Thermal Inequity in Richmond, VA: The Effect of an Unjust Evolution of the Urban Landscape on Urban Heat Islands

Land surface temperature and socioeconomic residential segregation in the Metropolitan Zone of San Luis Potosí, Mexico

Economic growth and urban sprawl in territorial systems produce an uneven distribution of infrastructure and services. This creates residential areas with high capital gains that are affordable only for the middle and upper classes. For lower-income groups, the only options are depressed urban areas with limited infrastructure. The economic dynamics of urban systems require large amounts of energy that contribute to an increase in the land surface temperature (LST). The objective of this research was to analyze urban heat and exposure inequalities of socioeconomically segregated groups during the last thirty years in the Metropolitan Zone of San Luis Potosí-Soledad de Graciano Sánchez, Mexico. A spatial and temporal analysis of Landsat 5 and 8 satellite imagery was used to determine the variation in LST over the last three decades. Socioeconomic residential segregation was calculated using the Theil index. With this data, a self-segregated sector with high capital gains was identified. This sector exhibited significant differences (p < 0.05) of -2.00 °C and -1.58 °C in average LST in the spring months compared to the most depressed urban sectors characterized by the largest concentrations of overcrowded social housing and the lowest educational indexes. The spatio-temporal patterns suggest that urban expansion has led to an unequal distribution of ecosystem services for temperature regulation, leaving the most vulnerable groups with higher exposure to the effects of urban heat.

SchoolHEAT: Racial and Ethnic Inequity in School Temperature

Exposure to high environmental temperature is detrimental to health through multiple pathways. This paper describes disparities in school-based high-temperature exposure at metropolitan schools in the United States. Using school location and sociodemographic data from the National Center for Education Statistics, neighborhood data from the US Census Bureau, and land surface temperature (LST) data from the Aqua Earth-observing satellite mission, we find that for every 10% more Black or Hispanic residents in the neighborhood, schools have LST 0.25 °C and 0.38 °C hotter, respectively. When the Black or Hispanic student population is greater than the neighborhood population, LST is an additional 0.20 °C and 0.40 °C for each 10% increase in students over neighborhood population, respectively. Black and Hispanic students are overrepresented in the hottest schools, making up 58.7% of students in the hottest 20% of schools, compared to only 30.0% of students in the coolest 20% of schools.

Correlation analysis of landscape patterns and urban thermal environment in Kunming based on a panel data model

With the development of urbanization, the spatial and temporal distribution characteristics of the urban landscape pattern play a decisive role in the intensity of the urban heat island (UHI) effect. A panel data model was constructed to study the relationship between the UHI effect and landscape pattern in Kunming from 1995 to 2020 at four different scales. The results indicate: (1) The landscape pattern of Kunming changed obviously with time, the artificial patch increased, the natural patch decreased, and the UHI effect became more and more obvious; (2) With an increase in scale, the number of influencing variables continues to grow, and the impact of artificial patches gradually intensifies; (3) The normalized difference water index (NDWI) has the greatest influence on the UHI, and the cooling effect is more obvious with the increase in scale. Unlike previous studies, the spatial configuration of the landscape in Kunming City had a stronger effect on the UHI effect than the landscape grouping and vegetation index; (4) This paper introduces the panel data model into the discussion of the UHI for the first time, providing a new method for better understanding the changing patterns of the urban thermal environment.

Opportunities for science centers and museums to cultivate a culture of climate action

Science centers and museums are uniquely positioned to spark climate action. In this commentary, we describe opportunities to further increase the field's impact through research on the psychological states that drive action and public engagement approaches for sparking those states. We also introduce Seeding Action, an initiative led by the Association of Science and Technology Centers to address the opportunities for cross-museum research and coordination.

Methodologic Strategies for Quantifying Associations of Historical and Contemporary Mortgage Discrimination on Population Health Equity: A Systematic Review

BACKGROUND

Mortgage discrimination refers to the systematic withholding of home mortgages from minoritized groups. In recent years, there has been an increase in empirical research investigating associations of historical and contemporary mortgage discrimination on contemporary  outcomes. Investigators have used a variety of measurement methods and approaches, which may have implications for results and interpretation.

