Retooling CalEnviroScreen: Cumulative Pollution Burden and Race-Based Environmental Health Vulnerabilities in California

Toward Language Justice in Environmental Health Sciences in the United States: A Case for Spanish as a Language of Science

BACKGROUND

Increasingly, marginalized communities are disproportionately facing the worsening effects of environmental hazards, including air pollution, water pollution, and climate change. Language isolation and accessibility has been understudied as a determinant of health. Spanish, despite being the second-most common language in the United States with some 41.8 million speakers, has been neglected among environmental health scientists. Building capacity in high-quality Spanish-language science communication, both for scientific and nonscientific audiences, can yield improvements in health disparities research, public health literacy, international collaborations, and diversity and inclusion efforts.

OBJECTIVES

In this article, we discuss the context of language diversity in environmental health sciences and offer recommendations for improving science communication in Spanish.

DISCUSSION

English is currently the predominant language for scientific discourse, but Spanish and other non-English languages are routinely used by many environmental health science students and professionals, as well as much of the public. To more effectively conduct and communicate environmental health work in Spanish, we suggest that researchers and scientific institutions a) foster structural changes, b) train emerging scholars and support established researchers, c) tap into community ways of knowing, and d) leverage emerging technologies. https://doi.org/10.1289/EHP12306.

Household conditions, COVID-19, and equity: Insight from two nationally representative surveys

Background

With people across the United States spending increased time at home since the emergence of COVID-19, housing characteristics may have an even greater impact on health. Therefore, we assessed associations between household conditions and COVID-19 experiences.

Methods

We used data from two nationally representative surveys: the Tufts Equity Study (TES; n = 1449 in 2021; n = 1831 in 2022) and the Household Pulse Survey (HPS; n = 147,380 in 2021; n = 62,826 in 2022). In the TES, housing conditions were characterized by heating/cooling methods; smoking inside the home; visible water damage/mold; age of housing unit; and self-reported concern about various environmental factors. In TES and HPS, household size was assessed. Accounting for sampling weights, we examined associations between each housing exposure and COVID-19 outcomes (diagnosis, vaccination) using separate logistic regression models with covariates selected based on an evidence-based directed acyclic graph.

Results

Having had COVID-19 was more likely among people who reported poor physical housing condition (odds ratio [OR] = 2.32; 95% confidence interval [CI] = 1.17-4.59; 2021), visible water damage or mold/musty smells (OR = 1.50; 95% CI = 1.10-2.03; 2022), and larger household size (5+ versus 1-2 people; OR = 1.53, 95% CI = 1.34-1.75, HPS 2022). COVID-19 vaccination was less likely among participants who reported smoke exposure inside the home (OR = 0.53; 95% CI = 0.31-0.90; 2022), poor water quality (OR = 0.42; 95% CI = 0.21-0.85; 2021), noise from industrial activity/construction (OR = 0.44; 95% CI = 0.19-0.99; 2022), and larger household size (OR = 0.57; 95% CI = 0.46-0.71; HPS 2022). Vaccination was also positively associated with poor indoor air quality (OR = 1.96; 95% CI = 1.02-3.72; 2022) and poor physical housing condition (OR = 2.27; 95% CI = 1.01-5.13; 2022). Certain heating/cooling sources were associated with COVID-19 outcomes.

Conclusions

Our study found poor housing conditions associated with increased COVID-19 burden, which may be driven by systemic disparities in housing, healthcare, and financial access to resources during the COVID-19 pandemic.

The Moderating Role of Housing Quality on Concentrated Poverty and Asthma-Related Emergency Department Visits Among Hispanics/Latinos

Background. Rates of asthma-related emergency department visits have been shown to vary significantly by place (i.e., neighborhood) and race/ethnicity. The moderating factors of asthmatic events among Hispanic/Latino-specific populations are known to a much lesser degree. Objective. To assess the extent to which housing moderates the effect of poverty on Hispanic/Latino-specific asthma-related emergency department (ED) visits at an ecological level. Methods. Using data from the Office of Statewide Health Planning and Development (OSHPD) and the 2016-2017 U.S. Census, a cross-sectional ecological analysis at the census tract-level was conducted. Crosswalk files from the U.S. Department of Housing and Urban Development were used to associate zip codes to census tracts. Negative binomial regression was used to estimate rate ratios. Results. The effect of poverty on asthma-related ED visits was significantly moderated by the median year of housing structures built. The effect of mid-level poverty (RR= 1.57, 95% CI 1.27, 1.95) and high-level poverty (RR= 1.47, 95% CI 1.22, 1.78) in comparison to low-level poverty, was significantly greater among census tracts with housing built prior to 1965 in comparison to census tract with housing built between 1965-2020. Conclusion. Communities with older housing structures tend to be associated with increased Hispanic/Latino ED visits apart from affluent communities.

