Assessment of the contribution of surfactants to mixture toxicity in French surface waters.

Surfactants are widely used 'down-the-drain' chemicals with the potential to occur at high concentrations in local water bodies and to be part of unintentional environmental mixtures. Recently, increased regulatory focus has been placed on the impacts of complex mixtures in aquatic environments and the substances that are likely to drive mixture risk. This study assessed the contribution of surfactants to the total mixture pressure in freshwater ecosystems. Environmental concentrations, collated from existing French monitoring data, were combined with estimated ecotoxicological thresholds to calculate hazard quotients (HQ) for each substance, and hazard indices (HI) for each mixture. Two scenarios were investigated to correct for concentrations below the limit of quantification (LOQ) in the dataset. The first (best-case) scenario assumed all values

Ecotoxicity of Lead to a Phytoplankton Community: Effects of pH and Phosphorus Addition and Implications for Risk Assessment.

Ecological risk assessment and water quality criteria for lead (Pb) are increasingly making use of bioavailability-based approaches to account for the impact of toxicity-modifying factors, such as pH and dissolved organic carbon. For phytoplankton, which are among the most Pb-sensitive freshwater species, a Pb bioavailability model has previously been developed based on standard single-species exposures at a high phosphorus (P) concentration and pH range of 6.0 to 8.0. It is well known that P can affect metal toxicity to phytoplankton and that the pH of many surface waters can be above 8.0. We aimed to test whether the single-species bioavailability model for Pb could predict the influence of pH on Pb toxicity to a phytoplankton community at both low and high P supply. A 10-species phytoplankton community was exposed to Pb for 28 days at two different pH levels (7.2 and 8.4) and two different P supply levels (low and high, i.e., total P input 10 and 100 µg/L, respectively) in a full factorial 2 × 2 test design. We found that the effects of total Pb on three community-level endpoints (biodiversity, community functioning, and community structure) were highly dependent on both pH and P supply. Consistent lowest-observed-effect concentrations (LOECs) ranged between 21 and >196 µg total Pb/L and between 10 and >69 µg filtered Pb/L. Long-term LOECs were generally higher, that is, 69 µg total Pb/L (42 µg filtered Pb/L) or greater, across all endpoints and conditions, indicating recovery near the end of the exposure period, and suggesting the occurrence of acclimation to Pb and/or functional redundancy. The highest toxicity of Pb for all endpoints was observed in the pH 7.2 × low P treatment, whereas the pH 8.4 × low P and pH 8.4 × high P treatment were the least sensitive treatments. At the pH 7.2 × high P treatment, the algal community showed an intermediate Pb sensitivity. The effect of pH on the toxicity of filtered Pb could not be precisely quantified because for many endpoints no effect was observed at the highest Pb concentration tested. However, the long-term LOECs (filtered Pb) at low P supply suggest a decrease in Pb toxicity of at least 1.6-fold from pH 7.2 to 8.4, whereas the single-species algal bioavailability model predicted a 2.5-fold increase. This finding suggests that bioavailability effects of pH on Pb toxicity cannot be extrapolated as such from the single species to the community level. Overall, our data indicate that, although the single-species algal Pb bioavailability model may not capture pH effects on Pb ecotoxicity in multispecies systems, the bioavailability-based hazardous concentration for 5% of the species was protective of long-term Pb effects on the structure, function, and diversity of a phytoplankton community in a relevant range of pH and P conditions. Environ Toxicol Chem 2023;42:2684-2700. © 2023 SETAC.

A framework for ecological risk assessment of metal mixtures in aquatic systems.

Although metal mixture toxicity has been studied relatively intensely, there is no general consensus yet on how to incorporate metal mixture toxicity into aquatic risk assessment. We combined existing data on chronic metal mixture toxicity at the species level with species sensitivity distribution (SSD)-based in silico metal mixture risk predictions at the community level for mixtures of Ni, Zn, Cu, Cd, and Pb, to develop a tiered risk assessment scheme for metal mixtures in freshwater. Generally, independent action (IA) predicts chronic metal mixture toxicity at the species level most accurately, whereas concentration addition (CA) is the most conservative model. Mixture effects are noninteractive in 69% (IA) and 44% (CA) and antagonistic in 15% (IA) and 51% (CA) of the experiments, whereas synergisms are only observed in 15% (IA) and 5% (CA) of the experiments. At low effect sizes (∼ 10% mixture effect), CA overestimates metal mixture toxicity at the species level by 1.2-fold (i.e., the mixture interaction factor [MIF]; median). Species, metal presence, or number of metals does not significantly affect the MIF. To predict metal mixture risk at the community level, bioavailability-normalization procedures were combined with CA or IA using SSD techniques in 4 different methods, which were compared using environmental monitoring data of a European river basin (the Dommel, The Netherlands). We found that the simplest method, in which CA is directly applied to the SSD (CASSD ), is also the most conservative method. The CASSD has median margins of safety (MoS) of 1.1 and 1.2 respectively for binary mixtures compared with the theoretically more consistent methods of applying CA or IA to the dose-response curve of each species individually prior to estimating the fraction of affected species (CADRC or IADRC ). The MoS increases linearly with an increasing number of metals, up to 1.4 and 1.7 for quinary mixtures (median) compared with CADRC and IADRC , respectively. When our methods were applied to a geochemical baseline database (Forum of European Geological Surveys [FOREGS]), we found that CASSD yielded a considerable number of mixture risk predictions, even when metals were at background levels (8% of the water samples). In contrast, metal mixture risks predicted with the theoretically more consistent methods (e.g., IADRC ) were very limited under natural background metal concentrations (<1% of the water samples). Based on the combined evidence of chronic mixture toxicity predictions at the species level and evidence of in silico risk predictions at the community level, a tiered risk assessment scheme for evaluating metal mixture risks is presented, with CASSD functioning as a first, simple conservative tier. The more complex, but theoretically more consistent and most accurate method, IADRC , can be used in higher tier assessments. Alternatively, the conservatism of CASSD can be accounted for deterministically by incorporating the MoS and MIF in the scheme. Finally, specific guidance is also given related to specific issues, such as how to deal with nondetect data and complex mixtures that include so-called data-poor metals. Environ Toxicol Chem 2018;37:623-642. © 2017 SETAC.

