Joint Medical Program, University of California Berkeley School of Public Health and University of California San Francisco School of Medicine, Berkeley, CA 94704, USA.
Division of Environmental Health Sciences, School of Public Health, University of California Berkeley, Berkeley, CA 94704, USA.
Int J Environ Res Public Health. 2020 Nov 5;17(21):8164. doi: 10.3390/ijerph17218164.
Wildfires, which are becoming more frequent and intense in many countries, pose serious threats to human health. To determine health impacts and provide public health messaging, satellite-based smoke plume data are sometimes used as a proxy for directly measured particulate matter levels. We collected data on particulate matter <2.5 μm in diameter (PM) concentration from 16 ground-level monitoring stations in the San Francisco Bay Area and smoke plume density from satellite imagery for the 2017-2018 California wildfire seasons. We tested for trends and calculated bootstrapped differences in the median PM concentrations by plume density category on a 0-3 scale. The median PM concentrations for categories 0, 1, 2, and 3 were 16, 22, 25, and 63 μg/m, respectively, and there was much variability in PM concentrations within each category. A case study of the Camp Fire illustrates that in San Francisco, PM concentrations reached their maximum many days after the peak for plume density scores. We found that air pollution characterization by satellite imagery did not precisely align with ground-level PM concentrations. Public health practitioners should recognize the need to combine multiple sources of data regarding smoke patterns when developing public guidance to limit the health effects of wildfire smoke.
野火在许多国家变得越来越频繁和剧烈,对人类健康构成严重威胁。为了确定健康影响并提供公共卫生信息,有时会使用卫星烟雾羽流数据作为直接测量的颗粒物水平的替代物。我们收集了加利福尼亚州 2017-2018 年野火季节来自旧金山湾区 16 个地面监测站的直径小于 2.5μm 的颗粒物(PM)浓度数据和卫星图像的烟雾羽流密度数据。我们测试了趋势,并按烟雾羽流密度类别(0-3 级)计算了中位数 PM 浓度的 bootstrap 差异。类别 0、1、2 和 3 的中位数 PM 浓度分别为 16、22、25 和 63μg/m,并且每个类别内的 PM 浓度变化很大。坎普火灾的案例研究表明,在旧金山,PM 浓度在烟雾羽流密度达到峰值后的许多天达到最大值。我们发现,卫星图像的空气污染特征与地面 PM 浓度并不完全一致。公共卫生从业者应该认识到,在制定限制野火烟雾对健康影响的公共指导方针时,需要结合有关烟雾模式的多个数据源。