Current practice and recommendations for advancing how human variability and susceptibility are considered in chemical risk assessment

A key element of risk assessment is accounting for the full range of variability in response to environmental exposures. Default dose-response methods typically assume a 10-fold difference in response to chemical exposures between average (healthy) and susceptible humans, despite evidence of wider variability. Experts and authoritative bodies support using advanced techniques to better account for human variability due to factors such as in utero or early life exposure and exposure to multiple environmental, social, and economic stressors.This review describes: 1) sources of human variability and susceptibility in dose-response assessment, 2) existing US frameworks for addressing response variability in risk assessment; 3) key scientific inadequacies necessitating updated methods; 4) improved approaches and opportunities for better use of science; and 5) specific and quantitative recommendations to address evidence and policy needs.Current default adjustment factors do not sufficiently capture human variability in dose-response and thus are inadequate to protect the entire population. Susceptible groups are not appropriately protected under current regulatory guidelines. Emerging tools and data sources that better account for human variability and susceptibility include probabilistic methods, genetically diverse in vivo and in vitro models, and the use of human data to capture underlying risk and/or assess combined effects from chemical and non-chemical stressors.We recommend using updated methods and data to improve consideration of human variability and susceptibility in risk assessment, including the use of increased default human variability factors and separate adjustment factors for capturing age/life stage of development and exposure to multiple chemical and non-chemical stressors. Updated methods would result in greater transparency and protection for susceptible groups, including children, infants, people who are pregnant or nursing, people with disabilities, and those burdened by additional environmental exposures and/or social factors such as poverty and racism.

County-Level Social Vulnerability Is Positively Associated with Cardiometabolic Disease in Colorado

Cardiometabolic diseases are a group of interrelated diseases that pose greater burden among socially vulnerable communities. The social vulnerability index (SVI) identifies communities vulnerable to emergencies and may also help determine communities at risk of adverse chronic health outcomes. However, no studies have examined the relationship between the SVI and cardiometabolic health outcomes in Colorado or focused on rural settings. The aim of this ecological study was to determine whether the county-level SVI is associated with county-level cardiometabolic health indicators with a particular focus on rurality and racial/ethnic diversity. We obtained 2014 SVI scores from the Centers for Disease Control and Prevention (scored 0–1; higher = more vulnerable) and 2013–2015 cardiometabolic health estimates from the Colorado Department of Public Health and Environment. The distribution of social determinants of health was spatially evaluated. Bivariate relationships between the SVI and cardiometabolic indicators were estimated using simple linear regression models. The highest SVI scores were observed in rural areas, including the San Luis Valley (mean: 0.78, median: 0.91), Southeast (mean: 0.72, median: 0.73), and Northeast (mean: 0.66, median: 0.76) regions. Across Colorado, the SVI accounted for 41% of the variability in overweight and obesity prevalence (p < 0.001), 17% of the variability in diabetes prevalence (p = 0.001), and 58% of the age-adjusted myocardial infarction hospitalization rate (p < 0.001). SVI values may be useful in determining a community’s burden of cardiometabolic diseases.