Systematic Evaluation of Chronic Metal-Mixture Toxicity to Three Species and Implications for Risk Assessment.

Metal contamination generally occurs as mixtures. However, it is yet unresolved how to address metal mixtures in risk assessment. Therefore, using consistent methodologies, we have set up experiments to identify which mixture model applies best at low-level effects, i.e., the independent action (IA) or concentration addition (CA) reference model. The toxicity of metal mixtures (Ni, Zn, Cu, Cd, and Pb) to Daphnia magna, Ceriodaphnia dubia, and Hordeum vulgare was investigated in different waters or soils, totaling 30 different experiments. Some mixtures of different metals, each individually causing <10% inhibition, yielded much larger inhibition (up to 66%) when dosed in combination. In general, IA was most accurate in predicting mixture toxicity, while CA was the most conservative. At low-effect levels important in risk assessments, CA overestimated mixture toxicity to daphnids and H. vulgare, on average, with a factor 1.4 to 3.6. Observed mixture interactions could be related to bioavailability or by competition interactions, either for binding sites of dissolved organic carbon or for biotic ligand sites. Our study suggests that the current metal-by-metal approach in risk evaluations may not be conservative enough for metal mixtures.

Comparison of four methods for bioavailability-based risk assessment of mixtures of Cu, Zn, and Ni in freshwater.

Although chemical risk assessment is still mainly conducted on a substance-by-substance basis, organisms in the environment are typically exposed to mixtures of substances. Risk assessment procedures should therefore be adapted to fit these situations. Four mixture risk assessment methodologies were compared for risk estimations of mixtures of copper (Cu), zinc (Zn), and nickel (Ni). The results showed that use of the log-normal species sensitivity distribution (SSD) instead of the best-fit distribution and sampling species sensitivities independently for each metal instead of using interspecies correlations in metal sensitivity had little impact on risk estimates. Across 4 different monitoring datasets, between 0% and 52% of the target water samples were estimated to be at risk, but only between 0% and 15% of the target water samples were at risk because of the mixture of metals and not any single metal individually. When a natural baseline database was examined, it was estimated that 10% of the target water samples were at risk because of single metals or their mixtures; when the most conservative method was used (concentration addition [CA] applied directly to the SSD, i.e., CASSD ). However, the issue of metal mixture risk at geochemical baseline concentrations became relatively small (2% of target water samples) when a theoretically more correct method was used (CA applied to individual dose response curves, i.e., CADRC ). Finally, across the 4 monitoring datasets, the following order of conservatism for the 4 methods was shown (from most to least conservative, with ranges of median margin of safety [MoS] relative to CASSD ): CASSD > CADRC (MoS = 1.17-1.25) > IADRC (independent action (IA) applied to individual dose-response curves; MoS = 1.38-1.60) > IASSD (MoS = 1.48-1.72). Therefore, it is suggested that these 4 methods can be used in a general tiered scheme for the risk assessment of metal mixtures in a regulatory context. In this scheme, the CASSD method could serve as a first (conservative) tier to identify situations with likely no potential risk at all, regardless of the method used (the sum toxic unit expressed relative to the 5% hazardous concentration [SumTUHC5 ] < 1) and the IASSD method to identify situations of potential risk, also regardless of the method used (the multisubstance potentially affected fraction of species using the IASSD method [msPAFIA,SSD ] > 0.05). The CADRC and IADRC methods could be used for site-specific assessment for situations that fall in between (SumTUHC5 > 1 and msPAFIA,SSD < 0.05). Environ Toxicol Chem 2017;36:2123-2138. © 2017 SETAC.