraph shall not be deemed to be
discretionary acts within the meaning of the
California Environmental Quality Act (Division 13
(commencing with Section 21000) of the Public
Resources Code).
• Chapter 3 pages 15-16
(a)(4)(C) A local government that can
demonstrate to the satisfaction of the
department the existence of one or more
• Chapter 3 pages 15-16
1388 of 1863
emergency shelters either within its jurisdiction
or pursuant to a multijurisdictional agreement
that can accommodate that jurisdiction’s need
for emergency shelter identified in paragraph (7)
may comply with the zoning requirements of
subparagraph (A) by identifying a zone or zones
where new emergency shelters are allowed with
a conditional use permit.
(a)(4)(D) A local government with an existing
ordinance or ordinances that comply with this
paragraph shall not be required to take
additional action to identify zones for emergency
shelters. The housing element must only describe
how existing ordinances, policies, and standards
are consistent with the requirements of this
paragraph.
• Chapter 3 pages 15-16
(a)(5) An analysis of potential and actual
governmental constraints upon the maintenance,
improvement, or development of housing for all
income levels, including the types of housing
identified in paragraph (1) of subdivision (c), and
[Note: The types of housing identified in Section
65583(c)(1) include multifamily rental housing,
factory-built housing, mobile homes, housing
for agricultural employees, supportive housing,
single-room occupancy units, emergency
shelters, and transitional housing.]
• Chapter 3
o pages 1-30
o pages 35-37
(a)(5) for persons with disabilities as identified in
the analysis pursuant to paragraph (7),
• Chapter 2 pages 39-42
(a)(5) including land use controls, • Chapter 3 pages 2-6 (a)(5) building codes and their enforcement, • Chapter 2 page 57-58 • Chapter 3
o page 17
o page 22
o pages 28-29
(a)(5) site improvements, • Chapter 3 pages 21, 26
(a)(5) fees and other exactions required of
developers,
• Chapter 3 pages 21, 23-25
(a)(5) local processing and permit procedures, • Chapter 3 pages 17-20, 26 (a)(5) and any locally adopted ordinances that
directly impact the cost and supply of residential
development.
• Chapter 3 page 13
(a)(5) The analysis shall also demonstrate local
efforts to remove governmental constraints that
hinder the locality from meeting its share of the
• Chapter 3 pages 12-15
1389 of 1863
regional housing need in accordance with Section
65584
(a)(5) and from meeting the need for housing for
persons with disabilities, supportive housing,
transitional housing, and emergency shelters
identified pursuant to paragraph (7).
• Chapter 3 pages 15-16
(a)(6) An analysis of potential and actual
nongovernmental constraints upon the
maintenance, improvement, or development of
housing for all income levels, including the
availability of financing,
• Chapter 3 pages 16-21
(a)(6) the price of land, • Chapter 3 pages 37-38
(a)(6) the cost of construction, • Chapter 3 pages 29-30 (a)(6) the requests to develop housing at
densities below those anticipated in the analysis
required by subdivision (c) of Section 65583.2,
• Chapter 6 pages 10-11
(a)(6) and the length of time between receiving
approval for a housing development and
submittal of an application for building permits
for that housing development that hinder the
construction of a locality’s share of the regional
housing need in accordance with Section 65584.
• Chapter 1 pages 3-4
• Chapter 3 pages 18-20
(a)(6) The analysis shall also demonstrate local
efforts to remove nongovernmental constraints
that create a gap between the locality’s planning
for the development of housing for all income
levels and the construction of that housing.
• Chapter 3 pages 37-38
(a)(7) An analysis of any special housing needs,
such as those of the
• Chapter 2 page 36
(a)(7) elderly; • Chapter 2 pages 37-39
(a)(7) persons with disabilities, including a
developmental disability, as defined in Section
4512 of the Welfare and Institutions Code;
• Chapter 2 pages 39-43
(a)(7) large families; • Chapter 2 pages 44-45
(a)(7) farmworkers; • Chapter 2 pages 51-52
(a)(7) families with female heads of households; • Chapter 2 pages 43-44 (a)(7) and families and persons in need of
emergency shelter.
• Chapter 2 pages 46-51
(a)(7) The need for emergency shelter shall be
assessed based on the capacity necessary to
accommodate the most recent homeless pointin-time count conducted before the start of the planning period, the need for emergency shelter
based on number of beds available on a yearround and seasonal basis, the number of shelter beds that go unused on an average monthly basis
within a one-year period, and the percentage of
• Chapter 3 pages 15-16
1390 of 1863
those in emergency shelters that move to
permanent housing solutions.
(a)(7) The need for emergency shelter may be
reduced by the number of supportive housing
units that are identified in an adopted 10-year
plan to end chronic homelessness and that are
either vacant or for which funding has been
identified to allow construction during the
planning period.
• This does not apply because the City has
not adopted a 10 year plan to reduce
homelessness.
(a)(7) An analysis of special housing needs by a
city or county may include an analysis of the
need for frequent user coordinated care housing
services.
• This optional analysis is not included.
(a)(8) An analysis of opportunities for energy
conservation with respect to residential
development. Cities and counties are encouraged
to include weatherization and energy efficiency
improvements as part of public7y subsidized
housing rehabilitation projects. This may include
energy efficiency measures that encompass the
building envelope, its heating and cooling
systems, and its electrical system.
• Chapter 2 pages 57-59
• Chapter 3 page 28
(a)(9) An analysis of existing assisted housing
developments that are eligible to change from
low-income housing uses during the next 10
years due to termination of subsidy contracts,
mortgage prepayment, or expiration of
restrictions on use. “Assisted housing
developments,” for the purpose of this section,
shall mean multifamily rental housing that
receives governmental assistance under federal
programs listed in subdivision (a) of Section
65863.10, state and local multifamily revenue
bond programs, local redevelopment programs,
the federal Community Development Block Grant
Program, or local in-lieu fees. “Assisted housing
developments” shall also include multifamily
rental units that were developed pursuant to a
local inclusionary housing program or used to
qualify for a density bonus pursuant to Section
65915.
• Chapter 2 pages 55-57
(a)(9)(A) The analysis shall include a listing of
each development by project name and address,
the type of governmental assistance received,
the earliest possible date of change from lowincome use, and the total number of elderly and nonelderly units that could be lost from the
• Chapter 2 page 57
1391 of 1863
locality’s low-income housing stock in each year
during the 10-year period. For purposes of state
and federally funded projects, the analysis
required by this subparagraph need only contain
information available on a statewide basis.
(a)(9)(B) The analysis shall estimate the total cost
of producing new rental housing that is
comparable in size and rent levels, to replace the
units that could change from low-income use,
and an estimated cost of preserving the assisted
housing developments. This cost analysis for
replacement housing may be done aggregately
for each five-year period and does not have to
contain a project-by-project cost estimate.
• This analysis is not required because the
City does not have any affordable units at
risk of conversion.
(a)(9)(C) The analysis shall identify public and
private nonprofit corporations known to the local
government that have legal and managerial
capacity to acquire and manage these housing
developments.
• Chapter 2 pages 58-59
(a)(9)(D) The analysis shall identify and consider
the use of all federal, state, and local financing
and subsidy programs that can be used to
preserve, for lower income households, the
assisted housing developments, identified in this
paragraph, including, but not limited to, federal
Community Development Block Grant Program
funds, tax increment funds received by a
redevelopment agency of the community, and
administrative fees received by a housing
authority operating within the community. In
considering the use of these financing and
subsidy programs, the analysis shall identify the
amounts of funds under each available program
that have not been legally obligated for other
purposes and that could be available for use in
preserving assisted housing developments.
• Chapter 2 pages 57-58
(b) (1) A statement of the community’s goals,
quantified objectives, and policies relative to
affirmatively furthering fair housing and to the
maintenance, preservation, improvement, and
development of housing.
• Chapter 4
• Chapter 6 page 23
• Chapter 7 Page 17, Program 3-B
• Chapter 7 Page 20, Program 3-G, 3
• Chapter 7 Page 26, AFFH Policy 2
(2) It is recognized that the total housing needs
identified pursuant to subdivision (a) may exceed
available resources and the community’s ability
to satisfy this need within the content of the
general plan requirements outlined in Article 5
(commencing with Section 65300). Under these
• Chapter 7
1392 of 1863
circumstances, the quantified objectives need
not be identical to the total housing needs. The
quantified objectives shall establish the
maximum number of housing units by income
category, including extremely low income, that
can be constructed, rehabilitated, and conserved
over a five-year time period.
(c) A program that sets forth a schedule of
actions during the planning period, each with a
timeline for implementation, that may recognize
that certain programs are ongoing, such that
there will be beneficial impacts of the programs
within the planning period, that the local
government is undertaking or intends to
undertake to implement the policies and achieve
the goals and objectives of the housing element
• Chapter 7
(c) through the administration of land use and
development controls,
• Chapter 7
(c) the provision of regulatory concessions and
incentives,
• Chapter 7
(c) the utilization of appropriate federal and state
financing and subsidy programs when available,
• Chapter 7
(c) and the utilization of moneys in a low- and
moderate-income housing fund of an agency if
the locality has established a redevelopment
project area pursuant to the Community
Redevelopment Law (Division 24 (commencing
with Section 33000) of the Health and Safety
Code).
• Chapter 7
In order to make adequate provision for the
housing needs of all economic segments of the
community, the program shall do all of the
following:
(c)(1) Identify actions that will be taken to make
sites available during the planning period with
appropriate zoning and development standards
and with services and facilities to accommodate
that portion of the city’s or county’s share of the
regional housing need for each income level that
could not be accommodated on sites identified in
the inventory completed pursuant to paragraph
(3) of subdivision (a) without rezoning, and to
comply with the requirements of Section
65584.09.
• Chapter 6
(c)(1) Sites shall be identified as needed to
affirmatively further fair housing
• Chapter 6 pages 15-16
• Appendix K
1393 of 1863
(c)(1) and to facilitate and encourage the
development of a variety of types of housing for
all income levels, including multifamily rental
housing,
• Chapter 3 Table 3-4
• Chapter 4 page 52
• Chapter 7 Program 2-G
(c)(1) factory-built housing, • Chapter 3 page 14
(c)(1) mobile homes, • Chapter 3 page 14
(c)(1) housing for agricultural employees, • Chapter 3 page 17 (c)(1) supportive housing, • Chapter 3 page 12-13
(c)(1) single-room occupancy units, • Chapter 3 pages 16-17 (c)(1) emergency shelters, • Chapter 3 pages 15-16
(c)(1) and transitional housing. • Chapter 3 page 12-13 (c)(1)(A) Where the inventory of sites, pursuant
to paragraph (3) of subdivision (a), does not
identify adequate sites to accommodate the
need for groups of all household income levels
pursuant to Section 65584, rezoning of those
sites, including adoption of minimum density and
development standards, for jurisdictions with an
eight-year housing element planning period
pursuant to Section 65588, shall be completed no
later than three years after either the date the
housing element is adopted pursuant to
subdivision (f) of Section 65585 or the date that
is 90 days after receipt of comments from the
department pursuant to subdivision (b) of
Section 65585, whichever is earlier, unless the
deadline is extended pursuant to subdivision (f).

