PDF HTML阅读 XML下载 导出引用 引用提醒 中国人均灰水足迹区域差异及因素分解 DOI: 10.5846/stxb201709291764 作者: 作者单位: 辽宁师范大学城环学院,辽宁师范大学海洋经济与可持续发展研究中心;辽宁师范大学城市与环境学院 作者简介: 通讯作者: 中图分类号: 基金项目: 国家社会科学重点基金(16AJY009) Regional inequality and factor decomposition of the per capita grey water footprint in China Author: Affiliation: College of Urban and Environment,Liaoning Normal University,College of Urban and Environment,Liaoning Normal University Fund Project: the National Social Science Key Foundation of China(NO.16AJY009) 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:促进我国整体水资源利用率和水环境质量的提升,已成为当前亟待解决的问题。为探究生产要素和其他传统因素对人均水资源环境差异的影响,基于对中国31省区(港、澳、台尚未统计)2000-2014年人均灰水足迹的测算,应用Theil指数和扩展的Kaya恒等式对其区域差异及驱动因子进行探究。结果表明:1)近年全国人均灰水足迹差异缓幅波动,组间差异指数逐渐提升,组内差异为总体差异的主要来源,西部地区组内差异最大。2)在单一要素方面,资本深化和技术效率为全国差异的主导因素,也分别为中、东部组内差异的主导因素;经济活度对各类差异的驱动效应最小,且西部除该效应外,都为驱动差异的重要因素。3)相互作用成分中,除西部资本产出效应与单位GDP灰水足迹相互作用的贡献值最高外,其他地区资本深化效应与单位资本存量灰水足迹相互作用的贡献较大。在技术效率效应与环境效率效应相互作用方面,技术效率的提升可以带动东、西部灰水足迹所占比重下降和中部灰水足迹比重提高。经济活度效应与就业人口人均灰水足迹相互作用的贡献最小。 Abstract:At present, there is an urgent need for solutions to enable an improvement in water resource use efficiency and water environment quality in China. Therefore, this study conducted detailed measurement of the per capita grey water footprint in 31 provinces of China (excluding Hong Kong, Macao, and Taiwan) from 2000 to 2014. This study explores the regional inequality and driving factors of the per capita grey water footprint to determine the influence of production and traditional factors on the inequality in per capita water resources and environment. The inequality analysis was performed using a factorial decomposition of the second Theil index of inequality. In particular, based on Kaya factors, we decomposed the per capita grey water footprint into the following five factors:environmental efficiency, technical efficiency, capital output, capital deepening, and economic activity. We found that the overall inequality of the per capita grey water footprint showed a slow fluctuation in recent years. The within-group inequality component was the main contributor to the overall inequality during the entire period, since its proportion of the total in 2014 was 59%. A slight decrease was noted in the within-group inequality in each region. In the three regions considered in this study, the within-group inequality was the largest in the western region, with the index reaching 0.0727 in 2014. The between-group inequality index of the total inequality increased annually, from 0.0067 in 2000 to 0.0449 in 2014, corresponding to an increase of 570%. In the aspect of single factors, capital deepening and technical efficiency are the dominant factors in the total and within-group inequality of the per capita grey water footprint of the central and eastern regions, respectively. Economic activity was the weakest driver of all inequality components. In addition to the economic activity, the other factors were vital for driving the within-group inequality of the per capita grey water footprint in the western region, among which technical efficiency was the strongest driver; the relative weight of this factor was 63.61%. The interaction component results showed that the contribution value of the interaction component between the capital output effect and the grey water footprint per unit GDP was the largest for the western region within-group inequality, and that between the capital deepening effect and the grey water footprint per unit of capital stock was greater in the other regions. In terms of the interaction component between the technical and environmental efficiency effects, 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 was minimal. 参考文献 相似文献 引证文献