Monthly Global Estimates of Fine Particulate Matter and Their Uncertainty
Monthly Global Estimates of Fine Particulate Matter and Their Uncertainty
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DOI：
10.1021/acs.est.1c05309
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发表时间：
2021-11-01
影响因子：
11.4
通讯作者：
Martin, Randall, V
中科院分区：
文献类型：
--
作者：
van Donkelaar, Aaron;Hammer, Melanie S.;Martin, Randall, V
基于卫星的全球细颗粒物（PM2.5）年度估计值被广泛用于空气质量评估。在这里，我们开发并应用了一种方法，用于1998-2019年期间的月度估计和不确定性，该方法结合了气溶胶光学深度的卫星检索、化学传输模型和地面测量，以确定季节性和间歇性暴露的特征，并有助于空气质量管理。许多人口密集地区的PM2.5浓度在冬季最高，东欧、西欧、南亚和东亚的PM2.5浓度比夏季高1.5-3.0倍。在南亚，1月份，区域人口加权月度平均PM2.5浓度超过90 μ g/m3，印度恒河平原部分地区的局部浓度约为200 μ g/m3。在东亚，2010-2019年期间，月平均PM2.5浓度下降了1.6-2.6 μ g/m(3)/年，夏季比冬季早2-3年开始下降。我们发现有证据表明，全球监测的地点往往位于比全球平均PM2.5暴露水平更清洁的地区，在全球南方存在较大的测量差距。不确定性估计值与观测到的地基和卫星衍生PM2.5之间的差异具有区域一致性。聚集值的不确定性评估表明，混合PM2.5估计值提供了精确的区域尺度表示，剩余不确定性与样本量成反比。
Annual global satellite-based estimates of fine particulate matter (PM2.5) are widely relied upon for air-quality assessment. Here, we develop and apply a methodology for monthly estimates and uncertainties during the period 1998-2019, which combines satellite retrievals of aerosol optical depth, chemical transport modeling, and ground-based measurements to allow for the characterization of seasonal and episodic exposure, as well as aid air-quality management. Many densely populated regions have their highest PM2.5 concentrations in winter, exceeding summertime concentrations by factors of 1.5-3.0 over Eastern Europe, Western Europe, South Asia, and East Asia. In South Asia, in January, regional population-weighted monthly mean PM2.5 concentrations exceed 90 mu g/m(3), with local concentrations of approximately 200 mu g/m3 for parts of the Indo-Gangetic Plain. In East Asia, monthly mean PM2.5 concentrations have decreased over the period 2010-2019 by 1.6-2.6 mu g/m(3)/year, with decreases beginning 2-3 years earlier in summer than in winter. We find evidence that global-monitored locations tend to be in cleaner regions than global mean PM2.5 exposure, with large measurement gaps in the Global South. Uncertainty estimates exhibit regional consistency with observed differences between ground-based and satellite-derived PM2.5. The evaluation of uncertainty for agglomerated values indicates that hybrid PM2.5 estimates provide precise regional-scale representation, with residual uncertainty inversely proportional to the sample size.