Considine Ellen M, Braun Danielle, Kamareddine Leila, Nethery Rachel C, deSouza Priyanka
Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts 02115, United States.
Department of Data Science, Dana-Farber Cancer Institute, Boston, Massachusetts 02215, United States.
Environ Sci Technol. 2023 Jan 9. doi: 10.1021/acs.est.2c06626.
U.S. Environmental Protection Agency (EPA) air quality (AQ) monitors, the "gold standard" for measuring air pollutants, are sparsely positioned across the U.S. Low-cost sensors (LCS) are increasingly being used by the public to fill in the gaps in AQ monitoring; however, LCS are not as accurate as EPA monitors. In this work, we investigate factors impacting the differences between an individual's true (unobserved) exposure to air pollution and the exposure reported by their nearest AQ instrument (which could be either an LCS or an EPA monitor). We use simulations based on California data to explore different combinations of hypothetical LCS placement strategies (e.g., at schools or near major roads), for different numbers of LCS, with varying plausible amounts of LCS device measurement errors. We illustrate how real-time AQ reporting could be improved (or, in some cases, worsened) by using LCS, both for the population overall and for marginalized communities specifically. This work has implications for the integration of LCS into real-time AQ reporting platforms.
美国环境保护局(EPA)的空气质量(AQ)监测器是测量空气污染物的“黄金标准”,在美国分布稀疏。公众越来越多地使用低成本传感器(LCS)来填补空气质量监测的空白;然而,LCS不如EPA监测器准确。在这项工作中,我们调查了影响个人真实(未观察到的)空气污染暴露与最近的空气质量仪器(可能是LCS或EPA监测器)报告的暴露之间差异的因素。我们使用基于加利福尼亚数据的模拟,针对不同数量的LCS,探索假设的LCS放置策略(例如,在学校或主要道路附近)的不同组合,以及不同程度的合理的LCS设备测量误差。我们说明了使用LCS对总体人群特别是边缘化社区的实时空气质量报告可能如何得到改善(或者在某些情况下恶化)。这项工作对将LCS集成到实时空气质量报告平台具有启示意义。