Environmental Justice Screening Tool Research Articles

Health Impacts of Environmental Inequalities in Redlined Areas

Chicago has a long history of redlining, a discriminatory housing process that has led to segregation in Chicago up to the modern day. This practice marginalized people of color and created a significant and still prevalent wealth gap between redlined and non-redlined communities. It is well known that poorer communities in Chicago are victims of negative environmental factors, such as industrial corridor proximity, and higher air pollution levels. There have been studies done on these things, but there are many overlapping factors that have led to Chicago’s prevalent inequality, creating a complex problem.
 Our study aimed to tackle some of this complexity and to analyze how various environmental indicators impacted the health outcomes of people based on the HOLC (Home Owners’ Loan Corporation) grade they lived in. We conducted a literature review to see which health impacts were tied to which significant environmental indicators and designed our technical portion to account for the complexity and inter-relation of the data, but we wanted to do more with the communities as well, rather than just analyzing data. A major part of our project was inspired by the work of Phillip Boda of UIC in regards to designing research centered around communities rather than around data. 
 We came to the conclusion that the scope of our project was larger and more complex than any two people sufficiently cover and decided to design a coding tool alongside our analysis that will allow for communities to both interpret our findings and run their own analyses in the ways they deem most useful. We hope that this can both provide communities with a more thorough understanding of the complex relations between the environment and health. We also hope to provide a tool that can be more useful than existing resources we’ve used and found to have issues, such as the EPA’s Environmental Justice Screening tool (EJScreen).
 We found that higher percentages of greenlined and bluelined areas had little significance to negative health outcomes, or lowered risk, while higher percentages of red and yellowlined areas had greater significance to the model, increasing risk of negative health outcomes with increasing area. The impact of environmental indicators on our model varied depending on the health impact being analyzed, but in the case of every health impact, there was a semi-linear positive trend when a model was created taking into account all of the independent variables and their coefficients.

Building a vision for more effective equity indices and planning tools

Recent years have seen a proliferation of equity indices and environmental justice screening tools to support more just environmental planning processes that attempt to quantify the concept of equity. While the equity index framework has proven important to advance the conversation around environmental equity and connect need to investments, we are concerned that these tools do not adequately address the intersectional nature of environmental justice concerns, effectively incorporate local knowledge on the lived experience of residents, or provide an actionable set of next steps to be taken. We see opportunities to rethink and expand on the equity index model to address issues of climate justice and preparedness through the development of Planning for Resilience and Equity through Accessible Community Technology (PREACT), a multipurpose and multi-scalar climate preparedness and neighborhood planning software application informed by both community need and community assets. This perspective article will discuss the theoretical and practical importance of adding these perspectives into screening tools and will describe our research in Philadelphia, PA aimed at understanding these challenges and developing a more inclusive and community-responsive methodology for effective tool development.

MD EJSCREEN v2.0: Visualizing Overburdening of Environmental Justice Issues Using the Updated Maryland Environmental Justice Screening Tool

MD EJSCREEN v2.0: Visualizing Overburdening of Environmental Justice Issues Using the Updated Maryland Environmental Justice Screening Tool

A mixtures approach to assessing relationships between environmental and social determinants of health and neonatal size and body composition in the Healthy Start cohort

Background: Previous studies have identified neighborhood-level environmental and social exposures associated with birth weight, but no studies have quantified the effects of simultaneous exposures across these domains. Here we used Bayesian Kernel Machine Regression (BKMR) to estimate the independent and joint effects of environmental and social exposures on birth weight in the Healthy Start cohort in Denver, CO.Methods: The initial selection of exposures was guided by an environmental justice screening tool developed for California. Data on neighborhood-level environmental (e.g., fine particulate matter, traffic counts, impervious surfaces) and social (e.g., hospitalization rates, educational attainment, and crime rates) exposures were assigned to pregnant mothers based on their census tract at enrollment. Birth weight was abstracted from medical records. We used a two-step approach to fit our model. First, we used a Bayesian nonparametric variable selection model to reduce the number of candidate exposures. Second, we fit a BKMR model with the exposures, interaction terms for all exposure pairs, and individual-level covariates.Results: We had complete data on birth weight, exposures, and covariates for 792 infants. Out of 19 exposures originally considered, the non-parametric Bayesian model selected 9 (3 environmental and 6 social). BKMR results showed a mixture with all exposures above the median was associated with decreased birth weight. The mixture components selected most frequently by the model were respiratory hospitalization rate and the percentage of households in poverty. Respiratory hospitalization rates had the greatest effect on birth weight (β = -0.03, SE = 0.06) when all other exposures were held at the 75th percentile. For some exposures (e.g., fine particulate matter), relationships with birth weight appeared non-linear.Conclusions: We identified joint effects of environmental and social exposures on birth weight. Results suggest that analyses within one domain may limit the identification of important interactions that are associated with neonatal outcomes.

