Environmental Justice Assessment Research Articles

Assessing Environmental Justice at the Urban Scale: The Contribution of Lichen Biomonitoring for Overcoming the Dichotomy between Proximity-Based and Distribution-Based Approaches

In this study, we tested the use of lichen biomonitoring techniques for the assessment of air quality disparities at the urban scale. We based our evaluation on the results of a previous lichen biomonitoring study carried out in Milan (Northern Italy), which estimates the contamination by potentially toxic elements (PTEs) and its distribution over the area, also providing an evaluation of the main emission sources. Therefore, we used the traditional methodologies for environmental justice assessment: the proximity-based and the distribution-based approaches. The workflow we propose is a data-driven selection of emission sources that contributes to overcoming the dichotomy between the two approaches and is now widely debated in the scientific community. A socio-economic deprivation index was elaborated for each census unit of Milan city and then related to the proximity of the emission sources previously selected. The results suggested that in the surrounding of industries and railways, the deprivation is higher, while the proximity of main roads is inhabited by wealthier populations. The distribution-based approach was run through a quantile regression analysis, and the outcome indicated that among the wealthier groups, an increase in contamination is followed by an increase in socio-economic deprivation, whilst among the deprived groups, people with greater economic opportunities tend, however, to live in worse air quality conditions due to the proximity of communication routes. This study poses the potential to review the classical methods of EJ assessment, providing a reliable workflow applicable in urban areas—the most vulnerable in terms of air quality disparities in the present and in the future.

Dynamic Traffic Data in Machine-Learning Air Quality Mapping Improves Environmental Justice Assessment.

Air pollution poses a critical public health threat around many megacities but in an uneven manner. Conventional models are limited to depict the highly spatial- and time-varying patterns of ambient pollutant exposures at the community scale for megacities. Here, we developed a machine-learning approach that leverages the dynamic traffic profiles to continuously estimate community-level year-long air pollutant concentrations in Los Angeles, U.S. We found the introduction of real-world dynamic traffic data significantly improved the spatial fidelity of nitrogen dioxide (NO2), maximum daily 8-h average ozone (MDA8 O3), and fine particulate matter (PM2.5) simulations by 47%, 4%, and 15%, respectively. We successfully captured PM2.5 levels exceeding limits due to heavy traffic activities and providing an "out-of-limit map" tool to identify exposure disparities within highly polluted communities. In contrast, the model without real-world dynamic traffic data lacks the ability to capture the traffic-induced exposure disparities and significantly underestimate residents' exposure to PM2.5. The underestimations are more severe for disadvantaged communities such as black and low-income groups, showing the significance of incorporating real-time traffic data in exposure disparity assessment.

A hyperlocal hybrid data fusion near-road PM2.5 and NO2 annual risk and environmental justice assessment across the United States.

Exposure to traffic-related air pollutants (TRAPs) has been associated with numerous adverse health effects. TRAP concentrations are highest meters away from major roads, and disproportionately affect minority (i.e., non-white) populations often considered the most vulnerable to TRAP exposure. To demonstrate an improved assessment of on-road emissions and to quantify exposure inequity in this population, we develop and apply a hybrid data fusion approach that utilizes the combined strength of air quality observations and regional/local scale models to estimate air pollution exposures at census block resolution for the entire U.S. We use the regional photochemical grid model CMAQ (Community Multiscale Air Quality) to predict the spatiotemporal impacts at local/regional scales, and the local scale dispersion model, R-LINE (Research LINE source) to estimate concentrations that capture the sharp TRAP gradients from roads. We further apply the Regionalized Air quality Model Performance (RAMP) Hybrid data fusion technique to consider the model's nonhomogeneous, nonlinear performance to not only improve exposure estimates, but also achieve significant model performance improvement. With a R2 of 0.51 for PM2.5 and 0.81 for NO2, the RAMP hybrid method improved R2 by ~0.2 for both pollutants (an increase of up to ~70% for PM2.5 and ~31% NO2). Using the RAMP Hybrid method, we estimate 264,516 [95% confidence interval [CI], 223,506-307,577] premature deaths attributable to PM2.5 from all sources, a ~1% overall decrease in CMAQ-estimated premature mortality compared to RAMP Hybrid, despite increases and decreases in some locations. For NO2, RAMP Hybrid estimates 138,550 [69,275-207,826] premature deaths, a ~19% increase (22,576 [11,288 - 33,864]) compared to CMAQ. Finally, using our RAMP hybrid method to estimate exposure inequity across the U.S., we estimate that Minorities within 100 m from major roads are exposed to up to 15% more PM2.5 and up to 35% more NO2 than their White counterparts.

