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China's carbon emission reduction: key provincial recognition and classification policies - based on spatial autocorrelation theories and methods


By the China Medium-Long-Term Economic Growth and Control on General Amount of Coal Research Group, Wu Hong, Xu Zhaoyuan

Report No 124, 2014 (Total 4623)


The research report describes carbon emissions in the entire country and different provincial regions, according to the change of time and spatial distribution, based on total carbon emissions and geographic information data from 1980-2011, with provincial-level administrative regions in the Chinese mainland as research subjects by virtue of spatial autocorrelation theories and methods.

The research shows four relative location relation and spatial agglomerations for border provincial regions – high-high carbon emissions area (priority carbon emissions reduction), high-low area (key), low-high area (observation) and low-low (buffer) – by calculating spatial autocorrelation indices for the entire province and for parts of the province. The results help display the provinces that need urgent carbon emissions reduction as well as different characteristics and potential for different provinces.

The country needs to classify provinces into the four areas and adopt suited policies to reduce carbon emissions in a dynamic way.