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. 2022 Mar 9;9(4):345–350. doi: 10.1021/acs.estlett.1c01012

Historical Redlining Is Associated with Present-Day Air Pollution Disparities in U.S. Cities

Haley M Lane †, Rachel Morello-Frosch ‡,§, Julian D Marshall ∥, Joshua S Apte †,‡,*
PMCID: PMC9009174  PMID: 35434171

Abstract

graphic file with name ez1c01012_0003.jpg

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 estimates of NO2 and PM2.5 air pollution levels, and (3) demographic information from the 2010 U.S. census. We find that pollution levels have a consistent and nearly monotonic association with HOLC grade, with especially 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-year-old racially discriminatory policy, continues to shape systemic environmental exposure disparities in the United States.

Keywords: air pollution, redlining, NO2, PM2.5

Introduction

In the United States, communities of color are exposed to higher levels of air pollution at every income level.1−4 As with other environmental justice (EJ) issues, the causes of systemic racial/ethnic air pollution exposure disparities are complex and rooted in part in historical patterns of exclusion and discrimination. While air quality has improved in the United States over the past several decades,5−7 people of color (POC), particularly Black and Hispanic Americans, are still exposed to higher-than-average levels of air pollution.8−11 We examine here how redlining, a historical, racially discriminatory 1930s federal mortgage appraisal policy, is associated with present-day air pollution disparities in 202 U.S. cities.

Racial/ethnic air pollution exposure disparities persist in part because the underlying sociological, economic, and policy drivers typically evolve on generational time scales. Multiple legacies of discrimination, including redlining and land use decision-making, have shaped the current spatial distributions of pollution sources among diverse communities.12−18 The resulting locations of emissions infrastructure, including roads, rail lines, industrial facilities, ports, and other major sources of pollution, are typically long-lived. Similarly, while housing discrimination was deemed unconstitutional more than 50 years ago, many areas in the United States remain racially segregated.19−22

Redlining has emerged as an area of interest because it is well documented and was explicit in its discriminatory implementation, widespread, and carried out by the federal government. Beginning in the 1930s, the federally sponsored Home Owners’ Loan Corporation (HOLC) drew maps characterizing neighborhood security for emergency home lending for several hundred U.S. cities in the wake of the Great Depression.23,24 These maps, which are digitized for 202 U.S. cities,25 graded neighborhoods on a four-point scale: A (most desirable), B (still desirable), C (definitely declining), and D (hazardous, i.e., redlined). Many neighborhoods received the worst grade due to the presence of Black and immigrant communities and/or known environmental pollution sources.25,26 For example, racist language provided to HOLC agents describes “infiltration of foreign-born, Negro, or lower-grade population” as cause for a lower neighborhood grade.25 Homes in D neighborhoods were typically ineligible for federally backed loans or favorable mortgage terms. This practice isolated communities of color, restricting their ability to build wealth through home ownership, and informed later local government land use decisions that placed hazardous industries in and near D neighborhoods.24 The discriminatory practices captured by the HOLC maps continued until 1968, when the Fair Housing Act banned racial discrimination in housing, yet the legacy of explicit racial discrimination still shapes patterns of racial residential segregation today.27

A growing body of scholarship finds associations between redlining and present-day environmental health disparities in U.S. cities. For example, in 64% of grade D neighborhoods, a majority (>50%) of the population is POC (i.e., not non-Hispanic White); in 74% of grade D neighborhoods, the median income is low to moderate.27 Redlining designations are associated with a variety of exposures, including greenspace prevalence,28 tree canopy,29−31 urban-heat exposure disparities,29,32,33 and health effects, including asthma,34 cancer,35,36 adverse birth outcomes,37,38 and overall urban health.39 To date, limited research has investigated air pollution exposure and redlining,31,34 despite its importance as an environmental risk factor.

We focus here on two key air pollutants that are significant causes of ill health and premature mortality, nitrogen dioxide (NO2) and fine particulate matter (PM2.5), and have distinct sources, atmospheric behavior, and spatial patterns. NO2 is a relatively short-lived, localized pollutant emitted by traffic, industry, power generation, and other high-temperature combustion processes. Urban areas tend to exhibit spatially sharp NO2 gradients because primary traffic emissions are a major source of NO2.40−43 In contrast, PM2.5 varies more on a regional scale because it has an atmospheric lifetime of days to weeks and is influenced strongly by both a broad array of emission sectors and multiple secondary formation processes.44−47

This paper explores associations between historical redlining and year-2010 air pollution levels and census demographics for 202 U.S. cities home to 65% of the U.S. urban population. We find monotonic and highly consistent associations between pollution levels and HOLC grades for both pollutants, with larger intraurban disparities associated with NO2. To the best of our knowledge, this study is the first full-scale examination of air pollution disparities relative to historical redlining and advances our understanding of the origins and persistence of inequities in air pollution exposures in the United States.

