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History and future of water footprint in the Yangtze River Delta of China.
- Source :
- Environmental Science & Pollution Research; Apr2024, Vol. 31 Issue 17, p25508-25523, 16p
- Publication Year :
- 2024
-
Abstract
- Quantifying the drivers of water footprint evolution in the Yangtze River Delta is vital for the optimization of China's total water consumption. The article aims to decompose and predict the water footprint of the Yangtze River Delta and provide policy recommendations for optimizing water use in the Yangtze River Delta. The paper applies the LMDI method to decompose the water footprint of the Yangtze River Delta and its provinces into five major drivers: water footprint structure, water use intensity, R&D scale, R&D efficiency, and population size. Furthermore, this paper combines scenario analysis and Monte Carlo simulation methods to predict the potential evolution trends of water footprint under the basic, general, and enhanced water conservation scenario, respectively. The results show that (1) the expansion of R&D scale is the main factor promoting the growth of water footprint, the improvement of R&D efficiency, and the reduction of water intensity are the main factors inhibiting the increase of water footprint, and the water footprint structure and population size have less influence on water footprint. (2) The evolution trend of water footprint of each province under three scenarios is different. Compared to the basic scenario, the water footprint decreases more in Shanghai, Zhejiang, and Anhui under the general and enhanced water conservation scenario. The increase in water footprint in Jiangsu under the enhanced scenario is smaller than that of the general water conservation scenario. [ABSTRACT FROM AUTHOR]
- Subjects :
- WATER conservation
MONTE Carlo method
WATER consumption
WATER use
Subjects
Details
- Language :
- English
- ISSN :
- 09441344
- Volume :
- 31
- Issue :
- 17
- Database :
- Complementary Index
- Journal :
- Environmental Science & Pollution Research
- Publication Type :
- Academic Journal
- Accession number :
- 177350834
- Full Text :
- https://doi.org/10.1007/s11356-024-32757-5