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Ecotoxicology and Public Health

Historical Redlining Is Associated with Disparities in Environmental Quality across California
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  • Cesar O. Estien*
    Cesar O. Estien
    Department of Environmental Science, Policy, and Management, University of California−Berkeley, 130 Mulford Hall, Berkeley, California 94720, United States
    *Email: [email protected]
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    Orcidhttps://orcid.org/0000-0001-8410-7371
  • Christine E. Wilkinson
    Christine E. Wilkinson
    Department of Environmental Science, Policy, and Management, University of California−Berkeley, 130 Mulford Hall, Berkeley, California 94720, United States
    California Academy of Sciences, 55 Music Concourse Drive, San Francisco, California 94118, United States
    More by Christine E. Wilkinson
  • Rachel Morello-Frosch
    Rachel Morello-Frosch
    Department of Environmental Science, Policy, and Management, University of California−Berkeley, 130 Mulford Hall, Berkeley, California 94720, United States
    School of Public Health, University of California−Berkeley, 2121 Berkeley Way, Berkeley, California 94720, United States
    More by Rachel Morello-Frosch
  • Christopher J. Schell
    Christopher J. Schell
    Department of Environmental Science, Policy, and Management, University of California−Berkeley, 130 Mulford Hall, Berkeley, California 94720, United States
    More by Christopher J. Schell
Open PDFSupporting Information (1)

Environmental Science & Technology Letters

Cite this: Environ. Sci. Technol. Lett. 2024, 11, 2, 54–59
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https://doi.org/10.1021/acs.estlett.3c00870
Published January 19, 2024

Copyright © 2024 The Authors. Published by American Chemical Society. This publication is licensed under

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Abstract

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Historical policies have been shown to underpin environmental quality. In the 1930s, the federal Home Owners’ Loan Corporation (HOLC) developed the most comprehensive archive of neighborhoods that would have been redlined by local lenders and the Federal Housing Administration, often applying racist criteria. Our study explored how redlining is associated with environmental quality across eight California cities. We integrated HOLC’s graded maps [grades A (i.e., “best” and “greenlined”), B, C, and D (i.e., “hazardous” and “redlined”)] with 10 environmental hazards using data from 2018 to 2021 to quantify the spatial overlap among redlined neighborhoods and environmental hazards. We found that formerly redlined neighborhoods have poorer environmental quality relative to those of other HOLC grades via higher pollution, more noise, less vegetation, and elevated temperatures. Additionally, we found that intraurban disparities were consistently worse for formerly redlined neighborhoods across environmental hazards, with redlined neighborhoods having higher pollution burdens (77% of redlined neighborhoods vs 18% of greenlined neighborhoods), more noise (72% vs 18%), less vegetation (86% vs 12%), and elevated temperature (72% vs 20%), than their respective city’s average. Our findings highlight that redlining, a policy abolished in 1968, remains an environmental justice concern by shaping the environmental quality of Californian urban neighborhoods.

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Introduction

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Urban environmental quality varies significantly due to differences in access to wealth and resources, (1,2) implicating societal inequities in perpetuating disparities in environmental quality. Heterogeneity in urban environmental quality and wealth is largely driven by racial segregation, racialized zoning practices, and other forms of racist government actions (e.g., limiting civic engagement of marginalized populations). (3−5) These dynamics have resulted in communities of color being disproportionately exposed to environmental hazards. (6,7) It is therefore critical to unpack how specific policies have perpetuated environmental harm in order to develop restorative policies.
Racial segregation is a practice and societal structure that underlies the spatial distribution of environmental hazards (e.g., heat risk, (8) noise (9)). A notable process formalizing racial segregation in the United States was redlining, a policy instituted by the Home Owners’ Loan Corporation (hereafter HOLC) following the Great Depression. (10,11) In the process, the HOLC created risk assessment maps to identify neighborhoods that would have been redlined by local lenders and the Federal Housing Administration via a ranking system denoting neighborhood quality, (12) from best (i.e., grade A, or “greenlined”) to hazardous (i.e., grade D, or “redlined”). However, their determination of decline, hazards, and investment risk were directly linked to Black and immigrant communities, with appraisers often noting the ethno-racial composition of neighborhoods. (10−13) The process of redlining reflected and codified existing racist practices, including zoning laws and discriminatory housing practices, leading to continued disinvestment in redlined neighborhoods. (11,12)
Formerly redlined neighborhoods have distinct ecologies compared to greenlined neighborhoods. (2,14) Recent research has shown that previously redlined neighborhoods have, for example, poorer air quality and intensified urban heat islands. (15−18) Due to these environmental inequities, humans residing in redlined neighborhoods today demonstrate higher rates of adverse health outcomes, including cancer, (19) cardiovascular disease, (20) and asthma. (21) Such outcomes may not be restricted to humans, as emerging research suggests wildlife species are also being impacted, (2,22,23) with potential additional negative feedbacks that affect human health. (24,25) Thus, understanding the association between redlining and environmental quality is crucial for mitigating and deconstructing the potential consequences for human and wildlife health within cities.
While prior redlining studies typically focus on a single metric, such as canopy cover, (26) hazards often co-occur spatially. Understanding where environmental hazards co-occur is crucial for assessing the potential synergistic interactions between them and the consequential cumulative impact on human and nonhuman organisms. Yet, comprehensive work examining multiple hazards across multiple cities is scarce, despite the high applicability for informing state and federal environmental justice policies.
Here, we leveraged HOLC maps to examine whether the practice of redlining is associated with environmental quality in California cities. We focused on California as it is the most populous state in the US (∼39 million people (27)), with 43 cities ranking in the top 200 largest US cities by population. (28) To assess environmental quality, we extracted relevant variables from CalEnviroScreen, a high-resolution environmental hazard mapping tool that uses the most recent publicly available data. (29) Notably, while CalEnviroScreen’s story map examines the relationship between redlining and environmental hazards, (30) it lacks a formal analysis that controls for city-level differences and neighborhood size. Thus, we evaluate environmental quality by examining the spatial distribution of various environmental hazards using CalEnviroScreen4.0 alongside other data sources (see Methods and Materials). We hypothesized that previously redlined neighborhoods would have poorer environmental quality (i.e., higher pollution, more noise, less vegetation, and elevated temperatures) than nonredlined neighborhoods.

Methods and Materials

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Data Sets and Geospatial Processing

We obtained HOLC-graded maps for Fresno, Los Angeles, Oakland, Sacramento, San Diego, San Francisco, San Jose, and Stockton via the Mapping Inequality project (13) (S1.1). Across California, there are 868 HOLC-graded neighborhoods: 109 A-graded, 273 B-graded, 331 C-graded, and 155 D-graded. We evaluated the following environmental hazards to assess environmental quality in relation to redlining: groundwater threats, lead risk from housing, particulate matter 2.5 (PM2.5), diesel particulate matter, toxic releases from facilities, hazardous waste generators and facilities, cleanup sites (i.e., brownfield sites), normalized difference vegetation index (NDVI), temperature, and noise pollution (S1.2). Geospatial analyses were conducted using ArcGIS Pro utilizing the “Zonal Statistics” tool to extract the mean for all hazards. Statistical analyses were completed in R v.4.1.0. (31)
We extracted the mean CalEnviroScreen4.0 score for each hazard per neighborhood and converted each score to a percentile to assess disparities between HOLC grades. We scaled it such that a score of 1 represents no environmental hazard burden, and a score of 100 represents the highest burden. We then used these percentiles, following CalEnviroScreen methods, (29) to produce a pollution burden for each neighborhood. The pollution burden metric represents a cumulative score of multiple environmental hazards within a neighborhood and includes groundwater threats, lead risk from housing, PM2.5, diesel PM, toxic releases from facilities, hazardous waste generators and facilities, and cleanup sites (S1.2).
To calculate NDVI and temperature, we used Landsat 8 OLI Level 1 (C2 L1) terrain-correct, with images from December 2020 and January 2021 where cloud cover was <20% and retained the appropriate bands (S1.2). We used these bands to calculate NDVI, which represents the amount of vegetation with lower values corresponding with less vegetation and land surface temperature in degree Celsius. To calculate noise pollution, we used HowLoud (https://howloud.com), which calculates noise pollution values caused by local traffic, airplane traffic, and other local sources of noise (S1.2).

Data Analysis

We ran general-linear mixed models to understand the effect of HOLC grades on environmental quality with HOLC grade as a fixed effect and city as a random effect to control for potential among-city differences using the glmmTMB package (32) (SM 1.3). We also included the area of a neighborhood as a log-offset variable to control for the fact that larger neighborhoods, by virtue of size, may have higher environmental hazards. We performed Tukey–Kramer’s posthoc analyses to determine which HOLC grade dyads (e.g., A vs C, A vs D) differed in the focal environmental hazard (S1.3). We report the mean, standard deviation, and D-grade comparisons below for each environmental hazard. We report model results and all pairwise comparisons in Supporting Information S2 and S3.
To further understand disparities in environmental quality, we considered intraurban disparities via investigating the relative difference per environmental hazard at the city-level between a neighborhood and their respective city. We did this by calculating a city’s average for each hazard, then subtracted a neighborhood’s environmental quality estimate from the city’s average, (13) such that a value of 0 would represent no disparity between a neighborhood’s environmental hazard and the corresponding city’s average value for that hazard. We then compared the interquartile range (IQR) (ANOVA comparisons are shown in the Supporting Information).