The Demographics of Citizen Science Participation and Its Implications for Data Quality and Environmental Justice

Citizen science programs have been growing in popularity in recent years and can provide various benefits to participants and their communities. We sought to determine whether these benefits are equitably accessible to all by examining potential demographic disparities in participation in our statewide citizen science program. We first explored whether Illinois RiverWatch participants are demographically and geographically representative of Illinois’s population. We conducted online surveys of current participants to gather information on demographics, including race, income, and education level, and then compared these responses with the population of Illinois as a whole using (US) census data. We also examined whether RiverWatch stream sites are disproportionately located in areas of low environmental justice concern, as determined by the US Environmental Protection Agency’s (US EPA’s) Environmental Justice screening tool. We used GIS to map all stream sites (n = 936) and determined whether they were located in areas of high or low environmental justice concern. The survey data indicate that RiverWatch participants are disproportionately white, highly educated, and affluent compared with the Illinois general population. In addition, we found RiverWatch sites tend to be located in areas of lower environmental justice concern, and that areas of high environmental justice concern are underrepresented. We discuss how disparities in demographics of participants can not only indicate need for improvement in the accessibility of a citizen science program but could also harm the quality of the river-monitoring data collected, as it leads to sampling that is not accurately representative.

Environmental justice screening tools: Implications for nursing.

Environmental justice (EJ) means socially and economically disadvantaged communities and citizens are entitled to an equally clean environment and resources to enjoy. EJ communities are mostly located close to polluters such as Superfund sites, coal-fired power plants and landfills and are more likely to be exposed to higher levels of environmental hazards than the U.S. population on average. It is often a difficult task to identify EJ communities and the environmental hazards in the communities without using specific EJ screening tools. Therefore, the goal of this manuscript is to introduce public health nurses to map-based EJ screening tools. This will help public health nurses to identify EJ communities and take appropriate actions. Public Health Nurses can also use other relevant web sites, such as the U.S. Environmental Protection Agency (EPA), National Institute of Environmental Health Sciences (NIEHS) and Toxicology Data Network (TOXNET) as resources concerning potential health effects of pollutants. Using the provided tools in this paper, nurses should be able to identify EJ communities and be united to recognize barriers of EJ communities and become promoters for EJ advocacy in practice, leadership and education.

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.

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.

A multivariate analysis of CalEnviroScreen: comparing environmental and socioeconomic stressors versus chronic disease

BackgroundThe health-risk assessment paradigm is shifting from single stressor evaluation towards cumulative assessments of multiple stressors. Recent efforts to develop broad-scale public health hazard datasets provide an opportunity to develop and evaluate multiple exposure hazards in combination.MethodsWe performed a multivariate study of the spatial relationship between 12 indicators of environmental hazard, 5 indicators of socioeconomic hardship, and 3 health outcomes. Indicators were obtained from CalEnviroScreen (version 3.0), a publicly available environmental justice screening tool developed by the State of California Environmental Protection Agency. The indicators were compared to the total rate of hospitalization for 14 ICD-9 disease categories (a measure of disease burden) at the zip code tabulation area population level. We performed principal component analysis to visualize and reduce the CalEnviroScreen data and spatial autoregression to evaluate associations with disease burden.ResultsCalEnviroScreen was strongly associated with the first principal component (PC) from a principal component analysis (PCA) of all 20 variables (Spearman ρ = 0.95). In a PCA of the 12 environmental variables, two PC axes explained 43% of variance, with the first axis indicating industrial activity and air pollution, and the second associated with ground-level ozone, drinking water contamination and PM2.5. Mass of pesticides used in agriculture was poorly or negatively correlated with all other environmental indicators, and with the CalEnviroScreen calculation method, suggesting a limited ability of the method to capture agricultural exposures. In a PCA of the 5 socioeconomic variables, the first PC explained 66% of variance, representing overall socioeconomic hardship. In simultaneous autoregressive models, the first environmental and socioeconomic PCs were both significantly associated with the disease burden measure, but more model variation was explained by the socioeconomic PCs.ConclusionsThis study supports the use of CalEnviroScreen for its intended purpose of screening California regions for areas with high environmental exposure and population vulnerability. Study results further suggest a hypothesis that, compared to environmental pollutant exposure, socioeconomic status has greater impact on overall burden of disease.

The Evolution of Empirical Environmental Justice Research Methods: A Call for Greater Use of Geographically Weighted Regression

Abstract A solid body of evidence demonstrates that minority and low-income communities in the United States and elsewhere suffer disproportionately from exposure to and impacts of environmental hazards. The methods and tools researchers have used to investigate claims of environmental injustices have evolved over time; this article explores the development of empirical methods for identifying potential environmental justice communities (EJCs), including environmental justice screening tools. The value of these methods and screening tools is discussed. An opportunity to supplement preliminary “screenings” for potential EJCs with geographically weighted regression is explored, while recognizing that these methods alone are not sufficient to confirm or deny environmental injustices.

