Hourly PM2.5 Estimation over Central and Eastern China Based on Himawari-8 Data

Remote Sensing

卷:12

Ying Li¹  Alexandru Tugui²  Kai Qin³  Yong Xue³  Yahui Che⁴  Jie Guang⁴  Cheng Fan⁴  Zixiang Wang⁴  Lu She⁴  Yanqing Xie⁴  Yanan Wen⁴ 

[1] China Academy of Culture and Tourism, Beijing International Studies University, Beijing 100024, China;

[2] Faculty of Economy and Business Administration, Alexandru Ioan Cuza University, Iasi, Blvd. Carol I no. 11 Corp B, Et. II, B505, 700506 Iasi, Romania;

[3] School of Environmental Science and Spatial Informatics, China University of Mining and Technology, No. 1 Daxue Road, Xuzhou 221116, China;

[4] State Key Laboratory of Remote Sensing Science, Jointly Sponsored by the Institute of Remote Sensing and Digital Earth of Chinese Academy of Sciences and Beijing Normal University, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100094, China;

关键词: himawari-8;    aod;    pm2.5;    igtwr;    china;    hourly;   

DOI  :  10.3390/rs12050855

来源: DOAJ

【 摘 要 】

In this study, an improved geographically and temporally weighted regression (IGTWR) model for the estimation of hourly PM2.5 concentration data was applied over central and eastern China in 2017, based on Himawari-8 Advanced Himawari Imager (AHI) data. A generalized distance based on the longitude, latitude, day, hour, and land use type was constructed. AHI aerosol optical depth, surface relative humidity, and boundary layer height (BLH) data were used as independent variables to retrieve the hourly PM_2.5 concentrations at 1:00, 2:00, 3:00, 4:00, 5:00, 6:00, 7:00, and 8:00 UTC (Coordinated Universal Time). The model fitting and cross-validation performance were satisfactory. For the model fitting set, the correlation coefficient of determination (R²) between the measured and predicted PM_2.5 concentrations was 0.886, and the root-mean-square error (RMSE) of 437,642 samples was only 12.18 µg/m³. The tenfold cross-validation results of the regression model were also acceptable; the correlation coefficient R² of the measured and predicted results was 0.784, and the RMSE was 20.104 µg/m³, which is only 8 µg/m³ higher than that of the model fitting set. The spatial and temporal characteristics of the hourly PM_2.5 concentration in 2017 were revealed. The model also achieved stable performance under haze and dust conditions.

【 授权许可】

Unknown