Since the soil quality Tool for Risk Identification, Assessment and Display approach introduced the “three lines of evidence” accounting for chemical, toxicological and ecological stressors to... Show moreSince the soil quality Tool for Risk Identification, Assessment and Display approach introduced the “three lines of evidence” accounting for chemical, toxicological and ecological stressors to explain adverse effects in biota, the assessment of contaminant risks in the environment has significantly evolved. The concept of chemical speciation, related to water characteristics, boosted the understanding of the role of free-ion activities in the overall accumulation of pollutants in biota. New modeling concepts (e.g. biotic ligand models) and measuring techniques were developed. This in turn triggered widespread research addressing the quantitative role of sediment in the overall water quality, focusing on redox interfaces. For contaminant mixtures in river catchments, complex relations between (bio)availability of compounds, including nutrients, help to explain aquatic toxicity. Variation in ecological patterns and processes across environmental or spatiotemporal gradients occur, which may identify ecological factors that influence contaminant fate and effects. Empirical evidence by meta-analysis and theoretical underpinning by modelling showed relationships between population growth rates and carrying capacities, across chemicals and across species. The potentially affected fraction (PAF) of species may be related to the mean species abundance, an often-used indicator in global change studies. Knowledge gaps remain on how pollutants travel through ecological communities and which species and species-relationships are affected. Outdoor experimental systems that examine the natural environment under controlled conditions may be useful at the higher biological level to investigate the impact of stressors on a variety of species, including mutual interactions. Show less
A toxicokinetic-toxicodynamic model was constructed to delineate the exposure-response causality. The model could be used: to predict metal accumulation considering the influence of water chemistry... Show moreA toxicokinetic-toxicodynamic model was constructed to delineate the exposure-response causality. The model could be used: to predict metal accumulation considering the influence of water chemistry and biotic ligand characteristics; to simulate the dynamics of subcellular partitioning considering metabolism, detoxification, and elimination; and to predict chronic toxicity as represented by biomarker responses from the concentration of metals in the fraction of potentially toxic metal. The model was calibrated with data generated from an experiment in which the Zebra mussel Dreissena polymorpha was exposed to Cu at nominal concentrations of 25 and 50 mu g/L and with varied Na+ concentrations in water up to 4.0 mmol/L for 24 days. Data used in the calibration included physicochemical conditions of the exposure environment, Cu concentrations in subcellular fractions, and oxidative stress-induced responses, i.e. glutathione-S-transferase activity and lipid peroxidation. The model explained the dynamics of subcellular Cu partitioning and the effect mechanism reasonably well. With a low affinity constant for Na+ binding to Cu2+ uptake sites, Na+ had limited influence on Cu2+ uptake at low Na+ concentrations in water. Copper was taken up into the metabolically available pool (MAP) at a largely higher rate than into the cellular debris. Similar Cu concentrations were found in these two fractions at low exposure levels, which could be attributed to sequestration pathways (metabolism, detoxification, and elimination) in the MAP. However, such sequestration was inefficient as shown by similar Cu concentrations in detoxified fractions with increasing exposure level accompanied by the increasing Cu concentration in the MAP. Show less
Le, T.T.Y.; Grabner, D.; Nachev, M.; Garcia, M.R.; Balsa-Canto, E.; Peijnenburg, W.J.G.M.; ... ; Sures, B. 2021
A toxicokinetic-toxicodynamic model based on subcellular metal partitioning is presented for simulating chronic toxicity of copper (Cu) from the estimated concentration in the fraction of... Show moreA toxicokinetic-toxicodynamic model based on subcellular metal partitioning is presented for simulating chronic toxicity of copper (Cu) from the estimated concentration in the fraction of potentially toxic metal (PTM). As such, the model allows for considering the significance of different pathways of metal sequestration in predicting metal toxicity. In the metabolically available pool (MAP), excess metals above the metabolic requirements and the detoxification and elimination capacity form the PTM fraction. The reversibly and irreversibly detoxified fractions were distinguished in the biologically detoxified compartment, while responses of organisms were related to Cu accumulation in the PTM fraction. The model was calibrated using the data on Cu concentrations in subcellular fractions and physiological responses measured by the glutathione S-transferase activity and the lipid peroxidation level during 24-day exposure of the Zebra mussel to Cu at concentrations of 25 and 50 mu g/L and varying Na+ concentrations up to 4.0 mmol/L. The model was capable of explaining dynamics in the subcellular Cu partitioning, e.g. the trade-off between elimination and detoxification as well as the dependence of net accumulation, elimination, detoxification, and metabolism on the exposure level. Increases in the net accumulation rate in the MAP contributed to increased concentrations of Cu in this fraction. Moreover, these results are indicative of ineffective detoxification at high exposure levels and spill-over effects of detoxification. Show less
Le, T.T.Y.; Nachev, M.; Grabner, D.; Garcia, M.R.; Balsa-Canto, E.; Hendriks, A.J.; ... ; Sures, B. 2021
