Multiple Linear Regression Modeling Predicts the Effects of Surface Water Chemistry on Acute Vanadium Toxicity to Model Freshwater Organisms

摘要

Multiple linear regression (MLR) modeling has been successfully used to predict how water chemistry variables influence the toxicity of cationic metals to aquatic organisms, but no MLR model exists for vanadium (V). Recent research has indicated that an increase in pH (from 6 to 9), or high concentrations of sodium (473 mg Na+/L), increase V toxicity toDaphnia pulex. In contrast, increases in alkalinity (100 mg as CaCO3) and sulfate (100 mg SO42-/L) reduce V toxicity. How these variables influence V toxicity toOncorhynchus mykiss(rainbow trout) was still unknown. Our results show that increasing pH from 6.2 to 8.9 tended to decrease the 96-h median lethal concentration (LC50) for V toxicity toO. mykissby 9.6 mg V/L. An alkalinity increase from 71 to 330 mg/L as CaCO(3)tended to increase the 96-h LC50 by 3.3 mg V/L, whereas when SO(4)(2-)rose from 150 to 250 mg/L, the LC50 significantly increased by 0.3 mg V/L followed by a significant decrease of 1 mg V/L when SO(4)(2-)was 250 mg/L. Sodium (between 100 and 336 mg/L) showed no effect on V toxicity toO. mykiss. The toxicity patterns forO. mykisswere similar to those observed forD. pulex, except for that of SO42-, potentially indicating different mechanisms of V uptake or regulation in the 2 species. The LC50s and associated water chemistry were combined to develop an MLR model forO. mykissandD. pulex. Alkalinity and pH modified V toxicity to both species, whereas SO(4)(2-)influenced V toxicity toD. pulex. Overall, MLR models should be considered for creating new local benchmarks or water quality guidelines for V.Environ Toxicol Chem2020;00:1-9. (c) 2020 SETAC