PURPOSE

We conducted a systematic review of peer-reviewed literature that has quantified links between both historical and current mortgage discrimination with contemporary adverse environmental, social, and health outcomes. Our goals were to document the methodology used to measure and assign mortgage discrimination, to assess implications for results and interpretation, and to make recommendations for future work.

METHODS

Following the Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines, literature searches were conducted in September 2022 using terms that combined concepts of mortgage discrimination, health, and neighborhood environment.

RESULTS

In total, 45 papers fit the eligibility criteria. In these, researchers investigated associations between mortgage discrimination and: (1) health outcomes (N = 28); (2) environmental and social exposures including heat, air pollution, greenspace, soil lead levels, and crime (N = 12); and (3) built environment features, including presence of retail alcohol, fast food, and tobacco stores (N = 5). Eleven included studies used Home Mortgage Discrimination Act (HMDA) data to identify racialized bias in mortgage discrimination or redlining, and 34 used Homeowner Loan Corporation (HOLC) maps. The construction and parametrization of mortgage discrimination or redlining and the spatial assignment of HOLC grades to contemporary addresses or neighborhoods varied substantially across studies.

CONCLUSIONS

Results from our review suggest the need for careful consideration of optimal methods to analyze mortgage discrimination such as HOLC spatial assignment or HMDA index parametrization, contemplation of covariates, and place-based knowledge of the study location.

Impact of tent shade on heat exposures and simulated heat strain for people experiencing homelessness

Concurrent increases in homelessness and heat intensity, duration, and frequency translate to an urban heat risk trap for the unsheltered population. Homelessness is both a driver and consequence of poor health, co-creating distinct geographies with various risk factors that exacerbate heat vulnerability. We tested the efficacy of different tent shadings over identical tents often observed in the Phoenix area (white bedsheet, mylar, tarp, and aluminum foil) and compared them to a control tent (uncovered) and ambient conditions. We monitored all meteorological variables at all six locations, notably Mean Radiant Temperature (MRT). The in-tent microclimate variability was applied to complete statistical and physiological modeling including substance use on heat strain. Findings indicate that tent shadings resulted in significantly lower in-tent MRT during the day (p < 0.05), but exacerbated in-tent thermal risk during the night compared to the control tent and ambient conditions. Furthermore, we found evidence that the temperature metric matters, and using only either MRT or air temperature (Tair) to assess "heat" could lead to inconsistent conclusions about in-tent microclimate. Interactions between shade types and time significantly amplified in-tent thermal risk. Physiological modeling indicates a higher risk of heat strain (core temperature beyond 40˚C) for people using substances. Decision makers should promote testing different heat intervening strategies toward realizing effective means of protecting human life and preventing heat illnesses. This study illuminates the need for an interdisciplinary approach to studying tents as shelters that considers the total heat load with heat strain modeling.

Unequal distributions of crowdsourced weather data in England and Wales

Personal weather stations (PWS) can provide useful data on urban climates by densifying the number of weather measurements across major cities. They do so at a lower cost than official weather stations by national meteorological services. Despite the increasing use of PWS data, little attention has yet been paid to the underlying socio-economic and environmental inequalities in PWS coverage. Using social deprivation, demographic, and environmental indicators in England and Wales, we characterize existing inequalities in the current coverage of PWS. We find that there are fewer PWS in more deprived areas which also observe higher proportions of ethnic minorities, lower vegetation coverage, higher building height and building surface fraction, and lower proportions of inhabitants under 65 years old. This implies that data on urban climate may be less reliable or more uncertain in particular areas, which may limit the potential for climate adaptation and empowerment in those communities.

