摘要
Effective management of large basins necessitates pinpointing the spatial and temporal drivers of primary index exceedances and urban risk factors,offering crucial insights for basin administrators.Yet,comprehensive examinations of multiple pollutants within the Yangtze River Basin remain scarce.Here we introduce a pollution inventory for urban clusters surrounding the Yangtze River Basin,analyzing water quality data from 102 cities during 2018e2019.We assessed the exceedance rates for six pivotal indicators:dissolved oxygen(DO),ammonia nitrogen(NH_(3)-N),chemical oxygen demand(COD),biochemical oxygen demand(BOD),total phosphorus(TP),and the permanganate index(COD_(Mn))for each city.Employing random forest regression and SHapley Additive exPlanations(SHAP)analyses,we identified the spatiotemporal factors influencing these key indicators.Our results highlight agricultural activities as the primary contributors to the exceedance of all six indicators,thus pinpointing them as the leading pollution source in the basin.Additionally,forest coverage,livestock farming,chemical and pharmaceutical sectors,along with meteorological elements like precipitation and temperature,significantly impacted various indicators'exceedances.Furthermore,we delineate five core urban risk components through principal component analysis,which are(1)anthropogenic and industrial activities,(2)agricultural practices and forest extent,(3)climatic variables,(4)livestock rearing,and(5)principal polluting sectors.The cities were subsequently evaluated and categorized based on these risk components,incorporating policy interventions and administrative performance within each region.The comprehensive analysis advocates for a customized strategy in addressing the discerned risk factors,especially for cities presenting elevated risk levels.
基金
financial support from the National Natural Science Foundation of China(Grant No.52170073)
the National Engineering Research Center for Bioenergy(Harbin Institute of Technology,Grant No.2021A001)
the State Key Laboratory of UrbanWater Resource and Environment(Harbin Institute of Technology)(Grant No.2021TS03)
We gratefully thank the financial support from the Joint Research program for ecological conservation and high-quality development of the Yellow River Basin(Grant No.2022-YRUC-01-0204)
We gratefully thank the contribution of the algorithm model and tool support by the artificial intelligence department of CECEP Digital Technology Co.,Ltd.We gratefully acknowledge the support of the Heilongjiang Province Touyan Team.
