Evaluation and Comparison of Spatio-Temporal Relationship between Multiple Satellite Aerosol Optical Depth (AOD) and Near-Surface PM2.5 Concentration over China

被引:2
|
作者
Xu, Qiangqiang [1 ]
Chen, Xiaoling [2 ]
Rupakheti, Dipesh [3 ]
Dong, Jiadan [2 ]
Tang, Linling [4 ,5 ]
Kang, Shichang [1 ,6 ]
机构
[1] Chinese Acad Sci, Northwest Inst Ecoenvironm & Resources, State Key Lab Cryospher Sci, Lanzhou 730000, Peoples R China
[2] Wuhan Univ, State Key Lab Informat Engn Surveying Mapping & R, Wuhan 430079, Peoples R China
[3] Nanjing Univ Informat Sci & Technol, Collaborat Innovat Ctr Atmospher Environm & Equip, Jiangsu Key Lab Atmospher Environm Monitoring & P, Nanjing 210044, Peoples R China
[4] Jiangxi Normal Univ, Sch Geog & Environm, Nanchang 330022, Jiangxi, Peoples R China
[5] Jiangxi Normal Univ, Key Lab Poyang Lake Wetland & Watershed Res, Minist Educ, Nanchang 330022, Jiangxi, Peoples R China
[6] Univ Chinese Acad Sci, Beijing 100049, Peoples R China
关键词
aerosol optical depth; PM2; 5; MODIS; MISR; VIIRS; AHI; AIR-POLLUTION; PARTICULATE MATTER; IMPACT; ASSOCIATIONS; VARIABILITY; RETRIEVALS; THICKNESS; EXPOSURE;
D O I
10.3390/rs14225841
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Given the advantages of remote sensing, an increasing number of satellite aerosol optical depths (AOD) have been utilized to evaluate near-ground PM2.5. However, the spatiotemporal relationship between AODs and PM2.5 still lacks a comprehensive investigation, especially in some regions with severe pollution within China. Here, we investigated the spatiotemporal relationships between several satellite AODs and the near-surface PM2.5 concentration across China and its 14 representative regions during 2016-2018 using the correlation coefficient (R), the PM2.5/AOD ratio (eta), the geo-detector (q), and the different aerosol-dominated regimes. The results showed that the MODIS AOD from the Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm strongly correlates with PM2.5 (R > 0.6) in China, particularly in the Chengyu (CY), Beijing-Tianjin-Hebei (BTH), and Yangtze River Delta (YRD) regions. The close correlations (R = 0.7) exist between PM2.5 and MODIS and VIIRS AOD from the deep blue (DB) algorithm in the CY, BTH, and YRD regions. Under the key aerosols affecting China (e.g., sulfate and dust), there is a strong correlation (R > 0.5) between the PM2.5 and MODIS and VIIRS AODs from the MAIAC and DB algorithms, with the higher concentration of ground-level PM2.5 per unit of these AODs (eta > 130). The MAIAC AOD (Terra/Aqua) can better explain the spatial distribution (q > 0.4) of PM2.5 than those of AODs from the dark target (DT) and DB algorithms applied to the MODIS over China and its specific regions across seasons. The performance of the Advanced Himawari Imager (AHI) AOD (R > 0.5, q > 0.3) was close to that of the MAIAC AOD during the spring and summer; however, it was far less than the MAIAC AOD in the autumn and winter seasons. The investigation provides instructions for estimating the near-surface PM2.5 concentration based on AOD in different regions of China.
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页数:20
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