以北京为研究区域, 利用MODIS气溶胶光学厚度产品AOT(Aerosol Optical Thickness)定量反演北京近地面PM2.5质量浓度。首先对MODIS AOT与对应地面实测PM2.5质量浓度为数据源, 两者的线性相关系数为0.323, 经过AOT标高订正和PM2.5湿度订正后, 两者相关系数升高为0.467; 进一步分析AOT与PM2.5的季节变化特征发现, 秋季相关性最高(0.802), 春季最低(0.252), 其他季节介于之间, 并深入分析了AOT与PM2.5自身物理化学特性及气象因子对两者相关性的影响机制; 最后在耦合标高和湿度订正基础上, 建立了一个近地面PM2.5质量浓度对数反演模型, 并与地面实测PM2.5样本进行对比分析, 结果显示均方根误差为2.84%, 平均误差为9.53%, 验证了该对数反演模型能较好的依据AOT反演近地面PM2.5质量浓度的可行性, 为卫星遥感高精度定量反演PM2.5提供了科学依据。
Urban haze is becoming more and more serious in these years, especially in the Yangtze River Delta region, the Pearl River Delta region, the Area of Beijing ferry look forward to and other cities, the PM2.5 particles are the main component. In order to mainly retrieve mass concentration about PM2.5 near the surface using MODIS AOT(aerosol optical thickness) data. Firstly, the comparison analyses between AOT from MODIS and corresponding PM2.5 mass concentration in situ are done, the direct linear correlation coefficient R=0.323. And then R=0.467 improved on the base of elevation correction for AOT and relative humidity correction for PM2.5 primarily. Secondly, the seasonal variations about AOT and PM2.5 in depth are analyzed, find that the correlation is highest in autumn, 0.802, and lowest in spring, 0.252, and other seasons are between them, and analyzing the effect mechanism from AOT and PM2.5 themselves' physical and chemical features and meteorological factors to the both correlativity. In the end, a logarithm reversion model about PM2.5 mass concentration coupled with the elevation and relative humidity correction is constructed, the RMSE is 2.84% and mean error is 9.53% respectively, compared to ground measured data. Studies show that this logarithm reversion model can retrieve PM2.5 mass concentration near the ground effectively using AOT, and provide a new scientific basis for PM2.5 reversion by remote sensing, and also valuable for haze detection.
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