Results

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Environmental Quality

After controlling for the area of a neighborhood and among-city variation, we found a strong relationship between HOLC grade and environmental quality (Figure 1; Table 1; S2.1; Figure S1). Across all environmental hazards, redlined neighborhoods had higher pollution burdens, less vegetation, more noise pollution, and higher temperatures (Figure 1; Table 1; Figure S1). Overall, HOLC grades significantly predict overall pollution burden for a neighborhood, with redlined neighborhoods having a significantly higher pollution burden than nonredlined neighborhoods (Table 1; Figure 1). Though redlined neighborhoods had higher pollution burdens than greenlined neighborhoods in every city but one (Figure S2), we only found significant differences in pollution burden between greenlined and redlined neighborhoods in five of the eight cities (Table S2). We found similar variation for each environmental hazard. Redlined and nonredlined neighborhoods showed no significant differences in PM2.5 and toxic releases, but did show significant differences in lead risk, groundwater threats, hazardous waste facilities, cleanup sites, and diesel PM (Table 1), with variation at the city-level for each environmental hazard (Figures S3–S7; Table S2). For example, although we found no significant differences overall in PM2.5 and toxic releases, we found significant differences in these hazards in three and four cities, respectively (Figures S8, S9; Table S2). We found significant differences between redlined and nonredlined neighborhoods in noise pollution, NDVI, and temperature (Figure 1B–D; Table 1). Noise pollution, NDVI, and temperature varied significantly in seven of the eight cities (Figures S10–S12; Table S2), though differences were not always between redlined and nonredlined neighborhoods.
Table 1. Environmental Hazards in California by HOLC grade
Environmental HazardGrade A(n = 109)Grade B(n = 273)Grade C(n = 331)Grade D(n = 155)A–D p-valueB–D p-valueC–D p-value
PM2.545.9 (23.8)45.2 (27.5)51.2 (29.3)54.4 (31.0)p = 0.6867p = 0.6105p = 0.7534
Diesel PM29.5 (23.9)41.3 (26.8)53.3 (26.6)68.5 (24.9)p < 0.0001p < 0.001p < 0.01
Lead risk35.5 (23.4)46.9 (27.2)52.3 (29.0)56.5 (29.8)p = 0.4856p < 0.05p = 0.9681
Groundwater threat35.4 (24.9)45.5 (27.8)52.1 (28.3)59.4 (28.3)p < 0.01p = 0.7998p = 0.0936
Toxic releases by facilities46.8 (25.6)47.0 (27.2)50.2 (30.2)53.0 (29.3)p = 0.7855p = 0.0813p = 0.8140
Hazardous waste facilities36.0 (22.8)44.2 (27.7)52.4 (27.7)60.7 (30.3)p < 0.001p = 0.4328p < 0.05
Cleanup sites39.0 (26.5)43.5 (27.9)51.1 (26.9)62.5 (29.6)p < 0.0001p < 0.01p < 0.0001
Pollution burden28.8 (21.8)40.4 (25.9)54.5 (27.8)68.1 (24.1)p < 0.0001p = 0.0001p < 0.0001
Noise pollution76.2 (3.5)78.1 (3.2)79.3 (3.2)80.6 (3.4)p < 0.01p < 0.0001p < 0.01
NDVI0.13 (0.03)0.09 (0.03)0.08 (0.02)0.07 (0.02)p < 0.0001p < 0.0001p < 0.001
Temperature (°C)16.1 (3.7)15.8 (3.8)16.4 (3.7)16.2 (3.9)p < 0.01p < 0.0001p < 0.001

Figure 1

Figure 1. Redlined neighborhoods have higher environmental hazards than nonredlined neighborhoods. We show (A) pollution burden, (B) noise pollution, (C) vegetation (NDVI*), and (D) temperature across HOLC grades. Pollution burden is a score based on the presence of various environmental hazard (see Methods and Materials). Noise pollution is on a scale of 50–100, with 100 representing a very loud environment. NDVI (i.e., vegetation) is on a scale of −1 to 1, with lower scores representing less vegetation. Black diamonds represent the mean and whiskers represent 95% confidence intervals. *NDVI = Normalized Differentiated Vegetation Index.

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Raw data for each environmental hazard is shown as mean (standard deviation) across HOLC grades (grades A = “best” and “greenlined”; B, C, and D = “hazardous” and “redlined”). PM2.5, diesel particulate matter, lead risk from housing, groundwater threat, toxic releases from facilities, hazardous waste facilities, cleanup sites, and pollution burden are shown as percentiles (1–100), where 1 represents no environmental hazard burden, and 100 represents a high burden. Noise pollution is on a scale of 50–100, with 100 representing a very loud environment using HowLoud’s soundscore (https://howloud.com). NDVI (i.e., vegetation) is on a scale of −1 to 1, with lower scores representing less vegetation. The number of graded neighborhoods for each HOLC grade is shown above the respective column. Pair-wise comparison between greenlined and redlined neighborhoods from generalized linear mixed-models that control for the area of a neighborhood and among-city variation are shown. Significant comparisons from Tukey–Kramer’s posthoc analyses are bolded. The remaining pairwise comparisons are found in Table S1 in Supporting Information.

Intraurban Disparities

Grade D ubiquitously exhibited environmental hazards that were worse than the city’s average (Figure 2; S2.2; Tables S3), with strong significance found between redlined and nonredlined neighborhoods (Table S4). Pollution was higher than average in 77% of redlined neighborhoods compared to 18% of greenlined neighborhoods across all cities (Figure 2A), with no IQR overlap for seven cities (i.e., A-graded 75th percentile was lower than D-graded 25th percentile; Figure S13). Similar directionality was observed for lead (61% of redlined vs 29% of greenlined neighborhoods) as well as water contamination (70% of redlined vs 29% of greenlined neighborhoods) (Figure S14), with both hazards showing no IQR overlap for three cities (Figures S15, S16). For air pollutants (i.e., PM2.5, diesel PM, and toxic releases), we found the same directionality again (Figure S14). PM2.5 was higher than average in 70% of redlined neighborhoods compared to 31% greenlined neighborhoods, with no IQR overlap for three cities (Figures S14, S17). Diesel PM was higher than average in 75% of redlined neighborhoods compared to 24% greenlined neighborhoods, with no IQR overlap for six cities (Figures S14, S18). Similarly, toxic releases were higher than average in 61% of redlined neighborhoods compared to 35% greenlined neighborhoods, with no IQR overlap for three cities (Figures S14, S19). We found the same directionality for cleanup sites (66% of redlined vs 43% of greenlined neighborhoods) and hazardous waste facilities (64% of redlined vs 30% of greenlined neighborhoods) (Figure S14), with both hazards showing no IQR overlap for two cities (Figures S20, S21). For noise pollution, 72% of redlined neighborhoods had higher levels of noise than average compared to 18% of greenlined neighborhoods (Figure 2B), with no IQR overlap for seven cities (Figure S22). For NDVI, 86% of redlined neighborhoods had less than average vegetation compared to 12% of greenlined neighborhoods with no IQR overlap for all cities (Figure 2C; Figure S23). Similar disparities were observed for temperature, with 72% of redlined neighborhoods having higher temperatures than average compared to 20% of greenlined neighborhoods (Figure 2D). For temperature, there was no IQR overlap for the six cities (Figure S24).

Figure 2

Figure 2. Redlined neighborhoods disproportionately face worse intraurban disparities in environmental hazards than nonredlined neighborhoods. Intraurban disparity analysis for (A) overall pollution burden, (B) noise pollution, (C) vegetation (NDVI*), and (D) temperature across HOLC grades. Horizontal zero line represents no difference between the city’s average and a neighborhood’s average environmental hazard. For graphs A–D, values above the line represent a higher environmental hazard value (i.e., higher pollution, more noise, and elevated temperature) than the corresponding cities average. For graph C, values below the line represent less vegetation value than the corresponding cities average. Black diamonds represent the mean and whiskers represent 95% confidence intervals. *NDVI = Normalized Differentiated Vegetation Index.

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Discussion

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Redlining and Environmental Quality

Redlining persisted across the United States from 1933 to 1968 in over 230 cities. (10,11) Alongside restrictive deeds, racialized zoning, steering, and social violence, redlining led to land use and decision making that worsened the environmental quality for redlined neighborhoods. (2,10,14) In this study, we assessed 868 previously HOLC-graded neighborhoods across eight California cities and found that redlining is strongly associated with environmental quality. Our results enrich the redlining literature by demonstrating that formerly redlined neighborhoods exhibit significantly poorer environmental quality than other HOLC grades, including less investigated hazards such as noise pollution, lead, and contaminated water. (33−35) This holds implications for human health disparities, as redlined neighborhoods in California are composed of census tracts with higher proportions of Hispanic and Black populations, as well as a people living in poverty, than greenlined neighborhoods. (36) Our results shed light on the enduring, far-reaching impact of redlining, a policy that was abolished almost 60 years ago, on contemporary environmental quality.
We found that redlined neighborhoods consistently face disproportionately worse environmental hazards with respect to their city’s average (i.e., intraurban disparity) across all 10 assessed hazards, often by several orders of magnitude. Intraurban analysis revealed that, despite some hazards not showing differences in environmental quality between HOLC grades, at either the state or city level, intraurban disparities are still strong. For example, though we did not find significant differences between greenlined and redlined neighborhoods for PM2.5 across all cities, we found large intraurban disparities, with redlined neighborhoods having double the proportion of neighborhoods that face higher levels of PM2.5 than greenlined neighborhoods. Thus, intraurban analyses, which explicitly examine relative city-level differences in environmental quality, may better capture contemporary social factors (e.g., contemporary lines of segregation) than general state-level analyses, despite controlling for city-level differences.

City-Level Variation in Environmental Hazards

The emergent patterns between redlining and environmental quality may vary by the city for several reasons. Since HOLC maps were drawn in the 1930s and 1940s, urban expansion has dramatically increased, (37) resulting in many cities expanding beyond the boundaries of their original HOLC maps. For instance, much of the Oakland metropolitan area and San Francisco lie within their original HOLC maps, compared to Fresno, Stockton, and Sacramento, which have experienced substantial growth, with most of the geographic expands of these cities now outside their respective HOLC geographic boundaries. Due to this sprawl and the associated movements in sociodemographics, more contemporary factors may be overriding the legacy effects produced by redlining. Namely, gentrification in these cities may ameliorate prior pollution burdens, resulting in concerted reinvestment that neutralizes differences among HOLC grades. Indeed, Californian cities are rapidly gentrifying, (38) with an influx of wealth and development potentially improving green space availability, quality, and distribution. (39) Modifications to the green infrastructure of certain neighborhoods can subsequently reduce urban heat, help to purify the air, and buffer against urban noise. (40,41)
Variation in environmental hazards may be influenced by a multitude of social and ecological factors. Notably, the unique geography and urban layouts of each California city, such as the distance to open water, highway concentration, population density, and housing distribution, may directly impact environmental hazard burdens. San Francisco, a coastal city on a peninsula, for example, has a 27% PM2.5 burden, whereas Fresno, a city surrounded by mountains, has a 97% PM2.5 burden. Yet, Los Angeles, another costal city, faces a PM2.5 burden (71%) similar to that of Fresno, despite its coastal location and dense infrastructure. Thus, the geographic and microclimatic conditions of each city may mediate the burdens experienced by human and nonhuman organisms. In parallel, contemporary policies and governance may also have mitigated or eliminated disparities in environmental quality, resulting in the lack of statistical differences across graded neighborhoods. Fresno, for example, where we found no differences in PM2.5 between HOLC grades, has undergone several management strategies since 1992 to reduce air pollution in the city and the greater San Joaquin, leading exposure to PM2.5 to be reduced by 85%, respectively. (42)
While no differences were found between redlined and nonredlined neighborhoods for certain environmental hazards, disparities may still exist. For instance, within the United States, racial–ethnic disparities for air pollution, (43,44) chemical toxins, (45) and water quality (46) still persist. Within California, recent research has shown that racially marginalized communities throughout California continue to face disproportionate exposure to oil and gas wells and the associated disturbances, (47) higher levels of water contamination, (48) and lower reductions in PM2.5. (49) Thus, although redlining is generally understood to underpin environmental quality, our results show that this may vary by city, and leveraging sociodemographic information (e.g., socioeconomics, race) in tandem with HOLC maps may be critical for elucidating environmental quality disparities.

Implications

Our results show that across California, redlined neighborhoods have disproportionately worse environmental quality than other HOLC grades, further implicating redlining as a major driver of contemporary disparities in environmental quality. These environmental inequities are multigenerational and will stubbornly persist without proper intervention and remediation. (25) We hope results from this work are pertinent to decision makers at the city- and state-levels by pinpointing neighborhoods that disproportionately suffer heavy environmental quality burdens. Moreover, this work holds potential for urban One Health initiatives, which recognize the shared health and well-being of the environment, people, and wildlife, highlighting that ongoing efforts to enhance urban resilience can benefit from considering legacy effects. Our work emphasizes that potential interventions for environmental inequities via policy, such as the White House’s Justice40 initiative, (50) must center social justice to effectively address environmental injustices produced by systemic racism.

