The grey water footprint of the Yangtze River Economic Belt, China: Spatial patterns, driving mechanism, and implications

Guangming Yang , Darong Li , Yizhi Qin , Hongxia Sheng

AIMS Environmental Science ›› 2025, Vol. 12 ›› Issue (4) : 721 -743.

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AIMS Environmental Science ›› 2025, Vol. 12 ›› Issue (4) :721 -743. DOI: 10.3934/environsci.2025032
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The grey water footprint of the Yangtze River Economic Belt, China: Spatial patterns, driving mechanism, and implications
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Abstract

Deteriorating water ecosystems pose a critical constraint to high-quality development in the Yangtze River Economic Belt (YREB). In this study, we analyzed the grey water footprint (GWF) in the YREB from 2009 to 2022 using panel data from 11 provinces/municipalities. A multi-sector pollutant load model was employed to calculate the GWF. Driving mechanisms were investigated using Random Forest (RF) and SHapley Additive exPlanations (SHAP) analysis, while spatial dynamics were assessed via standard deviational ellipse. The results indicated: (1) The regional GWF peaked in 2015 (489.9 billion m3), then decreased by 35.5% after 2016 due to the Yangtze River Protection initiative. Agriculture became the dominant contributor (53.1% share), especially in midstream provinces such as Hubei and Jiangxi. (2) Spatially, the GWF exhibited a northeast– southwest axial pattern. The ellipse area initially contracted to 80.22 km2 (2018) before rebounding, while the distribution centroid shifted 105 km northwestward. (3) The RF–SHAP model revealed key non-linear drivers; the GWF significantly decreased when the secondary/tertiary industry share exceeded 70% or solid waste utilization surpassed 85%. Environmental investment showed diminishing marginal returns beyond 35% of GDP. Urban green space per capita had an optimal GWF-reduction range of 12–16 m2; beyond 16 m2, it increased the GWF due to ecological encroachment effects. We recommend targeted agricultural non-point source control, industrial circular economy upgrades, and region-specific ecological management to achieve sustainable development.

Keywords

grey water footprint / random forest model / Yangtze River Economic Belt / threshold / influencing factors

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Guangming Yang, Darong Li, Yizhi Qin, Hongxia Sheng. The grey water footprint of the Yangtze River Economic Belt, China: Spatial patterns, driving mechanism, and implications. AIMS Environmental Science, 2025, 12 (4) : 721-743 DOI:10.3934/environsci.2025032

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