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核心刊物最新成果分享-EHP-Satellite-Based Spatiotemporal Trends in PM2.5
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Environmental Health Perspectives 全球反演PM2.5文章请参考我的另一个帖子 http://dx.doi.org/10.1289/ehp.1409481. Background: Three decades of rapid economic development is causing severe and widespread PM2.5 (particulate matter ≤ 2.5 μm) pollution in China. However, research on the health impacts of PM2.5 exposure has been hindered by limited historical PM2.5 concentration data. oBjectives: We estimated ambient PM2.5 concentrations from 2004 to 2013 in China at 0.1° resolution using the most recent satellite data and evaluated model performance with available groundobservations. Methods: We developed a two-stage spatial statistical model using the Moderate Resolution Imaging Spectroradiometer (MODIS) Collection 6 aerosol optical depth (AOD) and assimilated meteorology, land use data, and PM2.5 concentrations from China’s recently established groundmonitoring network. An inverse variance weighting (IVW) approach was developed to combine MODIS Dark Target and Deep Blue AOD to optimize data coverage. We evaluated modelpredicted PM2.5 concentrations from 2004 to early 2014 using ground observations. results: The overall model cross-validation R2 and relative prediction error were 0.79 and 35.6%,respectively. Validation beyond the model year (2013) indicated that it accurately predicted PM2.5concentrations with little bias at the monthly (R2 = 0.73, regression slope = 0.91) and seasonal (R2 = 0.79, regression slope = 0.92) levels. Seasonal variations revealed that winter was the most polluted season and that summer was the cleanest season. Analysis of predicted PM2.5 levels showed a mean annual increase of 1.97 μg/m3 between 2004 and 2007 and a decrease of 0.46 μg/m3 between 2008 and 2013. |
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