Spatiotemporal Variability and Influencing Factors of Aerosol Optical Depth over the Pan Yangtze River Delta during the 2014–2017 Period

Liang Cheng, Long Li, Longqian Chen, Sai Hu, Lina Yuan, Yunqiang Liu, Yifan Cui and Ting Zhang
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Liang Cheng: School of Environmental Science and Spatial Informatics, China University of Mining and Technology, Daxue Road 1, Xuzhou 221116, China
Long Li: School of Environmental Science and Spatial Informatics, China University of Mining and Technology, Daxue Road 1, Xuzhou 221116, China
Longqian Chen: School of Environmental Science and Spatial Informatics, China University of Mining and Technology, Daxue Road 1, Xuzhou 221116, China
Sai Hu: School of Environmental Science and Spatial Informatics, China University of Mining and Technology, Daxue Road 1, Xuzhou 221116, China
Lina Yuan: School of Environmental Science and Spatial Informatics, China University of Mining and Technology, Daxue Road 1, Xuzhou 221116, China
Yunqiang Liu: School of Environmental Science and Spatial Informatics, China University of Mining and Technology, Daxue Road 1, Xuzhou 221116, China
Yifan Cui: School of Environmental Science and Spatial Informatics, China University of Mining and Technology, Daxue Road 1, Xuzhou 221116, China
Ting Zhang: School of Environmental Science and Spatial Informatics, China University of Mining and Technology, Daxue Road 1, Xuzhou 221116, China

IJERPH, 2019, vol. 16, issue 19, 1-25

Abstract: Large amounts of aerosol particles suspended in the atmosphere pose a serious challenge to the climate and human health. In this study, we produced a dataset through merging the Moderate Resolution Imaging Spectrometers (MODIS) Collection 6.1 3-km resolution Dark Target aerosol optical depth (DT AOD) with the 10-km resolution Deep Blue aerosol optical depth (DB AOD) data by linear regression and made use of it to unravel the spatiotemporal characteristics of aerosols over the Pan Yangtze River Delta (PYRD) region from 2014 to 2017. Then, the geographical detector method and multiple linear regression analysis were employed to investigate the contributions of influencing factors. Results indicate that: (1) compared to the original Terra DT and Aqua DT AOD data, the average daily spatial coverage of the merged AOD data increased by 94% and 132%, respectively; (2) the values of four-year average AOD were high in the north-east and low in the south-west of the PYRD; (3) the annual average AOD showed a decreasing trend from 2014 to 2017 while the seasonal average AOD reached its maximum in spring; and that (4) Digital Elevation Model (DEM) and slope contributed most to the spatial distribution of AOD, followed by precipitation and population density. Our study highlights the spatiotemporal variability of aerosol optical depth and the contributions of different factors over this large geographical area in the four-year period, and can, therefore, provide useful insights into the air pollution control for decision makers.

Keywords: aerosol optical depth (AOD); Pan Yangtze River Delta; MODIS; gap-filling; geographical detector method; topography (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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