Predicting copper toxicity in zebrafish larvae under complex water chemistry conditions by using a toxicokinetic-toxicodynamic model.

Multiple water chemistry parameters influence metal toxicity in natural waters and accurate quantification of those influences may accelerate the development of site-specific water quality criteria (WQC) and further execute metal risk assessment for better protection of aquatic biota. Here, we investigated the effects of water chemistry parameters on copper (Cu) toxicity of larval zebrafish (Danio rerio) and then incorporated the effects of key parameters in a Toxicokinetic and Toxicodynamic (TK-TD) model. Further, the proposed TK-TD model was used to predict Cu toxicity in laboratory artificial waters as well as natural water samples. The predictive performance of the TK-TD model was evaluated in comparison to the biotic ligand model (BLM). The results showed that increasing Ca, Mg, pH, and fulvic acid (FA) levels significantly mitigated Cu toxicity in larvae, while K and Na levels had no significant effect on Cu toxicity. A predictive TK-TD model based on these data described 91 % of Cu accumulation and 87 % of survival of larvae exposed to Cu under 0, 2.5, 5, 10 mg/L FA. Compared with BLM, TK-TD model predicted better Cu accumulation and toxicity for an independent dataset in low DOC concentration (<10.95 mg L) of 9 sites in Haihe river (Tianjin, China) media during 96 h exposure. The BLM under-predicted the acute Cu toxicity to larvae when compared with observed values. In high DOC concentration (13.12-17.78 mg L) among three field sites, BLM and TK-TD model both under-predicted the acute Cu toxicity to larvae when compared with observed values. Our research provides a TK-TD approach for predicting Cu toxicity under complex water chemistry conditions and deriving Cu-WQC in different scenarios where there exist limits for using the BLM.