Environmental Justice in the Urban Landscape

Environmental justice is a crucial subfield within environmental politics. Environmental justice studies have often been focussed on sites of natural disasters; however, more recently the scope of environmental justice study has been expanded to include environmental justice in urban locations. First, this paper contains a literature review of prominent scholarly articles within the field of environmental justice, including historical examples of environmentally unjust policies, and the factors influencing environmental injustice. Next, this paper examines case studies of environmental hazards within North America. Finally, this paper makes policy recommendations to mitigate environmental injustice through a Canadian federal context such as mandating the creation of environmental justice assessments, in the Canadian provincial context, by encouraging the creation of an environmental justice framework, as well as through a municipal context, by encouraging the creation of an environmental justice assessment to create equity within city planning.

Developing Machine learning models for hyperlocal traffic related particulate matter concentration mapping

Recently, estimating air pollution concentrations and contributions from various sources has become a major research focus. Our research adds to the body of knowledge by developing machine learning (ML) models to avoid intermediate modeling steps using traffic and meteorological data. The ML model's overall performance in predicting air pollution concentrations at receptors outperforms previous methods. Our best model, Convolutional Long Short-Term Memory (ConvLSTM), has a Mean Relative Error (MRE) of 38.9%, which is lower than the 47.5% MRE for the single hidden layer model, the 63.2% MRE for the Convolutional Neural Network model, and the 41.5% MRE for ConvLSTM with time-series data. Memory cells help the ConvLSTM model predict a large number of spatially correlated observations. The novel ML modeling approach has low data requirements and is computationally efficient, which makes it promising for future transportation planning, epidemiology, and environmental justice assessments.

Advancing the practice of regional transportation equity analysis: a San Francisco bay area case study

As the transportation industry continues to evolve, it is urgent that we develop and implement methods for clearly evaluating the range of transportation engineering, planning, and policy impacts experienced by various population segments. While theories of transportation equity have advanced over the past decade, such advancements outpace existing methods for evaluating the fairness of large-scale transportation investments for disadvantaged communities. In this study, a regional activity-based travel model for the Bay Area, California is used to perform an equity analysis of two of the region’s transportation and land-use planning scenarios. Equity outcomes are tested relative to three equity standards: Equality, Proportionality, and Rawlsian justice. The primary objective is to demonstrate the usefulness of a full-scale activity-based travel model for regional transportation equity analysis. We demonstrate that fine-grained distributional measures play an important role in examining the individual and household-level impacts of regional transportation scenarios, and can complement existing Environmental Justice assessments and equity analyses by helping to explain underlying reasons for average group impacts. Distributional measures can further reveal harmful cases when disadvantaged groups are most likely to experience the disbenefits of the transportation scenarios. Yet, each type of measures in isolation does not tell the complete story of which planning scenario is likely to deliver more equitable outcomes. Finally, we demonstrate the significance of applying equity standards for ranking planning scenarios, and we find that the ranking of scenarios will vary according to the equity standard, as well as how associated evaluation criteria are defined.

