School of Business, Hohai University, Nanjing 211100, China.
School of Business, Hohai University, Nanjing 211100, China.
Sci Total Environ. 2022 Jan 1;802:149587. doi: 10.1016/j.scitotenv.2021.149587. Epub 2021 Aug 14.
Water shortages and poor water quality have become an urgent problem that is constraining the sustainable development of China. Grey water has been found to bring greater stress on the water supply than freshwater consumption, and the grey water footprint (GWF) has received significant attention as a comprehensive indicator to assess wastewater pollution. In this study, we analysed the grey water footprint in the Yangtze River Basin from 2003 to 2017 and established a Logarithmic mean divisia index (LMDI) model to decompose the grey water footprint efficiency into six key factors. Our findings are as follows: (1) The average grey water footprint (AGWF) in the central regions was 40% higher than eastern region and 172% higher than western region; (2) Economic effects and capital deepening effects are the main factors affecting positive changes in grey water footprint efficiency; (3) Based on an analysis of the driving factors of greywater footprint efficiency in each province, we conducted a territorial classification according to the primary driving factors in each province. Our results reflect the spatial distribution characteristics of the influencing factors on the grey water footprint effect in the Yangtze River Basin and will enable the government to formulate relevant policies for each subregion.
水资源短缺和水质较差已成为制约中国可持续发展的紧迫问题。已发现灰水对供水的压力大于淡水消耗，灰水足迹（GWF）作为评估废水污染的综合指标受到了极大关注。本研究分析了 2003 年至 2017 年长江流域的灰水足迹，并建立了对数平均迪氏分解指数（LMDI）模型，将灰水足迹效率分解为六个关键因素。我们的研究结果如下：（1）中部地区的平均灰水足迹（AGWF）比东部地区高 40%，比西部地区高 172%；（2）经济效应和资本深化效应是影响灰水足迹效率正向变化的主要因素；（3）基于对各省灰水足迹效率驱动因素的分析，根据各省的主要驱动因素进行了地域分类。研究结果反映了长江流域灰水足迹效应影响因素的空间分布特征，将有助于政府为各子区域制定相关政策。
