Generating Data Visualizations of Longitudinal Cohort Ambient Air Pollution Exposure
| Autor: | Andrew May, Jessica Castner, Luz Huntington-Moskos |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
Pollution
Organizational Behavior and Human Resource Management Strategy and Management media_common.quotation_subject Air pollution Pharmaceutical Science Participatory action research medicine.disease_cause Article Air Pollution Drug Discovery medicine Humans Clean Air Act Resource Conservation and Recovery Act Vehicle Emissions media_common Marketing Pharmacology Environmental justice Air Pollutants business.industry Data Visualization Environmental resource management Intervention (law) Environmental Justice Factory (object-oriented programming) Environmental science Health Services Research business Environmental Monitoring |
| Zdroj: | Comput Inform Nurs |
| ISSN: | 1538-9774 |
| Popis: | 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, United States. This factory had historically emitted high levels of benzene pollution and ceased operation in October 2018 due to violations of the United States Clean Air Act and United States Resource Conservation and Recovery Act. Using publicly-available air pollution and weather data, descriptive time series and windrose data visualizations were developed using open-source software as part of a 2-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. Windrose visualizations demonstrated that the wind typically blew towards 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 clean-up, 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. |
| Databáze: | OpenAIRE |
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