Next Article in Journal
An Improved Seeded Region Growing-Based Seamline Network Generation Method
Previous Article in Journal
Diffuse Attenuation Coefficient Retrieval in CDOM Dominated Inland Water with High Chlorophyll-a Concentrations
Previous Article in Special Issue
Correcting Measurement Error in Satellite Aerosol Optical Depth with Machine Learning for Modeling PM2.5 in the Northeastern USA
Article Menu
Issue 7 (July) cover image

Export Article

Open AccessArticle

Characteristic and Driving Factors of Aerosol Optical Depth over Mainland China during 1980–2017

Laboratory of Critical Zone Evolution, School of Earth Sciences, China University of Geosciences, Wuhan 430074, China
School of Resource and Environmental Science, Wuhan University, Wuhan 430079, China
Key Laboratory of Middle Atmosphere and Global Environment Observation (LAGEO), Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science & Technology, Nanjing 210044, China
Key Laboratory for Atmospheric Chemistry (LAC), Institute of Atmospheric Composition, Chinese Academy of Meteorological Sciences (CAMS), China Meteorological Administration (CMA), Beijing 100081, China
School of Marine Science, Nanjing University of Information Science & Technology, Nanjing 2100444, China
Author to whom correspondence should be addressed.
Remote Sens. 2018, 10(7), 1064;
Received: 18 May 2018 / Revised: 29 June 2018 / Accepted: 4 July 2018 / Published: 5 July 2018
(This article belongs to the Special Issue Aerosol Remote Sensing)
PDF [12987 KB, uploaded 5 July 2018]


Since the reform and opening up of China, the increasing aerosol emissions have posted great challenges to the country’s climate change and human health. The aerosol optical depth (AOD) is one of the main physical indicators quantifying the atmospheric turbidity and air pollution. In this study, 38-years (1980–2017) of spatial and temporal variations of AOD in China were analyzed using AOD records derived from MODIS atmosphere products and the MERRA-2 dataset. The results showed that the annual mean AOD values throughout China have gone through an increasing, but fluctuating, trend, especially in 1982 and in 1992 due to two volcano eruptions; the AOD values experienced a dramatically increasing period during 2000–2007 with the rapid economic development and “population explosions” in China/after 2008, the AOD values gradually decreased from 0.297 (2008) to 0.257 (2017). The AOD values in China were generally higher in spring than that in other seasons. The Sichuan Basin has always been an area with high AOD values owing to the strong human activity and the basin topography (hindering aerosol diffusions in the air). In contrast, the Qinghai Tibet Plateau has always been an area with low AOD values due to low aerosol emissions and clear sky conditions there. The trend analysis of AOD values during 1980–2017 in China indicated that the significant increasing trend was mainly observed in Southeastern China. By contrast, the AOD values in the northernmost of China showed a significant decreasing trend. Then, the contributions (AODP) of the AOD for black carbon aerosol (BCAOD), dust aerosol (DUAOD), organic carbon aerosol (OCAOD), sea salt aerosol (SSAOD), and SO4 aerosol (SO4AOD) to the total AOD values were calculated. The results showed that DUAOD (25.43%) and SO4AOD (49.51%) were found to be the main driving factors for the spatial and temporal variations of AOD values. Finally, the effects of anthropogenic aerosol emissions, socioeconomic factors, and land-use and land coverage changes on AOD were analyzed. The GDP, population density, and passenger traffic volume were found to be the main socioeconomic drivers for AOD distributions. Relatively larger AOD values were mainly found in urban land and land covered by water, while lower AOD values were found in grassland and permanent glacier areas. View Full-Text
Keywords: aerosol optical depth; spatial and temporal variation; driving factors; trend analysis; China aerosol optical depth; spatial and temporal variation; driving factors; trend analysis; China

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

Share & Cite This Article

MDPI and ACS Style

Qin, W.; Liu, Y.; Wang, L.; Lin, A.; Xia, X.; Che, H.; Bilal, M.; Zhang, M. Characteristic and Driving Factors of Aerosol Optical Depth over Mainland China during 1980–2017. Remote Sens. 2018, 10, 1064.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics



[Return to top]
Remote Sens. EISSN 2072-4292 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top