Influence of Geochemical Fractionation of Fulvic Acid on its Spectral Characteristics and its Protection Against Copper Toxicity to Daphnia magna

Abstract

Dissolved copper (Cu) can contribute to toxicity in aquatic systems impacted by acid mine drainage (AMD), and its bioavailability is influenced by aqueous complexation with organic ligands that predominantly include fulvic acids (FAs). Because the geochemical fractionation of FAs that accompanies sorption to hydrous aluminum oxides (HAOs) and hydrous iron oxides (HFOs) can alter Cu complexation with FA, we investigated FAs isolated from three categories of water (pristine, AMD, and in situ‐fractionated mixtures of pristine and AMD collected at stream confluences) in three mining‐impacted alpine watersheds in central Colorado, USA. We also conducted geochemical fractionation of field‐collected FAs and Suwannee River FAs by precipitating HAOs and HFOs in the laboratory. Spectral properties of the FAs (e.g., UV‐VIS absorbance) were altered by geochemical fractionation, and in acute toxicity tests with an aquatic invertebrate (Daphnia magna) Cu was more toxic in the presence of in situ‐ and laboratory‐fractionated FAs (median effect concentration [EC50] 19–50 µg Cu L−1) than in the presence of nonfractionated FAs (EC50 48–146 µg Cu L−1). After adjusting for the strain‐specific sensitivity of our D. magna, we improved the accuracy of Biotic Ligand Model predictions of Cu EC50 values for AMD‐related FAs by using an “effective dissolved organic carbon” based on spectral properties that account for among‐FA differences in protectiveness against Cu toxicity. However, some differences remained between predicted and measured EC50 values, especially for FAs from AMD‐related waters that might contain important metal‐binding moieties not accounted for by our measured spectral indices. Environ Toxicol Chem 2023;42:449–462. © 2022 SETAC

Bioavailability and Toxicity Models of Copper to Freshwater Life: The State of Regulatory Science

“…The mechanistic structure of the BLM gives greater potential flexibility for site‐specific use for unusual waters well outside the datasets used to develop the MLR (Mebane et al, 2020). Examples for which the MLR is untested include waters in which hardness is dominated by Mg, in waters with high hardness but low alkalinity (Van Genderen et al, 2007), or in direct proximity to some acid mine drainage waters (Dee et al, 2023). Conceptually, the refined BLM may be able to predict nonlinear pH–toxicity relations outside the pH 6 to 9 range that encompassed most of the MLR data.…”