A Heat Emergency: Urban Heat Exposure and Access to Refuge in Richmond, VA

The urban heat island effect exacerbates independent climate change-induced shifts toward longer, stronger, and more frequent heat extremes. Environmental inequity, driven by a history of racially motivated urban planning policies, has led particular demographics to bear the worst impacts of urban heat exposure and thus also climate change. These impacts cause adverse health outcomes in the form of heat emergencies. Through a novel demographic and spatial analysis of heat-related illness Emergency Medical Services data from Richmond, Virginia, this study investigates the relationships between heat health emergencies and intra-urban heat islands quantified through three heat exposure metrics. We also evaluate the accessibility of built refuge from urban heat in the form of public transit infrastructure, libraries, and government cooling centers in relation to these emergencies. We found that heat emergencies are inequitably distributed among racial, age, and socioeconomic groups in Richmond, particularly among residents identified as Male, Black or African American, 50+ years old, and experiencing mental health, intoxication, and/or homelessness. We found significant associations between the location of these heat emergencies and urban heat islands as estimated from remotely-sensed surface and community science-derived air temperature metrics, but not a co-estimated heat index. We also found that available refuge facilities are insufficiently located to protect individuals with reduced mobility across areas with the highest number of heat-related health emergencies. Community involvement in the mitigation and management of extreme heat threats, especially for those disproportionately impacted, is necessary to decrease the number of summertime heat illnesses.

Evaluating Methods for Mapping Historical Redlining to Census Tracts for Health Equity Research

Neighborhood characteristics including housing status can profoundly influence health. Recently, increasing attention has been paid to present-day impacts of "redlining," or historic area classifications that indicated less desirable (redlined) areas subject to decreased investment. Scholarship of redlining and health is emerging; limited guidance exists regarding optimal approaches to measuring historic redlining in studies of present-day health outcomes. We evaluated how different redlining approaches (map alignment methods) influence associations between redlining and health outcomes. We first identified 11 existing redlining map alignment methods and their 37 logical extensions, then merged these 48 map alignment methods with census tract life expectancy data to construct 9696 linear models of each method and life expectancy for all 202 redlined cities. We evaluated each model's statistical significance and R2 values and compared changes between historical and contemporary geographies and populations using Root Mean Squared Error (RMSE). RMSE peaked with a normal distribution at 0.175, indicating persistent difference between historical and contemporary geographies and populations. Continuous methods with low thresholds provided higher neighborhood coverage. Weighting methods had more significant associations, while high threshold methods had higher R2 values. In light of these findings, we recommend continuous methods that consider contemporary population distributions and mapping overlap for studies of redlining and health. We developed an R application {holcmapr} to enable map alignment method comparison and easier method selection.

Urban socioeconomic variation influences the ecology and evolution of trophic interactions

As urbanization expands, it is becoming increasingly important to understand how anthropogenic activity is affecting ecological and evolutionary processes. Few studies have examined how human social patterns within cities can modify eco-evolutionary dynamics. We tested how socioeconomic variation corresponds with changes in trophic interactions and natural selection on prey phenotypes using the classic interaction between goldenrod gall flies (Eurosta solidaginis) and their natural enemies: birds, beetles, and parasitoid wasps. We sampled galls from 84 sites across neighbourhoods with varying socioeconomic levels, and quantified the frequency of predation/parasitism on flies and natural selection by each enemy. We found that bird predation was higher in the highest income neighbourhoods, increasing the strength of selection for smaller galls. Wasp and beetle attack, but not their strength of selection, increased in lower income neighbourhoods. We show that socioeconomic variation in cities can have strong unintended consequences for the ecology and evolution of trophic interactions.

Surviving indoor heat stress in United States: A comprehensive review exploring the impact of overheating on the thermal comfort, health, and social economic factors of occupants

In the face of escalating global climate change and the increasing frequency of extreme heat events, the mitigation of building overheating has become an urgent priority. This comprehensive review converges insights from building science and public health domains to offer a thorough understanding of the multifaceted impacts of indoor overheating on occupants. The paper addresses a significant research gap by offering a holistic exploration of indoor overheating of residential buildings and its consequences, with a specific focus on the United States, an economically diverse nation that has been underrepresented in the literature. The review illuminates the effects of overheating on thermal comfort, health, and socio-economic aspects within the built environment. It emphasizes associated repercussions, including heightened cooling energy consumption, increased peak electricity demand, and elevated vulnerability, leading to exacerbated heat-related mortality and morbidity rates, especially among disadvantaged groups. The study concludes that vulnerabilities to these impacts are intricately tied to regional climatic conditions, highlighting the inadequacy of a one-size-fits-all approach. Tailored interventions for each climate zone are deemed necessary, considering the consistent occurrence of indoor temperatures surpassing outdoor levels, known as superheating, which poses distinct challenges. The research underscores the urgency of addressing indoor overheating as a critical facet of public health, acknowledging direct socioeconomic repercussions. It advocates for further research to inform comprehensive policies that safeguard public health across diverse indoor environments.

