Spatial variability of ecosystem exposure to home and personal care chemicals in Asia.

It is well recognized that there are currently limitations in the spatial and temporal resolution of environmental exposure models due to significant variabilities and uncertainties in model inputs and parameters. Here we present the updated Pangea multi-scale multimedia model based on the more spatially resolved, catchment-based hydrological HydroBASINS dataset covering the entire globe. We apply it to predict spatially-explicit exposure concentrations of linear alkylbenzene sulphonate (LAS) and triclosan (TCS) as two chemicals found in homecare (HC) and personal care (PC) products in river catchments across Asia, and test its potential for identifying/prioritizing catchments with higher exposure concentrations. In addition, we also identify the key parameters in the model framework driving higher concentrations and perform uncertainty analyses by applying Monte Carlo simulations on emissions and other non-spatial model inputs. The updated combination of Pangea with the HydroBASINS hydrological data represents a substantial improvement from the previous model with the gridded hydrological dataset (WWDRII) for modelling substance fate, with higher resolution and improved coverage in regions with lower flows, with the results demonstrating good agreement with monitored concentrations for TCS in both the freshwater (R2 = 0.55) and sediment (R2 = 0.81) compartments. The ranking of water basins by Predicted Environmental Concentrations (PECs) was similar for both TCS and LAS, with highest concentrations (Indus, Huang He, Cauvery, Huai He and Ganges) being one to two orders of magnitude greater than the water basins with lowest predicted PECs (Mekong and Brahmaputra). Emissions per unit volume of each catchment, chemical persistence, and river discharge were deemed to be the most influential factors on the variation of predicted PECs. Focusing on the Huang He (Yellow River) water basin, uncertainty confidence intervals (factor 31 for LAS and 6 for TCS) are much lower than the variability of predicted PECs across the Huang He catchments (factors 90,700 for LAS and 13,500 for TCS).

Modelling survival: exposure pattern, species sensitivity and uncertainty.

The General Unified Threshold model for Survival (GUTS) integrates previously published toxicokinetic-toxicodynamic models and estimates survival with explicitly defined assumptions. Importantly, GUTS accounts for time-variable exposure to the stressor. We performed three studies to test the ability of GUTS to predict survival of aquatic organisms across different pesticide exposure patterns, time scales and species. Firstly, using synthetic data, we identified experimental data requirements which allow for the estimation of all parameters of the GUTS proper model. Secondly, we assessed how well GUTS, calibrated with short-term survival data of Gammarus pulex exposed to four pesticides, can forecast effects of longer-term pulsed exposures. Thirdly, we tested the ability of GUTS to estimate 14-day median effect concentrations of malathion for a range of species and use these estimates to build species sensitivity distributions for different exposure patterns. We find that GUTS adequately predicts survival across exposure patterns that vary over time. When toxicity is assessed for time-variable concentrations species may differ in their responses depending on the exposure profile. This can result in different species sensitivity rankings and safe levels. The interplay of exposure pattern and species sensitivity deserves systematic investigation in order to better understand how organisms respond to stress, including humans.

QSARs for estimating intrinsic hepatic clearance of organic chemicals in humans.

Quantitative structure-activity relationships (QSARs) were developed to predict the in vitro clearance (CLINT) of xenobiotics metabolised in human hepatocytes (118 compounds) and microsomes (115 compounds). Clearance values were gathered from the scientific literature and multiple linear models were built and validated selecting at most 6 predictors from a pool of over 2000 potential molecular descriptors. For the hepatocytes QSAR, the explained variance (Radj(2)) was 67% and the predictive ability (Rext(2)) was 62%. For the microsomes QSAR, Radj(2) was 50% and Rext(2) 30%. For both liver assays, the most important descriptor relates to electronic properties of the compound. Functional groups of fragments were useful to identify specific compounds that have a deviating reaction rate compared to the others, such as polychlorobiphenyls (PCBs) and organic amides which were poorly metabolised by hepatocytes and microsomes, respectively. For hepatocytes, clearance was predominantly determined by electronic characteristics, while size and shape characteristics were less important and partitioning properties were absent. This may suggest that uptake across the membrane and enzyme binding are not rate-limiting steps. Particularly for hepatocytes the QSAR statistics are encouraging, allowing application of the outcomes in in vitro to in vivo extrapolation.

Towards a meaningful assessment of marine ecological impacts in life cycle assessment (LCA).

