Analysis of Jing-Jin-Tang district seven-year aerosol change using MODIS data

In this paper, we explored the changes of air quality over Jing-Jin-Tang (Beijing-Tianjin-Tangshan) district during the period from 2002 to 2009. Based on Moderate Resolution Imaging Spectroradiometer (MODIS) data, Dense Dark Vegetation (DDV) algorithm is employed to retrieve the aerosol optical thickness (AOT) with 1-km resolution. Comparison of the satellite inferred AOT and the values from ground-based Aerosol Robotic Network (AERONET) sun/sky radiometer measurements indicates a good agreement (R2=0.786) in Beijing site. We compared the spatial, monthly and annual variation over Jing-Jin-Tang district and analyzed the main factors of these changes. Our study indicates that there is a decreasing trend in the annual variation of AOT since 2004. The averages of AOT were commonly higher in spring and summer than those in autumn and winter, and the retrieved AOT over cities and southern areas is obviously larger than that over rural and northern areas respectively.

[1]  Y. Balkanski,et al.  Modeling the mineralogy of atmospheric dust sources , 1999 .

[2]  Peter R. J. North,et al.  Retrieval of land surface bidirectional reflectance and aerosol opacity from ATSR-2 multiangle imagery , 1999, IEEE Trans. Geosci. Remote. Sens..

[3]  Y. J. Kaufman,et al.  Satellite measurements of aerosol mass and transport , 1984 .

[4]  Chunsheng Zhao,et al.  Characterizations of aerosols over the Beijing region: A case study of aircraft measurements , 2006 .

[5]  Dong Han,et al.  Design and application of Haze Optic Thickness retrieval model for Beijing Olympic Games , 2009, 2009 IEEE International Geoscience and Remote Sensing Symposium.

[6]  Lorraine Remer,et al.  The MODIS 2.1-μm channel-correlation with visible reflectance for use in remote sensing of aerosol , 1997, IEEE Trans. Geosci. Remote. Sens..

[7]  B. Holben,et al.  Validation of MODIS aerosol optical depth retrieval over land , 2002 .

[8]  T. Deshler A review of global stratospheric aerosol: Measurements, importance, life cycle, and local stratospheric aerosol , 2008 .

[9]  Y. J. Kaufman,et al.  Measurements Of The Aerosol Optical Thickness And The Path Radiance - Implication On Aerosol Remote Sensing And Atmospheric Corrections , 1990, 10th Annual International Symposium on Geoscience and Remote Sensing.

[10]  Alexander Smirnov,et al.  Columnar aerosol optical properties at AERONET sites in central eastern Asia and aerosol transport to the tropical mid‐Pacific , 2005 .

[11]  Y. Kaufman,et al.  Algorithm for atmospheric corrections of aircraft and satellite imagery , 1992 .

[12]  R. Martin Satellite remote sensing of surface air quality , 2008 .

[13]  A. Kokhanovsky,et al.  Aerosol remote sensing over land: A comparison of satellite retrievals using different algorithms and instruments , 2007, Atmospheric Research.

[14]  Michael D. King,et al.  Aerosol properties over bright-reflecting source regions , 2004, IEEE Transactions on Geoscience and Remote Sensing.

[15]  Jun Wang,et al.  Satellite remote sensing of particulate matter and air quality assessment over global cities , 2006 .

[16]  Y. Kaufman,et al.  Algorithm for automatic atmospheric corrections to visible and near-IR satellite imagery , 1988 .

[17]  Teruyuki Nakajima,et al.  Development of a Two-Channel Aerosol Retrieval Algorithm on a Global Scale Using NOAA AVHRR , 1999 .

[18]  Jing Li,et al.  Evaluation of the MODIS aerosol optical depth retrieval over different ecosystems in China during EAST-AIRE , 2007 .

[19]  J. Seinfeld,et al.  Atmospheric Chemistry and Physics: From Air Pollution to Climate Change , 1997 .

[20]  M. L. Laucks,et al.  Aerosol Technology Properties, Behavior, and Measurement of Airborne Particles , 2000 .