Abstract Previous research has proposed use of satellite-retrieved aerosol optical depth (AOD) to generate geospatial assessments of near-surface PM2.5 mass concentrations and potentially to provide air quality forecasts. Spatiotemporal variability in PM2.5–AOD relationships over the eastern United States of America are analyzed using surface observations, satellite data, reanalysis data, and WRF-Chem simulations. Three primary metrics are analyzed: eta (η, the ratio of PM2.5 to AOD), the correlation coefficient (ρ) between daily values of PM2.5 to AOD, and hit rate (θ, defined as co-occurrence of high PM2.5 and AOD). It is shown that mean daily η exhibits substantial geospatial variability and a pronounced seasonal cycle. η computed for 301 EPA stations ranges from 21 to 155 μg m−3 and has a domain-wide median value of 70 μg m−3. Larger values of η occur in winter and fall. There is also evidence of diurnal variability in η. Lower values are derived in analyses using AOD from Terra (i.e. the morning overpass) than when AOD from the MODIS instrument onboard Aqua (i.e. the afternoon overpass). The spatial median η from Terra is 70 vs. 93 μg m−3 from Aqua. A majority of sites exhibit statistically significant lower values of η, ρ, and θ during 2013–2017 than 2003–2007, indicating a declining association between AOD and PM2.5. This has implications for the potential to use remotely-sensed AOD to generate geospatial estimates of near-surface PM2.5. The spatial distribution of η across the 301 locations exhibits a negative dependence on planetary boundary layer height and 10 m wind speed and a positive dependence on integrated humidity in lower troposphere, urban fraction, 2 m temperature, and vegetation coverage. Simulations with WRF-Chem indicate model-derived estimates of η, ρ, and θ are highly dependent on the aerosol scheme employed but the model captures some of the spatial variability and the correct dependence of η on meteorological and land use causes of that variability.

中文翻译：

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2003-2017年美国东部PM2.5与气溶胶光学深度关系的空间特征和时间演变

摘要 先前的研究建议使用卫星检索的气溶胶光学深度 (AOD) 来生成近地表 PM2.5 质量浓度的地理空间评估，并有可能提供空气质量预测。使用地表观测、卫星数据、再分析数据和 WRF-Chem 模拟分析了美国东部 PM2.5-AOD 关系的时空变化。分析了三个主要指标：eta（η，PM2.5 与 AOD 的比率）、PM2.5 每日值与 AOD 之间的相关系数（ρ）和命中率（θ，定义为高 PM2 .5 和 AOD）。结果表明，平均每日 η 表现出显着的地理空间变异性和明显的季节性周期。为 301 个 EPA 站计算的 η 范围从 21 到 155 μg m-3，全域中值为 70 μg m-3。较大的 η 值出现在冬季和秋季。也有证据表明 η 存在昼夜变化。使用 Terra 的 AOD（即早上的立交桥）进行分析时得出的值比 Aqua 上 MODIS 仪器的 AOD（即下午的立交桥）得出的值低。Terra 的空间中值 η 为 70，而 Aqua 为 93 μg m−3。大多数站点在 2013-2017 年期间的 η、ρ 和 θ 值在统计上显着低于 2003-2007 年，表明 AOD 与 PM2.5 之间的关联性下降。这对使用遥感 AOD 生成近地表 PM2.5 的地理空间估计的潜力具有影响。η 在 301 个地点的空间分布对行星边界层高度和 10 m 风速呈负相关性，对对流层低层、城市部分、2 m 的温度和植被覆盖度。使用 WRF-Chem 进行的模拟表明，模型衍生的 η、ρ 和 θ 估计值高度依赖于所采用的气溶胶方案，但该模型捕获了一些空间变异性以及 η 对气象和土地利用原因的正确依赖性。