Supporting Information

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The Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/acs.estlett.3c00870.

  • Detailed description of methods and materials, as well as Tables S1–S4 and Figures S1–S24, including city specific results (PDF)

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Most electronic Supporting Information files are available without a subscription to ACS Web Editions. Such files may be downloaded by article for research use (if there is a public use license linked to the relevant article, that license may permit other uses). Permission may be obtained from ACS for other uses through requests via the RightsLink permission system: http://pubs.acs.org/page/copyright/permissions.html.

Author Information

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  • Corresponding Author
  • Authors
    • Christine E. Wilkinson - Department of Environmental Science, Policy, and Management, University of California−Berkeley, 130 Mulford Hall, Berkeley, California 94720, United States;  California Academy of Sciences, 55 Music Concourse Drive, San Francisco, California 94118, United States
    • Rachel Morello-Frosch - Department of Environmental Science, Policy, and Management, University of California−Berkeley, 130 Mulford Hall, Berkeley, California 94720, United States;  School of Public Health, University of California−Berkeley, 2121 Berkeley Way, Berkeley, California 94720, United States
    • Christopher J. Schell - Department of Environmental Science, Policy, and Management, University of California−Berkeley, 130 Mulford Hall, Berkeley, California 94720, United States
  • Author Contributions

    C.O.E., R.M.-F., and C.J.S. designed the project. C.O.E. and C.E.W. acquired the data. C.O.E. led analysis with support from C.E.W. and C.J.S. C.O.E. and C.E.W. made the figures. C.O.E. wrote the original draft of the manuscript. C.O.E., C.E.W., R.M.-F., and C.J.S. contributed to writing and editing the manuscript.

  • Notes
    The authors declare no competing financial interest.

Acknowledgments

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We acknowledge and honor the communities who are overcoming the burdens and environmental injustices that have been placed upon them. We would like to thank Annie Taylor for her advice and guidance in ArcGIS and Python. C.O.E. was supported by the University of California, Berkeley’s Chancellor Fellowship, and the National Science Foundation Graduate Research Fellowship under Grant No. DGE-2146752. C.E.W. was supported by Schmidt Science Fellows, in partnership with the Rhodes Trust. R.M.-F. was supported by the National Institute of Environmental Health Sciences of the National Institutes of Health (NIH) under Award Number P42ES004705. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation.

