Racial and Income Disparities in Relation to a Proposed Climate Change Vulnerability Screening Method for California

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

“…The selection of these measures considered several factors, including the regional clustering of adjusted cumulative pollution burden summarized above and previous analyses of zip code-level CalEnviroScreen 1.1 data, which found that the San Joaquin Valley (SJV) and Greater Los Angeles area in Southern California had the highest cumulative impact scores among regions in the state [ 42 ]. In addition, complimentary cumulative impact mapping studies using the CEHII [ 36 , 37 ], the CEVA [ 26 , 40 ], and the EJSM [ 25 , 35 , 38 , 39 ] focus on both regions given their significant environmental health risks and unequal cumulative pollution burdens for nonwhites and other socially-marginalized populations. Given these insights and previous environmental inequality research on the social and spatial dimensions of cumulative ambient air pollution burdens in California [ 67 ], the spatial regression analyses featured below include separate variables for the percent of tract area that intersects boundaries for the SJV and South Coast air basins [ 62 ].…”

“…California is a nationally and internationally prominent site for advancing novel cumulative impact analyses, which are linked to the state’s precedent-setting EJ and climate policies [ 5 , 18 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 ]. Legislation passed in 1999 created the legal definition of EJ in California as “the fair treatment of people of all races, cultures, and incomes with respect to the development, adoption, implementation, and enforcement of environmental laws and policies” [ 27 ] (p. 489).…”

“…This definition of cumulative impact developed alongside the emergence of innovative cumulative impact mapping techniques in California that preceded the EJ screening tool released by the U.S. Environmental Protection Agency (U.S. EPA, Washington, DC, USA) in 2015 [ 35 ]. Four prominent cumulative impact mapping tools in California are the Cumulative Environmental Hazard Inequality Index (CEHII) [ 36 , 37 ], the Environmental Justice Screening Method (EJSM) [ 35 , 38 , 39 ] and its associated Climate Change Vulnerability Screening Method (CCVSM) [ 25 ], the Cumulative Environmental Vulnerability Assessment (CEVA) [ 26 , 40 ], and the California Community Environmental Health Screening Tool (CalEnviroScreen) [ 34 , 41 , 42 , 43 ]. These cumulative impact mapping techniques similarly model the spatial concentration of chemical and nonchemical environmental stressors, as well as “intrinsic” genetic susceptibilities and health conditions and “extrinsic” social vulnerability factors that are assumed to exacerbate the effects of environmental stressors [ 23 ].…”

“…Those other predictors include regional controls for tract location in select air basins of California and plausible emission sources in CalEnviroScreen (i.e., traffic density) and previously not included in CalEnviroScreen (i.e., the extent of industrial land zoning). The regression analyses test the following four hypotheses derived from previous research [ 10 , 11 , 25 , 26 , 36 , 37 , 39 , 40 , 42 , 51 , 52 , 53 , 54 ]. These hypotheses emphasize the significant positive effects that the residential segregation (i.e., elevated tract-level concentrations) of blacks and Latinas/os have independently—and in combination with other intrinsic and extrinsic vulnerability factors—on the concentration of cumulative environmental pollution burden in California and throughout the United States.…”

An Approach to Developing Local Climate Change Environmental Public Health Indicators, Vulnerability Assessments, and Projections of Future Impacts

“…The resulting vulnerability index will combine the socioeconomic and demographic data with built and natural environment data into a cumulative vulnerability index. Examples of methodologies for developing vulnerability indices and methods for sensitivity testing have been developed by English et al [ 31 ], Houghton et al [ 32 ], Jerrett et al [ 33 ], Reid et al [ 34 ], and Tate [ 35 , 36 ].…”