Rethinking of Environmental Health Risks: A Systematic Approach of Physical-Social Health Vulnerability Assessment on Heavy-Metal Exposure through Soil and Vegetables

In the field of environmental health risk assessment and management research, heavy metals in soil are a constant focus, largely because of mining and metallurgical activities, and other manufacturing or producing. However, systematic vulnerability, and combined research of social and physical vulnerability of the crowd, have received less attention in the research literature of environmental health risk assessment. For this reason, tentative design modelling for comprehensive environmental health vulnerability, which includes the index of physical and social vulnerability, was conducted here. On the basis of experimental data of heavy-metal pollution in soil and vegetables, and population and societal survey data in Daye, China, the physical, social, and comprehensive environmental health vulnerabilities of the area were analyzed, with each village as an evaluation unit. First, the polluted and reference areas were selected. Random sampling sites were distributed in the farmland of the villages in these two areas, with two sampling sites per village. Then, 204 vegetable samples were directly collected from the farmland from which the soil samples had been collected, composed of seven kinds of vegetables: cowpea, water spinach, amaranth, sweet potato leaves, tomato, eggplant, and pepper. Moreover, 400 questionnaires were given to the local residents in these corresponding villages, and 389 valid responses were obtained. The results indicated that (1) the average physical vulnerability values of the population in the polluted and reference areas were 3.99 and 1.00, respectively; (2) the village of Weiwang (WW) had the highest physical vulnerability of 8.55; (3) vegetable intake is exposure that should be paid more attention, as it contributes more than 90% to physical vulnerability among the exposure pathways; (4) arsenic and cadmium should be the priority pollutants, with average physical vulnerability value contributions of 63.9% and 17.0%, respectively; (5) according to the social vulnerability assessment, the village of Luoqiao (LQ) had the highest social vulnerability (0.77); (6) for comprehensive environmental health vulnerability, five villages near mining activities and two villages far from mine-affected area had high physical and social vulnerability, and are the urgent areas for environmental risk management. In order to promote environmental risk management, it is necessary to prioritize identifying vulnerable populations in the village-scale dimension as an innovative discovery.

RETRACTED: Neighborhood-level variability in asthma-related emergency department visits in Central Texas

Background:

The extent to which asthma-related ED visit incidence rates vary from neighborhood to neighborhood and predictors of neighorbood-level asthma ED visit burden are not well understood.

Objective:

To describe the census tract-level spatial distribution of asthma-related emergency department visits in Central Texas and identify neighborhood-level characteristics that explain variability in neighborhood-level asthma ED visit rates.

Methods:

Conditional autoregressive models were used to examine the spatial distribution of asthma-related ED visit incidence rates across Travis County, TX census tracts and to assess the contribution of census tract characteristics to their distribution.

Results:

There were distinct patterns in ED visit incidence rates at the census tract scale, which were largely unexplained by socioeconomic or selected built environment neighborhood characteristics. Racial and ethnic composition explained 33% of the variability of ED visit incidence rates across census tracts. Spatial patterns and the census tract predictors of ED visit incidence rates differed by racial and ethnic groups.

Conclusions:

Variability in asthma ED visit incidence rates are apparent at a smaller spatial scales than previously examined. The majority of the variability in census tract-level asthma ED visit rates in Central Texas is not explained by racial and ethnic composition or other neighborhood features. Race/ethnicity-specific estimates of neighborhood ED visit rates may be useful for identifying high burden neighborhoods for specific ethnic/racial groups, which otherwise would go unrecognized.

Asthma ED visit rates may vary among neighborhoods; neighborhood-level interventions or moving to a low incidence neighborhood may be effective in reducing asthma disparities and deserve further study.

Quantifying the Distribution of Environmental Health Threats and Hazards in Washington State Using a Cumulative Environmental Inequality Index

Background: Environmental racism, community stressors, and age-related susceptibility play a significant role in environmental inequality. The goal of this article was to use an inequality index (II) to assess the level of equality in environmental threats and hazards based on race, poverty, and age in Washington State. Methods: Using the Washington Environmental Health Disparities Map, we quantified the level of disproportionate burdens on communities with greater populations of people of color, people in poverty, children younger than 5, and people older than 65 using 3 cumulative environmental indices and 10 individual environmental indicators. Results: Census tracts with a higher proportion of people of color and those with people living below 185% federal poverty levels were found to be disproportionately burdened by environmental threats (II = -0.175 and II = -0.167, respectively, p < 0.001). Individual environmental indicators were found to disproportionately burden communities of color and low-income communities. Children younger than 5 were also disproportionately burdened by cumulative environmental indices (II = -0.076, p < 0.001) and individual indicators. Our analysis did not show disproportionate burden of environmental health threats based on the proportion of people older than 65 (II = 0.124, p < 0.001). Discussion: The disproportionate burden of the cumulative environmental threats on communities of color and low-income communities in this study corroborates similar analyses. These findings can be applied in policy and regulatory actions to correct the distributive environmental disparities. Conclusion: We found much higher burdens among historically marginalized communities and children who are more susceptible to environmental threats and hazards.

