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.
Tosadori, A., Di Guardo, A., Finizio, A. (2024). Spatial distributions and temporal trends (2009–2020) of chemical mixtures in streams and rivers across Lombardy region (Italy). SCIENCE OF THE TOTAL ENVIRONMENT, 919(1 April 2024) [10.1016/j.scitotenv.2024.170839].
Spatial distributions and temporal trends (2009–2020) of chemical mixtures in streams and rivers across Lombardy region (Italy)
Di Guardo, A
;Finizio, A
2024
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.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.