Concurrent Heat and Air Pollution Exposures among People Experiencing Homelessness

BACKGROUND

Extreme heat and air pollution are important human health concerns; exposure can affect mental and physical well-being, particularly during periods of co-occurrence. Yet, the impacts on people are largely determined by underlying health conditions, coupled with the length and intensity of exposure. Preexisting adverse health conditions and prolonged exposure times are more common for people experiencing homelessness, particularly those with intersectional identity characteristics (e.g., disease, ability, age, etc.). Partially due to methodological limitations, such as data scarcity, there is a lack of research at the intersection of this at-risk population within the climate-health domain.

OBJECTIVES

We have three distinct objectives throughout this article: a) to advance critical discussions around the state of concurrent high heat and air pollution exposure research as it relates to people experiencing homelessness; b) to assert the importance of heat and air pollution exposure research among a highly vulnerable, too-often homogenized population-people experiencing homelessness; and c) to underline challenges in this area of study while presenting potential ways to address such shortcomings.

DISCUSSION

The health insights from concurrent air pollution and heat exposure studies are consequential when studying unhoused communities who are already overexposed to harmful environmental conditions. Without holistic data sets and more advanced methods to study concurrent exposures, appropriate and targeted prevention and intervention strategies cannot be developed to protect this at-risk population. We highlight that a) concurrent high heat and air pollution exposure research among people experiencing homelessness is significantly underdeveloped considering the pressing human health implications; b) the severity of physiological responses elicited by high heat and air pollution are predicated on exposure intensity and time, and thus people without means of seeking climate-controlled shelter are most at risk; and c) collaboration among transdisciplinary teams is needed to resolve data resolution issues and enable targeted prevention and intervention strategies. https://doi.org/10.1289/EHP13402.

Thermal and pigment characterization of environmental fungi in the urban heat island of Baltimore City

One of the major barriers of fungal infections of mammals is the inability to grow and/or survive at mammalian body temperature, typically around 37°C. This has provided mammals an advantage over fungi. However, environmental fungi may soon adapt to persist at higher temperatures, consistent with mammalian body temperature, due to thermal selection pressures imposed by climate change, global warming, and increased frequency of extreme heat events. Consequently, there is a need for more updated information about the thermal tolerance range of fungi near humans, such as in urban areas. The heat island effect suggests that cities are up to 8°C warmer than their suburban counterparts because of increased heat production, asphalt coatings and reduced greenspace among other factors, and it is more common in lower income and marginalized urban communities. Thus, urban centers are at increased risk for the emergence of heat tolerant fungi. In this study, we developed a methodology to collect and archive fungal isolates from sidewalk and soil samples in both warmer and cooler neighborhoods in Baltimore, Maryland. We demonstrate a novel methodology for fungal sample collection from sidewalks, employing the use of standardized and commercially available taffy. Analysis of fungal isolates collected from warmer neighborhoods revealed greater thermal tolerance and lower pigmentation, suggesting local adaptation to heat. Lower pigmentation in hotter areas is consistent with the notion that fungi use pigmentation to help regulate their temperature. Further, we identified the robust presence of the polyextremotolerant fungus Aureobasidium pullalans from the warmest neighborhood in Baltimore, further showing that the extreme conditions of cities can drive proliferation of extremotolerant fungi. This study develops new techniques for environmental fungal collection and provides insight on the fungal census in an urban setting that can inform future work to study how urban environments may drive stress/thermotolerance in fungi, which could alter fungal interactions with humans and impact human health.

Creating building-level, three-dimensional digital models of historic urban neighborhoods from Sanborn Fire Insurance maps using machine learning

Sanborn Fire Insurance maps contain a wealth of building-level information about U.S. cities dating back to the late 19th century. They are a valuable resource for studying changes in urban environments, such as the legacy of urban highway construction and urban renewal in the 20th century. However, it is a challenge to automatically extract the building-level information effectively and efficiently from Sanborn maps because of the large number of map entities and the lack of appropriate computational methods to detect these entities. This paper contributes to a scalable workflow that utilizes machine learning to identify building footprints and associated properties on Sanborn maps. This information can be effectively applied to create 3D visualization of historic urban neighborhoods and inform urban changes. We demonstrate our methods using Sanborn maps for two neighborhoods in Columbus, Ohio, USA that were bisected by highway construction in the 1960s. Quantitative and visual analysis of the results suggest high accuracy of the extracted building-level information, with an F-1 score of 0.9 for building footprints and construction materials, and over 0.7 for building utilizations and numbers of stories. We also illustrate how to visualize pre-highway neighborhoods.

