Also discussed here: A Clearer Picture of China’s Air (1 page pdf, Nate Seltenrich, Environmental Health Perspectives, Feb.1, 2016)
Today we review measurements of PM 2.5 for China, derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) and the higher resolution (10 km) MODIS C6 DB AOD data, merged with the sparse ground network data from 2004 to 2013. During that time, the concentration levels of PM2.5 first increased to 2007 and then decreased from 2008 to 2013 except in the central east area of the country (near Beijing) as a result of policy decisions by the government to reduce PM 2.5 emissions. The time series of estimated data also indicated a maximum concentration in winter and a minimum in summer. The research demonstrates the value of satellite measurements to augment and extend surface networks.
Key Quotes:
“a nation - wide regulatory PM2.5 monitoring network did not exist until the end of 2012.”
“his study adopted a relatively coarse spatial resolution of 50km but did not attempt to estimate historical PM 2.5 levels. The coarse resolution was a result of the limited coverage of AOD values retrieved by the Moderate Resolution Imaging Spectroradiometer (MODIS; http://modis.gsfc.nasa.gov) instruments aboard the Terra and Aqua satellites launched by the National Aeronautics and Space Administration (NASA)”
“The overall mean PM 2.5 concentration was 77.05 μg/m3, and the mean value of our combined AOD was 0.69 “
“The seasonal patterns showed that the most polluted season was winter and the cleanest was summer, consistent with the results of our previous study”
“the overall regional trends are consistent with the environmental policy and regulation change in China. We found an inflection point for the monthly mean PM2.5 time series around 2008. The PM2.5 level increased steadily between 2004 and 2007, but the trend reversed or became non-significant after 2008, especially in the Beijing-Tianjin metropolitan region.”
“The two-stage satellite AOD model developed in the present study generated reliable historical monthly and seasonal PM2.5 predictions for China at 10-km resolution and with little bias, including data from the past decade, when the regulatory PM2.5 monitoring network did not exist.”
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