Notwithstanding the foregoing, for a local
government that fails to adopt a housing element
that the department has found to be in
substantial compliance with this article within
120 days of the statutory deadline in Section
65588 for adoption of the housing element,
rezoning of those sites, including adoption of
minimum density and development standards,
shall be completed no later than one year from
the statutory deadline in Section 65588 for
adoption of the housing element.
• Chapter 6
o page 7
o table 6-4 page 17
(c)(1)(B) Where the inventory of sites, pursuant
to paragraph (3) of subdivision (a), does not
identify adequate sites to accommodate the
need for groups of all household income levels
pursuant to Section 65584, the program shall
identify sites that can be developed for housing
within the planning period pursuant to
subdivision (h) of Section 65583.2. The
identification of sites shall include all
• Chapter 6 Table 6-6
1394 of 1863
components specified in Section 65583.2. Note:

Please see Section 65583.2 regarding the land
inventory and conformance with subdivision (h).
(c)(1)(C) Where the inventory of sites pursuant to
paragraph (3) of subdivision (a) does not identify
adequate sites to accommodate the need for
farmworker housing, the program shall provide
for sufficient sites to meet the need with zoning
that permits farmworker housing use by right,
including density and development standards
that could accommodate and facilitate the
feasibility of the development of farmworker
housing for low- and very low income
households.
• Chapter 7 Program 2-G
(c)(2) Assist in the development of adequate
housing to meet the needs of extremely low, very
low, low-, and moderate-income households.
• Chapter 4 page 16
• Chapter 6 pages 24-25
• Chapter 7 pages 10-11, Program 2-F
• Chapter 7 page 11, Program 2-G
• Chapter 7 page 12, Program 2-H
(c)(3) Address and, where appropriate and legally
possible, remove governmental and
nongovernmental constraints to the
maintenance, improvement, and development of
housing, including housing for all income levels
• Chapter 3
• Chapter 7 page 6, Program 1-I
• Chapter 7 page 10, Program 2-F
• Chapter 7 page 11, Program 2-G
(c)(3) and housing for persons with disabilities.