Determining spatial disparities and similarities regarding heat exposure, green provision, and social structure of urban areas - A study on the city district level in the Ruhr area, Germany

Heat islands and ongoing urbanization make cities places where the negative impacts of global climate change on society are becoming increasingly evident. Especially the interplay and potential multiplication of heat, low green provision, and the presence of socially deprived urban dwellers constitutes complex challenges. Emerging climate injustices and potential health issues require a powerful counter-reaction in form of adaptation action. For our study, we consider eight cities located in the densely populated and historically highly segregated Ruhr area in Western Germany, which is one of the largest metropolitan areas in Europe with a heterogeneous distribution of socio-spatial problems, economic potential, heat stress, and green infrastructures. We use land surface temperature (LST), data on green provision (normalized difference vegetation index (NDVI)), and social indicators to reveal the relationships between these indicators on the city district level (n = 275). Therefore, we first analyze the data regarding spatial autocorrelation (Moran's I) and clustering (Gi*) before calculating study area wide and city specific correlations between the three factors regarded. Finally, we conduct a cluster analysis (k-means) to disclose similar areas with or without multiple burdens. Our results show distinct disparities in heat exposure, green availability, and social status between city districts of the study area. We find strong negative correlations between LST and NDVI as well as between NDVI and social status. The relationship between LST and our social indicator remains ambiguous, affirming the necessity of further detailed studies. The cluster analysis furthermore allows for the visualization and classification of districts featuring similar characteristics regarding the researched components. We can discern in parts pronounced climate injustice in the studied cities, with a majority of people living in unfavorable environmental and socio-economic conditions. Our analysis supports governments and those responsible for urban planning in addressing climate injustice in the future.

The Relationship of Historical Redlining with Present-Day Neighborhood Environmental and Health Outcomes: A Scoping Review and Conceptual Model

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.

Environmental Health: A Position Paper From the American College of Physicians

Environmental health refers to the health effects associated with environmental factors, such as air pollution, water contamination, and climate change. Environmental hazards are associated with poor outcomes in common diseases, including diabetes and heart disease. In this position paper, the American College of Physicians (ACP) seeks to inform physicians about environmental health and offers policymakers recommendations to reduce the adverse health consequences of climate change, improve air and water quality, reduce exposure to toxic substances, and address environmental injustice. ACP affirms that all communities, including people of color, people with low income, and marginalized populations, deserve to live in a healthy environment.

Population-Based Disparities in U.S. Urban Heat Exposure from 2003 to 2018

Previous studies have shown, in the United States (U.S.), that communities of color are exposed to significantly higher temperatures in urban environments than complementary White populations. Studies highlighting this disparity have generally been cross-sectional and are therefore "snapshots" in time. Using surface urban heat island (SUHI) intensity data, U.S. Census 2020 population counts, and a measure of residential segregation, this study performs a comparative analysis between census tracts identified as prevalent for White, Black, Hispanic and Asian populations and their thermal exposure from 2003 to 2018. The analysis concentrates on the top 200 most populous U.S. cities. SUHI intensity is shown to be increasing on average through time for the examined tracts. However, based on raw observations the increase is only statistically significant for White and Black prevalent census tracts. There is a 1.25 K to ~2.00 K higher degree of thermal exposure on average for communities of color relative to White prevalent areas. When examined on an inter-city basis, White and Black prevalent tracts had the largest disparity, as measured by SUHI intensity, in New Orleans, LA, by <6.00 K. Hispanic (>7.00 K) and Asian (<6.75 K) prevalent tracts were greatest in intensity in San Jose, CA. To further explore temporal patterns, two models were developed using a Bayesian hierarchical spatial temporal framework. One models the effect of varying the percentages of each population group relative to SUHI intensity within all examined tracts. Increases in percentages of Black, Hispanic, and Asian populations contributed to statistically significant increases in SUHI intensity. White increases in population percentage witnessed a lowering of SUHI intensity. Throughout all modeled tracts, there is a statistically significant 0.01 K per year average increase in SUHI intensity. A second model tests the effect of residential segregation on thermal inequity across all examined cities. Residential segregation, indeed, has a statistically significant positive association with SUHI intensity based on this portion of the analysis. Similarly, there is a statistically significant 0.01 K increase in average SUHI intensity per year for all cities. Results from this study can be used to guide and prioritize intervention strategies and further urgency related to social, climatic, and environmental justice concerns.

