School of Ecological and Environmental Sciences, East China Normal University, Shanghai 200241, China; Shanghai Key Lab for Urban Ecological Processes and Eco-Restoration, East China Normal University, Shanghai 200241, China; Institute of Eco-Chongming (IEC), Shanghai 200062, China.
School of Ecological and Environmental Sciences, East China Normal University, Shanghai 200241, China; Shanghai Key Lab for Urban Ecological Processes and Eco-Restoration, East China Normal University, Shanghai 200241, China; Institute of Eco-Chongming (IEC), Shanghai 200062, China.
Sci Total Environ. 2021 Sep 1;785:147255. doi: 10.1016/j.scitotenv.2021.147255. Epub 2021 Apr 24.
The primary pollutants and pollution levels of surface water present spatial and temporal changes. This study quantified the grey water footprint (GWF) and surface water pollution level (WPL) in China from 2003 to 2018 based on four pollutants: chemical oxygen demand (COD), ammonia nitrogen (NH-N), total nitrogen (TN) and total phosphorus (TP). Additionally, the spatiotemporal distribution of the primary water pollutant (PWP) and driving forces of the GWF were analyzed based on the WPLs and the logarithmic mean Divisia index (LMDI) decomposition method. The results showed that the GWF in China decreased by 13% from 2003 to 2018 and the WPL decreased from 1.11 in 2003 to 0.94 in 2018. An analysis of regional GWFs with multiple pollutants could prevent the underestimation of GWFs and WPLs caused by changes in the PWPs. The GWF spatial distribution was high in the southeast and low in the northwest, while the provinces with larger WPLs were mainly concentrated in northern China. The PWP changed from COD to TN in 2007 because of the increase in nitrogen application in China, the low TN reduction capacity of wastewater treatment plants and the improved comprehensive utilization rate of livestock and poultry manure. The driving force analysis results showed that water efficiency and technological and industrial structural effects promoted the reduced GWF. Our research conclusions and policy suggestions could provide references for reducing the GWF and improving the water quality in China.
地表水污染主要污染物及其污染水平存在时空变化。本研究基于化学需氧量（COD）、氨氮（NH-N）、总氮（TN）和总磷（TP）等 4 种污染物，量化了 2003-2018 年中国的灰水足迹（GWF）和地表水环境污染水平（WPL）。此外，还基于 WPL 和对数平均迪维西亚指数（LMDI）分解法分析了主要水污染物（PWP）的时空分布及其 GWF 的驱动因素。结果表明，2003-2018 年中国 GWF 减少了 13%，WPL 从 2003 年的 1.11 降至 2018 年的 0.94。多污染物区域 GWF 分析可防止因 PWPs 变化而导致 GWF 和 WPL 的低估。GWF 空间分布呈现东南高西北低的特征，而 WPL 较大的省份主要集中在北方。2007 年，由于中国氮肥施用量增加、污水处理厂 TN 去除能力较低以及禽畜粪便综合利用率提高，PWP 由 COD 转变为 TN。驱动力分析结果表明，用水效率和技术及产业结构效应促进了 GWF 的减少。本研究的结论和政策建议可为减少中国 GWF 和改善水质提供参考。