Framing Environmental Health Decision-Making: The Struggle over Cumulative Impacts Policy

Little progress has been made to advance U.S. federal policy responses to growing scientific findings about cumulative environmental health impacts and risks, which also show that many low income and racial and ethnic minority populations bear a disproportionate share of multiple environmental burdens. Recent scholarship points to a “standard narrative” by which policy makers rationalize their slow efforts on environmental justice because of perceived lack of data and analytical tools. Using a social constructivist approach, ethnographic research methods, and content analysis, we examined the social context of policy challenges related to cumulative risks and impacts in the state of Maryland between 2014 and 2016. We identified three frames about cumulative impacts as a health issue through which conflicts over such policy reforms materialize and are sustained: (a) perceptions of evidence, (b) interpretations of social justice, and (c) expectations of authoritative bodies. Our findings illustrate that policy impasse over cumulative impacts is highly dependent on how policy-relevant actors come to frame issues around legislating cumulative impacts, rather than the “standard narrative” of external constraints. Frame analysis may provide us with more robust understandings of policy processes to address cumulative risks and impacts and the social forces that create health policy change.

Risk screening methods for extreme heat: Implications for equity-oriented adaptation

Morbidity and mortality impacts of extreme heat amplified by climate change will be unequally distributed among communities given pre-existing differences in socioeconomic, health, and environmental conditions. Many governments are interested in adaptation policies that target those especially vulnerable to the risks, but there are important questions about how to effectively identify and support communities most in need of heat adaptations. Here, we use an equity-oriented adaptation program from the state of California as a case study to evaluate the implications of the currently used environmental justice index (CalEnviroScreen 3.0) for the identification of socially vulnerable communities with climate change adaptation needs. As CalEnviroScreen is geared towards air and water pollution, we assess how community heat risks and adaptation needs would be evaluated differently under two more adaptation-relevant vulnerability indices: the Social Vulnerability Index and the Heat-Health Action Index. Our analysis considers communities at the census tract scale, as well as the patterns emerging at the regional scale. Using the current index, the state designates 25% of its census tracts as “disadvantaged” communities eligible for special adaptation funds. However, an additional 12.6% of the state’s communities could be considered vulnerable if the two other indices were considered instead. Only 13.4% of communities are vulnerable across all three vulnerability indices studied. Choice of vulnerability index shapes statewide trends in extreme heat risk and is linked to a community’s likelihood of receiving heat-related California Climate Investments (CCI) projects. Tracts that are vulnerable under the current pollution-focused index, but not under the heat-health specific index, received four times the number of heat-related interventions as tracts vulnerable under the reverse scenario. This study demonstrates important nuances relevant to implementing equity-oriented adaptation and explores the challenges, trade-offs, and opportunities in quantifying vulnerability.

Census Demographics and Chlorpyrifos Use in California's Central Valley, 2011-15: A Distributional Environmental Justice Analysis

Chlorpyrifos, an acetylcholinesterase inhibitor (ACI), is one of the most widely used insecticides in the world, and is generally recognized to be a moderate human neurotoxin. This paper reports a distributional environmental justice (dEJ) analysis of chlorpyrifos use in California’s Central Valley, examining the way distributions of environmental risks are associated with race, ethnicity, class, gender, and other systems of structural oppression. Spatial data on chlorpyrifos use were retrieved from California’s Department of Pesticide Registration public pesticide use records for 2011–2015. These data were combined with demographic data for the Central Valley from the American Community Survey (ACS). Spatial regression models were used to estimate effects of demographic covariates on local chlorpyrifos use. A novel bootstrap method was used to account for measurement error in the ACS estimates. This study finds consistent evidence that Hispanic population proportion is associated with increased local chlorpyrifos use. A 10-point increase in Hispanic proportion is associated with an estimated 1.05–1.4-fold increase in local chlorpyrifos use across Census tract models. By contrast, effects of agricultural employment and poverty on local chlorpyrifos use are ambiguous and inconsistent between Census tracts and Census-designated places.