The program shall remove constraints to, and
provide reasonable accommodations for housing
designed for, intended for occupancy by, or with
supportive services for, persons with disabilities.
• Chapter 2 pages 42-44
• Chapter 7 page 9, Program 2-D
• Chapter 7 page 10, Program 2-F
• Chapter 7 page 11, Program 2-G
• Chapter 7 page 28, Program 4-M
• Chapter 7 page 29, Program 4-O
• Chapter 7 pages 30-31, Program 4-Q
• Chapter 7 page 31, Program 4-R
(c)(3) Transitional housing and supportive
housing shall be considered a residential use of
property and shall be subject only to those
restrictions that apply to other residential
dwellings of the same type in the same zone.
• Chapter 3 pages 12-13
(c)(3) Supportive housing, as defined in Section
65650, shall be a use by right in all zones where
multifamily and mixed uses are permitted, as
provided in Article 11 (commencing with Section
65650).
• Chapter 3 pages 12-13
(c)(4) Conserve and improve the condition of the
existing affordable housing stock, which may
include addressing ways to mitigate the loss of
• Chapter 7 page 18, Program 3-E
• Chapter 7 page 19, Program 3-G
1395 of 1863
dwelling units demolished by public or private
action.
(c)(5) Promote and affirmatively further fair
housing opportunities and promote housing
throughout the community or communities for
all persons regardless of race, religion, sex,
marital status, ancestry, national origin, color,
familial status, or disability, and other
characteristics protected by the California Fair
Employment and Housing Act (Part 2.8
(commencing with Section 12900) of Division 3 of
Title 2), Section 65008, and any other state and
federal fair housing and planning law.
• Chapter 4
• Chapter 7 page 16, Program 3-A
• Chapter 7 page 21, Program 4-A
• Chapter 7 page 21, Program 4-B
• Chapter 7 page 22, Program 4-C
• Chapter 7 page 23, Program 4-D
• Chapter 7 pages 23-24, Program 4-E
• Chapter 7 page 24, Program 4-F
• Chapter 7 pages 24-25, Program 4-G
• Chapter 7 page 25, Program 4-H
• Chapter 7 page 26, Program 4-I
• Chapter 7 pages 26-27, Program 4-J
• Chapter 7 page 27, Program 4-K
• Chapter 7 pages 27-28, Program 4-L
• Chapter 7 page 28, Program 4-M
• Chapter 7 pages 28-29, Program 4-N
• Chapter 7 pages 29-30, Program 4-O
• Chapter 7 page 30, Program 4-P
• Chapter 7 pages 30-31, Program 4-Q
• Chapter 7 page 31, Program 4-R
• Chapter 7 pages 31-31, Program 4-S
(c)(6) Preserve for lower income households the
assisted housing developments identified
pursuant to paragraph (9) of subdivision (a).
• Chapter 7 page 19, Program 3-G
• Chapter 7 page 19, Program 3-H
(c)(6) The program for preservation of the
assisted housing developments shall utilize, to
the extent necessary, all available federal, state,
and local financing and subsidy programs
identified in paragraph (9) of subdivision (a),
except where a community has other urgent
needs for which alternative funding sources are
not available.
• Chapter 7 page 19, Program 3-G
• Chapter 7 page 19, Program 3-H
(c)(6) The program may include strategies that
involve local regulation and technical assistance.
• Chapter 7 page 19, Program 3-G
• Chapter 7 page 19, Program 3-H
(c)(7) Develop a plan that incentivizes and
promotes the creation of accessory dwelling
units that can be offered at affordable rent, as
defined in Section 50053 of the Health and Safety
Code, for very low, low-, or moderate-income
households. For purposes of this paragraph,
“accessory dwelling units” has the same meaning
as “accessory dwelling unit” as defined in
• Chapter 6 pages 23-24
• Chapter 7 page 30, Program 4-P
1396 of 1863
paragraph (4) of subdivision (i) of Section
65852.2.\
(c)(8) Include an identification of the agencies
and officials responsible for the implementation
of the various actions and the means by which
consistency will be achieved with other general
plan elements and community goals.
• Chapter 7
• Chapter 1 pages 5-7
(c)(9) Include a diligent effort by the local
government to achieve public participation of all
economic segments of the community in the
development of the housing element, and the
program shall describe this effort.
• Chapter 5
(c)(10)(A) Affirmatively further fair housing in
accordance with Chapter 15 (commencing with
Section 8899.50) of Division 1 of Title 2. The
program shall include an assessment of fair
housing in the jurisdiction that shall include all of
the following components:
• Chapter 4
(c)(10)(A)(i) A summary of fair housing issues in
the jurisdiction
• Appendices C-I
• Chapter 4 pages 58-59
(c)(10)(A)(i) and an assessment of the
jurisdiction’s fair housing enforcement and fair
housing outreach capacity.
• Chapter 4 pages 5-8
(c)(10)(A)(ii) An analysis of available federal,
state, and local data and knowledge to identify
integration and segregation patterns and trends,
• Chapter 4 pages 9-27
(c)(10)(A)(ii) racially or ethnically concentrated
areas of poverty and affluence,
• Chapter 4 page pages 28-29
(c)(10)(A)(ii) disparities in access to opportunity, • Chapter 2, page 9 • Chapter 4, pages 14, 19, 30-41, 58
• Chapter 7
o page 26 Programs 4-J, 4-K, 4-L
• Appendix H
(c)(10)(A)(ii) and disproportionate housing needs, • Chapter 4 o pages 42-50, 54-56
• Chapter 7
o Page 10 Program 2-G
o Page 12 Program 2-H
o Page 23 Program 4-E
o Page 24 Programs 4-F, 4-G
o Page 25 Programs 4-I, 4-H
o Page 28 Program 4-M
o Page 29 Program 4-N
o Page 29 Program 4-O
o Page 30 Program 4-P
o Page 30 Program 4-Q
1397 of 1863
o Page 31 Program 4-R
o Page 31 Program 4-S
• Appendix C
o Section IV pages 28-34
• Appendix D page 52
• Appendix G page 5-6
(c)(10)(A)(ii) including displacement risk. • Chapter 2 page 28 • Chapter 4 pages 3-4, 8, 18, 42, 48, 49,
• Chapter 7
o Page 24 Programs 4-F, 4-G
o Page 25 Program 4-H
o Page 26 Program 4-I
o Page 31 Program 4-S
• Appendix G page 7
(c)(10)(A)(ii) The analysis shall identify and
examine such patterns, trends, areas, disparities,
and needs, both within the jurisdiction.
• Chapter 2
• Chapter 4
o Pages 9-16
• Chapter 7
o Page 21 Program 4-A
o Page 26 Program 4-J
(c)(10)(A)(ii) and comparing the jurisdiction to
the region in which it is located, based on race
and other characteristics protected by the
California Fair Employment and Housing Act (Part

