Community-based participatory research for low-cost air pollution monitoring in the wake of unconventional oil and gas development in the Ohio River Valley: Empowering impacted residents through community science
Community-based participatory research for low-cost air pollution monitoring in the wake of unconventional oil and gas development in the Ohio River Valley: Empowering impacted residents through community science
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DOI：
10.1088/1748-9326/ac6ad6
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发表时间：
2022-06-01
影响因子：
6.7
通讯作者：
Westervelt, Daniel M.
中科院分区：
文献类型：
--
作者：
Raheja, Garima;Harper, Leatra;Westervelt, Daniel M.
俄亥俄州的贝尔蒙特县主要是非常规石油和天然气开发，导致环境空气污染严重。这里的居民选择与全国志愿者网络合作，开发一种参与式科学方法，以回答有关该县及其周边地区和河谷许多工业点源对社区健康的影响与污染暴露之间关系的问题。居民们首先向负责许可和保护公共卫生的政府机构提出问题，但他们指出，缺乏详细的数据，也不了解这些行业的影响。这些居民和环保倡导者正在利用由此产生的科学与EPA展开对话，希望最终合作制定更好地保护公众健康的空气质量标准。将由35个颗粒物和25个挥发性有机化合物传感器组成的公民主导的参与式低成本、高密度空气污染传感器网络与监管监测器的测量结果进行比较，结果显示相关性较低（始终R-2 < 0.55）。这种网络分析与排放羽流的补充模型相结合，揭示了该地区稀疏的监管空气污染监测网络的不足，并为公共卫生官员提供了许多途径，以进一步验证人们的经验，并通过执法和知情的许可做法来保护居民的健康。此外，本研究开发的协作最佳实践可作为其他社区科学工作的启动平台，这些工作旨在监测当地空气质量以应对工业增长。
Belmont County, Ohio is heavily dominated by unconventional oil and gas development that results in high levels of ambient air pollution. Residents here chose to work with a national volunteer network to develop a method of participatory science to answer questions about the association between impact on the health of their community and pollution exposure from the many industrial point sources in the county and surrounding area and river valley. After first directing their questions to the government agencies responsible for permitting and protecting public health, residents noted the lack of detailed data and understanding of the impact of these industries. These residents and environmental advocates are using the resulting science to open a dialogue with the EPA in hopes to ultimately collaboratively develop air quality standards that better protect public health. Results from comparing measurements from a citizen-led participatory low-cost, high-density air pollution sensor network of 35 particulate matter and 25 volatile organic compound sensors against regulatory monitors show low correlations (consistently R-2 < 0.55). This network analysis combined with complementary models of emission plumes are revealing the inadequacy of the sparse regulatory air pollution monitoring network in the area, and opening many avenues for public health officials to further verify people's experiences and act in the interest of residents' health with enforcement and informed permitting practices. Further, the collaborative best practices developed by this study serve as a launchpad for other community science efforts looking to monitor local air quality in response to industrial growth.