有毒金属对沉积物的污染对河流生态系统和人类健康都构成了重大威胁。在这项研究中,地理积累指数(Igeo),生物毒性评价方法,利用潜在生态风险指数(RI)对污染水平进行分析,生物毒性风险,小清河表层沉积物中有毒金属的潜在生态风险。为了识别有毒金属来源,采用Spearman相关和主成分分析与多元线性回归分析(PCA-MLR)。此外,冗余分析(RDA)用于研究影响沉积物中有毒金属积累的潜在驱动因素。结果表明,所研究的五种金属(Cr,Pb,As,Hg,和Cd)在1996-2020年期间表现出持续波动。中游被发现比上游和下游污染更严重。在研究领域,汞被确定为污染程度高的主要污染物,存在生物毒性风险和潜在生态风险。确定了两个时期的污染源:A(1996-2010)和B(2011-2020),工业,农业,交通,自然来源是主要的贡献者。A期间,工业来源占比最高(40.8%),其次是农业来源(36.6%),和地质自然来源(22.6%)。B期间,农业来源占比最高(42%),其次是工业和交通来源(32.4%),和地质自然来源(25.6%)。流域内有毒金属的分布受水体pH值的显著影响,沉积物有机质,人口密度,人均GDP。研究结果为济南小清河沉积物中有毒金属污染的防治和水资源管理提供了基础数据。此外,它为分析流域的相关生态和环境问题提供了参考。
The contamination of sediments by toxic metals poses a significant threat to both river ecosystems and human health. In this study, the geo-accumulation index (Igeo), biotoxicity evaluation method, and potential ecological risk index (RI) were employed to analyze the contamination level, biotoxicity risk, and potential ecological risk of toxic metals in surface sediments of the Xiaoqing River. To identify toxic metal sources, Spearman correlation and principal component analysis with multiple linear regression analysis (PCA-MLR) were employed. Additionally, redundancy analysis (RDA) was utilized to investigate potential driving factors affecting toxic metal accumulation in sediments. The results revealed that the levels of the five investigated metals (Cr, Pb, As, Hg, and Cd) showed constant fluctuations during the period 1996-2020. The midstream was found to be more polluted than the upstream and downstream. In the research area, Hg was identified as the primary contaminant with high levels of contamination, posing a biotoxicity risk and potential ecological risk. Pollution sources were identified for two periods: A (1996-2010) and B (2011-2020), with industrial, agricultural, traffic, and natural sources being the main contributors. During period A, industrial sources accounted for the highest proportion (40.8%), followed by agricultural sources (36.6%), and geological natural sources (22.6%). During period B, agricultural sources accounted for the highest proportion (42%), followed by industrial and traffic sources (32.4%), and geological natural sources (25.6%). The distribution of toxic metals in the basin was significantly influenced by water pH, sediment organic matter, population density, and per capita GDP. The study results provide fundamental data for preventing pollution and managing water resources contaminated with toxic metals in the sediments of the Xiaoqing River in Jinan. Additionally, it serves as a reference for analyzing related ecological and environmental issues in the basin.