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| EJ Screening Index (EJScreen-Style)× | Environmental Justice Spatial Analysis× | |
|---|---|---|
| Alan | Environmental Sociology | Environmental Sociology |
| Aile≠ | MCDM | Process / pipeline |
| Köken yılı≠ | 2015 | 2006 |
| Köken≠ | U.S. Environmental Protection Agency (EJScreen team) | Robert D. Bullard; Paul Mohai & Robin Saha |
| Tür≠ | Composite percentile index combining environmental and demographic indicators | Spatial pipeline for testing demographic disparities in hazard proximity |
| Seminal kaynak≠ | U.S. Environmental Protection Agency (2024). EJScreen Technical Documentation for Version 2.3. Washington, DC: U.S. EPA. link ↗ | Mohai, P., & Saha, R. (2006). Reassessing Racial and Socioeconomic Disparities in Environmental Justice Research. Demography, 43(2), 383-399. DOI ↗ |
| Diğer adlar | Environmental Justice Index, EJ Composite Indicator, EJScreen Index, Cumulative Environmental Burden Index | EJ Spatial Coincidence Analysis, Distance-Based Environmental Justice Assessment, Hazard-Demographic Proximity Analysis, Disparate Siting Analysis |
| İlişkili | 4 | 4 |
| Özet≠ | An EJ screening index is a composite indicator that combines an environmental burden measure with a demographic vulnerability measure to flag communities that experience both high pollution and concentrations of low-income residents and people of color. The canonical implementation is the U.S. Environmental Protection Agency's EJScreen tool, whose technical documentation specifies how each environmental indicator is paired with a demographic index and converted into a nationwide percentile. The method is deliberately a screening device rather than a definitive measure: it is meant to surface places that warrant a closer look, not to settle exposure or causation. Each EJ index multiplies an environmental indicator by the gap between local and national demographic disadvantage, so that both high pollution and high vulnerability are required to score highly. Percentile ranking then makes otherwise incommensurable indicators comparable across the country. The result is a transparent, reproducible map of potential environmental justice concern. | Environmental justice spatial analysis tests whether environmentally hazardous facilities are located disproportionately near poor and minority communities by comparing the demographics of populations close to hazards with those farther away. The field grew out of Robert Bullard's foundational documentation in Dumping in Dixie that African American communities in the U.S. South systematically bore the burden of noxious land uses. A central methodological turning point came with Paul Mohai and Robin Saha's 2006 Demography article, which showed that the long-dominant 'unit-hazard coincidence' method, comparing only the host tract or zip code, badly understated disparities, and that distance-based methods reveal larger and more consistent inequities. The modern analysis therefore treats proximity explicitly, drawing buffers or distance bands around hazard sites and apportioning population within them. It then asks whether race and income predict who lives in the burdened zone, controlling for plausible confounders. The result is a spatially explicit test of the disparate-burden hypothesis at the heart of the environmental justice movement. |
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