The Research Of Grey Water Footprint In China

The significance of the Water shortage and pollution is Very important,which has restricted the sustainable development of China's environmental,social and economic.The concept of grey water footprint provides a new analysis idea for comprehensive assessment of water resources scarcity and pollution.Total water resources in China are abundant,but its per capita share of water resources is much lower than the global average.And it also has the characteristic of water pollution and low water use efficiency.The papar firstly,applying the grey water footprint formula of Hoekstra,we calculated the grey footprint for 31 provinces,municipalities and autonomous regions in China from 1998 to 2012.The analysis is presented for the agricultural,industrial and domestic sectors.The results show that:China's total grey water footprint has increased from 5078.6×108m3 in 1998 to 4400.9×108m3 in 2012.The grey water footprint in the country revealed a fluctuating trend during these 15 years.Agriculture contributed the most to the grey water footprint,and industry the least.Secondly,on the basis of building load coefficient of grey water footprint,we calculated the Chinese provincial load coefficient of grey water footprint,and spatial autocorrelation methods were used to examine the grey water footprint load coefficient spatial correlation pattern and tendency.The results show that:?The grey water footprint load coefficient in China also had a fluctuating trend over the study period.The average grey water footprint load coefficient in the country over the 15 years has been classified into five categories.The first is provinces with a large load coefficient.The second is provinces with an above average load coefficient.The third is provinces with a medium load coefficient.The fourth is provinces with a below average load coefficient.The fifth is provinces with a small coefficient.?Analysis of the global spatial autocorrelation index of grey water footprint load coefficient in China from 1998 to 2012 shows that this coefficient has a spatial clustering feature,but this clustering has attenuated on an annual basis.Analysis of the local spatial autocorrelation index shows that regions with high-high correlation are mainly in North China and those with low-low correlation are largely in southern China.This paper lastly,This paper firstly,combined with the GDP data,the grey water footprint efficiency of 31 provinces in China from 1998 to 2012 was measured.By the extended Kaya identity and LMDI method to be used,the impacts of efficiency effect,structure effect,economic effect,endowment effect,development effect and technique effect on grey water footprint efficiency were examined in detail.This paper also calculated the average of absolute contribution rate of effect decomposition of grey water footprint efficiency in China,and the LSE model was applied to determine the spatial driving type.According to the analysis,The results clearly indicate the followings:?during the study period,the average of the grey water footprint in China is 4814.30 × 108m3,and grey water footprint efficiency from 16.30 yuan per cubic meter in 1998 to 89.32 yuan per cubic meter in 2012,the whole show the features that the economically developed areas is higher than the economically backward regions;?efficiency effect,economic effect,development effect and technique effect have positive impact on grey water footprint efficiency,structure effect and endowment effect have negative effect on grey water footprint efficiency,the affect of grey water footprint efficiency changes mainly by the efficiency effect and economic effect;?gray water footprint efficiency space drive types of china including two factors effect type,two factors effect type?,three factors effect,four factors effect type ?,four factors efffect type ?,five factors effect.The results of the research can not only enrichment the research of grey water footprint,but also provide theoretical support for rational utilization of regional water resources.