Human demands on marine resources and space are currently unprecedented and concerns are rising over observed declines in marine biodiversity. A quantitative understanding of the impact of industrial activities on the marine environment is thus essential. Life cycle assessment (LCA) is a widely applied method for quantifying the environmental impact of products and processes. LCA was originally developed to assess the impacts of land-based industries on mainly terrestrial and freshwater ecosystems. As such, impact indicators for major drivers of marine biodiversity loss are currently lacking. We review quantitative approaches for cause-effect assessment of seven major drivers of marine biodiversity loss: climate change, ocean acidification, eutrophication-induced hypoxia, seabed damage, overexploitation of biotic resources, invasive species and marine plastic debris. Our review shows that impact indicators can be developed for all identified drivers, albeit at different levels of coverage of cause-effect pathways and variable levels of uncertainty and spatial coverage. Modeling approaches to predict the spatial distribution and intensity of human-driven interventions in the marine environment are relatively well-established and can be employed to develop spatially-explicit LCA fate factors. Modeling approaches to quantify the effects of these interventions on marine biodiversity are less well-developed. We highlight specific research challenges to facilitate a coherent incorporation of marine biodiversity loss in LCA, thereby making LCA a more comprehensive and robust environmental impact assessment tool. Research challenges of particular importance include i) incorporation of the non-linear behavior of global circulation models (GCMs) within an LCA framework and ii) improving spatial differentiation, especially the representation of coastal regions in GCMs and ocean-carbon cycle models.

The utilisation of structural descriptors to predict metabolic constants of xenobiotics in mammals.

Quantitative structure-activity relationships (QSARs) were developed to predict the Michaelis-Menten constant (Km) and the maximum reaction rate (Vmax) of xenobiotics metabolised by four enzyme classes in mammalian livers: alcohol dehydrogenase (ADH), aldehyde dehydrogenase (ALDH), flavin-containing monooxygenase (FMO), and cytochrome P450 (CYP). Metabolic constants were gathered from the literature and a genetic algorithm was employed to select at most six predictors from a pool of over 2000 potential molecular descriptors using two-thirds of the xenobiotics in each enzyme class. The resulting multiple linear models were cross-validated using the remaining one-third of the compounds. The explained variances (R(2)adj) of the QSARs were between 50% and 80% and the predictive abilities (R(2)ext) between 50% and 60%, except for the Vmax QSAR of FMO with both R(2)adj and R(2)ext less than 30%. The Vmax values of FMO were independent of substrate chemical structure because the rate-limiting step of its catalytic cycle occurs before compound oxidation. For the other enzymes, Vmax was predominantly determined by functional groups or fragments and electronic properties because of the strong and chemical-specific interactions involved in the metabolic reactions. The most relevant predictors for Km were functional groups or fragments for the enzymes metabolising specific compounds (ADH, ALDH and FMO) and size and shape properties for CYP, likely because of the broad substrate specificity of CYP enzymes. The present study can be helpful to predict the Km and Vmax of four important oxidising enzymes in mammals and better understand the underlying principles of chemical transformation by liver enzymes.

Including carrier-mediated transport in oral uptake prediction of nutrients and pharmaceuticals in humans.

Most toxicokinetic models consider passive diffusion as the only mechanism when modeling the oral uptake of chemicals. However, the overall uptake of nutrients and xenobiotics, such as pharmaceuticals and environmental pollutants, can be increased by influx transport proteins. We incorporated carrier-mediated transport into a one-compartment toxicokinetic model originally developed for passive diffusion only. The predictions were compared with measured oral uptake efficiencies of nutrients and pharmaceuticals, i.e. the fraction of the chemical reaching systemic circulation. Including carrier-mediated uptake improved model predictions for hydrophilic nutrients (RMSE=10% vs. 56%, Coefficient of Efficiency CoE=0.5 vs. -9.6) and for pharmaceuticals (RMSE=21% vs. 28% and CoE=-0.4 vs. -1.1). However, the negative CoE for pharmaceuticals indicates that further improvements are needed. Most important in this respect is a more accurate estimation of vMAX and KM as well as the determination of the amount of expressed and functional transport proteins both in vivo and in vitro.

Toxicokinetic toxicodynamic (TKTD) modeling of Ag toxicity in freshwater organisms: whole-body sodium loss predicts acute mortality across aquatic species.