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    Mascarenhas, M.; Grattet, R.; Mege, K. Toxic Waste and race in twenty-first century America. Environ. Soc. 2021, 12, 108– 126,  DOI: 10.3167/ares.2021.120107
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    Jesdale, B. M.; Morello-Frosch, R.; Cushing, L. The Racial/Ethnic Distribution of Heat Risk–Related Land Cover in Relation to Residential Segregation. Environ. Health Perspect. 2013, 121, 811– 817,  DOI: 10.1289/ehp.1205919
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    The racial/ethnic distribution of heat risk-related land cover in relation to residential segregation
    Jesdale Bill M; Morello-Frosch Rachel; Cushing Lara
    Environmental health perspectives (2013), 121 (7), 811-7 ISSN:.
    OBJECTIVE: We examined the distribution of heat risk-related land cover (HRRLC) characteristics across racial/ethnic groups and degrees of residential segregation. METHODS: Block group-level tree canopy and impervious surface estimates were derived from the 2001 National Land Cover Dataset for densely populated urban areas of the United States and Puerto Rico, and linked to demographic characteristics from the 2000 Census. Racial/ethnic groups in a given block group were considered to live in HRRLC if at least half their population experienced the absence of tree canopy and at least half of the ground was covered by impervious surface (roofs, driveways, sidewalks, roads). Residential segregation was characterized for metropolitan areas in the United States and Puerto Rico using the multigroup dissimilarity index. RESULTS: After adjustment for ecoregion and precipitation, holding segregation level constant, non-Hispanic blacks were 52% more likely (95% CI: 37%, 69%), non-Hispanic Asians 32% more likely (95% CI: 18%, 47%), and Hispanics 21% more likely (95% CI: 8%, 35%) to live in HRRLC conditions compared with non-Hispanic whites. Within each racial/ethnic group, HRRLC conditions increased with increasing degrees of metropolitan area-level segregation. Further adjustment for home ownership and poverty did not substantially alter these results, but adjustment for population density and metropolitan area population attenuated the segregation effects, suggesting a mediating or confounding role. CONCLUSIONS: Land cover was associated with segregation within each racial/ethnic group, which may be explained partly by the concentration of racial/ethnic minorities into densely populated neighborhoods within larger, more segregated cities. In anticipation of greater frequency and duration of extreme heat events, climate change adaptation strategies, such as planting trees in urban areas, should explicitly incorporate an environmental justice framework that addresses racial/ethnic disparities in HRRLC.
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  9. 9
    Casey, J. A.; Morello-Frosch, R.; Mennitt, D. J.; Fristrup, K.; Ogburn, E. L.; James, P. Race/ethnicity, socioeconomic status, residential segregation, and spatial variation in noise exposure in the contiguous United States. Environ. Health Perspect. 2017, 125, 077017  DOI: 10.1289/EHP898
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    Race/Ethnicity, Socioeconomic Status, Residential Segregation, and Spatial Variation in Noise Exposure in the Contiguous United States
    Casey Joan A; Morello-Frosch Rachel; Mennitt Daniel J; Fristrup Kurt; Ogburn Elizabeth L; James Peter
    Environmental health perspectives (2017), 125 (7), 077017 ISSN:.
    BACKGROUND: Prior research has reported disparities in environmental exposures in the United States, but, to our knowledge, no nationwide studies have assessed inequality in noise pollution. OBJECTIVES: We aimed to a) assess racial/ethnic and socioeconomic inequalities in noise pollution in the contiguous United States; and b) consider the modifying role of metropolitan level racial residential segregation. METHODS: We used a geospatial sound model to estimate census block group-level median (L50) nighttime and daytime noise exposure and 90th percentile (L10) daytime noise exposure. Block group variables from the 2006-2010 American Community Survey (ACS) included race/ethnicity, education, income, poverty, unemployment, homeownership, and linguistic isolation. We estimated associations using polynomial terms in spatial error models adjusted for total population and population density. We also evaluated the relationship between race/ethnicity and noise, stratified by levels of metropolitan area racial residential segregation, classified using a multigroup dissimilarity index. RESULTS: Generally, estimated nighttime and daytime noise levels were higher for census block groups with higher proportions of nonwhite and lower-socioeconomic status (SES) residents. For example, estimated nighttime noise levels in urban block groups with 75% vs. 0% black residents were 46.3 A-weighted decibels (dBA) [interquartile range (IQR): 44.3-47.8 dBA] and 42.3 dBA (IQR: 40.4-45.5 dBA), respectively. In urban block groups with 50% vs. 0% of residents living below poverty, estimated nighttime noise levels were 46.9 dBA (IQR: 44.7-48.5 dBA) and 44.0 dBA (IQR: 42.2-45.5 dBA), respectively. Block groups with the highest metropolitan area segregation had the highest estimated noise exposures, regardless of racial composition. Results were generally consistent between urban and suburban/rural census block groups, and for daytime and nighttime noise and robust to different spatial weight and neighbor definitions. CONCLUSIONS: We found evidence of racial/ethnic and socioeconomic differences in model-based estimates of noise exposure throughout the United States. Additional research is needed to determine if differences in noise exposure may contribute to health disparities in the United States. https://doi.org/10.1289/EHP898
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    Hillier, A. E. Redlining and the Home Owners’ Loan Corporation. J. Urban Hist. 2003, 29, 394– 420,  DOI: 10.1177/0096144203029004002
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    Fishback, P.; Rose, J.; Snowden, K. A.; Storrs, T. New Evidence on Redlining by Federal Housing Programs in the 1930s. J. Urban Econ. 2022, 103462  DOI: 10.1016/j.jue.2022.103462
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    Nelson, R. K.; Winling, L.; Marciano, R.; Connolly, N.; Ayers, E. L. Mapping Inequality: Redlining in new deal America; American Panorama: An Atlas of United States History; University of Richmond, Digital Scholarship Lab, 2020.
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    Swope, C. B.; Hernández, D.; Cushing, L. J. The Relationship of Historical Redlining with Present-Day Neighborhood Environmental and Health Outcomes: A Scoping Review and Conceptual Model. J. Urban Health 2022, 99, 959– 983,  DOI: 10.1007/s11524-022-00665-z
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    The Relationship of Historical Redlining with Present-Day Neighborhood Environmental and Health Outcomes: A Scoping Review and Conceptual Model
    Swope Carolyn B; Hernandez Diana; Cushing Lara J
    Journal of urban health : bulletin of the New York Academy of Medicine (2022), 99 (6), 959-983 ISSN:.
    Following the Great Depression and related home foreclosures, the federal government established new agencies to facilitate access to affordable home mortgages, including the Home Owners' Loan Corporation (HOLC) and Federal Housing Administration (FHA). HOLC and FHA directed widespread neighborhood appraisals to determine investment risk, referred to as "redlining," which took into account residents' race. Redlining thereby contributed to segregation, disinvestment, and racial inequities in opportunities for homeownership and wealth accumulation. Recent research examines associations between historical redlining and subsequent environmental determinants of health and health-related outcomes. In this scoping review, we assess the extent of the current body of evidence, the range of outcomes studied, and key study characteristics, examining the direction and strength of the relationship between redlining, neighborhood environments, and health as well as different methodological approaches. Overall, studies nearly universally report evidence of an association between redlining and health-relevant outcomes, although heterogeneity in study design precludes direct comparison of results. We critically consider evidence regarding HOLC's causality and offer a conceptual framework for the relationship between redlining and present-day health. Finally, we point to key directions for future research to improve and broaden understanding of redlining's enduring impact and translate findings into public health and planning practice.
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    Lane, H. M.; Morello-Frosch, R.; Marshall, J. D.; Apte, J. S. Historical Redlining Is Associated with Present-Day Air Pollution Disparities in U.S. Cities. Environ. Sci. Technol. Lett. 2022, 9, 345– 350,  DOI: 10.1021/acs.estlett.1c01012
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    Historical Redlining Is Associated with Present-Day Air Pollution Disparities in U.S. Cities
    Lane, Haley M.; Morello-Frosch, Rachel; Marshall, Julian D.; Apte, Joshua S.
    Environmental Science & Technology Letters (2022), 9 (4), 345-350CODEN: ESTLCU; ISSN:2328-8930. (American Chemical Society)
    Communities of color in the United States are systematically exposed to higher levels of air pollution. We explore here how redlining, a discriminatory mortgage appraisal practice from the 1930s by the federal Home Owners' Loan Corporation (HOLC), relates to present-day intraurban air pollution disparities in 202 U.S. cities. In each city, we integrated three sources of data: (1) detailed HOLC security maps of investment risk grades [A ("best"), B, C, and D ("hazardous", i.e., redlined)], (2) year-2010 ests. of NO2 and PM2.5 air pollution levels, and (3) demog. information from the 2010 U.S. census. We find that pollution levels have a consistent and nearly monotonic assocn. with HOLC grade, with esp. pronounced (>50%) increments in NO2 levels between the most (grade A) and least (grade D) preferentially graded neighborhoods. On a national basis, intraurban disparities for NO2 and PM2.5 are substantially larger by historical HOLC grade than they are by race and ethnicity. However, within each HOLC grade, racial and ethnic air pollution exposure disparities persist, indicating that redlining was only one of the many racially discriminatory policies that impacted communities. Our findings illustrate how redlining, a nearly 80-yr-old racially discriminatory policy, continues to shape systemic environmental exposure disparities in the United States.
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    Cushing, L. J.; Li, S.; Steiger, B. B.; Casey, J. A. Historical red-lining is associated with fossil fuel power plant siting and present-day inequalities in air pollutant emissions. Nat. Energy 2023, 8, 52– 61,  DOI: 10.1038/s41560-022-01162-y
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    Nardone, A.; Chiang, J.; Corburn, J. Historic Redlining and Urban Health Today in U.S. Cities. Environ. Justice 2020, 13, 109– 119,  DOI: 10.1089/env.2020.0011
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    Hoffman, J. S.; Shandas, V.; Pendleton, N. The Effects of Historical Housing Policies on Resident Exposure to Intra-Urban Heat: A Study of 108 US Urban Areas. Climate 2020, 8, 12,  DOI: 10.3390/cli8010012
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    Krieger, N. Cancer stage at diagnosis, historical redlining, and current neighborhood characteristics: breast, cervical, lung, and colorectal cancers, Massachusetts, 2001–2015. American journal of epidemiology 2020, 189, 1065– 1075,  DOI: 10.1093/aje/kwaa045
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    Cancer Stage at Diagnosis, Historical Redlining, and Current Neighborhood Characteristics: Breast, Cervical, Lung, and Colorectal Cancers, Massachusetts, 2001-2015
    Krieger Nancy; Wright Emily; Chen Jarvis T; Waterman Pamela D; Huntley Eric R; Arcaya Mariana
    American journal of epidemiology (2020), 189 (10), 1065-1075 ISSN:.
    In the 1930s, maps created by the federal Home Owners' Loan Corporation (HOLC) nationalized residential racial segregation via "redlining," whereby HOLC designated and colored in red areas they deemed to be unsuitable for mortgage lending on account of their Black, foreign-born, or low-income residents. We used the recently digitized HOLC redlining maps for 28 municipalities in Massachusetts to analyze Massachusetts Cancer Registry data for late stage at diagnosis for cervical, breast, lung, and colorectal cancer (2001-2015). Multivariable analyses indicated that, net of age, sex/gender, and race/ethnicity, residing in a previously HOLC-redlined area imposed an elevated risk for late stage at diagnosis, even for residents of census tracts with present-day economic and racial privilege, whereas the best historical HOLC grade was not protective for residents of census tracts without such current privilege. For example, a substantially elevated risk of late stage at diagnosis occurred among men with lung cancer residing in currently privileged areas that had been redlined (risk ratio = 1.17, 95% confidence interval: 1.06, 1.29), whereas such risk was attenuated among men residing in census tracts lacking such current privilege (risk ratio = 1.01, 95% confidence interval: 0.94, 1.08). Research on historical redlining as a structural driver of health inequities is warranted.
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    Mujahid, M. S.; Gao, X.; Tabb, L. P.; Morris, C.; Lewis, T. T. Historical redlining and cardiovascular health: The Multi-Ethnic Study of Atherosclerosis. Proc. Natl. Acad. Sci. U. S. A. 2021, 118, e2110986118  DOI: 10.1073/pnas.2110986118
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    Historical redlining and cardiovascular health: the multi-ethnic study of atherosclerosis
    Mujahid, Mahasin S.; Gao, Xing; Tabb, Loni P.; Morris, Colleen; Lewis, Tene T.
    Proceedings of the National Academy of Sciences of the United States of America (2021), 118 (51), e2110986118CODEN: PNASA6; ISSN:0027-8424. (National Academy of Sciences)
    We investigated historical redlining, a government-sanctioned discriminatory policy, in relation to cardiovascular health (CVH) and whether assocns. were modified by present-day neighborhood phys. and social environments. Data included 4,779 participants (mean age 62 y; SD = 10) from the baseline sample of the Multi-Ethnic Study of Atherosclerosis (MESA; 2000 to 2002). Ideal CVH was a summary measure of ideal levels of seven CVH risk factors based on established criteria (blood pressure, fasting glucose, cholesterol, body mass index, diet, phys. activity, and smoking). We assigned MESA participants' neighborhoods to one of four grades (A: best, B: still desirable, C: declining, and D: hazardous) using the 1930s federal Home Owners' Loan Corporation (HOLC) maps, which guided decisions regarding mortgage financing. Two-level hierarchical linear and logistic models, with a random intercept to account for participants nested within neighborhoods (i.e., census tracts) were used to assess assocns. within racial/ethnic subgroups (non-Hispanic White, non-Hispanic Black, Hispanic, and non-Hispanic Chinese). We found that Black adults who lived in historically redlined areas had a 0.82 (95% CI -1.54, -0.10) lower CVH score compared to those residing in grade A (best) neighborhoods, in a given neighborhood and adjusting for confounders. We also found that as the current neighborhood social environment improved the assocn. between HOLC score and ideal CVH weakened (P < 0.10). There were no assocns. between HOLC grade and CVH measures or effect modification by current neighborhood conditions for any other racial/ethnic group. Results suggest that historical redlining has an enduring impact on cardiovascular risk among Black adults in the United States.
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    Lee, E. K. Health outcomes in redlined versus non-redlined neighborhoods: A systematic review and meta-analysis. Social Science & Medicine 2022, 294, 114696  DOI: 10.1016/j.socscimed.2021.114696
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    Health outcomes in redlined versus non-redlined neighborhoods: A systematic review and meta-analysis
    Lee Eun Kyung; Donley Gwendolyn; Ciesielski Timothy H; Gill India; Yamoah Owusua; Roche Abigail; Martinez Roberto; Freedman Darcy A
    Social science & medicine (1982) (2022), 294 (), 114696 ISSN:.
    BACKGROUND: Redlining was a racialized zoning practice in the U.S. that blocked fair access to home loans during the 1930s, and recent research is illuminating health problems in the current residents of these historically redlined areas. However, this work has not yet been holistically summarized. Here, we present the first systematic review and meta-analysis comparing health outcomes in redlined versus non-redlined neighborhoods in U.S. cities. METHODS: We extracted relevant articles in PubMed, Web of Science, Cochrane and Science Direct databases published from January 2010 to September 2021. RESULTS: The search revealed 12 studies on preterm births (n = 3), gunshot-related injuries (n = 2), cancer (n = 1), asthma (n = 1), self-rated health (n = 1), multiple health outcomes (n = 2), heat-related outcomes (n = 1) and COVID-19 incidence and mortality (n = 1). A meta-analysis of three studies found the odds of having preterm birth was significantly higher (OR = 1.41, 95% CI: 1.05, 1.88; p = 0.02) among women living in redlined areas compared to those in non-redlined areas. Review of other outcomes revealed that gunshot-related injuries, asthma, heat-related outcomes, and multiple chronic conditions were worse in redlined areas, while associations with cancer varied by cancer type. In terms of cause-specific mortality, one study revealed no link between residential redlining and infant mortality rate, while one study on COVID-19 outcomes was inconclusive. CONCLUSIONS: Overall, this review presents evidence that living in historically redlined areas is associated with increased risk of multiple serious adverse health outcomes. Further research on mechanisms, remediation, and neighborhood-level interventions is needed to strengthen the understanding of the impacts of redlining on health.
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    Wood, E. M. Historical racial redlining and contemporary patterns of income inequality negatively affect birds, their habitat, and people in Los Angeles, California. Ornithological Applications 2023, duad044  DOI: 10.1093/ornithapp/duad044
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    Redlining and Lead Poisoning: Causes and Consequences
    Karp Robert J
    Journal of health care for the poor and underserved (2023), 34 (1), 431-446 ISSN:.
    In 1934, the Federal Housing Authority precluded mortgage loans to residents of neighborhoods with non-White families or where housing was deteriorated; these were declared "hazardous" and labeled red on maps. In 1962 three redlined north Brooklyn neighborhoods had 41 children, all Black and Puerto Rican, with lead levels >60ug/dL. A review of public polices in the U.S. from 1898 to the present revealed that lead poisoning followed an income gradient with multiple disproportionate effects on non-White children in redlined neighborhoods. The poisonings diminished when federal and local regulations prevented lead exposure. While redlining had profound influences on both likelihood and severity of lead poisoning and its consequences, it was a mediator of effects. The principal causes were federal policies failing to prevent environmental contamination and local governments failing to prevent exposure.
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    Shkembi, A.; Smith, L. M.; Neitzel, R. L. Linking environmental injustices in Detroit, MI to institutional racial segregation through historical federal redlining. J. Expo Sci. Environ. Epidemiol 2022,  DOI: 10.1038/s41370-022-00512-y
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    Nelson-Olivieri, J. R.; Layden, T. J.; Antunez, E.; Khalighifar, A.; Lasky, M.; Laverty, T. M.; Sanchez, K. A.; Shannon, G.; Starr, S.; Verahrami, A. K.; Bombaci, S. P. Inequalities in noise will affect urban wildlife. Nature Ecology & Evolution 2024, 8, 163– 174,  DOI: 10.1038/s41559-023-02257-9
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    Inequalities in noise will affect urban wildlife
    Nelson-Olivieri Jasmine R; Layden Tamara J; Antunez Edder; Khalighifar Ali; Lasky Monica; Starr Steven; Verahrami Anahita K; Bombaci Sara P; Laverty Theresa M; Sanchez Karina A; Shannon Graeme
    Nature ecology & evolution (2024), 8 (1), 163-174 ISSN:.
    Understanding how systemic biases influence local ecological communities is essential for developing just and equitable environmental practices that prioritize both human and wildlife well-being. With over 270 million residents inhabiting urban areas in the United States, the socioecological consequences of racially targeted zoning, such as redlining, need to be considered in urban planning. There is a growing body of literature documenting the relationships between redlining and the inequitable distribution of environmental harms and goods, green space cover and pollutant exposure. However, it remains unknown whether historical redlining affects the distribution of urban noise or whether inequitable noise drives an ecological change in urban environments. Here we conducted a spatial analysis of how urban noise corresponds to the distribution of redlining categories and a systematic literature review to summarize the effects of noise on wildlife in urban landscapes. We found strong evidence to indicate that noise is inequitably distributed in redlined urban communities across the United States, and that inequitable noise may drive complex biological responses across diverse urban wildlife, reinforcing the interrelatedness of socioecological outcomes. These findings lay a foundation for future research that advances relationships between acoustic and urban ecology through centring equity and challenging systems of oppression in wildlife studies.
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    Nardone, A. Associations between historical residential redlining and current age-adjusted rates of emergency department visits due to asthma across eight cities in California: an ecological study. Lancet Planetary Health 2020, 4, e24– e31,  DOI: 10.1016/S2542-5196(19)30241-4
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    Cole, H. V S; Garcia Lamarca, M.; Connolly, J. J T; Anguelovski, I. Are green cities healthy and equitable? Unpacking the relationship between health, green space and gentrification. J. Epidemiol Community Health 2017, 71, 1118– 1121,  DOI: 10.1136/jech-2017-209201
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    Are green cities healthy and equitable? Unpacking the relationship between health, green space and gentrification
    Cole Helen V S; Garcia Lamarca Melisa; Connolly James J T; Anguelovski Isabelle; Anguelovski Isabelle
    Journal of epidemiology and community health (2017), 71 (11), 1118-1121 ISSN:.
    While access and exposure to green spaces has been shown to be beneficial for the health of urban residents, interventions focused on augmenting such access may also catalyse gentrification processes, also known as green gentrification. Drawing from the fields of public health, urban planning and environmental justice, we argue that public health and epidemiology researchers should rely on a more dynamic model of community that accounts for the potential unintended social consequences of upstream health interventions. In our example of green gentrification, the health benefits of greening can only be fully understood relative to the social and political environments in which inequities persist. We point to two key questions regarding the health benefits of newly added green space: Who benefits in the short and long term from greening interventions in lower income or minority neighbourhoods undergoing processes of revitalisation? And, can green cities be both healthy and just? We propose the Green Gentrification and Health Equity model which provides a framework for understanding and testing whether gentrification associated with green space may modify the effect of exposure to green space on health.
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    Developing Community-Level Policy and Practice to Reduce Traffic-Related Air Pollution Exposure
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    Environmental justice (Print) (2015), 8 (3), 95-104 ISSN:1939-4071.
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    Racial-ethnic disparities in exposure to air pollution in the United States (US) are well documented. Studies on the causes of these disparities highlight unequal systems of power and longstanding systemic racism-for example, redlining, white flight, and racial covenants-which reinforced racial segregation and wealth gaps and which concd. polluting land uses in communities of color. Our anal. is based on empirical ests. of ambient concns. for two important pollutants (NO2 and PM2.5). We show that spatially decompd. concns. can be used to infer and quantify types of root causes for local- to national-scale disparities. Urban-scale segregation is important yet reflects less than half of the overall national disparities. Other historical causes of national exposure disparities include those that led current populations of Black, Asian, and Hispanic Americans to live in larger cities; those outcomes are consistent with, for example, greater economic opportunity in large cities, land-takings from non-White farmers, and racism in homesteading and between-state migration. Our results suggest that contemporary national exposure disparities in the US reflect a broad set of historical local- to national-scale mechanisms-including racist laws and actions that include, but also extend beyond, urban-scale aspects-and offer a first attempt to quantify their relative importance.
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    American journal of public health (2022), 112 (1), 88-97 ISSN:.
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  • Abstract

