Jayajit Chakraborty

Street Trees and Equity: Evaluating the Spatial Distribution of an Urban Amenity

While urban disamenities and pollution sources have received considerable attention in environmental justice research, few studies have examined sociospatial inequities associated with the distribution of desirable land uses. In this paper we focus on addressing this limitation by investigating the environmental equity implications of street trees—an important publicly financed amenity that provides several direct and indirect benefits to urban residents. The specific objective was to determine if the spatial distribution of public right-of-way trees is equitable with respect to race and ethnicity, income, and housing tenure in the city of Tampa, Florida, USA. We seek to extend research on equity analysis of urban amenities through several methodological innovations, including: (a) accounting for the heterogeneity of urban land use; (b) utilizing high-resolution remote sensing techniques to quantify parcel-specific tree cover; and (c) using multivariate regression models that control for spatial dependence within the data. The results support the inequity hypothesis by indicating a significantly lower proportion of tree cover on public right-of-way in neighborhoods containing a higher proportion of African-Americans, low-income residents, and renters. These findings have important implications for local public investment and policy strategies.

Exploring the Use of Buffer Analysis for the Identification of Impacted Areas in Environmental Equity Assessment

Though circular buffer zones are commonly used in environmental equity assessment, the results obtained may not be entirely accurate because physical processes rarely operate in a perfectly symmetrical manner. An integrated approach, known as geographic plume analysis, accounts for directional biases in the distribution of hazards by using a chemical dispersion model to identify areas that are likely to be exposed to toxic releases. In this paper we implement, evaluate, and compare circular and plume-based approaches to environmental equity analysis in the city of Des Moines, Iowa. For each approach, three strategies were selected to define the spatial extent and form of the buffer used to compute the population at risk. In all cases, the analyses are based on census data units and on locations of hazardous facilities listed in EPAs 1994 Toxic Release Inventory (TRI) database. At each toxic site we generated: (i) circles of radii 0.5 and 1 mile, and (ii) a composite plume footprint based on the chemical ...

Automobiles, Air Toxics, and Adverse Health Risks: Environmental Inequities in Tampa Bay, Florida

Few environmental justice studies of air pollution have examined the adverse health implications of exposure to transportation-related emissions or used statistical techniques that are appropriate for spatial data. This article addresses these gaps by examining the distribution of cancer and respiratory risks from inhalation exposure to vehicular emissions of hazardous air pollutants in the Tampa Bay Metropolitan Statistical Area, Florida. This study advances quantitative environmental justice research by (a) focusing on mobile source air pollution instead of major point sources; (b) examining the health risks of disproportionate exposure; (c) including transportation disadvantaged individuals, in addition to minority and low-income residents; and (d) using multiple regression models that account for spatial dependence. Data from the U.S. Environmental Protection Agencys 1999 National-Scale Air Toxics Assessment are utilized to estimate lifetime cancer and respiratory health risks from on-road vehicles for census tracts in the study area. Inequities associated with these risk estimates are investigated using relevant demographic and socioeconomic variables from Census 2000. Statistical analyses are based on simple comparisons, conventional multiple regression, and a set of spatial regression models that address spatial autocorrelation. Results indicate that race or ethnicity plays a persistent explanatory role in the distribution of health risks from vehicular emissions, after controlling for well-documented contextual factors. Additionally, tracts characterized by higher population density and lower rates of home ownership and vehicle ownership are facing significantly greater cancer and respiratory risks from traffic-related pollutants. These findings have several implications for transportation and land use policy in and beyond Tampa Bay.

Measuring the Digital Divide in the United States: Race, Income, and Personal Computer Ownership

Abstract This article demonstrates how the Lorenz Curve and the Gini coefficient can be used to measure inequalities in home personal computer (PC) ownership in the United States at the national, regional, and state levels. Our empirical investigation, based on supplemental data from the Current Population Survey of the U.S. Census, indicates that income inequalities are substantially smaller within white households owning a PC than African American households, at all geographic scales. While income inequalities among PC owners (households) have decreased between 1994 and 2001 in all regions and states, the magnitude of this inequality has declined more rapidly among whites compared to African Americans.

Disproportionate Proximity to Environmental Health Hazards: Methods, Models, and Measurement

We sought to provide a historical overview of methods, models, and data used in the environmental justice (EJ) research literature to measure proximity to environmental hazards and potential exposure to their adverse health effects. We explored how the assessment of disproportionate proximity and exposure has evolved from comparing the prevalence of minority or low-income residents in geographic entities hosting pollution sources and discrete buffer zones to more refined techniques that use continuous distances, pollutant fate-and-transport models, and estimates of health risk from toxic exposure. We also reviewed analytical techniques used to determine the characteristics of people residing in areas potentially exposed to environmental hazards and emerging geostatistical techniques that are more appropriate for EJ analysis than conventional statistical methods. We concluded by providing several recommendations regarding future research and data needs for EJ assessment that would lead to more reliable results and policy solutions.