ToxicoKinetic ToxicoDynamic (TKTD) models are considered essential tools to further advance acute toxicity prediction of metals for a range of species and exposure conditions, but they are currently underutilized. We present a mechanistic TKTD model for acute toxicity prediction of silver (Ag) in freshwater organisms. In this new approach, we explicitly link relevant TKTD processes to species (physiological) characteristics, which facilitates model application to other untested freshwater organisms. The model quantifies the reduction in whole-body sodium concentration over time as a function of the target site inhibition over time, the target site density and the species-specific sodium turnover rate. Freshwater species are assumed to die instantly when they have lost a critical amount of their initial whole-body sodium concentration. Results show that mortality is significantly related to sodium loss (r(2) = 0.86) for various aquatic organisms and exposure durations. The model accurately predicts lethal effect concentrations for different freshwater organisms, including Daphnia magna, rainbow trout and juvenile crayfish, and is able to capture the observed size-specific variation of nearly 2 orders of magnitude in empirical LC50s.

Elucidating differences in metal absorption efficiencies between terrestrial soft-bodied and aquatic species.

It is unknown whether metal absorption efficiencies in terrestrial soft-bodied species can be predicted with the same metal properties as for aquatic species. Here, we developed models for metal absorption efficiency from the dissolved phase for terrestrial worms and several aquatic species, based on 23 metal physicochemical properties. For the worms, the absorption efficiency was successfully related to 7 properties, and is best predicted with the ionic potential. Different properties (8 in total) were found to be statistically significant in regressions predicting metal absorption in aquatic species, with the covalent index being the best predictor. It is hypothesized that metal absorption by soft-bodied species in soil systems is influenced by the rate of metal supply to the membrane, while in aquatic systems accumulation is solely determined by metal affinity to membrane bound transport proteins. Our results imply that developing predictive terrestrial bioaccumulation and toxicity models for metals must consider metal interactions with soil solids. This may include desorption of a cation bound to soil solids through ion exchange, or metal release from soil surfaces involving breaking of metal-oxygen bonds.

Mechanistically-based QSARs to describe metabolic constants in mammals.

Biotransformation is one of the processes which influence the bioaccumulation of chemicals. The enzymatic action of metabolism involves two processes, i.e. the binding of the substrate to the enzyme followed by a catalytic reaction, which are described by the Michaelis-Menten constant (Km) and the maximum rate (Vmax). Here, we developed Quantitative Structure-Activity Relationships (QSARs) for Log(1/Km) and LogVmax for substrates of four enzyme classes. We focused on oxidations catalysed by alcohol dehydrogenase (ADH), aldehyde dehydrogenase (ALDH), flavin-containing monooxygenase (FMO) and cytochrome P450 (CYP) in mammals. The chemicals investigated were xenobiotics, including alcohols, aldehydes, pesticides and drugs. We applied general linear models for this purpose, employing descriptors related to partitioning, geometric characteristics, and electronic properties of the substrates, which can be interpreted mechanistically. The explained variance of the QSARs varied between 20% and 70%, and it was larger for Log(1/Km) than for LogVmax. The increase of 1/Km with compound logP and size suggests that weak interactions are important, e.g. by substrate binding via desolvation processes. The importance of electronic factors for 1/Km was described in relation to the catalytic mechanism of the enzymes. Vmax was particularly influenced by electronic properties, such as dipole moment and energy of the lowest unoccupied molecular orbital. This can be explained by the nature of the catalysis, characterised by the cleavage and formation of covalent or ionic bonds (strong interactions). The present study may be helpful to understand the underlying principles of the chemical specific activity of four important oxidising enzymes.

Cellular uptake of nanoparticles as determined by particle properties, experimental conditions, and cell type.

The increased application of nanoparticles (NPs) is increasing the risk of their release into the environment. Although many toxicity studies have been conducted, the environmental risk is difficult to estimate, because uptake mechanisms are often not determined in toxicity studies. In the present study, the authors review dominant uptake mechanisms of NPs in cells, as well as the effect of NP properties, experimental conditions, and cell type on NP uptake. Knowledge of NP uptake is crucial for risk assessment and is essential to predict the behavior of NPs based on their physical-chemical properties. Important uptake mechanisms for eukaryotic cells are macropinocytosis, receptor-mediated endocytosis, and phagocytosis in specialized mammalian cells. The studies reviewed demonstrate that uptake into nonphagocytic cells depends strongly on NP size, with an uptake optimum at an NP diameter of approximately 50 nm. Increasing surface charges, either positive or negative, have been shown to increase particle uptake in comparison with uncharged NPs. Another important factor is the degree of (homo-) aggregation. Results regarding shape have been ambiguous. Difficulties in the production of NPs, with 1 property changed at a time, call for a full characterization of NP properties. Only then will it be possible to draw conclusions as to which property affected the uptake.

