Modeling the Dynamics of Mixture Toxicity and Effects of Organic Micropollutants in a Small River under Unsteady Flow Conditions

The presence of anthropogenic organic micropollutants in rivers poses a long-term threat to surface water quality. To describe and quantify the in-stream fate of single micropollutants, the advection–dispersion–reaction (ADR) equation has been used previously. Understanding the dynamics of the mixture effects and cytotoxicity that are cumulatively caused by micropollutant mixtures along their flow path in rivers requires a new concept. Thus, we extended the ADR equation from single micropollutants to defined mixtures and then to the measured mixture effects of micropollutants extracted from the same river water samples. Effects (single and mixture) are expressed as effect units and toxic units, the inverse of effect concentrations and inhibitory concentrations, respectively, quantified using a panel of in vitro bioassays. We performed a Lagrangian sampling campaign under unsteady flow, collecting river water that was impacted by a wastewater treatment plant (WWTP) effluent. To reduce the computational time, the solution of the ADR equation was expressed by a convolution-based reactive transport approach, which was used to simulate the dynamics of the effects. The dissipation dynamics of the individual micropollutants were reproduced by the deterministic model following first-order kinetics. The dynamics of experimental mixture effects without known compositions were captured by the model ensemble obtained through Bayesian calibration. The highly fluctuating WWTP effluent discharge dominated the temporal patterns of the effect fluxes in the river. Minor inputs likely from surface runoff and pesticide diffusion might contribute to the general effect and cytotoxicity pattern but could not be confirmed by the model-based analysis of the available effect and chemical data

Modeling the Dynamics of Mixture Toxicity and Effects of Organic Micropollutants in a Small River under Unsteady Flow Conditions

The presence of anthropogenic organic micropollutants in rivers poses a long-term threat to surface water quality. To describe and quantify the in-stream fate of single micropollutants, the advection–dispersion–reaction (ADR) equation has been used previously. Understanding the dynamics of the mixture effects and cytotoxicity that are cumulatively caused by micropollutant mixtures along their flow path in rivers requires a new concept. Thus, we extended the ADR equation from single micropollutants to defined mixtures and then to the measured mixture effects of micropollutants extracted from the same river water samples. Effects (single and mixture) are expressed as effect units and toxic units, the inverse of effect concentrations and inhibitory concentrations, respectively, quantified using a panel of in vitro bioassays. We performed a Lagrangian sampling campaign under unsteady flow, collecting river water that was impacted by a wastewater treatment plant (WWTP) effluent. To reduce the computational time, the solution of the ADR equation was expressed by a convolution-based reactive transport approach, which was used to simulate the dynamics of the effects. The dissipation dynamics of the individual micropollutants were reproduced by the deterministic model following first-order kinetics. The dynamics of experimental mixture effects without known compositions were captured by the model ensemble obtained through Bayesian calibration. The highly fluctuating WWTP effluent discharge dominated the temporal patterns of the effect fluxes in the river. Minor inputs likely from surface runoff and pesticide diffusion might contribute to the general effect and cytotoxicity pattern but could not be confirmed by the model-based analysis of the available effect and chemical data

Cellular Uptake Kinetics of Neutral and Charged Chemicals in <i>in Vitro</i> Assays Measured by Fluorescence Microscopy

Cellular uptake kinetics are key for understanding time-dependent chemical exposure in <i>in vitro</i> cell assays. Slow cellular uptake kinetics in relation to the total exposure time can considerably reduce the biologically effective dose. In this study, fluorescence microscopy combined with automated image analysis was applied for time-resolved quantification of cellular uptake of 10 neutral, anionic, cationic, and zwitterionic fluorophores in two reporter gene assays. The chemical fluorescence in the medium remained relatively constant during the 24-h assay duration, emphasizing that the proteins and lipids in the fetal bovine serum (FBS) supplemented to the assay medium represent a large reservoir of reversibly bound chemicals with the potential to compensate for chemical depletion by cell uptake, growth, and sorption to well materials. Hence FBS plays a role in stabilizing the cellular dose in a similar way as polymer-based passive dosing, here we term this process as serum-mediated passive dosing (SMPD). Neutral chemicals accumulated in the cells up to 12 times faster than charged chemicals. Increasing medium FBS concentrations accelerated uptake due to FBS-facilitated transport but led to lower cellular concentrations as a result of increased sorption to medium proteins and lipids. <i>In vitro</i> cell exposure results from the interaction of several extra- and intracellular processes, leading to variable and time-dependent exposure between different chemicals and assay setups. The medium FBS plays a crucial role for the thermodynamic equilibria as well as for the cellular uptake kinetics, hence influencing exposure. However, quantification of cellular exposure by an area under the curve (AUC) analysis illustrated that, for the evaluated bioassay setup, current <i>in vitro</i> exposure models that assume instantaneous equilibrium between medium and cells still reflect a realistic exposure because the AUC was typically reduced less than 20% compared to the cellular dose that would result from instantaneous equilibrium