Materials and Methods

Demographic and HOLC Data

We used georeferenced 1930s era HOLC maps developed by the University of Richmond’s Mapping Inequality project to identify HOLC codes in 202 cities (148 U.S. census urbanized areas) across the United States, shown in Figure S1.25 Mapped neighborhoods were categorized by HOLC into one of four grades: A, best; B, still desirable; C, definitely declining; or D, hazardous for mortgage appraisal. We linked HOLC maps to individual U.S. Census blocks from the most recent available decennial census (2010);48 census blocks provide a spatial resolution at approximately the scale of a city block in urban areas (geospatial procedures are described in the Supporting Information). The resulting data set incorporates 45 million people in 202 U.S. cities (n = 562,078 census blocks; average population of 80 people per block).

Because of urban expansion post-1930, the HOLC areas represent only a subset of the overall present-day urban footprint in most metropolitan areas: the present-day urban core. To provide context and comparison, we also separately extend our analysis to the full U.S. Census urbanized areas (CUA; n = 148) that contain the HOLC-mapped neighborhoods. These 148 CUAs had a year-2010 population of 161 million people (∼65% of the full U.S. population residing in urbanized areas in 2010).

We combine race/ethnicity data to develop four aggregate groupings for analysis: people who are Hispanic of any race [24% of HOLC population (Table S1)], non-Hispanic White (henceforth White, 43%), non-Hispanic Black (Black, 23%), and non-Hispanic Asian (Asian, 7%). The remaining 3% of the HOLC population (Other) includes Pacific Islander, Native American, and populations self-identifying as belonging to two or more races. The broader CUA population demographics are as follows: 56% White, 15% Black, 7% Asian, and 19% Hispanic.

Air Pollution Data

We characterized NO2 and PM2.5 levels using empirical (i.e., land-use regression) models developed by the Center for Air, Climate and Energy Solutions (CACES; www.caces.us/data).5 This data set provides annual ambient concentration predictions for census blocks for 1979–2015. We employ year-2010 pollution data here to align with the most recent available (2010) decennial census. This model surface and its predecessors are commonly used for disparity analyses1,2,49 and predict NO2 and PM2.5 at U.S. EPA monitoring sites with high fidelity (R2 = 0.81 and 0.84, respectively).1 Our core results are expressed as population-weighted statistics [i.e., population-weighted mean (PWM) and other percentiles from the population distribution of exposures].

We first aggregate data in terms of unadjusted statistics (e.g., the national PWM concentration for all blocks in the D grade). Next, to isolate associations between redlining and intraurban gradients, we present adjusted statistics that hold constant for city-to-city differences in air pollution and therefore reveal only within-urban disparities. This adjusted statistic is computed as the national PWM of the intraurban concentration difference, i.e., the difference between census block levels and the corresponding urban PWM across all HOLC areas in a CUA (see section S1.2 of the Supporting Information). An example of the input data sets for Atlanta, GA, is included in Figure S2, and population demographics are outlined in Table S1 and Figure S3.

Results and Discussion

Associations between Concentration and HOLC Category

Because HOLC-mapped areas tend to cover only city centers and exclude suburban areas, air pollution levels in the HOLC-mapped areas tend to be higher than in the corresponding overall CUAs (Figure S4). Year-2010 PWM concentrations were 15.0 ppb (NO2) and 10.6 μg m–3 (PM2.5) for the 45 million people residing in HOLC-mapped areas, versus 10.9 ppb (NO2) and 9.9 μg m–3 (PM2.5) for the corresponding CUAs.

Unadjusted national statistics show that redlining is strongly associated with NO2 and more weakly but detectably associated with PM2.5 (Figure 1a,b). PWM NO2 pollution levels are 6.0 ppb (56%) higher in the D-grade (“hazardous”) than in the A-grade census blocks (16.8 ppb vs 10.8 ppb). PWM concentrations increase monotonically across HOLC grades. For PM2.5, this monotonic association also holds, but the PWM difference between A and D groups is smaller, 0.4 μg m–3 (4%; 10.7 μg m–3 vs 10.3 μg m–3). The smaller difference for PM2.5 aligns with existing research showing comparatively smaller intraurban pollution variations that are superimposed on a larger regional (mostly secondary) background.50,51

Figure 1.