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    Figure 1

    Figure 1. Redlined neighborhoods have higher environmental hazards than nonredlined neighborhoods. We show (A) pollution burden, (B) noise pollution, (C) vegetation (NDVI*), and (D) temperature across HOLC grades. Pollution burden is a score based on the presence of various environmental hazard (see Methods and Materials). Noise pollution is on a scale of 50–100, with 100 representing a very loud environment. NDVI (i.e., vegetation) is on a scale of −1 to 1, with lower scores representing less vegetation. Black diamonds represent the mean and whiskers represent 95% confidence intervals. *NDVI = Normalized Differentiated Vegetation Index.

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    Figure 2

    Figure 2. Redlined neighborhoods disproportionately face worse intraurban disparities in environmental hazards than nonredlined neighborhoods. Intraurban disparity analysis for (A) overall pollution burden, (B) noise pollution, (C) vegetation (NDVI*), and (D) temperature across HOLC grades. Horizontal zero line represents no difference between the city’s average and a neighborhood’s average environmental hazard. For graphs A–D, values above the line represent a higher environmental hazard value (i.e., higher pollution, more noise, and elevated temperature) than the corresponding cities average. For graph C, values below the line represent less vegetation value than the corresponding cities average. Black diamonds represent the mean and whiskers represent 95% confidence intervals. *NDVI = Normalized Differentiated Vegetation Index.