Environmental Justice Assessment of Fine Particles, Ozone, and Mercury over the Pearl River Delta Region, China

Assessment of environmental justice (EJ, a concept related to the distributional fairness of environmental risks) is a crucial component in environmental risk management. However, the risks associated with air pollutants and toxins have rarely been evaluated jointly. Therefore, using an approach integrating modeling, data fusion, and health benefits analysis, we performed an EJ assessment on the mortalities caused by fine particle (PM2.5) and ozone (O3) concentrations and mercury (Hg) deposition over the Pearl River Delta (PRD) region. The concentration index (CI) was used to measure EJ in low-income distributions and age structures, and a larger value implied a greater EJ issue. The results revealed that the CIs of PM2.5, O3, and Hg were 0.35, 0.32, and 0.16, respectively, based on the percentage of the low-income population, and 0.39, 0.36, and 0.23, respectively, based on the elderly and children, indicating that environmental injustice was more prominent for PM2.5 and more reflected in the elderly and children. The center (e.g., Guangzhou) and some marginal areas (e.g., northeast of Jiangmen) in the PRD were overburdened areas with PM2.5, O3, and Hg pollution due to their intensive source emissions. Moreover, cumulative environmental risk (CER) corrected by population vulnerability exhibited significant differences among the cities; for example, cumulative environmental risk scores (CERSs) in Jiangmen, Huizhou, and Zhaoqing were 14.18 to 32.98 times higher than that in Shenzhen. Hence, the implementation of multipollutant control policies for local PM2.5, O3, and Hg in overburdened areas is recommended to further promote EJ in the PRD.

Combined Small- and Large-Scale Geo-Spatial Analysis of the Ruhr Area for an Environmental Justice Assessment

This paper investigates spatial relationships regarding the accessibility of urban green space, the overall yearly vitality of the surrounding vegetation, and additional indicators such as air and noise pollution, in urban areas. The analysis uses socio-economic data sets derived from a sophisticated disaggregation approach. It results from applying a new tool that processes data from coarse and small-scale data sets to smaller spatial units in order to derive more fine-grained insights into the characteristics of the smallest suburb. The consequent data sets are then augmented by comprehensive raster-based accessibility network analysis and the incorporation of measured data on air and noise pollution. Gaining an overview over the whole area on the one hand, and looking at smaller city districts in detail on the other, unveils whether there is an imbalance regarding all combined indicators. After correlating two socio-economic indicators, a spatial comparison of the preliminary results determines whether this approach reveals neighborhoods wherein residents of a lower socio-economic status are exposed to multiple threats at once. As a result, the paper presents a workflow to obtain a broader and, at the same time, more small-scale overview of polycentric agglomeration. Simultaneously, it provides a large-scale insight into single sites, right down to the city block level. Consequently, this study provides a sophisticated approach that helps to assess the quality, quantity and characteristics of the specific spatial distribution of environmental justice in small- to large-scale urban areas at a glance. The results help to identify regions of inequalities and disadvantages. They allow for querying additional values assigned to large-scale spatial units. These versatile variables provide a means to reveal other noticeable indicators. Furthermore, this entails the opportunity to evaluate the distinct living conditions of locally affected demographic groups, and improve them with tailored approaches. Finally, the results can enhance the perception of these living conditions, and be used to promote the capacity for organizing the lives of the respective residents more sustainably, helping the neighborhood to grow accordingly.

A Case Study on Assessment of Environmental Justice using GIS in Franklin County, Ohio, USA

Environmental justice is a growing concern in the United States. This study is an attempt to assess if fairness exists when it comes to the population of Franklin County concerning the location of industries based on environmental laws. Industries in Franklin County are taken into consideration and the areas surrounding it to assess the concern of environmental justice using tools in geographic information systems (GIS). This study concentrates on Franklin County as it is one of the most populated counties in Ohio as of 2019. Eleven major cities and industrial facilities are selected in Franklin County. A 4-mile buffer zone is considered around each city using ArcGIS to find the number of industries surrounding them. Pollution is gauged with the count of industries in the considered buffer zones. This study assumes that the number of industries is directly proportional to pollution. Minority and low-income data are extracted from the US Census Bureau. The number of minorities and low-income populations in the considered buffer zone is found using ArcMap. Minority population and income brackets of the population in a buffer zone are compared to the extent of industrial facilities in the same buffer zone. Statistical analysis is performed on the samples to find the correlation between the extent of industrial facilities and minorities to assess Environmental Justice. Another buffer is created using a 14-mile radius (with the centroid of the Franklin County as center) is created using EJSCREEN version 2019 to compare environmental indicators and demographic indicators with the NAAQs standard pollutants. A comparative analysis is performed to evaluate the results. The results indicate that there is no significant correlation between the minority population and industries in the selected 4-mile buffer zones. This approach can apply to any small geographic areas such as counties, zip codes, and census tracts to assess environmental justice.

