Resources & Industries ›› 2022, Vol. 24 ›› Issue (4): 30-41.DOI: 10.13776/j.cnki.resourcesindustries.20220410.001

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DRIVES FOR JIANGSU'S WATER FOOTPRINT EFFICIENCY CHANGES BASED ON LMDI-ATTRIBUTION

JIANG Xiangcheng, WANG Rui   

  1. (Business School, Hohai University, Nanjing  211100, China)
  • Received:2021-06-24 Revised:2021-01-19 Online:2022-08-20 Published:2022-09-02

基于LMDI-Attribution的江苏省水足迹效率变化驱动力分析

姜翔程,王睿   

  1. (河海大学 商学院,江苏 南京 211100)
  • 通讯作者: 王睿,硕士生,主要从事财务分析与金融市场研究。E-mail:938640158@qq.com
  • 作者简介:姜翔程,博士、副教授,主要从事金融工程与投资管理研究。E-mail: xcjiang@hhu.edu.cn
  • 基金资助:
    国家社会科学基金重大项目(19ZDA084);教育部人文社科规划基金(10YJA790080)

Abstract: Jiangsu province has the most total and per capita water footprint in the Yangtze River Economic Zone, and a severe water shortage which constraints Jiangsu's economy. This paper, from the perspective of water footprint and focusing on Jiangsu's water footprint efficiency changes, analyzes their drives and provides suggestions for sustainable development of Jiangsu's water resources. Jiangsu's water footprint results from 2010 to 2019 and extended Kaya formula are used to calculate the actual water use efficiency, water resource use technical level and water footprint. LDMI-attribution model is employed to estimate the drives with contribution of three water use sectors obtained. During the study period, Jiangsu shows a noted increase in water footprint efficiency, from 32.78 RMB/m3 in 2010 to 88.91 RMB/m3 in 2019,increasing by 171.25%, mostly driven by actual water use efficiency with a contribution 167%, followed by technical level with a contribution 26.15%. Water footprint proportion in agricultural use has relatively risen, and the water footprint structure contributes -21.67% to the change. Key drives come from actual uses in industrial and living sectors, 91.19% and 75.07% respectively, with only 0.73% from agricultural sector. In technical drives, most are contributed by living sector at 21.40%, followed by industrial sector at 4.79% and then by agricultural sector at -0.04%. In water footprint structural drives, only agricultural sector is positive at 0.06%, then living sector at -2.13% and industrial sector at -19.60%. This paper presents suggestions on constructing water-saving agricultural system to increase agricultural water use efficiency and to decrease agricultural water footprint proportion, keeping a downgrade of gray water footprint, limiting high pollution investments, supporting green development, stimulating province-wide consumption, optimizing foreign trading structure and increasing sustainable development capacity of water resources.

Key words: water footprint, drives, LMDI decomposition, attribution analysis, Jiangsu province

摘要: 在长江经济带各省市中,江苏省水足迹总量和人均量最大,缺水程度最严重,较低的水资源可持续发展能力制约了江苏省经济社会的发展。从水足迹视角,聚焦江苏省水足迹效率变化,分析水足迹效率变化的驱动因素和大小,为江苏省水资源可持续发展提出建议。基于2010—2019年江苏省水足迹计算结果,扩展Kaya恒等式构造出驱动水足迹效率变化的实际用水效率、水资源利用技术水平和水足迹结构3个因素,借助LMDI-Attribution模型计算各因素驱动力大小,并得到三大用水部门的具体贡献度。结果表明:研究期间江苏省水足迹效率增长幅度较大,从2010年的32.78元/m3增加到2019年的88.91元/m3,增幅为171.25%,其中实际用水效率为水足迹效率变化的最大驱动力,贡献了167%,其次为技术水平,贡献了26.15%;由于农业部门水足迹占比增大,水足迹结构对变化的影响为-21.67%;从用水部门来看,工业部门和生活部门的实际用水效率是最关键的驱动力,分别为91.19%和75.07%,农业部门仅为0.73%;技术水平驱动力中贡献最大的为生活部门的21.40%,其次为工业部门的4.79%,而农业部门为-0.04%;水足迹结构驱动力中仅农业部门是正向的,为0.06%,生活部门为-2.13%,工业部门为-19.60%。建议江苏省建立健全节水型农业体系,提高农业用水效率,降低农业部门水足迹所占比例,保持各用水部门灰水足迹的下降趋势,限制高污染企业的投资建设,支持绿色企业的发展;刺激省内消费需求,不断优化对外贸易结构,提升水资源可持续发展能力。

关键词: 水足迹, 驱动力, LMDI分解, 归因分析, 江苏省

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