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      Environmental health researchers, sociologists, policy-makers, and activists concerned about environmental justice argue that communities of color who are segregated in neighborhoods with high levels of poverty and material deprivation are also disproportionately exposed to phys. environments that adversely affect their health and well-being. Examg. these issues through the lens of racial residential segregation can offer new insights into the junctures of the political economy of social inequality with discrimination, environmental degrdn., and health. More importantly, this line of inquiry may highlight whether obsd. pollution-health outcome relationships are modified by segregation and whether segregation patterns impact diverse communities differently. This paper examines theor. and methodol. questions related to racial residential segregation and environmental health disparities. We begin with an overview of race-based segregation in the United States and propose a framework for understanding its implications for environmental health disparities. We then discuss applications of segregation measures for assessing disparities in ambient air pollution burdens across racial groups and go on to discuss the applicability of these methods for other environmental exposures and health outcomes. We conclude with a discussion of the research and policy implications of understanding how racial residential segregation impacts environmental health disparities.
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      Jesdale, B. M.; Morello-Frosch, R.; Cushing, L. The Racial/Ethnic Distribution of Heat Risk–Related Land Cover in Relation to Residential Segregation. Environ. Health Perspect. 2013, 121, 811– 817,  DOI: 10.1289/ehp.1205919
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      The racial/ethnic distribution of heat risk-related land cover in relation to residential segregation
      Jesdale Bill M; Morello-Frosch Rachel; Cushing Lara
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      OBJECTIVE: We examined the distribution of heat risk-related land cover (HRRLC) characteristics across racial/ethnic groups and degrees of residential segregation. METHODS: Block group-level tree canopy and impervious surface estimates were derived from the 2001 National Land Cover Dataset for densely populated urban areas of the United States and Puerto Rico, and linked to demographic characteristics from the 2000 Census. Racial/ethnic groups in a given block group were considered to live in HRRLC if at least half their population experienced the absence of tree canopy and at least half of the ground was covered by impervious surface (roofs, driveways, sidewalks, roads). Residential segregation was characterized for metropolitan areas in the United States and Puerto Rico using the multigroup dissimilarity index. RESULTS: After adjustment for ecoregion and precipitation, holding segregation level constant, non-Hispanic blacks were 52% more likely (95% CI: 37%, 69%), non-Hispanic Asians 32% more likely (95% CI: 18%, 47%), and Hispanics 21% more likely (95% CI: 8%, 35%) to live in HRRLC conditions compared with non-Hispanic whites. Within each racial/ethnic group, HRRLC conditions increased with increasing degrees of metropolitan area-level segregation. Further adjustment for home ownership and poverty did not substantially alter these results, but adjustment for population density and metropolitan area population attenuated the segregation effects, suggesting a mediating or confounding role. CONCLUSIONS: Land cover was associated with segregation within each racial/ethnic group, which may be explained partly by the concentration of racial/ethnic minorities into densely populated neighborhoods within larger, more segregated cities. In anticipation of greater frequency and duration of extreme heat events, climate change adaptation strategies, such as planting trees in urban areas, should explicitly incorporate an environmental justice framework that addresses racial/ethnic disparities in HRRLC.
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      Casey, J. A.; Morello-Frosch, R.; Mennitt, D. J.; Fristrup, K.; Ogburn, E. L.; James, P. Race/ethnicity, socioeconomic status, residential segregation, and spatial variation in noise exposure in the contiguous United States. Environ. Health Perspect. 2017, 125, 077017  DOI: 10.1289/EHP898
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      Race/Ethnicity, Socioeconomic Status, Residential Segregation, and Spatial Variation in Noise Exposure in the Contiguous United States
      Casey Joan A; Morello-Frosch Rachel; Mennitt Daniel J; Fristrup Kurt; Ogburn Elizabeth L; James Peter
      Environmental health perspectives (2017), 125 (7), 077017 ISSN:.
      BACKGROUND: Prior research has reported disparities in environmental exposures in the United States, but, to our knowledge, no nationwide studies have assessed inequality in noise pollution. OBJECTIVES: We aimed to a) assess racial/ethnic and socioeconomic inequalities in noise pollution in the contiguous United States; and b) consider the modifying role of metropolitan level racial residential segregation. METHODS: We used a geospatial sound model to estimate census block group-level median (L50) nighttime and daytime noise exposure and 90th percentile (L10) daytime noise exposure. Block group variables from the 2006-2010 American Community Survey (ACS) included race/ethnicity, education, income, poverty, unemployment, homeownership, and linguistic isolation. We estimated associations using polynomial terms in spatial error models adjusted for total population and population density. We also evaluated the relationship between race/ethnicity and noise, stratified by levels of metropolitan area racial residential segregation, classified using a multigroup dissimilarity index. RESULTS: Generally, estimated nighttime and daytime noise levels were higher for census block groups with higher proportions of nonwhite and lower-socioeconomic status (SES) residents. For example, estimated nighttime noise levels in urban block groups with 75% vs. 0% black residents were 46.3 A-weighted decibels (dBA) [interquartile range (IQR): 44.3-47.8 dBA] and 42.3 dBA (IQR: 40.4-45.5 dBA), respectively. In urban block groups with 50% vs. 0% of residents living below poverty, estimated nighttime noise levels were 46.9 dBA (IQR: 44.7-48.5 dBA) and 44.0 dBA (IQR: 42.2-45.5 dBA), respectively. Block groups with the highest metropolitan area segregation had the highest estimated noise exposures, regardless of racial composition. Results were generally consistent between urban and suburban/rural census block groups, and for daytime and nighttime noise and robust to different spatial weight and neighbor definitions. CONCLUSIONS: We found evidence of racial/ethnic and socioeconomic differences in model-based estimates of noise exposure throughout the United States. Additional research is needed to determine if differences in noise exposure may contribute to health disparities in the United States. https://doi.org/10.1289/EHP898
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    10. 10
      Hillier, A. E. Redlining and the Home Owners’ Loan Corporation. J. Urban Hist. 2003, 29, 394– 420,  DOI: 10.1177/0096144203029004002
      There is no corresponding record for this reference.
    11. 11
      Rothstein, R. The Color of Law: A Forgotten History of How Our Government Segregated America; Liveright Publishing, 2017.
      There is no corresponding record for this reference.
    12. 12
      Fishback, P.; Rose, J.; Snowden, K. A.; Storrs, T. New Evidence on Redlining by Federal Housing Programs in the 1930s. J. Urban Econ. 2022, 103462  DOI: 10.1016/j.jue.2022.103462
      There is no corresponding record for this reference.
    13. 13
      Nelson, R. K.; Winling, L.; Marciano, R.; Connolly, N.; Ayers, E. L. Mapping Inequality: Redlining in new deal America; American Panorama: An Atlas of United States History; University of Richmond, Digital Scholarship Lab, 2020.
      There is no corresponding record for this reference.
    14. 14
      Swope, C. B.; Hernández, D.; Cushing, L. J. The Relationship of Historical Redlining with Present-Day Neighborhood Environmental and Health Outcomes: A Scoping Review and Conceptual Model. J. Urban Health 2022, 99, 959– 983,  DOI: 10.1007/s11524-022-00665-z
      14
      The Relationship of Historical Redlining with Present-Day Neighborhood Environmental and Health Outcomes: A Scoping Review and Conceptual Model
      Swope Carolyn B; Hernandez Diana; Cushing Lara J
      Journal of urban health : bulletin of the New York Academy of Medicine (2022), 99 (6), 959-983 ISSN:.
      Following the Great Depression and related home foreclosures, the federal government established new agencies to facilitate access to affordable home mortgages, including the Home Owners' Loan Corporation (HOLC) and Federal Housing Administration (FHA). HOLC and FHA directed widespread neighborhood appraisals to determine investment risk, referred to as "redlining," which took into account residents' race. Redlining thereby contributed to segregation, disinvestment, and racial inequities in opportunities for homeownership and wealth accumulation. Recent research examines associations between historical redlining and subsequent environmental determinants of health and health-related outcomes. In this scoping review, we assess the extent of the current body of evidence, the range of outcomes studied, and key study characteristics, examining the direction and strength of the relationship between redlining, neighborhood environments, and health as well as different methodological approaches. Overall, studies nearly universally report evidence of an association between redlining and health-relevant outcomes, although heterogeneity in study design precludes direct comparison of results. We critically consider evidence regarding HOLC's causality and offer a conceptual framework for the relationship between redlining and present-day health. Finally, we point to key directions for future research to improve and broaden understanding of redlining's enduring impact and translate findings into public health and planning practice.
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    15. 15
      Lane, H. M.; Morello-Frosch, R.; Marshall, J. D.; Apte, J. S. Historical Redlining Is Associated with Present-Day Air Pollution Disparities in U.S. Cities. Environ. Sci. Technol. Lett. 2022, 9, 345– 350,  DOI: 10.1021/acs.estlett.1c01012
      15
      Historical Redlining Is Associated with Present-Day Air Pollution Disparities in U.S. Cities
      Lane, Haley M.; Morello-Frosch, Rachel; Marshall, Julian D.; Apte, Joshua S.
      Environmental Science & Technology Letters (2022), 9 (4), 345-350CODEN: ESTLCU; ISSN:2328-8930. (American Chemical Society)
      Communities of color in the United States are systematically exposed to higher levels of air pollution. We explore here how redlining, a discriminatory mortgage appraisal practice from the 1930s by the federal Home Owners' Loan Corporation (HOLC), relates to present-day intraurban air pollution disparities in 202 U.S. cities. In each city, we integrated three sources of data: (1) detailed HOLC security maps of investment risk grades [A ("best"), B, C, and D ("hazardous", i.e., redlined)], (2) year-2010 ests. of NO2 and PM2.5 air pollution levels, and (3) demog. information from the 2010 U.S. census. We find that pollution levels have a consistent and nearly monotonic assocn. with HOLC grade, with esp. pronounced (>50%) increments in NO2 levels between the most (grade A) and least (grade D) preferentially graded neighborhoods. On a national basis, intraurban disparities for NO2 and PM2.5 are substantially larger by historical HOLC grade than they are by race and ethnicity. However, within each HOLC grade, racial and ethnic air pollution exposure disparities persist, indicating that redlining was only one of the many racially discriminatory policies that impacted communities. Our findings illustrate how redlining, a nearly 80-yr-old racially discriminatory policy, continues to shape systemic environmental exposure disparities in the United States.
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    16. 16
      Cushing, L. J.; Li, S.; Steiger, B. B.; Casey, J. A. Historical red-lining is associated with fossil fuel power plant siting and present-day inequalities in air pollutant emissions. Nat. Energy 2023, 8, 52– 61,  DOI: 10.1038/s41560-022-01162-y
      There is no corresponding record for this reference.
    17. 17
      Nardone, A.; Chiang, J.; Corburn, J. Historic Redlining and Urban Health Today in U.S. Cities. Environ. Justice 2020, 13, 109– 119,  DOI: 10.1089/env.2020.0011
      There is no corresponding record for this reference.
    18. 18
      Hoffman, J. S.; Shandas, V.; Pendleton, N. The Effects of Historical Housing Policies on Resident Exposure to Intra-Urban Heat: A Study of 108 US Urban Areas. Climate 2020, 8, 12,  DOI: 10.3390/cli8010012
      There is no corresponding record for this reference.
    19. 19
      Krieger, N. Cancer stage at diagnosis, historical redlining, and current neighborhood characteristics: breast, cervical, lung, and colorectal cancers, Massachusetts, 2001–2015. American journal of epidemiology 2020, 189, 1065– 1075,  DOI: 10.1093/aje/kwaa045
      19
      Cancer Stage at Diagnosis, Historical Redlining, and Current Neighborhood Characteristics: Breast, Cervical, Lung, and Colorectal Cancers, Massachusetts, 2001-2015
      Krieger Nancy; Wright Emily; Chen Jarvis T; Waterman Pamela D; Huntley Eric R; Arcaya Mariana
      American journal of epidemiology (2020), 189 (10), 1065-1075 ISSN:.
      In the 1930s, maps created by the federal Home Owners' Loan Corporation (HOLC) nationalized residential racial segregation via "redlining," whereby HOLC designated and colored in red areas they deemed to be unsuitable for mortgage lending on account of their Black, foreign-born, or low-income residents. We used the recently digitized HOLC redlining maps for 28 municipalities in Massachusetts to analyze Massachusetts Cancer Registry data for late stage at diagnosis for cervical, breast, lung, and colorectal cancer (2001-2015). Multivariable analyses indicated that, net of age, sex/gender, and race/ethnicity, residing in a previously HOLC-redlined area imposed an elevated risk for late stage at diagnosis, even for residents of census tracts with present-day economic and racial privilege, whereas the best historical HOLC grade was not protective for residents of census tracts without such current privilege. For example, a substantially elevated risk of late stage at diagnosis occurred among men with lung cancer residing in currently privileged areas that had been redlined (risk ratio = 1.17, 95% confidence interval: 1.06, 1.29), whereas such risk was attenuated among men residing in census tracts lacking such current privilege (risk ratio = 1.01, 95% confidence interval: 0.94, 1.08). Research on historical redlining as a structural driver of health inequities is warranted.
