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Comparison of the Estimation Methods from Acute to Chronic Biotic Ligand Model‐Based Predicted No‐Effect Concentrations for Nickel in Freshwater Species

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Biotic ligand models (BLMs) and the sensitivities of indigenous species are used to assess the environmental risk considering the bioavailability of metals, such as nickel. However, the BLM‐based acute–to–chronic ratio… Click to show full abstract

Biotic ligand models (BLMs) and the sensitivities of indigenous species are used to assess the environmental risk considering the bioavailability of metals, such as nickel. However, the BLM‐based acute–to–chronic ratio (ACR) is required if the predicted no‐effect concentration (PNEC) cannot be derived from the chronic species sensitivity distribution (SSD). The applicability of the ACR approach for estimating BLM‐based PNEC for nickel from acute toxicity data was evaluated in the present study. The BLM‐based acute SSD for nickel was built using the sensitivities of 21 indigenous species and different taxon‐specific BLMs for each taxonomic group. To predict the acute sensitivity of invertebrates, the chronic crustacean nickel BLM with pH effect term, which can account for nickel toxicity at high pH levels, was used. This was used instead of the existing acute BLM for crustacean, which has too narrow a pH range to cover the pH dependency of toxicity. The final BLM‐based ACR of nickel, determined within a factor of 1.53 from the species‐specific acute and chronic sensitivities of the six species, was more reliable than the typical ACR estimated within a factor of 1.84. A linear relationship (r2 = 0.95) was observed between the PNECs using BLM‐based ACR and the PNECs derived from the BLM‐based chronic SSD of the European Union Risk Assessment Reports. In conclusion, the BLM‐based PNEC for nickel could be derived using the ACR approach, unlike when copper BLM was applied. The BLM‐based ACR for nickel is the first result calculated by directly comparing acute and chronic species sensitivities, and will contribute to the application of BLM‐based risk assessment in broader ecoregions. Environ Toxicol Chem 2023;42:914–927. © 2023 SETAC

Keywords: blm based; biotic ligand; predicted effect; acute chronic

Journal Title: Environmental Toxicology and Chemistry
Year Published: 2023

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