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MODIS气溶胶产品AOD与PM_(2.5)、PM_(10)浓度高度相关,已广泛应用在PM_(2.5)、PM_(10)浓度模拟。该研究以新疆维吾尔自治区大型露天煤炭开采区准东矿区为研究对象,结合实测的2014年5月、7月、9月、12月PM_(2.5)、PM_(10)质量浓度数据与经过垂直湿度订正的MODIS气溶胶产品AOD,利用多元回归进行拟合建模,从建立的40个模型中选取最优模型并据此对研究区PM_(2.5)、PM_(10)的质量浓度进行定量估算。结果表明:AOD与PM_(2.5)、PM_(10)呈极显著正相关;4个月AOD与PM_(2.5)、PM_(10)质量浓度估算模型最优模型均为多项式模型;其中7月AOD与PM_(2.5)质量浓度拟合模型较好(R~2=0.625 8),实测值与预测值拟合趋势线R~2为0.805 7;9月PM_(10)拟合模型效果理想(R~2=0.732 9),实测值与预测值拟合趋势线R~2为0.807 7;将AOD代入最优模型反演PM_(2.5),从空间层面上反映出各区域PM_(2.5)浓度差异明显。研究结果可为AOD的深度利用与PM_(2.5)、PM_(10)浓度的遥感估算提供参考,在大气污染物空间分布、监测大气环境质量、污染预测等方面都具有重要意义。
MODIS aerosol products are highly correlated with the concentrations of PM 2.5 and PM 10 and have been widely used in PM 2.5 and PM 10 concentration simulation. In this study, the quasi-Dong mine in large-scale opencast coal mining area in Xinjiang Uygur Autonomous Region was selected as the research object. Based on the measured data of PM 2.5 and PM 10 in May, July, September and December 2014, The modified MODIS aerosol product AOD was fitted and multivariate regression was used to model the model. The optimal model was selected from the 40 models and the mass concentration of PM_ (2.5) and PM_ (10) in the study area was quantitatively estimated. The results showed that there was a significant positive correlation between AOD and PM 2.5 and PM 10. The optimal models of AOD, PM 2.5 and PM 10 concentration in 4 months were all polynomial models. Among them, AOD The fitted curve of PM 2.5 concentration was better (R 2 = 0.625 8), and the fitting trend line R 2 was 0.805 7 between the measured and predicted values. The PM 10 fitting model was ideal (R ~ 2 = 0.732 9). The fitted trend line R ~ 2 between the measured and predicted values was 0.807 7. The AOD was substituted into the optimal model for the inversion of PM 2.5, reflecting the difference of PM 2.5 concentration in different regions obvious. The results can provide reference for the depth utilization of AOD and the remote sensing estimation of PM_ (2.5) and PM_ (10) concentrations, which are of great significance in the spatial distribution of atmospheric pollutants, the monitoring of atmospheric environmental quality and the prediction of pollution.