Figure 1

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Population-weighted distributions of NO2 and PM2.5 levels within HOLC-mapped areas at the census block level. Bars represent 25th and 75th percentiles. Medians are indicated with horizontal lines, and means by the dot marker; the overall mean is indicated by the dotted line. Unadjusted national distributions are presented for (a) NO2 and (b) PM2.5. Adjusted distributions (c and d) report the national distributions of intraurban differences for census blocks within a given HOLC grade relative to the PWM level within each city. In each panel, pollution level distributions are reported by both HOLC grade (left cluster) and race/ethnicity (right cluster). Vertical lines between these clusters reflect the pollution range of the group means: the difference in the population-weighted mean between groups A and D (left line) and between the highest-exposed and lowest-exposed racial/ethnic group. Panels c and d illustrate how intraurban disparities are consistently higher by historical HOLC grade than by race/ethnicity.

Redlining is also associated with intraurban pollution gradients. PWM NO2 pollution levels for each HOLC zone, relative to that city’s average level (Figure 1), are 1.0 and 0.1 ppb higher for D and C areas, respectively, and 0.8 and 2.0 ppb lower for B and A areas, respectively (Figure 1c). Therefore, the PWM intraurban difference between the D and A grades is ∼3 ppb NO2. Intraurban differences are smaller for PM2.5 than for NO2 (Figure 1d): maximum of 0.1 μg m–3 (D grade) and minimum of −0.3 μg m–3 (A grade), for a net 0.4 μg m–3 difference.

We find a high degree of city-to-city consistency in intraurban disparities. PWM NO2 levels are higher in D neighborhoods than overall (i.e., considering all HOLC-mapped areas) in 80% of the 202 cities and are lower in A neighborhoods than overall in 84% of cities. Disparities exist not only for the average (PWM) but also throughout the distribution. Indeed, in most (52%) cities, the interquartile ranges (IQRs) for NO2 exhibited no overlap for the A and D neighborhoods (i.e., the A group 75th percentile was lower than the D group 25th percentile). For PM2.5, disparities are again in the same direction though more modest. PWM PM2.5 levels were higher than average for D neighborhoods in 55% of cities and lower than average for A neighborhoods in 68% of the cities, and the A and D IQRs exhibit no overlap in 20% of cities. Overall, trends associated with redlining hold across city size (Figure S5), across geographical region (Figure S6), and for the most recent-year (2015) CACES model predictions (Figure S7).

HOLC security maps were drawn on the basis of the demographic makeup of neighborhoods, reflecting preexisting racial residential segregation. However, redlining further solidified and accelerated those patterns that exist today. In addition, areas graded as C or D often hosted industrial facilities, railroads, and other pollution sources. We find that, within HOLC-mapped areas, D-grade neighborhoods are more likely to be near industrial sources and that the average number of sources nearby increases from A to D (Figure S8). Additionally, the portion of people living near railroads and primary roadways increases monotonically by HOLC grade from A to D (Figure S9). While U.S. rail infrastructure was largely constructed before the 1930s, limited-access highways were constructed almost entirely after the 1930s and were preferentially constructed through Black and brown communities in U.S. cities. This comparison using rail lines and highways emphasizes that racial disparities in air pollution exposure reported here reflect infrastructure placement that occurred both before and after HOLC redlining.52,53

Disparities by Race/Ethnicity

We further stratified our results by comparing each HOLC-grade PWM concentration for individual racial/ethnic groups. Consistent with the substantial literature on racial/ethnic disparities for air pollution, we find that people of color experience higher-than-average NO2 and PM2.5 levels and are overrepresented within C and D neighborhoods, consistent with prior redlining research (Figure 1). For example, on average, PWM intraurban pollution differences for NO2 (Figure 1c) are greater than average for Hispanic, Asian, and Black populations (0.8, 0.4, and 0.2 ppb higher than the urban average, respectively) and below average for the White population (−0.6 ppb). Differences for PM2.5 are proportionally smaller (Figure 1d) but reflect similar racial disparities (PWMs of −0.1 μg m–3 for White and Asian populations and 0.1 μg m–3 for Black and Hispanic populations). Overall, intraurban PWM differences by HOLC grade are larger than by race/ethnicity (Figure 1). We find a substantially larger PWM differences between D and A HOLC grades (3.0 ppb NO2 and 0.4 μg m–3 PM2.5) than between the most- and least-exposed racial/ethnic groups [1.3 ppb NO2 and 0.26 μg m–3 PM2.5 (see Figure 1c,d)].