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    20. 20
      Mujahid, M. S.; Gao, X.; Tabb, L. P.; Morris, C.; Lewis, T. T. Historical redlining and cardiovascular health: The Multi-Ethnic Study of Atherosclerosis. Proc. Natl. Acad. Sci. U. S. A. 2021, 118, e2110986118  DOI: 10.1073/pnas.2110986118
      20
      Historical redlining and cardiovascular health: the multi-ethnic study of atherosclerosis
      Mujahid, Mahasin S.; Gao, Xing; Tabb, Loni P.; Morris, Colleen; Lewis, Tene T.
      Proceedings of the National Academy of Sciences of the United States of America (2021), 118 (51), e2110986118CODEN: PNASA6; ISSN:0027-8424. (National Academy of Sciences)
      We investigated historical redlining, a government-sanctioned discriminatory policy, in relation to cardiovascular health (CVH) and whether assocns. were modified by present-day neighborhood phys. and social environments. Data included 4,779 participants (mean age 62 y; SD = 10) from the baseline sample of the Multi-Ethnic Study of Atherosclerosis (MESA; 2000 to 2002). Ideal CVH was a summary measure of ideal levels of seven CVH risk factors based on established criteria (blood pressure, fasting glucose, cholesterol, body mass index, diet, phys. activity, and smoking). We assigned MESA participants' neighborhoods to one of four grades (A: best, B: still desirable, C: declining, and D: hazardous) using the 1930s federal Home Owners' Loan Corporation (HOLC) maps, which guided decisions regarding mortgage financing. Two-level hierarchical linear and logistic models, with a random intercept to account for participants nested within neighborhoods (i.e., census tracts) were used to assess assocns. within racial/ethnic subgroups (non-Hispanic White, non-Hispanic Black, Hispanic, and non-Hispanic Chinese). We found that Black adults who lived in historically redlined areas had a 0.82 (95% CI -1.54, -0.10) lower CVH score compared to those residing in grade A (best) neighborhoods, in a given neighborhood and adjusting for confounders. We also found that as the current neighborhood social environment improved the assocn. between HOLC score and ideal CVH weakened (P < 0.10). There were no assocns. between HOLC grade and CVH measures or effect modification by current neighborhood conditions for any other racial/ethnic group. Results suggest that historical redlining has an enduring impact on cardiovascular risk among Black adults in the United States.
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    21. 21
      Lee, E. K. Health outcomes in redlined versus non-redlined neighborhoods: A systematic review and meta-analysis. Social Science & Medicine 2022, 294, 114696  DOI: 10.1016/j.socscimed.2021.114696
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      Health outcomes in redlined versus non-redlined neighborhoods: A systematic review and meta-analysis
      Lee Eun Kyung; Donley Gwendolyn; Ciesielski Timothy H; Gill India; Yamoah Owusua; Roche Abigail; Martinez Roberto; Freedman Darcy A
      Social science & medicine (1982) (2022), 294 (), 114696 ISSN:.
      BACKGROUND: Redlining was a racialized zoning practice in the U.S. that blocked fair access to home loans during the 1930s, and recent research is illuminating health problems in the current residents of these historically redlined areas. However, this work has not yet been holistically summarized. Here, we present the first systematic review and meta-analysis comparing health outcomes in redlined versus non-redlined neighborhoods in U.S. cities. METHODS: We extracted relevant articles in PubMed, Web of Science, Cochrane and Science Direct databases published from January 2010 to September 2021. RESULTS: The search revealed 12 studies on preterm births (n = 3), gunshot-related injuries (n = 2), cancer (n = 1), asthma (n = 1), self-rated health (n = 1), multiple health outcomes (n = 2), heat-related outcomes (n = 1) and COVID-19 incidence and mortality (n = 1). A meta-analysis of three studies found the odds of having preterm birth was significantly higher (OR = 1.41, 95% CI: 1.05, 1.88; p = 0.02) among women living in redlined areas compared to those in non-redlined areas. Review of other outcomes revealed that gunshot-related injuries, asthma, heat-related outcomes, and multiple chronic conditions were worse in redlined areas, while associations with cancer varied by cancer type. In terms of cause-specific mortality, one study revealed no link between residential redlining and infant mortality rate, while one study on COVID-19 outcomes was inconclusive. CONCLUSIONS: Overall, this review presents evidence that living in historically redlined areas is associated with increased risk of multiple serious adverse health outcomes. Further research on mechanisms, remediation, and neighborhood-level interventions is needed to strengthen the understanding of the impacts of redlining on health.
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    22. 22
      Wood, E. M. Historical racial redlining and contemporary patterns of income inequality negatively affect birds, their habitat, and people in Los Angeles, California. Ornithological Applications 2023, duad044  DOI: 10.1093/ornithapp/duad044
      There is no corresponding record for this reference.
    23. 23
      Estien, C. O.; Fidino, M.; Wilkinson, C. E.; Morello-Frosch, R.; Schell, C. J. Historical redlining impacts wildlife biodiversity across California. EcoEvoRxiv Preprint , 2023.  DOI: 10.32942/X24K60 .
      There is no corresponding record for this reference.
    24. 24
      Atlas, R. M. One Health: Its Origins and Future. In One Health: The Human-Animal-Environment Interfaces in Emerging Infectious Diseases: The Concept and Examples of a One Health Approach; Mackenzie, J. S., Jeggo, M., Daszak, P., Richt, J. A., Eds.; Springer, 2013; pp 1– 13.  DOI: 10.1007/82_2012_223 .
      There is no corresponding record for this reference.
    25. 25
      Murray, M. H. One Health for All: Advancing Human and Ecosystem Health in Cities by Integrating an Environmental Justice Lens. Annu. Rev. Ecol. Evol. Syst. 2022, 53, 403– 426,  DOI: 10.1146/annurev-ecolsys-102220-031745
      There is no corresponding record for this reference.
    26. 26
      Locke, D. H.; Hall, B.; Grove, J. M.; Pickett, S. T. A.; Ogden, L. A.; Aoki, C.; Boone, C. G.; O’Neil-Dunne, J. P. M. Residential housing segregation and urban tree canopy in 37 US Cities. npj Urban Sustain 2021, 1, 1– 9,  DOI: 10.1038/s42949-021-00022-0
      There is no corresponding record for this reference.
    27. 27
      Annual Estimates of the Resident Population for the United States, Regions, States, District of Columbia, and Puerto Rico: April 1, 2020 to July 1, 2022, NST-EST2022-POP. U.S. Census Bureau. https://www.census.gov/data/tables/time-series/demo/popest/2020s-state-total.html (accessed 2023–11–29).
      There is no corresponding record for this reference.
    28. 28
      The 300 Largest Cities in the United States by Population, 2023. World Population Review https://worldpopulationreview.com/us-cities (accessed 2023–11–29).
      There is no corresponding record for this reference.
    29. 29
      CalEnviroScreen 4.0. California Office of Environmental Health Hazard Assessment. https://oehha.ca.gov/calenviroscreen/report/draft-calenviroscreen-40 (accessed 2023–11–29).
      There is no corresponding record for this reference.
    30. 30
      Pollution and Prejudice, ArcGIS StoryMaps. California Environmental Protection Agency. https://storymaps.arcgis.com/stories/f167b251809c43778a2f9f040f43d2f5 (accessed 2023–11–29).
      There is no corresponding record for this reference.
    31. 31
      R: A language and environment for statistical computing, Supplemental Information References; R Core Team, 2021
      There is no corresponding record for this reference.
    32. 32
      Magnusson, A. Package ‘glmmTMB’, R Package Version 0.2.0, 2017.
      There is no corresponding record for this reference.
    33. 33
      Karp, R. J. Redlining and Lead Poisoning: Causes and Consequences. Journal of Health Care for the Poor and Underserved 2023, 34, 431– 446,  DOI: 10.1353/hpu.2023.0028
      33
      Redlining and Lead Poisoning: Causes and Consequences
      Karp Robert J
      Journal of health care for the poor and underserved (2023), 34 (1), 431-446 ISSN:.
      In 1934, the Federal Housing Authority precluded mortgage loans to residents of neighborhoods with non-White families or where housing was deteriorated; these were declared "hazardous" and labeled red on maps. In 1962 three redlined north Brooklyn neighborhoods had 41 children, all Black and Puerto Rican, with lead levels >60ug/dL. A review of public polices in the U.S. from 1898 to the present revealed that lead poisoning followed an income gradient with multiple disproportionate effects on non-White children in redlined neighborhoods. The poisonings diminished when federal and local regulations prevented lead exposure. While redlining had profound influences on both likelihood and severity of lead poisoning and its consequences, it was a mediator of effects. The principal causes were federal policies failing to prevent environmental contamination and local governments failing to prevent exposure.
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    34. 34
      Shkembi, A.; Smith, L. M.; Neitzel, R. L. Linking environmental injustices in Detroit, MI to institutional racial segregation through historical federal redlining. J. Expo Sci. Environ. Epidemiol 2022,  DOI: 10.1038/s41370-022-00512-y
      There is no corresponding record for this reference.
    35. 35
      Nelson-Olivieri, J. R.; Layden, T. J.; Antunez, E.; Khalighifar, A.; Lasky, M.; Laverty, T. M.; Sanchez, K. A.; Shannon, G.; Starr, S.; Verahrami, A. K.; Bombaci, S. P. Inequalities in noise will affect urban wildlife. Nature Ecology & Evolution 2024, 8, 163– 174,  DOI: 10.1038/s41559-023-02257-9
      35
      Inequalities in noise will affect urban wildlife
      Nelson-Olivieri Jasmine R; Layden Tamara J; Antunez Edder; Khalighifar Ali; Lasky Monica; Starr Steven; Verahrami Anahita K; Bombaci Sara P; Laverty Theresa M; Sanchez Karina A; Shannon Graeme
      Nature ecology & evolution (2024), 8 (1), 163-174 ISSN:.
      Understanding how systemic biases influence local ecological communities is essential for developing just and equitable environmental practices that prioritize both human and wildlife well-being. With over 270 million residents inhabiting urban areas in the United States, the socioecological consequences of racially targeted zoning, such as redlining, need to be considered in urban planning. There is a growing body of literature documenting the relationships between redlining and the inequitable distribution of environmental harms and goods, green space cover and pollutant exposure. However, it remains unknown whether historical redlining affects the distribution of urban noise or whether inequitable noise drives an ecological change in urban environments. Here we conducted a spatial analysis of how urban noise corresponds to the distribution of redlining categories and a systematic literature review to summarize the effects of noise on wildlife in urban landscapes. We found strong evidence to indicate that noise is inequitably distributed in redlined urban communities across the United States, and that inequitable noise may drive complex biological responses across diverse urban wildlife, reinforcing the interrelatedness of socioecological outcomes. These findings lay a foundation for future research that advances relationships between acoustic and urban ecology through centring equity and challenging systems of oppression in wildlife studies.
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    36. 36
      Nardone, A. Associations between historical residential redlining and current age-adjusted rates of emergency department visits due to asthma across eight cities in California: an ecological study. Lancet Planetary Health 2020, 4, e24– e31,  DOI: 10.1016/S2542-5196(19)30241-4
      There is no corresponding record for this reference.
    37. 37
      Angel, S.; Parent, J.; Civco, D. L.; Blei, A. M. Making Room for a Planet of Cities; Lincoln Institute of Land Policy, 2011.
      There is no corresponding record for this reference.
    38. 38
      Kwak, N. H. Anti-gentrification campaigns and the fight for local control in California cities. New Global Studies 2018, 12, 9– 20,  DOI: 10.1515/ngs-2018-0008
      There is no corresponding record for this reference.
    39. 39
      Cole, H. V S; Garcia Lamarca, M.; Connolly, J. J T; Anguelovski, I. Are green cities healthy and equitable? Unpacking the relationship between health, green space and gentrification. J. Epidemiol Community Health 2017, 71, 1118– 1121,  DOI: 10.1136/jech-2017-209201
      39
      Are green cities healthy and equitable? Unpacking the relationship between health, green space and gentrification
      Cole Helen V S; Garcia Lamarca Melisa; Connolly James J T; Anguelovski Isabelle; Anguelovski Isabelle
      Journal of epidemiology and community health (2017), 71 (11), 1118-1121 ISSN:.
      While access and exposure to green spaces has been shown to be beneficial for the health of urban residents, interventions focused on augmenting such access may also catalyse gentrification processes, also known as green gentrification. Drawing from the fields of public health, urban planning and environmental justice, we argue that public health and epidemiology researchers should rely on a more dynamic model of community that accounts for the potential unintended social consequences of upstream health interventions. In our example of green gentrification, the health benefits of greening can only be fully understood relative to the social and political environments in which inequities persist. We point to two key questions regarding the health benefits of newly added green space: Who benefits in the short and long term from greening interventions in lower income or minority neighbourhoods undergoing processes of revitalisation? And, can green cities be both healthy and just? We propose the Green Gentrification and Health Equity model which provides a framework for understanding and testing whether gentrification associated with green space may modify the effect of exposure to green space on health.
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    40. 40
      Brugge, D. Developing Community-Level Policy and Practice to Reduce Traffic-Related Air Pollution Exposure. Environmental Justice 2015, 8, 95– 104,  DOI: 10.1089/env.2015.0007
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      Developing Community-Level Policy and Practice to Reduce Traffic-Related Air Pollution Exposure
      Brugge Doug; Bright Oliver-John M; Patton Allison P; Durant John L; Bob Alex; Reisner Ellin; Zamore Wig; Lowe Lydia; Newman Jim
