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ESTIMATING PM2.5 IN THE BEIJING-TIANJIN-HEBEI REGION USING MODIS AOD PRODUCTS FROM 2014 TO 2015
Author(s) -
Yuenan Li,
Jianjun Wang,
Cheng Chen,
Yifei Chen,
Jonathan Li
Publication year - 2016
Publication title -
the international archives of the photogrammetry, remote sensing and spatial information sciences/international archives of the photogrammetry, remote sensing and spatial information sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.264
H-Index - 71
eISSN - 1682-1777
pISSN - 1682-1750
DOI - 10.5194/isprsarchives-xli-b2-721-2016
Subject(s) - beijing , moderate resolution imaging spectroradiometer , environmental science , particulates , megacity , air pollution , china , population , aerosol , pollution , meteorology , estimation , satellite , geography , physical geography , climatology , environmental health , medicine , ecology , chemistry , economy , archaeology , engineering , organic chemistry , management , economics , biology , aerospace engineering , geology
Fine particulate matter with a diameter less than 2.5 μm (PM2.5) has harmful impacts on regional climate, economic development and public health. The high PM2.5 concentrations in China’s urban areas are mainly caused by the combustion of coal and gasoline, industrial pollution and unknown/uncertain sources. The Beijing-Tianjin-Hebei (BTH) region with a land area of 218,000 km<sup>2</sup>, which contains 13 cities, is the biggest urbanized region in northern China. The huge population (110 million, 8% of the China’s population), local heavy industries and vehicle emissions have resulted in severe air pollution. Traditional models have used 10 km Moderate-resolution Imaging Spectroradiometer (MODIS) Aerosol Optical Depth (AOD) products and proved the statistical relationship between AOD and PM2.5. In 2014, the 3 km MODIS AOD product was released which made PM2.5 estimations with a higher resolution became possible. This study presents an estimation on PM2.5 distributions in the BTH region from September 2014 to August 2015 by combining the MODIS satellite data, ground measurements of PM2.5, meteorological parameters and social-economic factors based on the geographically weighted regression model. The results demonstrated that the 10 km AOD product provided results with a slightly higher accuracy although the 3 km AOD product could provide more information about the spatial variations of PM2.5 estimations. Additionally, compared with the global regression, the geographically weighed model was able to improve the estimation results.

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