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Published on: January 7, 2019
Spatial autocorrelation analysis of Chinese inter-provincial industrial chemical oxygen demand discharge
Xiaofeng Zhao1, Xianjin Huang, Yibo Liu
1School of Government, Nanjing University, 22 Hankou Road, Nanjing 210093, China. zhao-xf@126.com
Abstract:
A spatial autocorrelation analysis method is adopted to process the spatial dynamic change of industrial Chemical Oxygen Demand (COD) discharge in China over the past 15 years. Studies show that amount and intensity of industrial COD discharges are on a decrease, and the tendency is more remarkable for discharge intensity. There are large differences between inter-provincial discharge amount and intensity, and with different spatial differentiation features. Global spatial autocorrelation analysis reveals that Global Moran's I of discharge amount and intensity is on the decrease. In space, there is an evolution from an agglomeration pattern to a discretization pattern. Local spatial autocorrelation analysis shows that the agglomeration area of industrial COD discharge amount and intensity varies greatly in space with time. Stringent environmental regulations and increased funding for environmental protections are the crucial factors to cut down industrial COD discharge amount and intensity.