Regional Estimates of Chemical Composition of Fine Particulate Matter Using a Combined Geoscience-Statistical Method with Information from Satellites, Models, and Monitors: V4.NA.02.MAPLE

We estimate ground-level fine particulate matter (PM_2.5) total and compositional mass concentrations over North America by combining Aerosol Optical Depth (AOD) retrievals from the NASA MODIS, MISR, and SeaWIFS instruments with the GEOS-Chem chemical transport model, and subsequently calibrated to regional ground-based observations of both total and compositional mass using Geographically Weighted Regression (GWR) as detailed in the provided reference for V4.NA.02. V4.NA.02.MAPLE further modified the V4.NA.02 GWR method with additional developments as part of the MAPLE (Mortality–Air Pollution Associations in Low-Exposure Environments) project. This adjustment was of particular value over low concentrations. The GWR method of individual components remains unchanged from V4.NA.02, but are provided are percentages to ensure mass closure and recommended to be applied to the V4.NA.02.MAPLE total PM_2.5. Annual datasets are provided in NetCDF [.nc]. Gridded files use the WGS84 projection. Compositional estimates are provided for sulfate (SO4), nitrate (NO3), ammonium (NH4), organic matter (OM), black carbon (BC), mineral dust (DUST), and sea-salt (SS). Percentages are denoted with a ‘p’ after component identifiers within filenames. A slight change in file name has been included for 2017, corresponding to minor internal changes compared to earlier years. Overall, however, the dataset is consistent throughout its entire time period and can be appropriately used for trend analysis. <strong>Reference:</strong><br> van Donkelaar, A., R. V. Martin, et al. (2019). <strong>Regional Estimates of Chemical Composition of Fine Particulate Matter using a Combined Geoscience-Statistical Method with Information from Satellites, Models, and Monitors.</strong> Environmental Science &amp; Technology, 2019, doi:10.1021/acs.est.8b06392.我们通过将美国国家航空航天局（National Aeronautics and Space Administration, NASA）MODIS、MISR及SeaWIFS仪器获取的气溶胶光学厚度（Aerosol Optical Depth, AOD）反演数据，与GEOS-Chem化学传输模型相结合，估算了北美地区近地面细颗粒物（PM₂.₅）的总质量浓度及其组分质量浓度；随后依据V4.NA.02的公开参考文献中的方法，使用地理加权回归（Geographically Weighted Regression, GWR）对总质量与组分质量的区域地面观测数据完成校准。V4.NA.02.MAPLE进一步针对V4.NA.02的GWR方法进行了修改，相关改进作为MAPLE（低暴露环境下的死亡率与空气污染关联，Mortality–Air Pollution Associations in Low-Exposure Environments）项目的一部分完成。该调整在低浓度区域具有特殊应用价值。各组分的GWR方法仍与V4.NA.02版本保持一致，但为确保质量闭合，数据提供了各组分占比，且建议将其应用于V4.NA.02.MAPLE的总PM₂.₅数据。本数据集以NetCDF [.nc]格式提供年度数据，网格化文件采用WGS84投影坐标系。组分估算涵盖硫酸盐（SO₄）、硝酸盐（NO₃）、铵盐（NH₄）、有机质（OM）、黑碳（BC）、矿物粉尘（DUST）以及海盐（SS）。文件名中的组分标识符后加"p"以表示占比数据。2017年的文件名略有调整，对应与早年相比的小幅内部修改。不过总体而言，该数据集在整个时间序列中保持一致，可适用于趋势分析。<strong>参考文献：</strong><br>van Donkelaar, A., R. V. Martin, 等. (2019). <strong>结合卫星、模型与监测信息的地球科学-统计联合方法估算细颗粒物化学组分的区域分布</strong>. 《环境科学与技术》, 2019, doi:10.1021/acs.est.8b06392.