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Analysis of Spatial and Temporal Variability of PM10 Concentrations Using MODIS Aerosol Optical Thickness in the Pearl River Delta Region, China

Category: Articles

Volume: 13 | Issue: 3 | Pages: 862-876
DOI: 10.4209/aaqr.2012.09.0234

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Junyu Zheng 1,2, Wenwei Che1,2, Zhuoyun Zheng1,3, Liangfu Chen4, Liuju Zhong5

  • 1 College of Environmental Science and Engineering, South China University of Technology, Guangzhou 510006, China
  • 2 Pearl River Delta Atmospheric Environmental Research Joint Laboratory, Guangzhou 510006, China
  • 3 Shenzhen Academy of Environmental Science, Shenzhen 518001, China
  • 4 State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing Applications, Chinese Academy of Sciences, Beijing 100101, China
  • 5 Guangdong Provincial Environmental Monitoring Center, Guangzhou 510045, China


Characterizing spatial and temporal variations of PM pollution is critical for a thorough understanding of its formation, transport and accumulation in the atmosphere. In this study, Aerosol Optical Thickness (AOT) data retrieved from a Moderate Resolution Imaging Spectroradiometer (MODIS) were used to investigate the spatial and temporal variations of PM10 (particles with aerodynamic diameters of less than 10 μm) pollution in the Pearl River Delta (PRD) region. Seasonal linear regression models between 1-km retrieved MODIS AOT data and ground PM10 measurements were developed for the PRD region with meteorological corrections, and were subjected to a validation against observations from the regional air monitoring network in this region from 2006 to 2008, with an overall error of less than 50%. Consistent with ground observations, the estimated PM10 concentrations from the regression models appeared to be highest in winter, lower in autumn and spring, and lowest in summer. A high PM10 concentration band was detected over the inner part of the PRD region, where heavy industries and dense populations are located. The shape and concentration levels of this band exhibit significant seasonal variations, which shift with synoptic wind direction, indicating different source regions and their contributions to the PM10 pollution in the PRD region. Several discrete “hot spots” were found in the southwest of the PRD region during spring and other seasons, where no ground measurements are available. The reasons for the formation of these hot spots are unclear, and further investigations are needed. Despite the limitations of this work, the results demonstrate the effectiveness of retrieving remote sensing data for characterizing regional aerosol pollution, together with ground measurements. The combination of satellite data and ground monitoring presented in this work can help in better understanding the sources, formation mechanisms and transport process of particulate matters on a regional scale.


Aerosol Optical Depth Satellite remote sensing Particulate matter Regression models

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