Environmental Justice Assessment of Fine Particles, Ozone, and Mercury over the Pearl River Delta Region, China

Environmental Justice Assessment of Fine Particles, Ozone, and Mercury over the Pearl River Delta Region, China

Retooling Environmental Justice

This Article responds to environmental justice arguments that undermine, rather than safeguard, health and environmental quality for low-income and minority populations.  Efforts by scholars and practitioners to clearly define “environmental injustice” to facilitate use of racial discrimination legal frameworks have had minimal success and are ultimately limiting the ability to embrace a broader arsenal of weapons in the fight against injustice.  The greatest weapon of the environmental justice movement is its people.  Environmental justice must evolve more rapidly beyond efforts to merely give communities voice, and actually redistribute power and decision making to open up opportunities for social movement intersection.  The struggle to define environmental justice is difficult because it attempts to crystalize the efforts of converging social movements that continue.  This Article advocates more explicit acceptance of environmental justice as a movement which requires focus on new strategies and tools that address historic pollution and prevent future inequitable environmental impacts.  Considering the past, present, and future of environmental justice, this article advocates for expedited cleanups of historically polluted areas, mandatory environmental justice assessments (EJA) in existing planning processes, and robust environmental justice components in local land use plans; these coordinated strategies would empower communities to realize a vison of land use freed of the historic imposition of inequity.

Assessing Green Space Potential Accessibility through Urban Artificial Building Data in Nanjing, China

Green spaces play an important role in improving the health and quality of life of urban residents, and environmental justice has become one of the most debated topics for scholars and governments in China. The accessibility of green space has been recognized as an effective method for the assessment of environmental justice. Population and green space are the two basic elements for evaluating green space accessibility. However, high-precision population data are difficult to obtain. To address this issue, we propose a straightforward method to assess green space accessibility using urban artificial building data and investigate how green space distribution is correlated with the population. Our analysis uses urban artificial building data and green space data from 2018 in Nanjing, China. The results show that the overall amount of green space, is not only very low, but also unevenly distributed. From the urban center to the city outskirts, the green space changed representing an M-shaped pattern, while the population sharply declined. Given the serious mismatch between the population and green space, only about 26.4% and 51.8% of Nanjing residents could access green space within 400 and 800 m, respectively, which was far below that in cities in developed countries. For residents’ wellbeing, governments must consider increasing green space provision and promoting equal access.

An Environmental Justice Assessment of the Waste Treatment Facilities in Shanghai: Incorporating Counterfactual Decomposition into the Hedonic Price Model

Environmental justice (EJ) has become an increasingly significant issue for environmental management and has thus attracted increasing government and public attention. Although some studies have used techniques of proximity based on geographical information systems to assess EJ, their research is limited to individual or household data. Unlike the conventional hedonic price model (HPM) examining the effects of environmental features on housing rent, this article incorporates counterfactual decomposition into the HPM to estimate the environmental pressure on different groups by comparing the externality effects of municipal solid waste treatment facilities (MSWTFs) on two separate groups of people. To explore whether and, if so, the extent to which, vulnerable groups of people are restricted to disproportionate impacts of hazardous environmental facilities, this research uses Shanghai as the study area to highlight specific locations and exemplify the environmental injustice between the rich and the poor. The results, which represent the relationship between environmental quality and property prices, indicate that environmental quality is a robust predictor of housing rent. Simultaneously, the results suggest that some people conform better to environmental pressure than do others. Thus, the environmental impact of MSWTFs on different populations should be considered, and compensation policies should be implemented for disadvantaged groups.

Socioeconomic Disparities in Vape Shop Density and Proximity to Public Schools in the Conterminous United States, 2018.