2.8 (commencing with Section 12900) of Division
3 of Title 2) and Section 65008.
• Chapter 3 pages 25,26
• Chapter 4 pages 7, 8, 10, 18, 21, 28, 30,
31, 33, 36, 43, 47
(c)(10)(A)(iii) An assessment of the contributing
factors, including the local and regional historical
origins
• Chapter 4, Section J pages 54-55
(c)(10)(A)(iii) and current policies and practices,
for the fair housing issues identified under
clauses (i) and (ii).
• Appendix A
o Program 3-E
o Program 6-A
o Program 6-B
(c)(10)(A)(iv) An identification of the jurisdiction’s
fair housing priorities and goals, giving highest
priority to those factors identified in clause (iii)
that limit or deny fair housing choice or access to
opportunity, or negatively impact fair housing or
civil rights compliance,
• Chapter 4 Pages 8, 16, 52-59
(c)(10)(A)(iv) and identifying the metrics and
milestones for determining what fair housing
results will be achieved.
• Chapter 4 pages 21-32
(c)(10)(A)(v) Strategies and actions to implement
those priorities and goals, which may include, but
are not limited to, enhancing mobility strategies
• Chapter 4 pages 21-32
1398 of 1863
(c)(10)(A)(v) and encouraging development of
new affordable housing in areas of opportunity,
• Chapter 4 pages 28-32, AFFH Policy 3
(c)(10)(A)(v) as well as place-based strategies to
encourage community revitalization, including
preservation of existing affordable housing,
• Chapter 7 pages 26-28, AFFH Policy 2
• Chapter 7 page 19, Program 3-G
• Chapter 7 page 19, Program 3-H
(c)(10)(A)(v) and protecting existing residents
from displacement.
• Chapter 7 page 19, Program 3-H
• Chapter 7 pages 21-26, AFFH Policy 1
(c)(10)(B) A jurisdiction that completes or revises
an assessment of fair housing pursuant to
Subpart A (commencing with Section 5.150) of
Part 5 of Subtitle A of Title 24 of the Code of
Federal Regulations, as published in Volume 80
of the Federal Register, Number 136, page
42272, dated July 16, 2015, or an analysis of
impediments to fair housing choice in accordance
with the requirements of Section 91.225 of Title
24 of the Code of Federal Regulations in effect
before August 17, 2015, may incorporate
relevant portions of that assessment or revised
assessment of fair housing or analysis or revised
analysis of impediments to fair housing into its
housing element.
• Not applicable
(c)(10)(C) The requirements of this paragraph
shall apply to housing elements due to be revised
pursuant to Section 65588 on or after January 1,
2021.
• See responses to (c)(10)(A)(i) through (v)
above.
(d)(1) A local government may satisfy all or part
of its requirement to identify a zone or zones
suitable for the development of emergency
shelters pursuant to paragraph (4) of subdivision
(a) by adopting and implementing a
multijurisdictional agreement, with a maximum
of two other adjacent communities, that requires
the participating jurisdictions to develop at least
one year-round emergency shelter within two
years of the beginning of the planning period.
• Not applicable because the City has no
such multijurisdictional agreement for
emergency shelters.
(d)(2) The agreement shall allocate a portion of
the new shelter capacity to each jurisdiction as
credit toward its emergency shelter need, and
each jurisdiction shall describe how the capacity
was allocated as part of its housing element.
• Not applicable because the City has no
such multijurisdictional agreement for
emergency shelters.
(d)(3) Each member jurisdiction of a
multijurisdictional agreement shall describe in its
housing element all of the following:
• Not applicable because the City has no
such multijurisdictional agreement for
emergency shelters.
1399 of 1863
(d)(3)(A) How the joint facility will meet the
jurisdiction’s emergency shelter need.
(d)(3)(B) The jurisdiction’s contribution to the
facility for both the development and ongoing
operation and management of the facility.
(d)(3)(C) The amount and source of the funding
that the jurisdiction contributes to the facility.
• Not applicable because the City has no
such multijurisdictional agreement for
emergency shelters.
(d)(4) The aggregate capacity claimed by the
participating jurisdictions in their housing
elements shall not exceed the actual capacity of
the shelter.
• Not applicable because the City has no
such multijurisdictional agreement for
emergency shelters.
(e) Except as otherwise provided in this article,
amendments to this article that alter the
required content of a housing element shall
apply to both of the following:
• Not applicable.
(1) A housing element or housing element
amendment prepared pursuant to subdivision (e)
of Section 65588 or Section 65584.02, when a
city, county, or city and county submits a draft to
the department for review pursuant to Section
65585 more than 90 days after the effective date
of the amendment to this section.
• Not applicable.
(2) Any housing element or housing element
amendment prepared pursuant to subdivision (e)
of Section 65588 or Section 65584.02, when the
city, county, or city and county fails to submit the
first draft to the department before the due date
specified in Section 65588 or 65584.02.
• Not applicable.
(f) – (j): Not applicable
• Section 65583.1(a)
(a) The Department of Housing and Community
Development, in evaluating a proposed or
adopted housing element for substantial
compliance with this article, … may also allow a
city or county to identify sites for accessory
dwelling units based on the number of accessory
dwelling units developed in the prior housing
element planning period whether or not the
units are permitted by right, the need for these
units in the community, the resources or
incentives available for their development, and
any other relevant factors, as determined by the
department.
• Chapter 6 pages 22-23
(b) Sites that contain permanent housing units
located on a military base undergoing closure or
conversion as a result of action pursuant to the
Defense Authorization Amendments and Base
• No applicable because none of the
housing sites are former military bases.
1400 of 1863
Closure and Realignment Act (Public Law 100-
526), the Defense Base Closure and Realignment
Act of 1990 (Public Law 101-510), or any
subsequent act requiring the closure or
conversion of a military base may be identified as
an adequate site if the housing element
demonstrates that the housing units will be
available for occupancy by households within the
planning period of the element. No sites
containing housing units scheduled or planned
for demolition or conversion to nonresidential
uses shall qualify as an adequate site.
• Section 65583.2
(a) A city’s or county’s inventory of land suitable
for residential development pursuant to
paragraph (3) of subdivision (a) of Section 65583
shall be used to identify sites throughout the
community, consistent with paragraph (10) of
subdivision (c) of Section 65583,
• Chapter 6 pages 15-16
• Appendix K
(a) that can be developed for housing within the
planning period and that are sufficient to provide
for the jurisdiction’s share of the regional
housing need for all income levels pursuant to
Section 65584. As used in this section, “land
suitable for residential development” includes all
of the following sites that meet the standards set
forth in subdivisions (c) and (g):
• Chapter 6 page 1
(a)(1) Vacant sites zoned for residential use. • Chapter 6 Table 6-4 (a)(2) Vacant sites zoned for nonresidential use
that allows residential development.
• Chapter 6 Table 6-4
(a)(3) Residentially zoned sites that are capable
of being developed at a higher density, including
sites owned or leased by a city, county, or city
and county
• Chapter 6 Table 6-4
(a)(4) Sites zoned for nonresidential use that can
be redeveloped for residential use, and for which
the housing element includes a program to
rezone the site, as necessary, rezoned for, to
permit residential use, including sites owned or
leased by a city, county, or city and county.
• Chapter 6 Table 6-4
• Chapter 7 Program 2-E
(b) The inventory of land shall include all of the
following:
(b)(1) A listing of properties by assessor parcel
number.