Children at risk: measuring racial/ethnic disparities in potential exposure to air pollution at school and home

Study objective: This paper addresses the environmental justice implications of children’s health by exploring racial/ethnic disparities in potential exposure to air pollution, based on both school and home locations of children and three different types of pollution sources, in Orange County, Florida, USA. Methods: Using geocoded school and residence locations of 151 709 children enrolled in the public school system, distribution functions of proximity to the nearest source are generated for each type of air pollution source in order to compare the exposure potential of white, Hispanic, and black children. Discrete buffer distances are utilised to provide quantitative comparisons for statistical testing. Main results: At any given distance from each type of pollution source, the cumulative proportion of Hispanic or black children significantly exceeds the corresponding proportion of white children, for both school and home locations. Regardless of race, however, a larger proportion of children are potentially exposed to air pollution at home than at school. Conclusions: This study addresses the growing need to consider both daytime and nighttime activity patterns in the assessment of children’s exposure to environmental hazards and related health risks. The results indicate a consistent pattern of racial inequity in the spatial distribution of all types of air pollution sources examined, with black children facing the highest relative levels of potential exposure at both school and home locations.

Residential Proximity to Environmental Hazards and Adverse Health Outcomes

How living near environmental hazards contributes to poorer health and disproportionate health outcomes is an ongoing concern. We conducted a substantive review and critique of the literature regarding residential proximity to environmental hazards and adverse pregnancy outcomes, childhood cancer, cardiovascular and respiratory illnesses, end-stage renal disease, and diabetes. Several studies have found that living near hazardous wastes sites, industrial sites, cropland with pesticide applications, highly trafficked roads, nuclear power plants, and gas stations or repair shops is related to an increased risk of adverse health outcomes. Government agencies should consider these findings in establishing rules and permitting and enforcement procedures to reduce pollution from environmentally burdensome facilities and land uses.

Using GIS to Assess the Environmental Justice Consequences of Transportation System Changes

Although environmental justice research has typically focused on locations of industrial toxic releases or waste sites, recent developments in GIS and environmental modeling provide a foundation for developing measures designed to evaluate the consequences of transportation system changes. In this paper, we develop and demonstrate a workable GIS-based approach that can be used to assess the impacts of a transportation system change on minorites and low-income residents. We focus specifically on two adverse affects: vehicle-generated air pollution and noise. The buffer analysis capabilities of GIS provide a preliminary assessment of environmental justice. We integrate existing environmental pollution models with GIS software to identify the specific locations where noise and air pollution standards could be violated because of the proposed system change. A comparison of the geographic boundaries of these areas with the racial and economic characteristics of the underlying population obtained from block level census data provides a basis for evaluating disproportionate impacts. An existing urban arterial in Waterloo, Iowa, is used to illustrate the methods developed in this research.

Using Geographic Plume Analysis to assess community vulnerability to hazardous accidents

Abstract This paper describes a methodology that can be used to determine the demographic composition of a population affected by the release of toxic substances at truck accident sites. In this Geographic Plume Analysis (GPA) approach, a chemical dispersion model provides a toxic dispersal “footprint”, given information about local weather conditions and the type of chemical released. This footprint is superimposed on a demographic database to determine the composition of the affected population. The GPA approach is tested in the city of Des Moines, Iowa, to determine whether different racial and income groups are disproportionately affected by the hazards from accidents. The locations of 45 intersections that experienced the highest frequency of truck accidents from 1990 to 1992 were obtained. At each location, a plume footprint was generated, based on the release of chlorine, a commonly transported toxic material in Des Moines. Similar plumes were generated at 50 random locations in the city and similar estimates were made. The results indicated that areas most likely to experience exposure to hazardous materials transported by trucks were those with a higher proportion of minorities and low-income households, as compared to the city as a whole.

Acute exposure to extremely hazardous substances: an analysis of environmental equity.

Although environmental equity research has focused primarily on chronic pollution sources, recent advances in environmental modeling and geographic information systems (GIS) provide a foundation for developing measures that can be used to evaluate differential exposure to acute pollution events. This article describes a methodology that uses facility-specific information to develop a risk surface representing the spatial distribution of accidental exposure to hazardous substances in a study area. Environmental pollution models recommended by the U.S. Environmental Protection Agency were used in conjunction with GIS software to achieve this objective. The methodology was implemented in a large metropolitan region (Hillsborough County, Florida) to examine disproportionate exposure to worst-case releases of extremely hazardous substances. The environmental inequity hypothesis was investigated by directly comparing the distribution of potential exposures within each racial (non-White versus White) and income (below poverty versus above poverty) subgroup. The results indicate that a significantly large proportion of both non-White and impoverished individuals resided in areas potentially exposed to multiple accidental releases.