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Using high-resolution satellite aerosol optical depth to estimate daily PM2.5 geographical distribution in Mexico City

机译:使用高分辨率卫星气溶胶光学深度估算墨西哥城每天的PM2.5地理分布

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摘要

Recent advances in estimating fine particle (PM2.5) ambient concentrations use daily satellite measurements of aerosol optical depth (AOD) for spatially and temporally resolved exposure estimates. Mexico City is a dense megacity that differs from other previously modeled regions in several ways: it has bright land surfaces, a distinctive climatological cycle, and an elevated semi-enclosed air basin with a unique planetary boundary layer dynamic. We extend our previous satellite methodology to the Mexico City area, a region with higher PM2.5 than most US and European urban areas. Using a novel 1 km resolution AOD product from the MODIS instrument, we constructed daily predictions across the greater Mexico City area for 2004–2014. We calibrated the association of AOD to PM2.5 daily using municipal ground monitors, land use, and meteorological features. Predictions used spatial and temporal smoothing to estimate AOD when satellite data were missing. Our model performed well, resulting in an out-of-sample cross validation R2 of 0.724. Cross-validated root mean squared prediction error (RMSPE) of the model was 5.55 μg/m3. This novel model reconstructs long- and short-term spatially resolved exposure to PM2.5 for epidemiological studies in Mexico City.
机译:估算细颗粒物(PM2.5)环境浓度的最新进展是使用每日卫星测量的气溶胶光学深度(AOD)进行空间和时间解析的暴露估算。墨西哥城是一个人口稠密的特大城市,在许多方面与以前的其他地区有所不同:它拥有明亮的土地表面,独特的气候周期以及高架的半封闭式空气盆,具有独特的行星边界层动力。我们将以前的卫星方法扩展到墨西哥城地区,该地区的PM2.5高于大多数美国和欧洲城市地区。使用来自MODIS仪器的新型1 km分辨率AOD产品,我们构建了2004-2014年整个大墨西哥城地区的每日天气预报。我们每天使用市政地面监测仪,土地使用和气象特征,对AOD与PM2.5的关联进行校准。当缺少卫星数据时,预测使用空间和时间平滑来估计AOD。我们的模型表现良好,得出的样本外交叉验证R 2 为0.724。交叉验证的模型均方根预测误差(RMSPE)为5.55μg/ m 3 。这个新颖的模型重建了在墨西哥城进行流行病学研究的长期和短期空间分辨的PM2.5暴露量。

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