• Chapter 6 pages 15-16
• Appendix K
1401 of 1863
(b)(2) The size of each property listed pursuant to
paragraph (1), and the general plan designation
and zoning of each property.
• Chapter 6 pages 15-16
• Appendix K
(b)(3) For nonvacant sites, a description of the
existing use of each property.
• Chapter 6 pages 15-16
• Appendix K
(b)(3) If a site subject to this paragraph is owned
by the city or county, the description shall also
include whether there are any plans to dispose of
the property during the planning period and how
the city or county will comply with Article 8
(commencing with Section 54220) of Chapter 5 of
Part 1 of Division 2 of Title 5.
• Not applicable because none of the sites
in the inventory are city-owned.
(b)(4) A general description of any environmental
constraints to the development of housing within
the jurisdiction, the documentation for which has
been made available to the jurisdiction. This
information need not be identified on a sitespecific basis. • Chapter 3 pages 35-37
(b)(5)(A) A description of existing or planned
water, sewer, and other dry utilities supply,
including the availability and access to
distribution facilities.
• Chapter 3 pages 21, 27
(b)(5)(B) Parcels included in the inventory must
have sufficient water, sewer, and dry utilities
supply available and accessible to support
housing development or be included in an
existing general plan program or other
mandatory program or plan, including a program
or plan of a public or private entity providing
water or sewer service, to secure sufficient
water, sewer, and dry utilities supply to support
housing development. This paragraph does not
impose any additional duty on the city or county
to construct, finance, or otherwise provide
water, sewer, or dry utilities to parcels included
in the inventory.
• Chapter 3 pages 21, 27
(b)(6) Sites identified as available for housing for
above moderate-income households in areas not
served by public sewer systems. This information
need not be identified on a site-specific basis.
• Chapter 6 Table 6-4
(b)(7) A map that shows the location of the sites
included in the inventory, such as the land use
map from the jurisdiction’s general plan, for
reference purposes only.
• Chapter 6 page 13
(c) Based on the information provided in
subdivision (b), a city or county shall determine
whether each site in the inventory can
• Appendix K
1402 of 1863
accommodate the development of some portion
of its share of the regional housing need by
income level during the planning period, as
determined pursuant to Section 65584. The
inventory shall specify for each site the number
of units that can realistically be accommodated
on that site and whether the site is adequate to
accommodate lower income housing, moderateincome housing, or above moderate-income housing.
(c) A nonvacant site identified pursuant to
paragraph (3) or (4) of subdivision (a) in a prior
housing element and a vacant site that has been
included in two or more consecutive planning
periods that was not approved to develop a
portion of the locality’s housing need shall not be
deemed adequate to accommodate a portion of
the housing need for lower income households
that must be accommodated in the current
housing element planning period unless the site
is zoned at residential densities consistent with
paragraph (3) of this subdivision and the site is
subject to a program in the housing element
requiring rezoning within three years of the
beginning of the planning period to allow
residential use by right for housing developments
in which at least 20 percent of the units are
affordable to lower income households. An
unincorporated area in a nonmetropolitan
county pursuant to clause (ii) of subparagraph (B)
of paragraph (3) shall not be subject to the
requirements of this subdivision to allow
residential use by right.
• Chapter 6 Table 6-4
(c) Notwithstanding the foregoing, for a local
government that fails to adopt a housing element
that the department has found to be in
substantial compliance with state law within 120
days of the statutory deadline in Section 65588
for adoption of the housing element, rezoning
pursuant to this subdivision shall be completed
no later than one year from the statutory
deadline in Section 65588 for adoption of the
housing element.
• San Bruno intends to adopt its Housing
Element by the January 31, 2023 due
date and therefore will not be subject to
the one-year rezoning requirement.
(c) The analysis shall determine whether the
inventory can provide for a variety of types of
housing, including multifamily rental housing,
• Chapter 4 page 58
(c) factory-built housing, mobilehomes, • Chapter 3 page 15 1403 of 1863
(c) housing for agricultural employees, supportive
housing,
• Chapter 3 pages 16-17
• Chapter 7 Program 2-G
(c) single-room occupancy units, • Chapter 3 pages 16-17 • Chapter 7 Program 2-G
(c) emergency shelters, and • Chapter 3 page 15
• Chapter 7 Program 2-G
(c) transitional housing • Chapter 3 pages 12-13
(c) and whether the inventory affirmatively
furthers fair housing.
• Chapter 4 page 58
(c) The city or county shall determine the number
of housing units that can be accommodated on
each site as follows:
(c)(1) If local law or regulations require the
development of a site at a minimum density, the
department shall accept the planning agency’s
calculation of the total housing unit capacity on
that site based on the established minimum
density. If the city or county does not adopt a law
or regulation requiring the development of a site
at a minimum density, then it shall demonstrate
how the number of units determined for that site
pursuant to this subdivision will be
accommodated.
• Chapter 6 Table 6-4
• Chapter 6 page 6
(c)(2) The number of units calculated pursuant to
paragraph (1) shall be adjusted as necessary,
based on the land use controls and site
improvements requirement identified in
paragraph (5) of subdivision (a) of Section 65583,
• Chapter 6 Table 6-4
• Chapter 6 page 6
(c)(2) the realistic development capacity for the
site,
• Chapter 6 Table 6-4
• Chapter 6 page 6
(c)(2) typical densities of existing or approved
residential developments at a similar affordability
level in that jurisdiction,
• Chapter 6 Table 6-4
• Chapter 6 page 6
(c)(2) and on the current or planned availability
and accessibility of sufficient water, sewer, and
dry utilities.
• Chapter 6 Table 6-4
(c)(2)(A) A site smaller than half an acre shall not
be deemed adequate to accommodate lower
income housing need unless the locality can
demonstrate that sites of equivalent size were
successfully developed during the prior planning
period for an equivalent number of lower income
housing units as projected for the site or unless
the locality provides other evidence to the
department that the site is adequate to
accommodate lower income housing.
• Chapter 6 pages 11 and 14
1404 of 1863
(c)(2)(B) A site larger than 10 acres shall not be
deemed adequate to accommodate lower
income housing need unless the locality can
demonstrate that sites of equivalent size were
successfully developed during the prior planning
period for an equivalent number of lower income
housing units as projected for the site or unless
the locality provides other evidence to the
department that the site can be developed as
lower income housing.
• Chapter 6 pages 11 and 14
(c)(2)(B) For purposes of this subparagraph, “site”
means that portion of a parcel or parcels
designated to accommodate lower income
housing needs pursuant to this subdivision.
• Appendix K
(c)(2)(C) A site may be presumed to be realistic
for development to accommodate lower income
housing need if, at the time of the adoption of
the housing element, a development affordable
to lower income households has been proposed
and approved for development on the site.
• Appendix K
(c)(3) For the number of units calculated to
accommodate its share of the regional housing
need for lower income households pursuant to
paragraph (2), a city or county shall do either of
the following:
(c)(3)(A) Provide an analysis demonstrating how
the adopted densities accommodate this need.

