The relationships between PM2.5 and aerosol optical depth (AOD) in mainland China: About and behind the spatio-temporal variations

Qianqian Yang; Qiangqiang Yuan; Linwei Yue; Tongwen Li; Huanfeng Shen; Liangpei Zhang

doi:10.1016/j.envpol.2019.02.071

The relationships between PM_2.5 and aerosol optical depth (AOD) in mainland China: About and behind the spatio-temporal variations

Environ Pollut. 2019 May:248:526-535. doi: 10.1016/j.envpol.2019.02.071. Epub 2019 Feb 25.

Authors

Qianqian Yang¹, Qiangqiang Yuan², Linwei Yue³, Tongwen Li⁴, Huanfeng Shen⁴, Liangpei Zhang⁵

Affiliations

¹ School of Geodesy and Geomatics, Wuhan University, Wuhan, Hubei, 430079, China.
² School of Geodesy and Geomatics, Wuhan University, Wuhan, Hubei, 430079, China; Key Laboratory of Geospace Environment and Geodesy, Ministry of Education, Wuhan University, Wuhan, 430079, Hubei, China. Electronic address: yqiang86@gmail.com.
³ Faculty of Information Engineering, China University of Geosciences, Wuhan, Hubei, 430074, China.
⁴ School of Resource and Environmental Sciences, Wuhan University, Wuhan, Hubei, 430079, China.
⁵ State Key Laboratory of Information Engineering, Survey Mapping and Remote Sensing, Wuhan University, Wuhan, Hubei, 430079, China.

PMID: 30831349
DOI: 10.1016/j.envpol.2019.02.071

Abstract

Satellite aerosol products have been widely used to retrieve ground PM_2.5 concentration because of their wide coverage and continuous spatial distribution. While more and more studies have focused on the retrieval algorithms, the foundation for the retrieval-relationship between PM_2.5 and satellite aerosol optical depth (AOD) has not been fully investigated. In this study, the relationships between PM_2.5 and AOD were investigated in 368 cities in mainland China from February 2013 to December 2017, at different temporal and regional scales. Pearson correlation coefficients and the PM_2.5/AOD ratio were used as indicators. Firstly, we established the relationship between PM_2.5 and AOD in terms of the spatio-temporal variations, and discuss the impact of some potential factors for a better understanding of the spatio-temporal variations. Spatially, we found that the correlation is higher in the Beijing-Tianjin-Hebei and Chengyu regions and weaker in coastal areas. The PM_2.5/AOD ratio shows an obvious north-south difference, with the ratio in North China higher than South China. Temporally, the correlation coefficient tends to be higher in May and September, with the PM_2.5/AOD ratio higher in winter and lower in summer. As for interannual variations, we detected a decreasing tendency for the PM_2.5-AOD correlation and PM_2.5/AOD ratio for recent years. Then, to determine the impact of the weakening of the PM_2.5-AOD relationship on PM_2.5 remote sensing retrieval performance, a geographically weighted regression (GWR) retrieval experiment was conducted. The results showed that the performance of retrievals is also decreasing while PM_2.5-AOD relationship getting weaker. Our study investigated the PM_2.5-AOD relationship over a large extent at the city scale, and investigated the temporal variations in terms of interannual variations. The results will be useful for the satellite retrieval of PM_2.5 concentration and will help us to further understand the PM_2.5 pollution situation in mainland China.

Keywords: AOD; Influencing factors; PM(2.5); Relationships; Spatio-temporal variations.

MeSH terms

Aerosols / analysis*
Air Pollutants / analysis*
Air Pollution / analysis*
Beijing
China
Cities
Environmental Monitoring / methods*
Geography
Particulate Matter / analysis*
Seasons
Spatial Regression
Spatio-Temporal Analysis*

Substances

Aerosols
Air Pollutants
Particulate Matter