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assification results also demonstrated that the proportion of very high ecological risk sites have increased from 11% to 22%. The element with the highest MRI contribution rate changed from mercury to cadmium, which was caused by the reduction of the ecological risk level from very high to moderate. The results demonstrated that the significant pollution changes in the trace elements in the floodplain sediments of the Poyang Lake basin were primarily caused by human activities, such as mineral exploitation, smelting, and industrial and agricultural production. Our findings can provide scientific evidence for the prevention and control of river pollution and the optimal management of a watershed ecosystem.In order to clarify the pollution levels of heavy metals in the drinking water sources of the Lijiang River Basin, surface water samples were collected from 62 sites throughout the Lijiang River during May 2019. Heavy metals, including As, Cd, Cr, Mn, Cu, Zn, Hg, Co, and Sb, in the water samples were analysed. Health risk assessments associated with these nine heavy metals were conducted using the health risk assessment model from the US EPA. The results indicated that the order of the average concentrations of heavy metals in the water samples were Mn > Zn > As > Cr > Cu > Sb > Co > Cd > Hg. No heavy metals exceeded the limit values of the drinking water health standards in China (GB 5749-2006), and the concentrations were lower than the limitations of Grade Ⅰ level in the environmental quality standards for surface water (GB 3838-2002). According to the spatial distribution, the high contents areas of As, Cr, Zn, and Sb were predominantly distributed downstream of the Lijiang River, while the high contents ere far below the maximum allowance levels recommended by the ICRP.In this study, the hydrochemical characteristics of surface water in the Yarkant River Basin of Xinjiang and their controlling factors were analyzed using a Piper trilinear diagram, Gibbs diagram, saturation index, ion proportional relationship, and other methods. The study has significance to the surface water resources in the basin for development and utilization. The results indicated that the pH of the surface water ranged from 7.40 to 8.33, with a mean value of 7.92, which was weakly alkaline. The mean value of the total dissolved solids (TDS) of the river, canal, and reservoir water exhibited an increasing trend. The TDS mean of the river was 429.24 mg·L-1, higher than the average value of rivers worldwide (115 mg·L-1). The hydrochemical types of the river water were predominantly HCO3·SO4-Ca·Na and SO4·HCO3·Cl-Ca·Na·Mg types, of the canal water was mainly HCO3·SO4·Cl-Ca·Na type, and of the reservoir water was mostly the SO4·Cl-Na·Ca type. The TDS of the river water along the Yarkant River and Tiznap River demonstrated a continuous increase and fluctuation trend, respectively, while the variation of the primary ions was relatively complex. The primary ions of surface water were mostly influenced by rock weathering, evaporation crystallization, and cation exchange, in which gypsum and rock salt were predominantly dissolved in the process of rock weathering. In addition, human activities had significant effects on the chemical composition of the surface water downstream.Different land uses have different impacts on the water quality of the region. Multiple isotopes (δD-H2O, δ18O-H2O, δ15N-NO3-, and δ18O-NO3-) and the SIAR (stable isotope analysis in R) model were applied to identify the nitrate sources and estimate the proportional contributions of multiple nitrate sources in a river in a typical urban area (the Grand Canal, Hangzhou) and a river in a typical forest and agricultural area (Yuying Riveri). The results indicated that there were different degrees of nitrogen pollution in the Grand Canal and Yuying River; NO3--N and NH4+-N are the predominant forms of nitrogen in the Grand Canal, and the primary form of nitrogen in Yuying River was NO3--N. There was an obvious linear relationship between the hydrogen and oxygen isotopes (R2=0.78). The δD-H2O and δ18O-H2O values for the Grand Canal and Yuying River were distributed along the local meteoric waterline, indicating that precipitation served as the primary water source in these rivers. All of the δ18O-NO3- values of th stronger human activities primarily due to the sporadic discharge of domestic sewage and urban runoff. Chemical fertilizer is the main NO3- source in the Yuying River near the forest and agricultural area, suggesting that the nitrogen pollution caused by agricultural non-point sources was extremely serious. The contribution of precipitation decreased in the areas of substantial human activities. The isotopic fractionation produced by denitrification was affected by the contributions of the NO3- sources, which were calculated by SIAR model. Sewage/manure and chemical fertilizer produced significant impacts, followed by soil nitrogen and precipitation.Research on health and the economic losses caused by PM2.5 pollution nationwide is critical for pollution control planning. First, the spatiotemporal distribution of PM2.5 and exposure levels were simulated and analyzed using the air quality model (WRF-Chem) in China in 2016. Then, the health burden and economic loss caused by PM2.5 pollution were estimated using environmental health risk and environmental value assessment methods. Finally, the health and economic benefits from achieving specific PM2.5 control targets were estimated. selleck inhibitor In 2016 in China, high levels of PM2.5 were concentrated in Beijing-Tianjin-Hebei and the surrounding areas, the Yangtze River Delta, the Sichuan Basin, and the desert areas in northwest China. Furthermore, 71.49% of the total population of China was exposed to an environment with PM2.5 concentrations higher than 35 μg·m-3. Subsequently, the national PM2.5-related mortality was 1.06 million, accounting for 10.9% of the total deaths in China. Stroke and ischemic heart disease accounted for approximately 80% of the total PM2.5-related deaths caused by the five diseases studied. Meanwhile, the PM2.5 pollution resulted in economic losses of 705.93 billion yuan, which was 0.95% of the Gross Domestic Product (GDP) in 2016. There were significant spatial differences in the health burden and economic loss, which primarily occurred in regions with high PM2.5 levels or population density. Moreover, reducing PM2.5 to 35 μg·m-3 would only result in a 17.11% reduction in the health burden and economic loss, while a more exacting standard (reducing PM2.5 to 10 μg·m-3) would bring 80.47% of the health and economic benefits. It is suggested that environmental managers further strengthen their control to better protect the health and wealth benefits of residents, especially for sensitive groups, such as patients with cardio-cerebrovascular diseases, particularly in areas with high premature mortality.