NYenviroScreen: An open-source data driven method for identifying potential environmental justice communities in New York State. Issue 124 (October 2021)

• Record Type: Journal Article
• Authors: Petroni, Michael; Howard, Sarah; Howell, I. Brielle; Collins, Mary B.
• Is Part Of: Environmental science & policy. Issue 124(2021)
• Page Start: 348
• Page End: 358
• Publication Date: 2021-10
• Subjects: Actionable science -- Environmental justice -- Environmental policy -- Interactive data visualization -- Cumulative risk screening; Environmental policy -- Periodicals; Environmental sciences -- Periodicals; Environnement -- Politique gouvernementale -- Périodiques; Sciences de l'environnement -- Périodiques; Environmental policy; Environmental sciences; Periodicals; Electronic journals; 363.70561
• DOI: 10.1016/j.envsci.2021.07.004
• Languages: English
• ISSNs: 1462-9011

Abstract

Highlights: We present a framework for identifying disadvantaged environmental justice communities and communicating results for the purposes of public protections and equity investments. Cumulative burden, key variable clustering, and spatial relationship classifications methods are utilized. Code for accessing raw data, curating data on multiple scales, visualizing results in an interactive data viewer are made available and discussed. Abstract: In 2003, the New York State Department of Environmental Conservation began designating Potential Environmental Justice Areas (PEJA) for the purpose of providing public participation opportunities to disadvantaged communities during permitting deliberations. We developed NYenviroScreen to help stakeholders understand, review, and provide input for how future PEJA designation might be updated and improved, including for identifying disadvantaged communities under the newly enacted Climate Leadership and Community Protection Act (CLCPA). We present and compare three potential update methods and provide an interactive web application for investigating model components and composition. The three methods are: (i) three factor clustering using the Jenks natural breaks algorithm, (ii) a cumulative impact model adapted from CalEPA's CalEnviroScreen, and (iii) a hybrid approach that uses both methods and incorporates Federal and State recognized tribal land areas. NYenviroScreen brings together federal and state data sources related to population health, sociodemographics, environmental risk factors, and potential pollution exposures for 15, 463 census block groups. We find that a hybrid approach provides the most robust coverage for both rural and urban areas of New York State. This publicly accessible innovative approach is an important, data driven effort toward the pursuit of environmental justice in New York State.