Modelling bioaccumulation of oil constituents in aquatic species.

Crude oil poses a risk to marine ecosystems due to its toxicity and tendency to accumulate in biota. The present study evaluated the applicability of the OMEGA model for estimating oil accumulation in aquatic species by comparing model predictions of kinetic rates (absorption and elimination) and bioconcentration factors (BCF) with measured values. The model was a better predictor than the means of the measurements for absorption and elimination rate constants, but did not outperform the mean measured BCF. Model estimates and measurements differed less than one order of magnitude for 91%, 80% and 61% of the absorption and elimination rates and BCFs of all oil constituents, respectively. Of the "potentially modifying" factors: exposure duration, biotransformation, molecular mass, and water temperature, the last two tended to influence the performance of the model. Inclusion of more explanatory variables in the bioaccumulation model, like the molecular mass, is expected to improve model performance.

Environmental exposure assessment of engineered nanoparticles: why REACH needs adjustment.

Engineered nanomaterials (ENMs) possess novel properties making them attractive for application in a wide spectrum of fields. These novel properties are not accounted for in the environmental risk assessment methods that the Registration, Evaluation, Authorization, and Restriction of Chemicals (REACH) proposes in their guidance on environmental exposure estimation, although ENMs are already applied in a variety of consumer and industrial products. It is thus necessary to evaluate the guidance document REACH provides on environmental exposure estimation on its applicability to ENMs. This is most urgently the case for engineered nanoparticles (ENPs), as the novel properties are most often only applicable to them. The environmental fate of ENPs was reviewed and compared to the environmental fate of chemicals according to the REACH guidance. Major deviations between the fate of ENPs and predicted fate by REACH were found. They were related to at least 1 of 3 major assumptions made in REACH guidance: 1) in REACH, environmental alteration processes are all thought of as removal processes, whereas alterations of ENPs in the environment may greatly affect their properties, environmental effects, and behavior, 2) in REACH, chemicals are supposed to dissolve instantaneously and completely on release into the environment, whereas ENPs should be treated as nondissolved nanosized solids, and 3) in REACH, partitioning of dissolved chemicals to solid particles in air, water, and soil is estimated with thermodynamic equilibrium coefficients, but in the case of ENPs thermodynamic equilibrium between "dispersed" and "attached" states is generally not expected. The environmental exposure assessment of REACH therefore needs adjustment to cover the specific environmental fate of ENPs. Incorporation of the specific environmental fate processes of ENPs into the environmental risk assessment framework of REACH requires a pragmatic approach.

Including ecotoxic impacts on warm-blooded predators in life cycle impact assessment.

In current life cycle impact assessment, the focus of ecotoxicity is on cold-blooded species. We developed a method to calculate characterization factors (CFs) for the impact assessment of chemical emissions on warm-blooded predators in freshwater food chains. The method was applied to 329 organic chemicals. The CF for these predators was defined as a multiplication of the fate factor (FF), exposure factor (XF), bioaccumulation factor (BF), and effect factor (EF). Fate factors and XFs were calculated with the model USES-LCA 2.0. Bioaccumulation factors were calculated with the model OMEGA, for chemical uptake via freshwater, food, and air. Effect factors were calculated based on experimental, median lethal doses (LD50). The concentration buildup (CB) of the chemicals (i.e., FF, XF, and BF over the 3 routes of exposure) showed a range of 7 to 9 orders of magnitude, depending on the emission compartment. Effect factors displayed a range of 7 orders of magnitude. Characterization factors ranged 9 orders of magnitude. After emissions to freshwater, the relative contribution of the uptake routes to CB were 1% (90% confidence interval [CI]: 0%-2%) for uptake from air, 43% (11%-50%) for uptake from water, and 56% (50%-87%) for uptake from food. After an emission to agricultural soil, the contribution was 11% (0%-80%) for uptake from air, 39% (5%-50%) for uptake from water, and 50% (11%-83%) for uptake from food. Uptake from air was mainly relevant for emissions to air (on average 42%, 90% CI: 5%-98%). Characterization factors for cold-blooded species were typically 4 orders of magnitude higher than CFs for warm-blooded predators. The correlation between both types of CFs was low, which means that a high relative impact on cold-blooded species does not necessarily indicate a high relative impact on warm-blooded predators. Depending on the weighing method to be considered, the inclusion of impacts on warm-blooded predators can change the relative ranking of toxic chemicals in a life cycle assessment.

Including impacts of particulate emissions on marine ecosystems in life cycle assessment: the case of offshore oil and gas production.