Collins T, Rubio R. Distributional Environmental Injustices for a Minority Group without Minority Status: Arab Americans and Residential Exposure to Carcinogenic Air Pollution in the US

Distributional environmental injustices in residential exposure to air pollution in Arab American enclaves have not been examined. We conducted our investigation at the census tract-level across the continental United States using a set of socio-demographic variables to predict cancer risk from hazardous air pollutant (HAP) exposure. Arab enclaves had a mean cancer risk score of 44.08, as compared to 40.02 in non-enclave tracts. In terms of the specific origin groups, Moroccan enclaves had the highest cancer risk score (46.93), followed by Egyptian (45.33), Iraqi (43.13), Jordanian (41.67), and Lebanese (40.65). In generalized estimating equations controlling for geographic clustering and other covariates, Arab enclaves had significantly higher cancer risks due to HAPs (p < 0.001) than non-enclaves. When looking at specific ethnic origins, Iraqi, Palestinian, and Lebanese enclaves had significantly higher cancer risks due to HAPs (all p < 0.01) than non-enclaves. Results reveal significant environmental injustices for Arab American enclaves that should be examined in future studies. Results suggest that environmental injustice may be another way in which Arab Americans are disadvantaged as a racialized minority group without minority status.

The Washington State Environmental Health Disparities Map: Development of a Community-Responsive Cumulative Impacts Assessment Tool

Communities across Washington State have expressed the need for neighborhood-level information on the cumulative impact of environmental hazards and social conditions to illuminate disparities and address environmental justice issues. Many existing mapping tools have not explicitly integrated community voice and lived experience as an integral part of their development. The goals of this project were to create a new community–academic–government partnership to collect and summarize community concerns and to develop a publicly available mapping tool that ranks relative environmental health disparities for populations across Washington State. Using a community-driven framework, we developed the Washington Environmental Health Disparities Map, a cumulative environmental health impacts assessment tool. Nineteen regularly updated environmental and population indicators were integrated into the geospatial tool that allows for comparisons of the cumulative impacts between census tracts. This interactive map provides critical information for the public, agencies, policymakers, and community-based organizations to make informed decisions. The unique community–academic–government partnership and the community-driven framework can be used as a template for other environmental and social justice mapping endeavors.

MI-Environment: Geospatial patterns and inequality of relative heat stress vulnerability in Michigan

Heat stress causes morbidity and mortality and is increasing with climate change. Heat stress can pose particular challenges in northern regions not well adapted to heat. To assist decision makers, we identified the relative vulnerability of census tracts within Michigan to factors that increase exposure to heat stress or reflect susceptibilities in the population based on a California heat vulnerability index. In the MI-Environment assessment, we used a Geographic Information System (GIS) to combine future ensemble climate model projections to create a total of 9 geospatial and demographic variables. As part of a broader planned cumulative environmental exposure assessment, the statewide heat vulnerability index (HVI) maps display the location and relative magnitude of exposure on three metrics: built environment (Place), future expected long-term temperature averages (Temperature), and population susceptibility (People). We observed varied and distinct patterns for each of the three component indices. We assessed how equitably those exposures are distributed by racial and socioeconomic factors. This analysis showed that each of the component indices and the aggregate HVI are disproportionately distributed along racial and socioeconomic lines in Michigan. Census tracts with higher percentages of people of color had larger exposure to HVI factors with a deviation from equity of -0.115 [95% CI -0.108, -0.122]. Similarly, for census tracts with higher percentage of people experiencing poverty, the deviation from equity was -0.101 [95% CI -0.094, -0.107]. The MI-Environment visualization tool can help communities prepare for climate change and resolve inequities by identifying census tracts with the most vulnerable residents and highest potential exposures.