We conducted an environmental justice assessment examining the distribution of specialty vape shops in relation to where minority and low-income youth live and attend school. We collated and examined the density of vape shops in public school districts in 2018 throughout the conterminous United States using geographic information systems. We calculated the proximity of vape shops to public middle and high schools through nearest neighbor analysis in QGIS software. We examined the statistical relationships between the density of vape shops in school districts, and proximity to schools, with the proportion of racial/ethnic minorities and those living in poverty. We found that vape shops are more densely distributed, and are in closer proximity to schools, in school districts with higher proportions of Asian and Black or African American populations. However, vape shops were further away from schools in school districts with higher proportions of the population in poverty. The proximity and higher density of vape shops in relationship to schools in Asian and Black or African American communities may result in disproportionate health impacts due to greater access and exposure to vape products and advertisements. Our results may help school district administrators prioritize and target efforts to curb youth vaping (e.g., health education curricula) in these school districts with high density and closer proximity of vape shops to schools. Policy efforts, such as local ordinances restricting the promotion and sale of vaping products close to schools, could help prevent disproportionate human and environmental health impacts to minorities.

May lichen biomonitoring of air pollution be used for environmental justice assessment? A case study from an area of N Italy with a municipal solid waste incinerator

In this work, we aimed to identify the contribution of a municipal solid waste incinerator (MSWI) to the air contamination of a complex urbanized area of N Italy using lichen transplants as biomonitors, and to compare the values of contamination with the data of socio-economic deprivation of the population living in the area. The method adopted allowed the identification of the elements of atmospheric origin that contaminate the study area. Although not distinguishable from the background, the contribution of the MSWI could be apportioned and mercury emerged as atmospheric tracer. Although not posing immediate risk, it is advisable to monitor in time the accumulation of Hg in biological systems. Consistently with similar studies, in the surrounding of the MSWI, we observed also the highest socio-economic deprivation. Overall, we found a close correlation between socio-economic deprivation and air pollution, clearly showing that the most disadvantaged population is clustered in the most polluted areas.

The Development of a Cumulative Stressors and Resiliency Index (CSRI) to Examine Environmental Health Risk: A South Carolina Assessment

Several South Carolina (SC) communities are overburdened by pollution and may suffer from environmental health disparities. They may also lack access to resiliency buffers (community assets) that can counteract negative environmental exposures. To effectively address this double disparity, improvements in screening approaches and cumulative risk assessment (CRA) methods are needed to better understand and mitigate risk. The purpose of this study was to develop a cumulative stressors and resiliency index (CSRI) to rank human health and environmental risks at the census tract level in SC. We performed Principal Component Analysis (PCA) on variable subcategories to reduce the proposed indicators to 20 that reflected environmental stress and resiliency in communities impacted by environmental injustice. CSRI scores (0 - 100) were computed at the census tract level and high-risk (HR) census tracts were identified as CSRI scores in the 90th percentile. We performed a one-way analysis of variance (ANOVA) on CSRI scores by Environmental Affairs (EA) region and linear regression for percent non-white and CSRI scores. Choropleth maps were developed in ArcMap 10.5 using natural breaks to visualize spatial relationships. CSRI scores ranged from 7.4 – 64.0. The mean CSRI score for SC was 29.1, which was lower than the mean score for Upstate (35.2) and Midlands (31.7) regions. The one-way ANOVA results indicated a statistically significant difference in CSRI scores by EA region (p <0.0001) except between the Lowcountry and Pee Dee regions [95% CI: -1.53, 2.68]. Based on the regression results, a one-unit increase in the percentage of non-white populations per census tract increased CSRI scores by roughly 6.1%. The results of our study provide a blueprint for targeting low resiliency communities for public health interventions and supports the inclusion of resilience factors in environmental justice (EJ) assessments.

