Generating Data Visualizations of Longitudinal Cohort Ambient Air Pollution Exposure: Report-Back Intervention Development in Participatory Action Research. Issue 1 (19th August 2021)

• Record Type: Journal Article
• Authors: Castner, Jessica; Huntington-Moskos, Luz; May, Andrew
• Is Part Of: Computers, informatics, nursing. Volume 40:Issue 1(2022)
• Page Start: 44
• Page End: 52
• Publication Date: 2021-08-19
• Subjects: Air pollutants -- Community-based participatory research -- Informatics -- Policy -- Public health informatics; Nursing -- Data processing -- Periodicals; 610.730285
• DOI: 10.1097/CIN.0000000000000821
• Languages: English
• ISSNs: 1538-2931

Abstract

Abstract : Supplemental digital content is available in the text. Abstract : A civic engagement and data science design was used to develop a report-back intervention to address stakeholder concerns related to air emissions surrounding a coke oven factory near Buffalo, NY. This factory had historically emitted high levels of benzene pollution and ceased operation in October 2018 because of violations of the US Clean Air Act and US Resource Conservation and Recovery Act. Using publicly available air pollution and weather data, descriptive time series and wind-rose data visualizations were developed using open-source software as part of a two-page report-back brief. Data from two air toxics monitoring sites in this direction suggest that industrial sources were likely the major contributor to the benzene in the air at these locations prior to May 2018, after which traffic emissions became the likely major contributor. Wind-rose visualizations demonstrated that the wind typically blew toward the northeast, which was qualitatively consistent with locations of stakeholder concerns. With the factory closed, collective efforts subsequently shifted to address traffic emission air pollution sources, factory site cleanup, and ground and water pollution mitigation. Because this intervention utilized open-source software and publicly available data, it can serve as a blueprint for future data-driven nursing interventions and community-led environmental justice efforts.