Disaster Microbiology-a New Field of Study

Natural and human-made disasters can cause tremendous physical damage, societal change, and suffering. In addition to their effects on people, disasters have been shown to alter the microbial population in the area affected. Alterations for microbial populations can lead to new ecological interactions, with additional potentially adverse consequences for many species, including humans. Disaster-related stressors can be powerful forces for microbial selection. Studying microbial adaptation in disaster sites can reveal new biological processes, including mechanisms by which some microbes could become pathogenic and others could become beneficial (e.g., used for bioremediation). Here we survey examples of how disasters have affected microbiology and suggest that the topic of "disaster microbiology" is itself a new field of study. Given the accelerating pace of human-caused climate change and the increasing encroachment of the natural word by human activities, it is likely that this area of research will become increasingly relevant to the broader field of microbiology. Since disaster microbiology is a broad term open to interpretation, we propose criteria for what phenomena fall under its scope. The basic premise is that there must be a disaster that causes a change in the environment, which then causes an alteration to microbes (either a physical or biological adaptation), and that this adaptation must have additional ramifications.

Changes in Container-Breeding Mosquito Diversity and Abundance Along an Urbanization Gradient are Associated With Dominance of Arboviral Vectors

Environmental conditions associated with urbanization are likely to influence the composition and abundance of mosquito (Diptera, Culicidae) assemblages through effects on juvenile stages, with important consequences for human disease risk. We present six years (2011-2016) of weekly juvenile mosquito data from distributed standardized ovitraps and evaluate how variation in impervious cover and temperature affect the composition and abundance of container-breeding mosquito species in Maryland, USA. Species richness and evenness were lowest at sites with high impervious cover (>60% in 100-m buffer). However, peak diversity was recorded at sites with intermediate impervious cover (28-35%). Four species were observed at all sites, including two recent invasives (Aedes albopictus Skuse, Ae. japonicus Theobald), an established resident (Culex pipiens L), and one native (Cx. restuans Theobald). All four are viral vectors in zoonotic or human transmission cycles. Temperature was a positive predictor of weekly larval abundance during the growing season for each species, as well as a positive predictor of rapid pupal development. Despite being observed at all sites, each species responded differently to impervious cover. Abundance of Ae. albopictus larvae was positively associated with impervious cover, emphasizing that this medically-important vector not only persists in the warmer, impervious urban landscape but is positively associated with it. Positive temperature effects in our models of larval abundance and pupae occurrence in container habitats suggest that these four vector species are likely to continue to be present and abundant in temperate cities under future temperature scenarios.

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

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 PM_2.5 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 PM_2.5 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.

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

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 PM_2.5 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 PM_2.5 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.

Fine-Grained Large-Scale Vulnerable Communities Mapping via Satellite Imagery and Population Census Using Deep Learning

One of the challenges in the fight against poverty is the precise localization and assessment of vulnerable communities’ sprawl. The characterization of vulnerability is traditionally accomplished using nationwide census exercises, a burdensome process that requires field visits by trained personnel. Unfortunately, most countrywide censuses exercises are conducted only sporadically, making it difficult to track the short-term effect of policies to reduce poverty. This paper introduces a definition of vulnerability following UN-Habitat criteria, assesses different CNN machine learning architectures, and establishes a mapping between satellite images and survey data. Starting with the information corresponding to the 2,178,508 residential blocks recorded in the 2010 Mexican census and multispectral Landsat-7 images, multiple CNN architectures are explored. The best performance is obtained with EfficientNet-B3 achieving an area under the ROC and Precision-Recall curves of 0.9421 and 0.9457, respectively. This article shows that publicly available information, in the form of census data and satellite images, along with standard CNN architectures, may be employed as a stepping stone for the countrywide characterization of vulnerability at the residential block level.