Racialized Structural Vulnerability: Neighborhood Racial Composition, Concentrated Disadvantage, and Fine Particulate Matter in California

This study contributes to previous research by advancing a “racialized structural vulnerability” framework and presenting a new empirical analysis of the relationship between neighborhood Asian, Black, and Latinx composition; extrinsic and intrinsic vulnerability; and PM_2.5 exposures in California with secondary data from 2004–2014. Principal component analyses revealed that tract Latinx composition was highly correlated with extrinsic vulnerability (economic disadvantage and limited English-speaking ability), and that tract Black composition was highly correlated with intrinsic vulnerability (elevated prevalence of asthma-related emergency department visits and low birth weight). Spatial lag regression models tested hypotheses regarding the association between Asian, Black, and Latinx population vulnerability factors and the 2009–2011 annual average PM_2.5 percentile rankings, net of emissions and spatial covariates. Results indicated that the percent Latinx population, followed by the regional clustering of PM_2.5, and the percent of non-Latinx Black and non-Latinx Asian population were the strongest positive multivariable correlates of PM_2.5 percentile rankings, net of other factors. Additional analyses suggested that despite shifting demographic and spatial correlates of 2012–2014 PM_2.5 exposures, the tracts’ Black and Latinx composition and location in the San Joaquin Valley remain important vulnerability factors with implications for future research and policy.

Vehicular Air Pollution in Houston, Texas: An Intra-Categorical Analysis of Environmental Injustice

This article contributes to distributive environmental justice (EJ) research on air pollution by analyzing racial/ethnic and related intra-categorical disparities in health risk from exposure to on-road hazardous air pollutants (HAPs) in Harris County, Texas. Previous studies in this urban area have not examined intra-ethnic heterogeneity in EJ outcomes or disproportionate exposure to vehicular pollutants. Our goal was to determine how the EJ implications of cancer risk from exposure to on-road HAP sources differ across and within each major racial/ethnic group (Hispanics, non-Hispanic Blacks, and non-Hispanic Whites), based on data from the Environmental Protection Agency's National-Scale Air Toxics Assessment (2011) and American Community Survey (2009-2013). Statistical analyses are based on generalized estimating equations which account for clustering of analytic units. Results indicated that Hispanics and non-Hispanic Blacks are exposed to significantly higher cancer risk than non-Hispanic Whites. When each racial/ethnic group was disaggregated based on contextually relevant characteristics, individuals who are in poverty, foreign-born, renters, and have limited English proficiency are found to be disproportionately located in areas exposed to significantly higher cancer risk, regardless of their major racial/ethnic designation. Our findings underscore the need to conduct intra-categorical EJ analysis for uncovering inequalities that get concealed when broadly defined racial/ethnic categories are used.

The burden of carcinogenic air toxics among Asian Americans in four US metro areas

This study investigated disparities in residential exposure to carcinogenic air pollutants among Asian Americans, including Asian ancestry subgroups, in four US metro areas with high proportions of Asians, i.e., Honolulu, Los Angeles, San Francisco Bay Area, and Seattle. Generalized estimating equations adjusting for socioeconomic status, population density and clustering show that a greater proportion of Asian Americans in census tracts was associated with significantly greater health risk in all four metro areas. Intracategorical disparities were uncovered for Asian ancestry. A greater proportion Korean was positively associated with risk in four metro areas; greater proportion Chinese and Filipino were positively associated with risk in three of the four metro areas. While Asian Americans are infrequently examined in environmental justice research, these results demonstrate that Asian Americans experience substantial distributional environmental injustices in these four metro areas and that ancestry is an important dimension of intracategorical complexity.

Hurricane Harvey and people with disabilities: Disproportionate exposure to flooding in Houston, Texas

While numerous environmental justice (EJ) studies have found socially disadvantaged groups such as racial/ethnic minorities and low-income individuals to be disproportionately affected by environmental hazards, previous EJ research has not examined whether disabled individuals are disproportionately exposed to natural hazards. Our article addresses this gap by conducting the first distributive EJ study of the relationship between flooding caused by Hurricane Harvey and locations of people with disabilities in Harris County, the most populous county in Texas that was severely impacted by this disaster. Our objective is to determine whether the areal extent of flooding at the neighborhood (census tract) level is disproportionately distributed with respect to people with any disability and with specific types of disabilities, after controlling for relevant socio-demographic factors. Our study integrates cartographic information from Harvey's Inundation Footprint developed by the U.S. Federal Emergency Management Agency with data on disability and socio-demographic characteristics from the 2012-2016 American Community Survey. Statistical analyses are based on bivariate correlations and multivariate generalized estimating equations, a modeling technique appropriate for clustered data. Results indicate that the areal extent of Harvey-induced flooding is significantly greater in neighborhoods with a higher proportion of disabled residents, after controlling for race/ethnicity, socioeconomic factors, and clustering. Disabled individuals with cognitive and ambulatory difficulties are more likely to reside in neighborhoods with a higher proportion of flooded area, compared to those facing other types of difficulties. These results represent an important starting point for more detailed investigation on the disproportionate impacts associated with Hurricane Harvey for people with disabilities. Our findings also highlight the growing need to consider individuals with physical and mental disabilities in future EJ research, as well as planning and management of natural disasters.