The analysis shall include, but is not limited to,
factors such as market demand, financial
feasibility, or information based on development
project experience within a zone or zones that
provide housing for lower income households.
• Chapter 6 Table 6-6
• Chapter 6 page 17
(c)(3)(B) The following densities shall be deemed
appropriate to accommodate housing for lower
income households:
(i) For an incorporated city within a
nonmetropolitan county and for a
nonmetropolitan county that has a micropolitan
area: sites allowing at least 15 units per acre.
(ii) For an unincorporated area in a
nonmetropolitan county not included in clause
(i): sites allowing at least 10 units per acre.
(iii) For a suburban jurisdiction: sites allowing at
least 20 units per acre.
(iv) For a jurisdiction in a metropolitan county:
sites allowing at least 30 units per acre.
• Chapter 6 page 11
(4)(A) For a metropolitan jurisdiction: • Chapter 6 page 11 1405 of 1863
(4)(A)(i) At least 25 percent of the jurisdiction’s
share of the regional housing need for moderateincome housing shall be allocated to sites with zoning that allows at least 4 units of housing, but
not more than 100 units per acre of housing.
• Chapter 6 Table 6-4
(4)(A)(ii) At least 25 percent of the jurisdiction’s
share of the regional housing need for above
moderate-income housing shall be allocated to
sites with zoning that allows at least 4 units of
housing.
• Chapter 6 Table 6-4
(B) The allocation of moderate-income and above
moderate-income housing to sites pursuant to
this paragraph shall not be a basis for the
jurisdiction to do either of the following:
(i) Deny a project that does not comply with the
allocation.
(ii) Impose a price minimum, price maximum,
price control, or any other exaction or condition
of approval in lieu thereof. This clause does not
prohibit a jurisdiction from imposing any price
minimum, price maximum, price control,
exaction, or condition in lieu thereof, pursuant to
any other law.
(iii) The provisions of this subparagraph do not
constitute a change in, but are declaratory of,
existing law with regard to the allocation of sites
pursuant to this section.
(C) This paragraph does not apply to an
unincorporated area.
(D) For purposes of this paragraph:
(i) “Housing development project” has the same
meaning as defined in paragraph (2) of
subdivision (h) of Section 65589.5.
(ii) “Unit of housing” does not include an
accessory dwelling unit or junior accessory
dwelling unit that could be approved pursuant to
Section 65852.2 or Section 65852.22 or through a
local ordinance or other provision implementing
either of those sections. This paragraph shall not
limit the ability of a local government to count
the actual production of accessory dwelling units
or junior accessory dwelling units in an annual
progress report submitted pursuant to Section
65400 or other progress report as determined by
the department.
(E) Nothing in this subdivision shall preclude the
subdivision of a parcel, provided that the
1406 of 1863
subdivision is subject to the Subdivision Map Act
(Division 2 (commencing with Section 66410)) or
any other applicable law authorizing the
subdivision of land.
(d) For purposes of this section, a metropolitan
county, nonmetropolitan county, and
nonmetropolitan county with a micropolitan area
shall be as determined by the United States
Census Bureau. A nonmetropolitan county with a
micropolitan area includes the following
counties: Del Norte, Humboldt, Lake, Mendocino,
Nevada, Tehama, and Tuolumne and other
counties as may be determined by the United
States Census Bureau to be nonmetropolitan
counties with micropolitan areas in the future.
(e) (1) Except as provided in paragraph (2), a
jurisdiction shall be considered suburban if the
jurisdiction does not meet the requirements of
clauses (i) and (ii) of subparagraph (B) of
paragraph (3) of subdivision (c) and is located in a
Metropolitan Statistical Area (MSA) of less than
2,000,000 in population, unless that jurisdiction’s
population is greater than 100,000, in which case
it shall be considered metropolitan. A county, not
including the City and County of San Francisco,
shall be considered suburban unless the county is
in an MSA of 2,000,000 or greater in population
in which case the county shall be considered
metropolitan.
(2)(A)(i) Notwithstanding paragraph (1), if a
county that is in the San Francisco-OaklandFremont California MSA has a population of less than 400,000, that county shall be considered
suburban. If this county includes an incorporated
city that has a population of less than 100,000,
this city shall also be considered suburban. This
paragraph shall apply to a housing element
revision cycle, as described in subparagraph (A)
of paragraph (3) of subdivision (e) of Section
65588, that is in effect from July 1, 2014, to
December 31, 2028, inclusive.
(2)(A)(ii) A county subject to this subparagraph
shall utilize the sum existing in the county’s
housing trust fund as of June 30, 2013, for the
development and preservation of housing
affordable to low- and very low-income
households.
1407 of 1863
(f) A jurisdiction shall be considered metropolitan
if the jurisdiction does not meet the
requirements for “suburban area” above and is
located in an MSA of 2,000,000 or greater in
population unless that jurisdiction’s population is
less than 25,000 in which case it shall be
considered suburban.
(g)(1) For sites described in paragraph (3) of
subdivision (b) [non-vacant sites], the city or
county shall specify the additional development
potential for each site within the planning period
and shall provide an explanation of the
methodology used to determine the
development potential.
• Chapter 6 pages 10-11
• Chapter 6 Table 6-4
(g)(1) The methodology shall consider factors
including the extent to which existing uses may
constitute an impediment to additional
residential development,
• Chapter 6 Table 6-6
(g)(1) the city’s or county’s past experience with
converting existing uses to higher density
residential development,
• Chapter 6 pages 6-7
(g)(1) the current market demand for the existing
use,
• Chapter 6 Table 6-6
(g)(1) an analysis of any existing leases or other
contracts that would perpetuate the existing use
or prevent redevelopment of the site for
additional residential development,
• Chapter 6 Table 6-6
(g)(1) development trends, • Chapter 6 page 6-9
(g)(1) market conditions, • Chapter 6 pages 8-9
(g)(1) and regulatory or other incentives or
standards to encourage additional residential
development on these sites.
• Chapter 7 Program 2-E
• Chapter 7 Program 2-H
• Chapter 7 Program 2-K
• Chapter 7 Program 2-M
(g)(2) In addition to the analysis required in
paragraph (1), when a city or county is relying on
nonvacant sites described in paragraph (3) of
subdivision (b) to accommodate 50 percent or
more of its housing need for lower income
households, the methodology used to determine
additional development potential shall
demonstrate that the existing use identified
pursuant to paragraph (3) of subdivision (b) does
not constitute an impediment to additional
residential development during the period
covered by the housing element. An existing use
shall be presumed to impede additional
• Chapter 6 Table 6-6
1408 of 1863
residential development, absent findings based
on substantial evidence that the use is likely to
be discontinued during the planning period.
(g)(3) Notwithstanding any other law, and in
addition to the requirements in paragraphs (1)
and (2), sites that currently have residential uses,
or within the past five years have had residential
uses that have been vacated or demolished, that
are or were subject to a recorded covenant,
ordinance, or law that restricts rents to levels
affordable to persons and families of low or very
low income, subject to any other form of rent or
price control through a public entity’s valid
exercise of its police power, or occupied by low
or very low income households, shall be subject
to a policy requiring the replacement of all those
units affordable to the same or lower income
level as a condition of any development on the
site. Replacement requirements shall be
consistent with those set forth in paragraph (3)
of subdivision (c) of Section 65915.
• Not applicable because none of the sites
in the inventory contain existing housing
units.
(h) The program required by subparagraph (A) of
paragraph (1) of subdivision (c) of Section 65583
shall accommodate 100 percent of the need for
housing for very low and low-income households
allocated pursuant to Section 65584 for which
site capacity has not been identified in the
inventory of sites pursuant to paragraph (3) of
subdivision (a) on sites that shall be zoned to
permit owner-occupied and rental multifamily
residential use by right for developments in
which at least 20 percent of the units are
affordable to lower income households during
the planning period.
• Chapter 7 Program 2-D
(h) These sites shall be zoned with minimum
density and development standards that permit
at least
• Chapter 7 Program 2-D
(h) 16 units per site at a density of at least 16
units per acre in jurisdictions described in clause
(i) of subparagraph (B) of paragraph (3) of
subdivision (c),
(h) shall be at least 20 units per acre in
jurisdictions described in clauses (iii) and (iv) of
subparagraph (B) of paragraph (3) of subdivision
(c)
• Chapter 7 Program 2-D
1409 of 1863
(h) and shall meet the standards set forth in
subparagraph (B) of paragraph (5) of subdivision
(b).
• Chapter 7 Program 2-D
(h) At least 50 percent of the very low and lowincome housing need shall be accommodated on sites designated for residential use and for which
nonresidential uses or mixed uses are not
permitted, except that a city or county may
accommodate all of the very low and low-income
housing need on sites designated for mixed uses
if those sites allow 100 percent residential use
and require that residential use occupy 50
percent of the total floor area of a mixed-use
project.
• Appendix K
1410 of 1863
Exhibit C