A framework for siting and dispatch of emerging energy resources to realize environmental and health benefits: Case study on peaker power plant displacement

Emerging grid resources such as energy storage and demand response have the potential to provide numerous environmental and societal benefits, but are primarily sited and operated to provide grid-specific services without optimizing these co-benefits. We present a four-metric framework to identify priority regions to deploy and dispatch these technologies to displace marginal grid air emissions with high environmental and health impacts. To the standard metrics of total mass and rate of air pollutant emissions we add location and time, to prioritize emission displacement near densely populated areas with poor air quality, especially at times when air pollutant concentrations exceed regulatory standards. We illustrate our framework with a case study using storage, demand response, and other technologies to displace peaker power plants, the highest-rate marginal emitters on the California grid. We combine spatial-temporal data on plant electricity generation, air quality standard exceedance days, and population characteristics available from environmental justice screening tool CalEnviroScreen 2.0 to determine where emissions reductions may have the greatest marginal benefit. This screening approach can inform grid siting decisions, such as storage in lieu of peaker plants in high impact regions, or dispatch protocol, such as triggering demand response instead of peaker plants on poor air quality days.

Racial/Ethnic Disparities in Cumulative Environmental Health Impacts in California: Evidence From a Statewide Environmental Justice Screening Tool (CalEnviroScreen 1.1).

We used an environmental justice screening tool (CalEnviroScreen 1.1) to compare the distribution of environmental hazards and vulnerable populations across California communities. CalEnviroScreen 1.1 combines 17 indicators created from 2004 to 2013 publicly available data into a relative cumulative impact score. We compared cumulative impact scores across California zip codes on the basis of their location, urban or rural character, and racial/ethnic makeup. We used a concentration index to evaluate which indicators were most unequally distributed with respect to race/ethnicity and poverty. The unadjusted odds of living in one of the 10% most affected zip codes were 6.2, 5.8, 1.9, 1.8, and 1.6 times greater for Hispanics, African Americans, Native Americans, Asian/Pacific Islanders, and other or multiracial individuals, respectively, than for non-Hispanic Whites. Environmental hazards were more regressively distributed with respect to race/ethnicity than poverty, with pesticide use and toxic chemical releases being the most unequal. Environmental health hazards disproportionately burden communities of color in California. Efforts to reduce disparities in pollution burden can use simple screening tools to prioritize areas for action.

Racial/Ethnic Disparities In Cumulative Environmental Health Impacts In California: Evidence From A Statewide Environmental Justice Screening Tool (Calenviroscreen 1.1)

Residential proximity and exposure to pollutants in the U.S. is often greater in low income communities and communities of color, which can contribute to greater health burdens of environmentally-s...

Environmental Reviews and Case Studies: Accounting for Diversity in Environmental Justice Screening Tools: Toward Multiple Indices of Disproportionate Impact

To comply with President Bill Clinton's Executive Order 12898 addressing environmental justice, the United States Environmental Protection Agency (EPA) has been working for over two decades to develop consistent indices and screening tools to measure disproportionate impact and identify environmental justice communities. Its efforts have been complicated by methodological problems, divergent interpretations of policy, and concerns about the misuse of such screening tools. This review of recent scholarship and developments in EPA environmental justice policy proposes that instead of a single index of disproportionate impact associated with a single type of environmental justice community, regulatory agencies should aim to produce screening tools that incorporate multiple indices of impact and a diverse typology of environmental justice communities. It argues that adopting such an approach would not only better reflect the environmental justice movement's emphasis on difference and diversity, but also produce more effective and acceptable screening tools that are less susceptible to misuse.

Environmental Justice in Permitting: State Innovations to Advance Accountability

Over the past two decades, significant progress has been made to bring environmental justice (EJ) considerations to the forefront of domestic environmental permitting, siting, and policy-making activities. When the increasingly coordinated voice of community grassroots organizations is combined with more focused EJ-oriented efforts on the part of the U.S. Environmental Protection Agency (EPA), state regulatory agencies, and permitted industries, EJ is no longer an afterthought in the context of most developmental and industrial activities. However, ensuring meaningful consideration of EJ issues in the decision making which surrounds these development and industrial activities — such that outcomes may change and true fairness and equity are promoted — requires accountability on all sides. EJ accountability can be promoted through a variety of mechanisms, including through regulation, policy, and law designed to require or promote environmental health and data reporting, community consultation and outreach, demographic studies, corporate personnel training, community capacity building, relevant combinations of local, state, or federal agency workgroups, and the application of EJ screening tools. This Article reflects on the important role state agencies play in promoting fairness and transparency via the process of limiting and managing discharges to the environment through permitting or otherwise authorizing industrial and other developmental activities. This Article looks at several U.S. state policies and procedures that promote the consideration of EJ in environmental siting and permitting. This Article concludes that these states can lead the way for others in showing how to ensure that EJ considerations are more than a mere check box exercise, and that systems with higher degrees of accountability are the most appropriate in an arena so subjective that it is prone to be given inconsistent or ineffective consideration such as EJ.