Utilization of the Maryland Environmental Justice Screening Tool: A Bladensburg, Maryland Case Study

Maryland residents' knowledge of environmental hazards and their health effects is limited, partly due to the absence of tools to map and visualize distribution of risk factors across sociodemographic groups. This study discusses the development of the Maryland EJSCREEN (MD EJSCREEN) tool by the National Center for Smart Growth in partnership with faculty at the University of Maryland School of Public Health. The tool assesses environmental justice risks similarly to the U.S. Environmental Protection Agency's (USEPA) EJSCREEN tool and California's tool, CalEnviroScreen 3.0. We discuss the architecture and functionality of the tool, indicators of importance, and how it compares to USEPA's EJSCREEN and CalEnviroScreen. We demonstrate the use of MD EJSCREEN through a case study on Bladensburg, Maryland, a town in Prince George's County (PG) with several environmental justice concerns including air pollution from traffic and a concrete plant. Comparison reveals that environmental and demographic indicators in MD EJSCREEN most closely resemble those in EPA EJSCREEN, while the scoring is most similar to CalEnviroScreen. Case study results show that Bladensburg has a Prince George's environmental justice score of 0.99, and that National Air Toxics Assessment (NATA) air toxics cancer risk is concentrated in communities of color.

Impaired Water Hazard Zones: Mapping Intersecting Environmental Health Vulnerabilities and Polluter Disproportionality

This study advanced a rigorous spatial analysis of surface water-related environmental health vulnerabilities in the California Bay-Delta region, USA, from 2000 to 2006. It constructed a novel hazard indicator—“impaired water hazard zones’’—from regulatory estimates of extensive non-point-source (NPS) and point-source surface water pollution, per section 303(d) of the U.S. Clean Water Act. Bivariate and global logistic regression (GLR) analyses examined how established predictors of surface water health-hazard exposure vulnerability explain census block groups’ proximity to impaired water hazard zones in the Bay-Delta. GLR results indicate the spatial concentration of Black disadvantage, isolated Latinx disadvantage, low median housing values, proximate industrial water pollution levels, and proximity to the Chevron oil refinery—a disproportionate, “super emitter”, in the Bay-Delta—significantly predicted block group proximity to impaired water hazard zones. A geographically weighted logistic regression (GWLR) specification improved model fit and uncovered spatial heterogeneity in the predictors of block group proximity to impaired water hazard zones. The modal GWLR results in Oakland, California, show how major polluters beyond the Chevron refinery impair the local environment, and how isolated Latinx disadvantage was the lone positively significant population vulnerability factor. The article concludes with a discussion of its scholarly and practical implications.

A Novel Environmental Justice Indicator for Managing Local Air Pollution

Environmental justice efforts in the United States seek to provide equal protection from environmental hazards, such as air pollution, to all groups, particularly among traditionally disadvantaged populations. To accomplish this objective, the U.S. EPA has previously required states to use an environmental justice screening tool as part of air quality planning decision-making. The generally utilized approach to assess potential areas of environmental justice concern relies on static comparisons of environmental and demographic information to identify areas where minority and low income populations experience elevated environmental exposures, but does not include any additional information that may inform the trade-offs that sub-populations of varying socio-demographic groups make when choosing where to reside in cities. In order to address this limitation, job accessibility (measured by a mobility index defining the number of jobs available within a set commuting time) was developed as a novel environmental justice indicator of environmental justice priority areas at the local level. This approach is modeled using real-world data in Allegheny County, PA (USA), and identifies areas with relatively high levels of outdoor air pollution and low access to jobs. While traditional tools tend to flag the poorest neighborhoods for environmental justice concerns, this new method offers a more refined analysis, targeting populations suffering from the highest environmental burden without the associated benefits of urban living.