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The estimation of Aerosol Optical Depth in eastern China based on regression analysis

机译：基于回归分析的中国气溶胶光学深度估算

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The atmospheric pollution and air quality issues are getting worse in China, the formation mechanism of aerosols and their environment effects attracted more and more attention. Aerosol Optical Depth (AOD) is one of the most important parameters which can indicate the atmospheric turbidity and aerosol load. High-quality AOD data are significant for the study in the atmospheric environment (i.e., air quality). This paper used MODIS/Terra AOD in 2008 to improve the coverage of MODIS/Aqua AOD, which was based on linear regression analysis model. RMSE between estimation value and AOD_(Aqua) detected through satellite is 0.132. The average value of test data was 0.812. The average of regression result was 0.807. It showed that the regression model between AOD_(Terra) and AOD_(Aqua) worked well. Also, we built two sets of estimation models (MODIS AOD and OMI AOD) through stepwise regression analysis model. One is using OMI AOD and meteorological elements to estimate MODIS AOD. The value of RMSE was 0.113, which represents 13.916% of the average(R~2=0.782). The other one is using MODIS AOD and meteorological elements to estimate OMI AOD. RMSE of the model is 0.132, which represents 18.182% of the average (R~2=0.726).
机译：大气污染和空气质量问题在中国越来越差，气溶胶的形成机制及其环境影响吸引了越来越多的关注。气溶胶光学深度（AOD）是最重要的参数之一，可以指示大气浊度和气溶胶载荷。高质量的AOD数据对于大气环境（即空气质量）的研究很重要。本文在2008年使用了MODIS / TERRA AOD，提高了MODIS / AQUA AOD的覆盖范围，即基于线性回归分析模型。通过卫星检测到的估计值和AOD_（AQUA）之间的RMSE为0.132。测试数据的平均值为0.812。回归结果的平均值为0.807。它表明，AOD_（Terra）和AOD_（AQUA）之间的回归模型很好地工作。此外，我们通过逐步回归分析模型建立了两组估计模型（MODIS AOD和OMI AOD）。一个是使用OMI AOD和气象元素来估计MODIS AOD。 RMSE的值为0.113，其平均值的13.916％（R〜2 = 0.782）。另一个是使用MODIS AOD和气象元素来估计OMI AOD。该模型的RMSE为0.132，其平均值的18.182％（R〜2 = 0.726）。

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