Combined Burden of Heat and Particulate Matter Air Quality in WA Agriculture.
Combined Burden of Heat and Particulate Matter Air Quality in WA Agriculture.
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DOI：
10.1080/1059924x.2020.1795032
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发表时间：
2021-01
影响因子：
2.4
通讯作者：
Spector J
中科院分区：
文献类型：
--
作者：
Austin E;Kasner E;Seto E;Spector J
为了评估华盛顿州农业中高温和空气质量暴露的综合负担，方法是：1)描述野火季节期间高温和PM2.5暴露的时空模式；2)描述这些联合暴露对农业工人人口的潜在影响；以及3)确定解决农村地区这一负担的数据差距。我们结合了县级数据来探索数据可用性，并估计了2010至2018年间华盛顿农业工人因高温和PM2.5共同暴露造成的负担。季度农业工人人数估计与气象站网络和环境空气污染监测点的数据联系在一起。一个地理信息系统显示了最近发生的野火事件中的县、空气监测点、农作物和烟雾扩散模型的图像。我们发现，在高温和PM2.5暴露下，存在很大的时空变异性。PM2.5暴露的最大峰值往往出现在高温指数为85°F左右和夏季发生野火的时候。农业人口最多的县往往同时面临最大的高温和PM2.5暴露，这些暴露往往在第三季度(7-9月)最高，当时人口数量也最高。此外，我们观察到，在某些农村地区，获得当地空气质量信息的机会有限。我们的发现为有关农村地区最高风险地区、一年中的时间和数据可用性的努力提供了信息。了解暴露的时空模式符合精准农业框架，是解决农村农业环境中的公平问题的基础。
To evaluate the combined burden of heat and air quality exposure in Washington State agriculture by: 1) characterizing the spatiotemporal pattern of heat and PM2.5 exposures during wildfire seasons; 2) describing the potential impact of these combined exposures on agricultural worker populations; and 3) identifying data gaps for addressing this burden in rural areas. We combined county-level data to explore data availability and estimate the burden of heat and PM2.5 co-exposures for Washington agricultural workers from 2010 to 2018. Quarterly agricultural worker population estimates were linked with data from a weather station network and ambient air pollution monitoring sites. A geographical information system displayed counties, air monitoring sites, agricultural crops, and images from a smoke dispersion model during recent wildfire events. We found substantial spatial and temporal variability in high heat and PM2.5 exposures. The largest peaks in PM2.5 exposures tended to occur when the heat index was around 85°F and during summers when there were wildfires. Counties with the largest agricultural populations tended to have the greatest concurrent high heat and PM2.5 exposures, and these exposures tended to be highest during the third quarter (July-September), when population counts were also highest. Additionally, we observed limited access to local air quality information in certain rural areas. Our findings inform efforts about highest risk areas, times of year, and data availability in rural areas. Understanding the spatiotemporal pattern of exposures is consistent with the precision agriculture framework and is foundational to addressing equity in rural agricultural settings.