基于IPAT-LMDI的中国水足迹变化驱动力分析  

Driving forces for change of water footprint in China based on IPAT-LMDI model

作　　者：奚旭 孙才志[1] 赵良仕[1] 

机构地区：[1]辽宁师范大学城市与环境学院,辽宁大连116029

出　　处：《水利经济》2014年第5期1-5,71,共5页Journal of Economics of Water Resources

基　　金：国家社会科学基金(11BJY063);教育部新世纪优秀人才项目(NECT-13-0844)

摘　　要：通过构建水足迹变化的IPAT模型,将引起中国水足迹变化的驱动因素分解成人口、富裕和技术3种人文因素,并通过LMDI分解模型测度了1997—2011年这3种因素对中国水足迹变化的贡献率以及各省市这3种因素的年均贡献率。结果表明:富裕程度对引起水足迹变化的影响程度最大,人口的影响力最小,两者都是正向驱动因子,技术效应具有双向驱动效果,而当前基本上为负向驱动力;人口对水足迹影响最大的省市包括上海、浙江和广东等人口密度比较大的省市;富裕程度对水足迹影响最大的省市包括广西、宁夏和陕西等经济水平相对落后的地区;技术效应对水足迹影响最大的省市包括浙江、广东等经济强省。最后分析了相应对策以及需要进一步完善的问题。By establishing IPAT model for change of water footprint,the driving forces for change of water footprint in China are decomposed into three humanistic factors of population, affluence and technology. The contribution rates of the above three factors to change of China's water footprint as well as their average annual contribution rates in various provinces in China from 1997 to 2011 are measured using the LMDI decomposition model. The results show that the impact of the degree of affluence on change of water footprint is the greatest,that of the population is the smallest,both of which are positive driving factors,and the technology has bidirectional driving effects,while currently it is substantially negative driving force. The provinces and regions with the most impact of populations on water footprints include Shanghai,Zhejiang and Guangdong with relatively large population density. Those with the most impact of affluence on water footprint include Guangxi,Ningxia and Shanxi with relatively poor economic level. Those with the most impact of technical effects on water footprint include Zhejiang and Guangdong with strong economy. Finally,some countermeasures and potential improvements are put forward.

关 键 词：水足迹 驱动因素 IPAT模型 LMDI分解 

分 类 号：F062.1[经济管理—政治经济学]