RESPONSE TO HCD FINDINGS
1411 of 1863
HE Section Subsection No. Comment SB Response HE Section/Page# Appendix A
Review and
Revision
1 Analysis must be included for all programs in the previous housing element including progress and actual results for each.

More analysis has been added to
each program evaluation for the
previous cycle.

Appendix A
Appendix A
Review and
Revision
2 Provide a description of how the objectives and programs of the updated element incorporate changes resulting from the evaluation of the previous HE.

More description about how certain
programs from the previous
Housing Element were
incorporated into the current
Housing Element have been added
throughout the evaluation
Appendix A
Appendix A
Review and
Revision
3 If the City failed to make adequate sites available to accommodate the regional housing need in the prior planning period, the City must zone or rezone sites to accommodate any unaccommodated need within the first year of the 2023-2031 planning period. (Gov. Code, § 65584.09.) Program 2-A was necessary to demonstrate compliance with the adequate sites requirement in the previous planning period, however it was not completed. To demonstrate adequate sites were made available in the prior planning period, the element must include an analysis or programs demonstrating compliance with the statutory requirements. For additional information, see HCD’s AB 1233 Memorandum at https://www.hcd.ca.gov/hcd-memos and the Building Blocks at https://www.hcd.ca.gov/review-and-revise.

Program 2-A from the previous
cycle was to be completed within 3
years of Housing Element adoption
but was instead completed six
years after element adoption.

Adequate sites were made
available after the initial delay.

However, the city continued to
entitle housing projects in the TCP
during the delay.

Program 2-A on
page 13
Appendix A
Review and
Revision
4 The element must evaluate the effectiveness of goals, policies, and related actions in meeting the housing needs of special needs populations (e.g., elderly, persons with disabilities, large households, female headed households, farmworkers and persons experiencing homelessness).

Additional evaluation regarding the
effectiveness of those programs
that impact special needs
populations has been added.

See Appendix page
A-54
Chapter 4
AFFH
Integration &
Segregation 5 The element must evaluate racial patterns at a regional basis, comparing the City to the region. Added narrative and maps pp. 4-8 to 4-11 Chapter 4
AFFH
Integration &
Segregation 6
Must discuss and analyze data on persons with disabilities for trends over time and patterns across census tracts as well as evaluate patterns at a regional basis.

New information from Housing
Choices and maps pp. 4-17 to 4-19
Chapter 4
AFFH
Integration &
Segregation 7 Must describe and analyze concentrations of income and familial status geographically throughout the City. Added narrative and maps income: pp. 4-14 to
4-17
familial status: pp. 4-
19 to 4-21
Chapter 4
AFFH
Access to
Opportunity 8
While the element identified an area of access to education with lower outcomes, it must describe and analyze how that affects fair housing and other factors.

Added narrative and maps
pp. 4-28 to 4-30 and
summary on pp. 4-33
to 4-37
1412 of 1863
Chapter 4
AFFH
Access to
Opportunity 9 The element should describe and analyze the access to jobs throughout the City and for protected classes. Added narrative and maps pp. 4-29 to 4-30 and
summary on pp. 4-33
to 4-37
Chapter 4
AFFH
Access to
Opportunity 10 The element should describe and analyze the access to transit throughout the City and for protected classes. Added narrative and maps pp. 4-30 to 4-32 and
summary on pp. 4-33
to 4-37
Chapter 4
AFFH
Disproportionate
Housing Needs 11 The element must analyze the areas of poor environmental outcomes and identify actions to address fair housing issues. Added narrative and maps pp. 4-32 to 4-35 Chapter 4
AFFH
Disproportionate
Housing Needs 12 Describe any geographic concentration of cost burden, overcrowding by tenure, and substandard housing. Added narrative and maps pp. 4-39 to 4-46 Chapter 4
AFFH
Disproportionate
Housing Needs 13 Describe and analyze areas sensitive to displacement, including displacement risk due to disaster. Added narrative and maps pp. 4-43 to 4-46 Chapter 4
AFFH
Site Inventory
Analysis 14
The element must identify whether sites improve or exacerbate fair housing issues in the City. If sites exacerbate conditions, the element should identify further program actions that will be taken to promote equitable quality of life throughout the community (e.g., antidisplacement and place-based community revitalization strategies).

