4.7 Article

Spatial-temporal variation and driving factors decomposition of agricultural grey water footprint in China

期刊

JOURNAL OF ENVIRONMENTAL MANAGEMENT
卷 318, 期 -, 页码 -

出版社

ACADEMIC PRESS LTD- ELSEVIER SCIENCE LTD
DOI: 10.1016/j.jenvman.2022.115601

关键词

Agricultural water pollution; Grey water footprint; Spatial-temporal analysis; Factor decomposition analysis; Standard deviational ellipse; Generalized divisia index method

资金

  1. Fundamental Research Funds for the Central Universities [B220203012]
  2. Postgraduate Research & Practice Innovation Program of Jiangsu Province [KYCX21_0445]
  3. National Natural Science Foun-dation of China [71874101, 72104127, 72004116]

向作者/读者索取更多资源

The study analyzed the agricultural grey water footprint (GWF) of 31 provincial regions in China from 2011 to 2019 and found that overall agricultural GWF decreased with significant differences among provinces, with higher agricultural GDP areas generally having higher agricultural GWF. The research also revealed that the growth of agricultural GWF is mainly driven by agricultural GDP and limited by agricultural GWF intensity.
The management of agricultural water pollution is crucial to alleviate the water crisis and promote regional sustainable development. Therefore, it is necessary to clarify the spatial-temporal variation characteristics of the agricultural grey water footprint (GWF) and accurately identify its main influencing factors, aiming at formulating differentiated regional management strategies. Based on this, the agricultural GWFs of 31 provincial regions in China from 2011 to 2019 were firstly calculated, and then the spatial-temporal variation characteristics of agricultural GWF were analyzed using the ArcGIS software and Standard Deviational Ellipse (SDE) method. Finally, the Generalized Divisia Index Method (GDIM) was creatively introduced to decompose the factors of agricultural GWF change and their respective contributions at the national and provincial levels. The main results are as follow: (1) Agricultural GWF in China decreased on the whole and showed significant provincial differences. Among them, the agricultural GWF of Henan Province was the largest while that of Shanghai City was the smallest. Compared with 2011, most provinces saw a decrease in agricultural GWF in 2019 while Yunnan, Tibet, Qinghai, Ningxia and Xinjiang Provinces achieved growth. (2) Areas with higher agricultural GDP generally had higher agricultural GWF. The spatial distribution of agricultural GWF and breeding GWF generally tended to be consistent, with the lower value in northwest and southeast of China and higher value in the northeast and southwest of China. Meanwhile, the mean center of SDE of agricultural GWF was located in Henan Province from 2011 to 2018, and shifted to Shaanxi Province in 2019, showing a slight northwest shift. (3) Agricultural GWF intensity and agricultural GDP had the largest restraining effect and driving effect on agricultural GWF growth, respectively. Additionally, China has achieved decoupling between agricultural GWF and agricultural GDP, reflecting that the patterns of agricultural production and consumption have become more sustainable. The findings of this study can provide important decision-making insights for agricultural water pollution management and industry adjustment.

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