Research On The Grey Water Footprint In China

In order to enhance the utilization of water resources and the quality of water environment in China and to enrich relevant theories and researches of the water resources environment and the grey water footprint,this paper estimates the grey water footprint of agriculture,industry and household in all provinces and autonomous regions of China(the data of Hong Kong and Macao special administrative regions and Taiwan province have not been counted)from 2000 to 2014,explores the regional characteristics,changing rules and driving forces of grey water footprint,per capita grey water footprint and grey water economic productivity,and proposed countermeasures and suggestions to promote water resources environment protection and the sustainable development of economy and society.Firstly,based on calculating grey water footprint in China from 2000 to 2014,we select the population and GDP as indicators,and use the Gini coefficient to study the spatial and structural equilibrium of the grey water footprint of China during 2000-2014 in this paper.The results suggest that(1)In terms of regional equilibrium,the economic grey water footprint is close to the warning line(0.4)for a long time,and compared with the balance of population grey water footprint,the equilibrium of economic grey water footprint is worse,at the same time,the proportionality of the eastern regions in the economic grey water footprint and western regions in the population grey water footprint is relatively low;(2)In structural equilibrium respect,the Gini coefficient of economic grey water footprint has been raised to0.5896,that is to say,the proportionality has reached the"big gap"range,and the Gini coefficient of both agriculture and industry is fluctuating in the vicinity of 0.4 in these years;(3)From the point of view of the marginal effect,we could improve the overall equilibrium by reducing the grey water footprint of the heavily polluted regions of the West and the agricultural grey water footprint of each province,and promote the improvement of the equity of China’s water environment effectively.Secondly,this paper systematically measures the per capita grey water footprint in China from 2000 to 2014.And capital and labor factors which are most critical in production factors are first introduced into the research about driving effect of per capita grey water footprint,besides,the traditional environmental efficiency and technical efficiency factors are coupled.Subsequently using the extended Kaya identity and LMDI model,the driving effect of the above factors on per capita grey water footprint is analyzed synthetically.The results show that:(1)Nationwide,the biggest reduction effect comes from the technical efficiency effect,the reduction effect of capital output effect has been improved in recent years,and the increment effect of capital deepening is most(the annual average value exceeds 52.29m~3 per capita).(2)The distribution pattern of the technical efficiency effect,the capital output effect and the capital deepening effect show northwest high and southeast low;the effect of environmental efficiency and technical efficiency on Hebei,Beijing,Tianjin and Shandong have greater decrement effect on the per capita grey water footprint,and the effect of technological efficiency and capital output is more favorable for the reduction of per capita grey water footprint on other provinces;in addition,the effect of capital deepening will lead to significant increase in per capita grey water footprint in all provinces,and the increment in Tibet is over 400m~3per capita.Thirdly,this study explores the regional inequality and driving factors of the per capita grey water footprint to examine the influence of production factors and traditional factors on the inequality in per capita water resources and environment.The inequality analysis is carried out using a factorial decomposition of the second Theil index of inequality.Specifically,based on Kaya factors,the per capita grey water footprint is decomposed into five factors,including environmental efficiency,technical efficiency,capital output,capital deepening,and economic activity.We found that the overall inequality of the per capita grey water footprint has displayed a slow fluctuation in recent years.The within-group inequality component was the main contributor to the overall inequality during the entire period.There was a slight decrease in the within-group inequality in each region.In the three regions considered in this study,the within-group inequality was largest in the western region.The between-group inequality index of total inequality increased year by year.In the aspect of single factors,capital deepening and technical efficiency are the dominant factors in the total inequality of the per capita grey water footprint,as well as in the within-group inequality of the per capita grey water footprint of the central and eastern regions,respectively.Economic activity is the weakest driver of all inequality components.In addition to the economic activity effect,the other effects in the western region are the vital factors driving the within-group inequality of the per capita grey water footprint;among other factors,technical efficiency is the strongest driver of within-group inequality of the per capita grey water footprint in the western region.The interaction component results show that the contribution value of the interaction component between the capital output effect and the grey water footprint per unit GDP is the largest for the western region within-group inequality,and the contribution value of the interaction component between the capital deepening effect and the grey water footprint per unit of capital stock is greater in other regions.In terms of the interaction component between the technical efficiency effect and environmental efficiency effect,the improvement in technical efficiency can lead to a decrease in the proportion of grey water footprint in the eastern and western regions,and an increase in the proportion of grey water footprint in the central region.The contribution of the interaction component between economic activity and the per capita grey water footprint of the employment population is minimal.Fourthly,in order to explore the solutions to enable the sustainable development of the water resource environment and economy in China,the present study investigated the economic productivity of grey water(EPGW),which was defined as the ratio of gross domestic product to grey water footprint.Based on an analysis of regional characteristics and spatial correlation of the EPGW in China from 2000 to 2014,we used the spatial Durbin model to examine the relationship between human factors and the EPGW.We found that the EPGW in China increased over time and that the nationwide productivity increased from19.85 yuan/m~3 in 2000 to 107.93 yuan/m~3 in 2014.In the eastern region,the EPGW was significantly higher than that of the central and western regions and was lowest in the western region.The difference in average productivity,over 15 years,between the eastern region and the central and western regions was>50 yuan/m~3.From 2000 to 2014,the EPGW in China exhibited a significant positive auto-correlation in regards to spatial distribution,and the spatial agglomeration degree was higher and not randomly distributed.In recent years,however,inter regional differentiation in the EPGW has intensified.From the national perspective,the optimization of industrial structure,urbanization,and social welfare are conducive to the growth of the EPGW in local regions.Therefore,improving the level of education and social welfare has positively affected the EPGW in other areas.Improving education,urbanization,social welfare,and the proportion of tertiary industry could positively impact the EPGW of the eastern region.And improving education could also have a significant positive impact on the EPGW of the eastern region’s outer area.Reducing social welfare in the central region has positively affected the EPGW of the adjoining and surrounding areas.The total effect coefficient of urbanization reached 4.8446 in the western region,and improving social welfare positively affected the EPGW of the western region’s outer area.In addition,various regions need to reduce the disparity between the EPGW of urban and rural areas,improve the GDP of rural areas,and promote a healthy development in both economy and environment.Finally,the paper applies regression analyses to assess the impact of environmental regulation,innovation-driven,urbanization level,education level,infrastructure level,the optimization degree of industrial structure and the level of foreign investment on the EPGW in China.Of the core variables,environmental regulation and innovation-driven levels both have significant positive effects on the improvement of the EPGW at the scope of the entire country,while the positive impact of environmental regulation and innovation-driven levels on the EPGW in the central and western regions is higher than in the eastern region.Apart from the infrastructure level,the other explanatory variables all have significant positive impacts on the EPGW both overall and in the eastern regions;improving the optimization degree of industrial structure and level of foreign investment has obvious positive effects on the EPGW in the central region;and the western region’s efforts to strengthen the construction of urbanization and improve the infrastructure level can significantly enhance the EPGW.