New subsections titled "Site
Inventory Analysis Findings" were
added to each section that
addresses this question for race,
income, disability, familial status,
all fh factors related to access to
opportunity and all fh factrors
related to disproportionate housing
needs. New program actions were
added and included in FHAP as
well as in chapter 7 on policies and
programs.

Throughout chapter
4, FHAP
Chapter 4
AFFH
Site Inventory
Analysis 15
Address the income categories of identified sites with respect to location, the number of sites and units by all income groups, and how that affects the existing patterns for all components of the New subsections titled "Site
Inventory Analysis Findings" was
added to each section and
Throughout chapter
4 1413 of 1863
assessment of fair housing (e.g., segregation and integration, access to opportunity).
provides this information in both
narrative and table format.

Chapter 4
AFFH
Fair Housing
Action Plan
(Goals, Actions,
Metrics,
Milestones)
16 Goals and actions must specifically respond to the analysis and to the identified and prioritized contributing factors to fair housing issues and must be significant and meaningful enough to overcome identified patterns and trends. Actions must have specific commitment, milestones, geographic targeting and metrics or numerical targets and, as appropriate, address housing mobility enhancement, new housing choices and affordability in high opportunity areas, placebased strategies for community preservation and revitalization and displacement protection.

New program actions were added
where needed and programs were
edited to provide milestones,
metrics
New AFFH
Programs included
which respond
directly to AFFH
analysis are: 5-E, 5-
F, 5-I, 5-J, 5-L, 5-N,
5-O, 5-P, 5-U, 5-V,
and 5-W
Chapter 2
Needs
Analysis
Housing Stock
Condition 17
Estimate of the number of units in need of rehabilitation and replacement (possible sources are: recent windshield survey, estimates from the code enforcement agency, or information from knowledgeable builders/developers, including non-profit housing developers or organizations).
analysis added page 2-36
Chapter 2
Needs
Analysis
Housing Costs 18
While the element includes estimated rents for residents, it utilizes American Community Survey (ACS) data. The element should supplement census data with other sources (e.g., local knowledge).

Additional rental data added page 2-24
Chapter 2
Needs
Analysis
Persons with
Disabilities 19*
While the element quantifies the number of persons with disabilities, it must also analyze their special housing needs. For a complete analysis, the element should discuss challenges faced by the population, the existing resources to meet those needs, an assessment of any gaps in resources, and proposed policies, programs, and funding to help address those gaps.

Analysis added for disability
housing needs. pages 2-40, 2-41
Chapter 6
Sites
Inventory
Progress
Meeting RHNA 20
The City’s RHNA may be reduced by the number of new units built since June 30, 2022; however, the element must demonstrate their affordability based on actual sales price, rent level, or other mechanisms ensuring affordability (e.g., deed restrictions). The element should also discuss the status, any barriers to development and other relevant factors to demonstrate their availability in the planning period.
10 dwellings have been
constructed in the city since July 1,
2022. Paragraph added.
page 6-7
1414 of 1863
Chapter 6
Sites
Inventory
Sites Inventory 21
The element must list sites by parcel number, parcel size, zoning, general plan designation, describing existing uses for nonvacant sites and include a calculation of the realistic capacity of each site. While the element includes most of these requirements, the inventory must include the calculation of units in whole number increments. In addition, sites that are identified for rezone must include existing and proposed general plan and zoning designations. The element must also ensure there are sufficient sites identified in the inventory, either with existing zoning or proposed rezones to meet the lower and moderate income RHNA.

See Table 6-4 pages 6-13 to 6-15
Chapter 6
Sites
Inventory
Realistic
Capacity 22
While the element provides assumptions of buildout for sites included in the inventory, it must also provide support for these assumptions (e.g., recent project examples). For example, the element should demonstrate what specific trends, factors, and other evidence led to the assumptions.

Most density assumptions are
based on actual projects or
projects submitted nearby for
similary situated sites.
page 6-16 and table
6-6
Chapter 6
Sites
Inventory
Realistic
Capacity 23
The estimate of the number of units for each site must be adjusted as necessary, based on the land use controls and site improvements and typical densities of existing or approved residential developments at a similar affordability level.

None of the unit estimates have
been adjusted but more
justification has been provided.

Some of the estimates are based
on submitted projects.
see Tables 6-5 and
6-6
Chapter 6
Sites
Inventory
Realistic
Capacity 24 The element should describe what factors were included in the realistic capacity assumptions, especially in the mixed-use zones. Additional justification added See table 6-6 Chapter 6
Sites
Inventory
Realistic
Capacity 25
The element includes many sites in the transit-oriented development (TOD) which does not include a maximum density. Assumptions of realistic capacity should be supported with examples.

The following project examples
were added to support
assumptions: 111 San Bruno, Mills
Park, and 732 - 740 ECR.
see page 6-16
Chapter 6
Sites
Inventory
Realistic
Capacity 26
Some sites in the inventory assume over 200 units an acre (including site 1 on page 6-13). These assumptions should be supported with examples. Examples to support realistic capacity assumptions should also include affordability levels, and percent of maximum densities.

Site #1 is the densest site in the
inventory. No assumptions were
made for this site because it is
based on a submitted application.

Staff noted projects with submitted
applications are denser than staff
previously anticipated. The density
assumptions for sites without
submitted applications was based
on the project details of similar
sites nearby. More information has
Table 6-6
1415 of 1863
been added to the justification to
make this connection more explicit.

Chapter 6
Sites
Inventory
Realistic
Capacity 27
The calculation of residential capacity must also account for the likelihood of residential development in zoning where 100 percent nonresidential uses are allowed. The analysis should be based on factors such as development trends including nonresidential, performance standards requiring residential uses or other relevant factors such as enhanced policies and programs. For example, the element could analyze all development activity in these nonresidential zones, how often residential development occurs and adjust residential capacity calculations, policies, and programs accordingly.

Discussion added. Page 6-11
Chapter 6
Sites
Inventory
Zoning for
Lower-Income
Households
28 The element must demonstrate zoning appropriate to accommodate housing for lower-income households. For sites with zoning meeting specified densities or default densities (30 units per acre in San Bruno), no analysis is required. Otherwise, the element must include analysis based on statutory factors. While the element identifies densities of at least 30 units per acre for many of the sites to accommodate housing for lower-income households, other sites do not meet the default density. As a result, if relying on densities less than 30 units per
acre to accommodate the lower-income RHNA, an analysis must be included to demonstrate how the zoning encourages the development of units affordable for lower income households. Please see HCD’s Building Blocks for more information.

The city imposes a 15% affordable
housing requirement on all
residential developments of 5+
units. This requirement applies to
sites that don't meet the default
density requirement.

Page 6 ends

San Bruno City CouncilJanuary 24, 2023

San Bruno City Council
January 24, 2023