Territorialising REDD+: Conflicts over market-based forest conservation in Lindi, Tanzania

In this paper we use the lens of political ecology to shed light on the causes and effects of pro-poor REDD+ induced land use conflicts. We build our study on recent theoretical work on territorialisation in nature conservation to analyse the conflicts and outcomes of the TFCG/Mjumita REDD+ project in Lindi, Tanzania. Drawing on qualitative fieldwork in two case study villages we argue that conservation organisations increasingly make use of participatory tools, FPIC procedures and good governance principles to include local populations in the creation of what we call market-based conservation territories (MBCT). In contrast to project developer’s claims of win–win benefits, we highlight the mixed outcomes of MBCTs and argue that their performance-driven nature and reliance on formal governance arrangements lead to the enclosure of common forests. This inevitably causes conflicts between and within villages over the meaning, ownership and access to forest resources, especially given the importance of customary relations in tropical rural contexts. We argue that despite the extensive community engagement strategy and genuine pro-poor approach of the REDD+ project, project proponents were unable to prevent land use conflicts and risks of economic and physical displacement. The specific social, economic and political conditions shaped the implementation of the project which led to negative consequences to some stakeholders despite genuinely noble intentions. Therefore, we argue that in order to achieve more positive results when creating MBCT, project developers must better acknowledge the inherent trade-offs of markets in conservation and take the limitations and realities of local governance context better into account. We suggest a more explicit assessment of social and environmental justice in the project and more context-specific efforts to prevent social harm from conservation. Theoretically, our study contributes to a better understanding of territorialisation processes under the current trend of market-based conservation.

An environmental justice assessment of public beach access in Miami, Florida

The scope of empirical environmental justice (EJ) research has expanded beyond hazards exposure to scrutinize social inequities in access to amenities, but no prior study has examined the EJ implications of public beach access. Furthermore, quantitative research on white privilege is very scarce. To address these knowledge gaps, our study examines racial/ethnic and socioeconomic inequities in access to public beaches in the Miami metropolitan statistical area, Florida. Public beach accessibility is modeled with an innovative geospatial approach that involves population weighted distances to beach access sites. To assess EJ implications of public beach access for various racial/ethnic and socioeconomically vulnerable groups, spatial regression models are estimated using census tract-level data. Results indicate that beaches are more accessible to neighborhoods with a higher proportion of non-Hispanic Whites, while neighborhoods with higher percentages of Hispanics and socioeconomically disadvantaged residents have limited access. This study demonstrates the importance of assessing white privilege and access to environmental amenities in EJ research to better understand social inequities.

Australia’s first national level quantitative environmental justice assessment of industrial air pollution

This study presents the first national level quantitative environmental justice assessment of industrial air pollution in Australia. Specifically, our analysis links the spatial distribution of sites and emissions associated with industrial pollution sources derived from the National Pollution Inventory, to Indigenous status and social disadvantage characteristics of communities derived from Australian Bureau of Statistics indicators. Our results reveal a clear national pattern of environmental injustice based on the locations of industrial pollution sources, as well as volume, and toxicity of air pollution released at these locations. Communities with the highest number of polluting sites, emission volume, and toxicity-weighted air emissions indicate significantly greater proportions of Indigenous population and higher levels of socio-economic disadvantage. The quantities and toxicities of industrial air pollution are particularly higher in communities with the lowest levels of educational attainment and occupational status. These findings emphasize the need for more detailed analysis in specific regions and communities where socially disadvantaged groups are disproportionately impacted by industrial air pollution. Our empirical findings also underscore the growing necessity to incorporate environmental justice considerations in environmental planning and policy-making in Australia.

Tribal Environmental Justice: Vulnerability, Trusteeship, and Equity under NEPA

The goal of environmental justice (EJ) is for all peoples to achieve the same degree of protection from environmental and health hazards. This suggests that impacts should be evaluated from the perspective of the affected community because only the community truly knows what is at risk from adverse impacts. If the EJ assessment is based solely on spatial analysis of demographic data with a criterion that 20% of a local community must be of a single ethnic group or below a certain income level in order to be recognized as an environmental justice community, then impacts to tribal natural resources and well-being will often be overlooked or significantly underestimated. When American Indian tribes and tribal resources are affected on or off a reservation, a proper impact assessment requires considerations of natural resource trusteeship, federal fiduciary trust obligations across ceded or usual and accustomed areas, and the spatial distribution of natural resources that are potentially impacted. This can be done within a standard National Environmental Policy Act (NEPA) format by adding tribal narratives and tribal impact measures.