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意大利伦巴第地区(意大利)河流中化学混合物的空间分布和时间变化趋势(2009-2020 年)。

Spatial distributions and temporal trends (2009-2020) of chemical mixtures in streams and rivers across Lombardy region (Italy).

机构信息

Department of Earth and Environmental Sciences DISAT, University of Milano-Bicocca, Piazza della Scienza 1, 20126 Milano, Italy.

Department of Earth and Environmental Sciences DISAT, University of Milano-Bicocca, Piazza della Scienza 1, 20126 Milano, Italy.

出版信息

Sci Total Environ. 2024 Apr 1;919:170839. doi: 10.1016/j.scitotenv.2024.170839. Epub 2024 Feb 9.

Abstract

Chemical mixtures in the environment are of increasing concern in the scientific community and regulators. Indeed, evidence indicates that aquatic wildlife and humans can be simultaneously and successively exposed to multiple chemicals mainly originating from different anthropic sources by direct uptake from water and indirectly via eating aquatic organisms. This study analyses a large set of sampling data referring to the entire Lombardy region, the most industrialised and at the same time the most important agriculture area in Italy, investigating the presence and potential effects of chemical mixtures in surface water bodies. We enriched and further developed an approach based on a previous work, where the overall mixture toxicity was evaluated for three representative aquatic organisms (algae, Daphnia, fish) using the concentration addition model to combine exposure with ecotoxicological data. The calculation of the mixture toxicity has been realised for two scenarios, namely best- and worst-case scenarios. The former considered only quantified compounds in the monitoring campaign, while the latter also included substances with concentrations below the limit of quantification (LoQ). Differences between the two scenario results established the potential toxicity range. Our findings revealed that differences were minimal when the calculated toxicity in the best-case scenario indicated potential risk and, on the contrary, they suggest that the worst-case scenario is overly conservative; we could also state that including substances with concentrations below the LoQ when calculating the overall toxicity of the mixture is useless and then we focused solely on the best-case scenario. The analysis of spatial and temporal risk trends together with contaminant types and target organisms highlighted specific clusters of contamination. Finally, in several cases, our study found that only few compounds were responsible for the majority of mixture toxicity.

摘要

环境中的化学混合物是科学界和监管机构日益关注的问题。事实上,有证据表明,水生野生动物和人类可以同时且连续地通过直接从水中摄取以及间接地通过食用水生生物而接触到主要源自不同人为来源的多种化学物质。本研究分析了大量涉及整个伦巴第地区(意大利工业化程度最高且同时也是最重要的农业区)的采样数据,调查了地表水体内化学混合物的存在和潜在影响。我们对基于先前工作的方法进行了丰富和进一步发展,该方法使用浓度加和模型将暴露与生态毒理学数据相结合,评估了三种代表性水生生物(藻类、水蚤、鱼类)的总体混合物毒性。混合物毒性的计算针对两种情况,即最佳情况和最差情况。前者仅考虑监测活动中定量的化合物,而后者还包括浓度低于定量限(LoQ)的物质。两种情况结果之间的差异确定了潜在毒性范围。我们的研究结果表明,当最佳情况下计算出的毒性表明存在潜在风险时,差异最小,而相反,最坏情况下的情况则过于保守;我们还可以说,在计算混合物的总体毒性时,包括浓度低于 LoQ 的物质是无用的,因此我们仅专注于最佳情况。对空间和时间风险趋势以及污染物类型和目标生物的分析突出了特定的污染群集。最后,在许多情况下,我们的研究发现只有少数几种化合物对大多数混合物毒性负责。

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