Next, we examined how racial/ethnic disparities interact with historical HOLC grade. Figure 2 illustrates PWM intraurban disparities that exist by race/ethnicity along the A–D HOLC grade gradient. Smaller, but still substantial, intraurban racial/ethnic disparities exist for PM2.5 and NO2 within each historical HOLC grade. On average, the within-grade white population experiences lower than average levels of NO2 and PM2.5 while the Hispanic population experiences above average levels. The Black population experiences consistently above HOLC-grade-average PM2.5 levels while the Asian population experiences above HOLC-grade-average NO2 levels. These within-grade disparities are nearly as large as the overall racial/ethnic disparity for the HOLC-mapped areas, implying that a substantial portion of the racial/ethnic exposure disparity within the study areas exists independently of historical HOLC status.

Figure 2.

Figure 2

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Population-weighted mean annual intraurban PWM levels by HOLC grade and race/ethnicity for (a) NO2 and (b) PM2.5. All race/ethnicity groups demonstrate monotonic increases by HOLC grade. Disparities by HOLC grade were larger than those associated with differences between racial/ethnic groups (100% higher for NO2 and 50% higher for PM2.5).

Racial/ethnic air pollution disparities reported here are subdivided next into two distinct effects: those that are associated with historical HOLC redlining and those that are not. To explore the sensitivity of our overall results to racial/ethnic segregation (i) between and (ii) within each HOLC grade, we used stylized demographic scaling factors to mathematically redistribute the populations in every city to (as a counterfactual approach) eliminate intraurban racial/ethnic segregation first between, and then within, HOLC grades (details in section S1.3). The reduction in racial/ethnic disparity from removing between-grade segregation was larger for NO2 than for PM2.5. However, both results were modest relative to the reductions produced by removing within-grade segregation (Figure S10). These findings may reflect various factors, including changes in demographics since the 1930s (e.g., gentrification), within-grade gradients of proximity to undesirable/polluting land uses (potentially preceding redlining), and later emission source placement (e.g., highways).

Figure S11 offers a complementary insight. Intraurban air pollution disparities show distinct relationships with demographics, but there is also a stratified gradient from HOLC grade A to D for nearly any level of demographic composition. This suggests redlining disparity effects are one of multiple factors that contribute to intraurban racial/ethnic disparities in pollution exposure. Importantly, if one could remove all between-grade disparities, that would only modestly change the overall, because within-grade disparities are the larger contributor to overall racial/ethnic disparities.

Broader Implications

Converging lines of evidence from our analysis suggest the following key points. First, redlining is associated with substantial intraurban air pollution disparities for NO2 and PM2.5. These findings are consistent with a broad body of evidence that adverse historical HOLC designations are associated with worse present-day local environmental quality and health outcomes, including air pollution, green space,28 tree canopy,29−31 COVID risk,54 and urban heat.29,32,33 Second, for the 45 million Americans who live in HOLC-mapped areas, NO2 and PM2.5 disparities by grade are larger than those by race/ethnicity. Third, despite the substantial association between HOLC redlining and aggregate pollution disparities, we find that intraurban racial/ethnic disparities in NO2 and PM2.5 are only moderately correlated with historical HOLC status; most of the disparities we observe are within grade rather than between grade. This finding likely reflects that historical redlining is only one of many racially discriminatory policies that have contributed to disparate environmental exposures for people of color.

Findings here highlight that present-day disparities in U.S. urban pollution levels reflect a legacy of structural racism in federal policy-making—and resulting investment flows and land use decisions—apparent in maps drawn more than 80 years ago. NO2 and PM2.5 are considered “short-lived” pollutants (atmospheric lifetimes of approximately hours and days, respectively), yet the systems that created these disparities span more than a human lifetime. Results from this work55 can support decision-makers in their efforts to improve air pollution policy in ways that address exposure inequities. Future work should propose, evaluate, and implement solutions that can benefit disparately impacted communities. Fully addressing exposure inequities will require transformations sustained across generations.

Acknowledgments

This publication was developed as part of the Center for Air, Climate and Energy Solutions (CACES), which was supported under Assistance Agreement No. R835873 awarded by the U.S. Environmental Protection Agency. It has not been formally reviewed by EPA. The views expressed in this document are solely those of authors and do not necessarily reflect those of the Agency. EPA does not endorse any products or commercial services mentioned in this publication.

Supporting Information Available

The Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/acs.estlett.1c01012.

  • Detailed description of materials and methods, supporting demographic tables, and supporting figures S1–S11 (PDF)

The authors declare no competing financial interest.

Notes

Extended data55 are available at doi:10.6084/m9.figshare.19193243.

Supplementary Material

ez1c01012_si_001.pdf (2.2MB, pdf)

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