TY - JOUR
T1 - Tracing surface water pollution in China's supply chain
AU - Sun, Siao
AU - Konar, Megan
AU - Tang, Qiuhong
AU - Fu, Guangtao
AU - Fang, Chuanglin
AU - Wang, Jing
AU - Ni, Yong
AU - Ma, Ting
N1 - Publisher Copyright:
© 2023 Elsevier B.V.
PY - 2023/9
Y1 - 2023/9
N2 - Decades of economic growth in China were enabled by rapid industrialization with insufficient water quality controls. Previous studies have traced water pollution discharges or grey water footprint using the multi-regional input–output (MRIO) model. However, there is a research gap in understanding the relation between surface water pollutant concentrations and final consumption of local and external basins. Here, we present the first national analysis to map surface water quality degradation in watersheds embedded in China's supply chains. To do this, we developed a basin-specific relationship between surface water pollution concentration and discharge, and combined it with the MRIO model to trace the water pollution of different basins through the trade of products and services. We find that ∼50% chemical oxygen demand (COD) and ∼46% ammonium nitrogen (NH4+-N) discharges from production processes can be traced to consumer demands beyond the basin where the pollution was initially released. 0.3–2.2 mg/L COD and 0.03–0.31 mg/L NH4+-N water quality degradation (the range indicates pollution concentration in different basins) can be attributed to final consumption of commodities from other basins in China. International consumers contributed to increased degradation of water quality (0.43 mg/L COD in Huai River Basin and 0.07 mg/L NH4+-N in Hai River Basin). High pollution concentrations were often concentrated in dry North China, because water scarce basins in this region are more susceptible to human pollution loadings. Basins outsourcing water pollution were mainly developed economies that outsourced production and subsequent water quality impairments to other basins. This study highlights the interactions between water quality and supply chains.
AB - Decades of economic growth in China were enabled by rapid industrialization with insufficient water quality controls. Previous studies have traced water pollution discharges or grey water footprint using the multi-regional input–output (MRIO) model. However, there is a research gap in understanding the relation between surface water pollutant concentrations and final consumption of local and external basins. Here, we present the first national analysis to map surface water quality degradation in watersheds embedded in China's supply chains. To do this, we developed a basin-specific relationship between surface water pollution concentration and discharge, and combined it with the MRIO model to trace the water pollution of different basins through the trade of products and services. We find that ∼50% chemical oxygen demand (COD) and ∼46% ammonium nitrogen (NH4+-N) discharges from production processes can be traced to consumer demands beyond the basin where the pollution was initially released. 0.3–2.2 mg/L COD and 0.03–0.31 mg/L NH4+-N water quality degradation (the range indicates pollution concentration in different basins) can be attributed to final consumption of commodities from other basins in China. International consumers contributed to increased degradation of water quality (0.43 mg/L COD in Huai River Basin and 0.07 mg/L NH4+-N in Hai River Basin). High pollution concentrations were often concentrated in dry North China, because water scarce basins in this region are more susceptible to human pollution loadings. Basins outsourcing water pollution were mainly developed economies that outsourced production and subsequent water quality impairments to other basins. This study highlights the interactions between water quality and supply chains.
KW - Environmental footprint
KW - Input-output analysis
KW - Socio-economic system
KW - Supply chain
KW - Surface water pollution
KW - Water quality
UR - http://www.scopus.com/inward/record.url?scp=85165535548&partnerID=8YFLogxK
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U2 - 10.1016/j.jhydrol.2023.129960
DO - 10.1016/j.jhydrol.2023.129960
M3 - Article
AN - SCOPUS:85165535548
SN - 0022-1694
VL - 624
JO - Journal of Hydrology
JF - Journal of Hydrology
M1 - 129960
ER -