      Environmental justice (Print) (2015), 8 (3), 95-104 ISSN:1939-4071.
      The literature consistently shows associations of adverse cardiovascular and pulmonary outcomes with residential proximity to highways and major roadways. Air monitoring shows that traffic-related pollutants (TRAP) are elevated within 200-400 m of these roads. Community-level tactics for reducing exposure include the following: 1) HEPA filtration; 2) Appropriate air-intake locations; 3) Sound proofing, insulation and other features; 4) Land-use buffers; 5) Vegetation or wall barriers; 6) Street-side trees, hedges and vegetation; 7) Decking over highways; 8) Urban design including placement of buildings; 9) Garden and park locations; and 10) Active travel locations, including bicycling and walking paths. A multidisciplinary design charrette was held to test the feasibility of incorporating these tactics into near-highway housing and school developments that were in the planning stages. The resulting designs successfully utilized many of the protective tactics and also led to engagement with the designers and developers of the sites. There is a need to increase awareness of TRAP in terms of building design and urban planning.
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    41. 41
      Ow, L. F.; Ghosh, S. Urban cities and road traffic noise: Reduction through vegetation. Applied Acoustics 2017, 120, 15– 20,  DOI: 10.1016/j.apacoust.2017.01.007
      There is no corresponding record for this reference.
    42. 42
      Olsen, J. South Central Fresno Community Emissions Reduction Program 2021 Annual Report; San Joaquin Valley Air Pollution Control District , 2021.
      There is no corresponding record for this reference.
    43. 43
      Liu, J.; Marshall, J. D. Spatial Decomposition of Air Pollution Concentrations Highlights Historical Causes for Current Exposure Disparities in the United States. Environ. Sci. Technol. Lett. 2023, 10, 280– 286,  DOI: 10.1021/acs.estlett.2c00826
      43
      Spatial Decomposition of Air Pollution Concentrations Highlights Historical Causes for Current Exposure Disparities in the United States
      Liu, Jiawen; Marshall, Julian D.
      Environmental Science & Technology Letters (2023), 10 (3), 280-286CODEN: ESTLCU; ISSN:2328-8930. (American Chemical Society)
      Racial-ethnic disparities in exposure to air pollution in the United States (US) are well documented. Studies on the causes of these disparities highlight unequal systems of power and longstanding systemic racism-for example, redlining, white flight, and racial covenants-which reinforced racial segregation and wealth gaps and which concd. polluting land uses in communities of color. Our anal. is based on empirical ests. of ambient concns. for two important pollutants (NO2 and PM2.5). We show that spatially decompd. concns. can be used to infer and quantify types of root causes for local- to national-scale disparities. Urban-scale segregation is important yet reflects less than half of the overall national disparities. Other historical causes of national exposure disparities include those that led current populations of Black, Asian, and Hispanic Americans to live in larger cities; those outcomes are consistent with, for example, greater economic opportunity in large cities, land-takings from non-White farmers, and racism in homesteading and between-state migration. Our results suggest that contemporary national exposure disparities in the US reflect a broad set of historical local- to national-scale mechanisms-including racist laws and actions that include, but also extend beyond, urban-scale aspects-and offer a first attempt to quantify their relative importance.
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    44. 44
      Clark, L. P.; Harris, M. H.; Apte, J. S.; Marshall, J. D. National and Intraurban Air Pollution Exposure Disparity Estimates in the United States: Impact of Data-Aggregation Spatial Scale. Environ. Sci. Technol. Lett. 2022, 9, 786– 791,  DOI: 10.1021/acs.estlett.2c00403
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      National and Intraurban Air Pollution Exposure Disparity Estimates in the United States: Impact of Data-Aggregation Spatial Scale
      Clark, Lara P.; Harris, Maria H.; Apte, Joshua S.; Marshall, Julian D.
      Environmental Science & Technology Letters (2022), 9 (9), 786-791CODEN: ESTLCU; ISSN:2328-8930. (American Chemical Society)
      Air pollution exposure disparities by race/ethnicity and socioeconomic status have been analyzed using data aggregated at various spatial scales. Our research question is this: To what extent does the spatial scale of data aggregation impact the estd. exposure disparities. We compared disparities calcd. using data spatially aggregated at five administrative scales (state, county, census tract, census block group, census block) in the contiguous United States in 2010. Specifically, for each of the five spatial scales, we calcd. national and intraurban disparities in exposure to fine particles (PM2.5) and nitrogen dioxide (NO2) by race/ethnicity and socioeconomic characteristics using census demog. data and an empirical statistical air pollution model aggregated at that scale. We found, for both pollutants, that national disparity ests. based on state and county scale data often substantially underestimated those estd. using tract and finer scales; in contrast, national disparity ests. were generally consistent using tract, block group, and block scale data. Similarly, intraurban disparity ests. based on tract and finer scale data were generally well correlated for both pollutants across urban areas, although in some cases intraurban disparity ests. were substantially different, with tract scale data more frequently leading to underestimates of disparities compared to finer scale analyses.
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    45. 45
      Hu, G.; Feng, K.; Sun, L. Multiscale Analysis of the Relationship between Toxic Chemical Hazard Risks and Racial/Ethnic and Socioeconomic Groups in Texas, USA. Environ. Sci. Technol. 2023, 57, 2019– 2030,  DOI: 10.1021/acs.est.2c04302
      45
      Multiscale Analysis of the Relationship between Toxic Chemical Hazard Risks and Racial/Ethnic and Socioeconomic Groups in Texas, USA
      Hu, Guangxiao; Feng, Kuishuang; Sun, Laixiang
      Environmental Science & Technology (2023), 57 (5), 2019-2030CODEN: ESTHAG; ISSN:1520-5851. (American Chemical Society)
      Although quant. environmental (in)justice research demonstrates a disproportionate burden of toxic chem. hazard risks among racial/ethnic minorities and people in low socioeconomic positions, limited knowledge exists on how racial/ethnic and socioeconomic groups across geog. spaces experience toxic chem. hazards. This study analyzed the spatial non-stationarity in the assocns. between toxic chem. hazard risk and community characteristics of census block groups in Texas, USA, for 2017 using a multiscale geog. weighted regression. The results showed that the percentage of Black or Asian population has significant pos. assocns. with toxic risk across block groups in Texas, meaning that racial minorities suffered more from toxic risk wherever they are located in the state. By contrast, the percentage of Hispanic or Latino has a pos. relationship with toxic risk, and the relationship varies locally and is only significant in eastern areas of Texas. Statistical assocns. between toxic risk and socioeconomic variables are not stationary across the state, showing sub-state patterns of spatial variation in terms of the sign, significant level, and magnitude of the coeff. Income has a significant neg. assocn. with toxic risk around the Dallas-Fort Worth-Arlington Metropolitan Statistical Area. Proportions of people without high school diploma and the unemployment rate both have pos. relationships with toxic risk in the eastern area of Texas. Our findings highlight the importance of identifying the spatial patterns of the assocn. between toxic chem. hazard risks and community characteristics at the census block group level for addressing environmental inequality.
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    46. 46
      Liddie, J. M.; Schaider, L. A.; Sunderland, E. M. Sociodemographic Factors Are Associated with the Abundance of PFAS Sources and Detection in U.S. Community Water Systems. Environ. Sci. Technol. 2023, 57, 7902– 7912,  DOI: 10.1021/acs.est.2c07255
      46
      Sociodemographic Factors Are Associated with the Abundance of PFAS Sources and Detection in U.S. Community Water Systems
      Liddie, Jahred M.; Schaider, Laurel A.; Sunderland, Elsie M.
      Environmental Science & Technology (2023), 57 (21), 7902-7912CODEN: ESTHAG; ISSN:1520-5851. (American Chemical Society)
      Drinking water contaminated by per- and polyfluoroalkyl substances (PFAS) is a widespread public health concern, and exposure-response relationships are known to vary across sociodemog. groups. However, research on disparities in drinking water PFAS exposures and the siting of PFAS sources in marginalized communities is limited. Here, we use monitoring data from 7873 U.S. community water systems (CWS) in 18 states to show that PFAS detection is pos. assocd. with the no. of PFAS sources and proportions of people of color who are served by these water systems. Each addnl. industrial facility, military fire training area, and airport in a CWS watershed was assocd. with a 10-108% increase in perfluorooctanoic acid and a 20-34% increase in perfluorooctane sulfonic acid in drinking water. Waste sector sources were also significantly assocd. with drinking water PFAS concns. CWS watersheds with PFAS sources served higher proportions of Hispanic/Latino and non-Hispanic Black residents compared to those without PFAS sources. CWS serving higher proportions of Hispanic/Latino and non-Hispanic Black residents had significantly increased odds of detecting several PFAS. This likely reflects disparities in the siting of PFAS contamination sources. Results of this work suggest that addressing environmental justice concerns should be a component of risk mitigation planning for areas affected by drinking water PFAS contamination.
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    47. 47
      Gonzalez, D. J. X.; Nardone, A.; Nguyen, A. V.; Morello-Frosch, R.; Casey, J. A. Historic redlining and the siting of oil and gas wells in the United States. J. Expo. Sci. Environ. Epidemiol. 2023, 33, 76– 83,  DOI: 10.1038/s41370-022-00434-9
      47
      Historic redlining and the siting of oil and gas wells in the United States
      Gonzalez, David J. X.; Nardone, Anthony; Nguyen, Andrew V.; Morello-Frosch, Rachel; Casey, Joan A.
      Journal of Exposure Science & Environmental Epidemiology (2023), 33 (1), 76-83CODEN: JESEBS; ISSN:1559-0631. (Nature Portfolio)
      Abstr.: Background: The presence of active or inactive (i.e., postprodn.) oil and gas wells in neighborhoods may contribute to ongoing pollution. Racially discriminatory neighborhood security maps developed by the Home-Owners Loan Corporation (HOLC) in the 1930s may contribute to environmental exposure disparities. Objective: To det. whether receiving worse HOLC grades was assocd. with exposure to more oil and gas wells. Methods: We assessed exposure to oil and gas wells among HOLC-graded neighborhoods in 33 cities from 13 states where urban oil and gas wells were drilled and operated. Among the 17 cities for which 1940 census data were available, we used propensity score restriction and matching to compare well exposure neighborhoods that were similar on obsd. 1940 sociodemog. characteristics but that received different grades. Results: Across all included cities, redlined D-graded neighborhoods had 12.2 ± 27.2 wells km-2, nearly twice the d. in neighborhoods graded A (6.8 ± 8.9 wells km-2). In propensity score restricted and matched analyses, redlined neighborhoods had 2.0 (1.3, 2.7) more wells than comparable neighborhoods with a better grade. Significance: Our study adds to the evidence that structural racism in federal policy is assocd. with the disproportionate siting of oil and gas wells in marginalized neighborhoods.
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    48. 48
      Pace, C. Inequities in Drinking Water Quality Among Domestic Well Communities and Community Water Systems, California, 2011–2019. Am. J. Public Health 2022, 112, 88– 97,  DOI: 10.2105/AJPH.2021.306561
      48
      Inequities in Drinking Water Quality Among Domestic Well Communities and Community Water Systems, California, 2011-2019
      Pace Clare; Balazs Carolina; Bangia Komal; Depsky Nicholas; Renteria Adriana; Morello-Frosch Rachel; Cushing Lara J
      American journal of public health (2022), 112 (1), 88-97 ISSN:.
      Objectives. To evaluate universal access to clean drinking water by characterizing relationships between community sociodemographics and water contaminants in California domestic well areas (DWAs) and community water systems (CWSs). Methods. We integrated domestic well locations, CWS service boundaries, residential parcels, building footprints, and 2013-2017 American Community Survey data to estimate sociodemographic characteristics for DWAs and CWSs statewide. We derived mean drinking and groundwater contaminant concentrations of arsenic, nitrate, and hexavalent chromium (Cr[VI]) between 2011 and 2019 and used multivariate models to estimate relationships between sociodemographic variables and contaminant concentrations. Results. We estimated that more than 1.3 million Californians (3.4%) use domestic wells and more than 370 000 Californians rely on drinking water with average contaminant concentrations at or above regulatory standards for 1 or more of the contaminants considered. Higher proportions of people of color were associated with greater drinking water contamination. Conclusions. Poor water quality disproportionately impacts communities of color in California, with the highest estimated arsenic, nitrate, and Cr(VI) concentrations in areas of domestic well use. Domestic well communities must be included in efforts to achieve California's Human Right to Water. (Am J Public Health. 2022;112(1):88-97. https://doi.org/10.2105/AJPH.2021.306561).
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      https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A280%3ADC%252BB2cbovVykug%253D%253D&md5=190a4fff25ed6af4eee9c828fa3909a7
    49. 49
      Mejía-Duwan, J.; Hino, M.; Mach, K. J. Emissions redistribution and environmental justice implications of California’s clean vehicle rebate project. PLOS Climate 2023, 2, e0000183  DOI: 10.1371/journal.pclm.0000183
      There is no corresponding record for this reference.
    50. 50
      Justice40 Initiative, Environmental Justice. The White House. https://www.whitehouse.gov/environmentaljustice/justice40/ (accessed 2023–11–29).
      There is no corresponding record for this reference.

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