Life cycle assessment is increasingly used to assess the environmental performance of fossil energy systems. Two of the dominant emissions of offshore oil and gas production to the marine environment are the discharge of produced water and drilling waste. Although environmental impacts of produced water are predominantly due to chemical stressors, a major concern regarding drilling waste discharge is the potential physical impact due to particles. At present, impact indicators for particulate emissions are not yet available in life cycle assessment. Here, we develop characterization factors for 2 distinct impacts of particulate emissions: an increased turbidity zone in the water column and physical burial of benthic communities. The characterization factor for turbidity is developed analogous to characterization factors for toxic impacts, and ranges from 1.4 PAF (potentially affected fraction) · m(3) /d/kg(p) (kilogram particulate) to 7.0 x 10³ [corrected] for drilling mud particles discharged from the rig. The characterization factor for burial describes the volume of sediment that is impacted by particle deposition on the seafloor and equals 2.0 × 10(-1) PAF · m(3) /d/kg(p) for cutting particles. This characterization factor is quantified on the basis of initial deposition layer characteristics, such as height and surface area, the initial benthic response, and the recovery rate. We assessed the relevance of including particulate emissions in an impact assessment of offshore oil and gas production. Accordingly, the total impact on the water column and on the sediment was quantified based on emission data of produced water and drilling waste for all oil and gas fields on the Norwegian continental shelf in 2008. Our results show that cutting particles contribute substantially to the total impact of offshore oil and gas production on marine sediments, with a relative contribution of 55% and 31% on the regional and global scale, respectively. In contrast, the contribution of particulate emissions to the total impact on the marine water column is of minor importance. We conclude that particles are an important stressor in marine ecosystems, particularly for marine sediment, and particulate emissions should therefore be included in a (life cycle) impact assessment of offshore oil and gas production.

Integration of biotic ligand models (BLM) and bioaccumulation kinetics into a mechanistic framework for metal uptake in aquatic organisms.

Both biotic ligand models (BLM) and bioaccumulation models aim to quantify metal exposure based on mechanistic knowledge, but key factors included in the description of metal uptake differ between the two approaches. Here, we present a quantitative comparison of both approaches and show that BLM and bioaccumulation kinetics can be merged into a common mechanistic framework for metal uptake in aquatic organisms. Our results show that metal-specific absorption efficiencies calculated from BLM-parameters for freshwater fish are highly comparable, i.e. within a factor of 2.4 for silver, cadmium, copper, and zinc, to bioaccumulation-absorption efficiencies for predominantly marine fish. Conditional affinity constants are significantly related to the metal-specific covalent index. Additionally, the affinity constants of calcium, cadmium, copper, sodium, and zinc are significantly comparable across aquatic species, including molluscs, daphnids, and fish. This suggests that affinity constants can be estimated from the covalent index, and constants can be extrapolated across species. A new model is proposed that integrates the combined effect of metal chemodynamics, as speciation, competition, and ligand affinity, and species characteristics, as size, on metal uptake by aquatic organisms. An important direction for further research is the quantitative comparison of the proposed model with acute toxicity values for organisms belonging to different size classes.

Human and environmental impact assessment of postcombustion CO2 capture focusing on emissions from amine-based scrubbing solvents to air.

Carbon Capture and Storage (CCS) has become a key technology in climate change mitigation programs worldwide. CCS is well-studied in terms of greenhouse gas emission reduction potential and cost of implementation. Impacts on human health and the environment have, however, received considerably less attention. In this work, we present a first assessment of human health and environmental impacts of a postcombustion CO(2) capture facility, focusing on emissions from amine-based scrubbing solvents and their degradation products to air. We develop characterization factors for human toxicity for monoethanolamine (MEA) as these were not yet available. On the basis of the limited information available, our assessment indicates that amine-based scrubbing results in a 10-fold increase in toxic impact on freshwater ecosystems and a minor increase in toxic impacts on terrestrial ecosystems. These increases are attributed to emissions of monoethanolamine. For all other impact categories, i.e., human toxicity, marine ecotoxicity, particulate matter formation, photochemical oxidant formation, and terrestrial acidification, the CO(2) capture facility performs equally well to a conventional NGCC power plant, albeit substantial changes in flue gas composition. The oxidative degradation products of MEA, i.e., formaldehyde, acetaldehyde, and ammonia, do not contribute significantly to total environmental impacts.

Bioaccumulation potential of air contaminants: combining biological allometry, chemical equilibrium and mass-balances to predict accumulation of air pollutants in various mammals.