Chronic toxicity of copper (Cu) at sublethal levels is associated with ionoregulatory disturbance and oxidative stress. These factors were considered in a toxicokinetic-toxicodynamic model in the... Show moreChronic toxicity of copper (Cu) at sublethal levels is associated with ionoregulatory disturbance and oxidative stress. These factors were considered in a toxicokinetic-toxicodynamic model in the present study. The ionoregulatory disturbance was evaluated by the activity of the Na+/K+-ATPase enzyme (NKA), while oxidative stress was presented by lipid peroxidation (LPO) and glutathione-S-transferase (GST) activity. NKA activity was related to the binding of Cu2+ and Na+ to NKA. LPO and GST activity were linked with the simulated concentration of unbound Cu. The model was calibrated using previously reported data and empirical data generated when zebra mussels were exposed to Cu. The model clearly demonstrated that Cu might inhibit NKA activity by reducing the number of functional pump sites and the limited Cu-bound NKA turnover rate. An ordinary differential equation was used to describe the relationship between the simulated concentration of unbound Cu and LPO/GST activity. Although this method could not explain the fluctuations in these biomarkers during the experiment, the measurements were within the confidence interval of estimations. Model simulation consistently shows nonsignificant differences in LPO and GST activity at two exposure levels, similar to the empirical observation. Show less
Chemistry describes transformation of matter with reaction equations and corresponding rate constants. However, accurate rate constants are not always easy to get. Here we focus on radical... Show moreChemistry describes transformation of matter with reaction equations and corresponding rate constants. However, accurate rate constants are not always easy to get. Here we focus on radical oxidation reactions. Analysis of over 500 published rate constants of hydroxyl radicals led us to hypothesize that a modified linear free-energy relationship (LFER) could be used to predict rate constants speedily, reliably and accurately. LFERs correlate the Gibbs activation-energy with the Gibbs energy of reaction. We calculated the latter as the sum of one-electron transfer and, if appropriate, proton transfer. We parametrized specific transition state effects to orbital delocalizability and the polarity of the reactant. The calculation time for 500 reactions is less than 8 hours on a standard desktop-PC. Rate constants were also calculated for hydrogen and methyl radicals; these controls show that the predictions are applicable to a broader set of oxidizing radicals. An accuracy of 30–40% (standard deviation) with reference to reported experimental values was found suitable for the screening of complex chemical systems for possibly relevant reactions. In particular, potentially relevant reactions can be singled out and scrutinized in detail when prioritizing chemicals for environmental risk assessment. Show less
After use and disposal of chemical products, many types of polymer particles end up in the aquatic environment with potential toxic effects to primary producers like green algae. In this study, we... Show moreAfter use and disposal of chemical products, many types of polymer particles end up in the aquatic environment with potential toxic effects to primary producers like green algae. In this study, we have developed Quantitative Structure-Activity Relationships (QSARs) for a set of highly structural diverse polymers which are capable to estimate green algae growth inhibition (EC50). The model (N = 43, R2 = 0.73, RMSE = 0.28) is a regression-based decision tree using one structural descriptor for each of three polymer classes separated based on charge. The QSAR is applicable to linear homo polymers as well as copolymers and does not require information on the size of the polymer particle or underlying core material. Highly branched polymers, non-nitrogen cationic polymers and polymeric surfactants are not included in the model and thus cannot be evaluated. The model works best for cationic and non-ionic polymers for which cellular adsorption, disruption of the cell wall and photosynthesis inhibition were the mechanisms of action. For anionic polymers, specific properties of the polymer and test characteristics need to be known for detailed assessment. The data and QSAR results for anionic polymers, when combined with molecular dynamics simulations indicated that nutrient depletion is likely the dominant mode of toxicity. Nutrient depletion in turn, is determined by the non-linear interplay between polymer charge density and backbone flexibility. Show less
Quantifying mean annual flow of rivers (MAF) at ungauged sites is essential for assessments of global water supply, ecosystem integrity and water footprints. MAF can be quantified with spatially... Show moreQuantifying mean annual flow of rivers (MAF) at ungauged sites is essential for assessments of global water supply, ecosystem integrity and water footprints. MAF can be quantified with spatially explicit process-based models, which might be overly time-consuming and data-intensive for this purpose, or with empirical regression models that predict MAF based on climate and catchment characteristics. Yet, regression models have mostly been developed at a regional scale and the extent to which they can be extrapolated to other regions is not known. In this study, we developed a global-scale regression model for MAF based on a dataset unprecedented in size, using observations of discharge and catchment characteristics from 1885 catchments worldwide, measuring between 2 and 10(6) km(2). In addition, we compared the performance of the regression model with the predictive ability of the spatially explicit global hydrological model PCR-GLOBWB by comparing results from both models to independent measurements. We obtained a regression model explaining 89% of the variance in MAF based on catchment area and catchment averaged mean annual precipitation and air temperature, slope and elevation. The regression model performed better than PCR-GLOBWB for the prediction of MAF, as root-mean-square error (RMSE) values were lower (0.29-0.38 compared to 0.49-0.57) and the modified index of agreement (d) was higher (0.80-0.83 compared to 0.72-0.75). Our regression model can be applied globally to estimate MAF at any point of the river network, thus providing a feasible alternative to spatially explicit process based global hydrological models. (C) 2016 Elsevier B.V. All rights reserved. Show less
