Mullen Casey, Flores Aaron, Grineski Sara, Collins Timothy
Department of Sociology, University of Utah, 380 S 1530 E, Rm. 301, Salt Lake City, UT, 84112, United States.
Department of Geography, University of Utah, 260 Central Campus Dr., Rm. 4625, Salt Lake City, UT, 84112, United States.
Environ Res. 2022 Apr 15;206:112612. doi: 10.1016/j.envres.2021.112612. Epub 2021 Dec 23.
Non-governmental air quality monitoring networks include low-cost, networked air pollution sensors hosted at homes and schools that display real-time pollutant concentration estimates on publicly accessible websites. Such networks can empower people to take health-protective actions, but their unplanned organization may produce an uneven spatial distribution of sensors. Barriers to acquiring sensors may disenfranchise particular social groups. To test this directly, we quantitatively examine if there are social inequalities in the distribution of sensors in a non-governmental air quality monitoring network (PurpleAir) in Los Angeles County, California. We paired sociodemographic data from the American Community Survey and estimates of PM concentrations from the USEPA's Downscaler model at the census tract level (n = 2203) with a sensors per capita (SPC) variable, which is based on population proximity to PurpleAir sensors (n = 696) in Los Angeles County. Findings from multivariable generalized estimating equations (GEEs) controlling for clustering by housing age and value reveal patterns of environmental injustice in the distribution of PurpleAir sensors across Los Angeles County census tracts. Tracts with higher percentages of Hispanic/Latino/a and Black residents and lower median household income had decreased SPC. There was a curvilinear (concave) relationship between the percentage of renter-occupants and SPC. Sensors were concentrated in tracts with greater percentages of adults and seniors (vs. children), higher occupied housing density, and higher PM pollution. Results reveal social inequalities in the self-organizing PurpleAir network, suggesting another layer of environmental injustice such that residents of low-income and minority neighborhoods have reduced access to information about local air pollution.
非政府空气质量监测网络包括安置在家庭和学校的低成本联网空气污染传感器，这些传感器在公众可访问的网站上显示实时污染物浓度估计值。此类网络可使人们能够采取保护健康的行动，但其未经规划的组织方式可能导致传感器的空间分布不均衡。获取传感器的障碍可能会使特定社会群体无法享有相关权益。为了直接验证这一点，我们定量研究了加利福尼亚州洛杉矶县一个非政府空气质量监测网络（PurpleAir）中传感器分布是否存在社会不平等现象。我们将美国社区调查中的社会人口数据以及美国环境保护局（USEPA）的降尺度模型在普查区层面（n = 2203）对颗粒物浓度的估计值，与基于洛杉矶县居民距PurpleAir传感器的人口接近程度得出的人均传感器数量（SPC）变量进行配对。通过控制住房年龄和价值聚类的多变量广义估计方程（GEEs）得出的结果，揭示了PurpleAir传感器在洛杉矶县各普查区分布中的环境不公正模式。西班牙裔/拉丁裔居民和黑人居民比例较高且家庭收入中位数较低的普查区，其人均传感器数量减少。租房者占比与人均传感器数量之间存在曲线（凹形）关系。传感器集中在成年人和老年人（相对于儿童）比例更高、住房占用密度更高以及颗粒物污染更严重的普查区。结果揭示了自发组织的PurpleAir网络中的社会不平等现象，表明存在另一层面的环境不公正，即低收入和少数族裔社区的居民获取当地空气污染信息的机会减少。