In the present study we develop and test a uniform model intended for single compartment analysis in the context of human and environmental risk assessment of airborne contaminants. The new aspects of the model are the integration of biological allometry with fugacity-based mass-balance theory to describe exchange of contaminants with air. The developed model is applicable to various mammalian species and a range of chemicals, while requiring few and typically well-known input parameters, such as the adult mass and composition of the species, and the octanol-water and air-water partition coefficient of the chemical. Accumulation of organic chemicals is typically considered to be a function of the chemical affinity for lipid components in tissues. Here, we use a generic description of chemical affinity for neutral and polar lipids and proteins to estimate blood-air partition coefficients (K(ba)) and tissue-air partition coefficients (K(ta)) for various mammals. This provides a more accurate prediction of blood-air partition coefficients, as proteins make up a large fraction of total blood components. The results show that 68% of the modeled inhalation and exhalation rate constants are within a factor of 2.1 from independent empirical values for humans, rats and mice, and 87% of the predicted blood-air partition coefficients are within a factor of 5 from empirical data. At steady-state, the bioaccumulation potential of air pollutants is shown to be mainly a function of the tissue-air partition coefficient and the biotransformation capacity of the species and depends weakly on the ventilation rate and the cardiac output of mammals.

Cadmium bioaccumulation factors for terrestrial species: application of the mechanistic bioaccumulation model OMEGA to explain field data.

In environmental risk assessment of metals it is often assumed that the biota-to-soil accumulation factor (BSAF) is generic and constant. However, previous studies have shown that cadmium bioaccumulation factors of earthworms and small mammals are inversely related to total soil concentrations. Here, we provide an overview of cadmium accumulation in terrestrial species belonging to different trophic levels, including plants, snails and moles. Internal metal concentrations of these species are less than linearly related to total soil levels, which is in accordance with previously observed trends. The mechanistic bioaccumulation model OMEGA (Optimal Modeling for Ecotoxicological Applications) is used to provide a quantitative explanation of these trends in cadmium accumulation. Our results indicate that the model accurately predicts cadmium accumulation in earthworms, voles and shrews when accounting for geochemical availability of metals and saturable uptake kinetics.

Estimating bioconcentration factors, lethal concentrations and critical body residues of metals in the mollusks Perna viridis and Mytilus edulis using ion characteristics.

Quantitative structure-activity relationships (QSARs) for metal bioconcentration factors (BCF) and median acute lethal water concentrations (LC50) were developed for two species of mollusks, Perna viridis and Mytilus edulis. These endpoints were related to four metal ion characteristics, the covalent index (chi(2)(m)r) (r represents the ion radius in A), the softness index (sigma(p)), the hydrolysis constant (K(OH)) and the ionic index (Z(2)/r). The BCF and LC50 were significantly correlated to chi(m)(2)r. The coefficients of determination r(2) for the relationships with other metal descriptors were much lower. Critical body residue (CBR) QSARs were derived by multiplying the chi(2)(m)r-based BCF and LC50 regressions. The CBRs were independent of the covalent index chi(2)(m)r, as BCF and LC50 scaled to chi(2)(m)r with slope that had opposite signs. Comparison of the estimated CBRs with independent empirical values confirmed the predicted trends, but substantial deviations were noted too.

Metal bioaccumulation in aquatic species: quantification of uptake and elimination rate constants using physicochemical properties of metals and physiological characteristics of species.

Mechanistic bioaccumulation models are powerful tools in environmental risk assessment as they provide insight in varying accumulation patterns across species, contaminants, and conditions, and they are applicable beyond tested cases. In these models key parameters, as absorption and elimination rate constants, are predicted based on chemical specific properties and physiological characteristics. However, due to the complex environmental behavior of metals, the development of mechanistic bioaccumulation models has lagged behind that for organic chemicals. Absorption and elimination rate constants of organic substances have long been linked to their octanol-water partition coefficient, yet no equivalent quantitative relationships exist for metals. In the present study, we successfully related metal absorption rate constants to a metal specific property, the covalent index, and a species-characteristic, the ventilation rate. This quantitative relationship holds for a wide range of organisms and metals, i.e., 17 aquatic species and 10 metals, suggesting that a generic modeling approach of metal uptake kinetics is feasible for aquatic organisms. In contrast, elimination rate constants show no metal - specific character. Average, weight-corrected elimination rate constants are relatively similar among metals and species, suggesting that a single weight-corrected elimination rate constant can be used in bioaccumulation studies on aquatic species.