Temporal-spatial decomposition computing of regional water intensity for Yangtze River Economic Zone in China based on LMDI model

被引:28
作者
Yao, Longqin [1 ,2 ]
Xu, Jingru [3 ]
Zhang, Lina [4 ]
Pang, Qinghua [3 ]
Zhang, Chenjun [3 ]
机构
[1] Hohai Univ, Sch Business, Nanjing, Jiangsu, Peoples R China
[2] Yancheng Teachers Univ, Coll Business, Yancheng, Jiangsu, Peoples R China
[3] Hohai Univ, Sch Business Adm, Changzhou, Jiangsu, Peoples R China
[4] Hubei Univ Econ, Coll Low Carbon Econ, Wuhan, Hubei, Peoples R China
基金
中国国家自然科学基金;
关键词
Water intensity; Spatial decomposition; LMDI; Water resource policy; Yangtze River Economic Zone; ENERGY; PERFORMANCE;
D O I
10.1016/j.suscom.2018.11.008
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
The shortage of water resources has become a burning issue constraining China's sustained development. Quantifying the driving effect of temporal and spatial differences of water intensity in Yangtze River Economic Zone is very important to Three Red Lines and the dual implementation action of water resources and intensity. In this study, an Index Decomposition Analysis-Logarithmic Mean Divisia Index (IDA-LMDI) model is developed to decompose the temporal-spatial differences of water intensity into intensity effect and structure effect from 2000 and 2015 in Yangtze River Economic Zone. Our findings are as follows. (1)Industrial water intensity and industrial structure are primary and secondary factors that promote the reduction of water intensity, the water intensity of the three industries has generally declined. (2)The primary industry and secondary industry contribute more to the decline of water intensity than the tertiary industry and the primary industry transfers to the secondary industry and the tertiary industry to drive the decline of water intensity. (3)The gap between the water intensity of each province and the average level of the Yangtze River Economic Zone gradually narrowed, and there are significant differences in the evolution trend of intensity effect and structural effect in each province. (4)Only water intensity of the three industries in Zhejiang is always lower than average level, nevertheless, Jiangxi, Hunan are always higher than average level, the proportion of primary industry in GDP in the Yangtze River Delta (Shanghai, Jiangsu and Zhejiang) is less than the average level. Therefore, the provinces should give consideration to the improvement of industrial water efficiency and industrial structure adjustment and other water resources policies to promote the decline of water intensity, greatly improve the effective utilization coefficient of irrigation water and reuse of industrial water. Government should increase support for the management, capital and technology of less developed provinces in the Yangtze River Economic Zone. Provinces should focus on policies that reduce the water intensity, Zhejiang and Chongqing can be a model for other provinces to learn from advanced experience, especially in Zhejiang. (C) 2018 Elsevier Inc. All rights reserved.
引用
收藏
页码:119 / 128
页数:10
相关论文
共 23 条
  • [1] A spatial-temporal decomposition approach to performance assessment in energy and emissions
    Ang, B. W.
    Su, Bin
    Wang, H.
    [J]. ENERGY ECONOMICS, 2016, 60 : 112 - 121
  • [2] LMDI decomposition approach: A guide for implementation
    Ang, B. W.
    [J]. ENERGY POLICY, 2015, 86 : 233 - 238
  • [3] Multi-country comparisons of energy performance: The index decomposition analysis approach
    Ang, B. W.
    Xu, X. Y.
    Su, Bin
    [J]. ENERGY ECONOMICS, 2015, 47 : 68 - 76
  • [4] Ang B.W., 2004, Encyclopedia of Energy, P761
  • [5] The LMDI approach to decomposition analysis: a practical guide
    Ang, BW
    [J]. ENERGY POLICY, 2005, 33 (07) : 867 - 871
  • [6] Decomposition analysis for policymaking in energy: which is the preferred method?
    Ang, BW
    [J]. ENERGY POLICY, 2004, 32 (09) : 1131 - 1139
  • [7] A survey of index decomposition analysis in energy and environmental studies
    Ang, BW
    Zhang, FQ
    [J]. ENERGY, 2000, 25 (12) : 1149 - 1176
  • [8] [Anonymous], 2011, Econ. Geogr
  • [9] Chen D. J., 2008, RESOUR ENV, V18, P211
  • [10] Liu C., 2012, RESOUR SCI, V34, P2299