Probabilistic risk assessment of fifteen metal(loid)s and their mixtures in surface sediment of Hongze Lake (China) using the diffusive gradients in thin films (DGT) technique

文献类型： 外文期刊

第一作者： Ma, Changjiang

作者： Ma, Changjiang;Wang, Meirong;Gu, Yang-Guang;Gu, Yang-Guang;Jordan, Richard W.;Jiang, Shi-Jun;Gu, Yang-Guang

作者机构：

关键词： Inclusion-exclusion principle; Aquatic biota; DGT-labile metals; Ecological risk; Metal mixtures; Freshwater lake

期刊名称：INTERNATIONAL JOURNAL OF SEDIMENT RESEARCH （ 影响因子：3.7； 五年影响因子：3.8 ）

ISSN： 1001-6279

年卷期： 2025 年 40 卷 3 期

页码：

收录情况： SCI

摘要： Freshwater lakes in China face increasing environmental pressures due to rapid urbanization and industrialization, with metal pollution emerging as a significant concern. Despite this, the ecological risk assessment of metal mixtures in lake sediment remains limited. The current study addresses this gap by utilizing the diffusive gradients in thin films (DGT) technique to investigate the distribution and ecological risk of metals and arsenic in surface sediment of Hongze Lake, China. Substantial variations in metal concentrations were found across sampling sites, with average values of manganese (Mn) (1,730.56 mg/L) and iron (Fe) (930.58 mg/L) being notably high. The ecological risk quotient (RQ) values for Mn and Fe exceeded 1 at all sites, indicating substantial ecological risks, while copper (Cu) and arsenic (As) had RQ values near or above 1 at most sites. A joint probabilistic risk assessment using the species sensitivity distribution (SSD) method revealed a 30.31% probability of concurrent toxic effects on aquatic organisms. These results highlight the pressing need for proactive measures to mitigate metal contamination risks in Hongze Lake. The current study provides critical insight into the ecological risks associated with metal pollution and underscores the importance of effective environmental management to preserve the lake's ecosystem. (c) 2025 International Research and Training Centre on Erosion and Sedimentation. Publishing services by Elsevier B.V. on behalf of KeAi Communications Co. Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

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