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Microbial biomass and acclimation can affect the removal of organic chemicals in natural surface waters. In order to account for these effects and develop more robust models for biodegradation, we have compiled and curated removal data for un-acclimated (pristine) surface waters on which we developed quantitative structure-activity relationships (QSARs). Global analysis of the very heterogeneous dataset including neutral, anionic, cationic and zwitterionic chemicals (N = 233) using a random forest algorithm showed that useful predictions were possible (Q ext 2 = 0.4-0.5) though relatively large standard errors were associated (SDEP ∼0.7). Classification of the chemicals based on speciation state and metabolic pathway showed that biodegradation is influenced by the two, and that the dependence of biodegradation on chemical characteristics is non-linear. Class-specific QSAR analysis indicated that shape and charge distribution determine the biodegradation of neutral chemicals (R 2 ∼ 0.6), e.g. through membrane permeation or binding to P450 enzymes, whereas the average biodegradation of charged chemicals is 1 to 2 orders of magnitude lower, for which degradation depends more directly on cellular uptake (R 2 ∼ 0.6). Further analysis showed that specific chemical classes such as peptides and organic halogens are relatively less biodegradable in pristine surface waters, resulting in the need for the microbial consortia to acclimate. Additional literature data was used to verify an acclimation model (based on Monod-type kinetics) capable of extrapolating QSAR predictions to acclimating conditions such as in water treatment, downstream lakes and large rivers under μg L -1 to mg L -1 concentrations. The framework developed, despite being based on multiple assumptions, is promising and needs further validation using experimentation with more standardised and homogenised conditions as well as adequate characterization of the inoculum used.

There is a need to study the time course of toxic chemical effects on organisms because there might be a time lag between the onset of chemical exposure and the corresponding adverse effects. For aquatic organisms, crude oil and oil constituents originating from either natural seeps or human activities can be relevant case studies. In the present study the authors tested a generic toxicokinetic model to quantify the time-varying effects of various oil constituents on the survival of aquatic organisms. The model is based on key parameters applicable to an array of species and compounds with baseline toxicity reflected by a generic, internal toxicity threshold or critical body burden (CBB). They compared model estimates with experimental data on the effects of 8 aromatic oil constituents on the survival of aquatic species including crustaceans and fish. The average model uncertainty, expressed as the root mean square error, was 0.25 (minimum-maximum, 0.04-0.67) on a scale between 0 and 1. The estimated survival was generally lower than the measured survival right after the onset of oil constituent exposure. In contrast, the model underestimated the maximum mortality for crustaceans and fish observed in the laboratory. Thus, the model based on the CBB concept failed to adequately predict the lethal effects of the oil constituents on crustaceans and fish. Possible explanations for the deviations between model estimates and observations may include incorrect assumptions regarding a constant lethal body burden, the absence of biotransformation products, and the steady state of aromatic hydrocarbon concentrations in organisms. Clearly, a more complex model approach than the generic model used in the present study is needed to predict toxicity dynamics of narcotic chemicals. Environ Toxicol Chem 2017;36:128-136. © 2016 SETAC., (© 2016 SETAC.)

In the current study differences were evaluated between a complex 3D multistage population model (SINMOD) and a simpler consumer-resource population model for estimating the effects of crude oil on the marine copepod Calanus finmarchicus. The SINTEF OSCAR model was used to simulate hypothetical oil spills in the Lofoten area in 1995, 1997, and 2001. Both population models simulated a negligible effect of crude oil on the Calanus' biomass when assuming low species sensitivity. The simple model estimated a larger effect on the biomass (up to a 100% decline) compared to the complex model (maximum decline of 60-80%) at high species sensitivity to crude oil. These differences may be related to the inclusion of copepod advection in the complex model. Our study showed that if little data is available to parameterize a model, or if computational resources are scarce, the simple model could be used for risk screening. Nevertheless, the possibility of including a dilution factor for time-varying biomass should be examined to improve the estimations of the simple model. The complex model should be used for a more in depth risk analysis, as it includes physical processes such as the drift of organisms and differentiation between developmental stages., (Copyright © 2016 Elsevier Ltd. All rights reserved.)

Due to increasing application, release of nanoparticles (NPs) and nanomaterials into the environment becomes likely. Knowledge about NP uptake in organisms is crucial for risk assessment including estimations on the behavior of NPs based on their physicochemical properties. In the present study, the authors have applied current scientific knowledge to construct a mathematical model, which estimates the transport of NPs through a model biological membrane. The semi-empirical model developed showed all parameters studied to substantially affect the agglomeration of the NPs in suspension, thereby also affecting passive transport. The authors quantified the effects of pH, ionic strength, organic matter concentration of medium, and NP size of several inorganic NPs on the permeation through the lipid membrane. Model outcomes and experimental results described in literature were strongly correlated for several metal oxide NPs. With caution, the model may be used to explain some of the existing variance in nano-uptake and toxicity experiments., (© 2014 SETAC.)

Increasing CO2 atmospheric levels lead to increasing ocean acidification, thereby enhancing calcium carbonate dissolution of calcifying species. We gathered peer-reviewed experimental data on the effects of acidified seawater on calcifying species growth, reproduction, and survival. The data were used to derive species-specific median effective concentrations, i.e., pH50, and pH10, via logistic regression. Subsequently, we developed species sensitivity distributions (SSDs) to assess the potentially affected fraction (PAF) of species exposed to pH declines. Effects on species growth were observed at higher pH than those on species reproduction (mean pH10 was 7.73 vs 7.63 and mean pH50 was 7.28 vs 7.11 for the two life processes, respectively) and the variability in the sensitivity of species increased with increasing number of species available for the PAF (pH10 standard deviation was 0.20, 0.21, and 0.33 for survival, reproduction, and growth, respectively). The SSDs were then applied to two climate change scenarios to estimate the increase in PAF (ΔPAF) by future ocean acidification. In a high CO2 emission scenario, ΔPAF was 3 to 10% (for pH50) and 21 to 32% (for pH10). In a low emission scenario, ΔPAF was 1 to 4% (for pH50) and 7 to 12% (for pH10). Our SSDs developed for the effect of decreasing ocean pH on calcifying marine species assemblages can also be used for comparison with other environmental stressors.

Many studies have focused on natural stress factors that shape the spatial and temporal distribution of calanoid copepods, but bioassays have shown that copepods are also sensitive to a broad range of contaminants. Although both anthropogenic and natural stress factors are obviously at play in natural copepod communities, most studies consider only one or the other. In the present investigation, we modeled the combined impact of both anthropogenic and natural stress factors on copepod populations. The model was applied to estimate Eurytemora affinis densities in the contaminated Scheldt estuary and the relatively uncontaminated Darß-Zingst estuary in relation to temperature, salinity, chlorophyll a, and sediment concentrations of cadmium, copper, and zinc. The results indicated that temperature was largely responsible for seasonal fluctuations of E. affinis densities. Our model results further suggested that exposure to zinc and copper was largely responsible for the reduced population densities in the contaminated estuary. The model provides a consistent framework for integrating and quantifying the impacts of multiple anthropogenic and natural stress factors on copepod populations. It facilitates the extrapolation of laboratory experiments to ecologically relevant end points pertaining to population viability.

Screening level models for environmental assessment of engineered nanoparticles (ENP) are not generally available. Here, we present SimpleBox4Nano (SB4N) as the first model of this type, assess its validity, and evaluate it by comparisons with a known material flow model. SB4N expresses ENP transport and concentrations in and across air, rain, surface waters, soil, and sediment, accounting for nanospecific processes such as aggregation, attachment, and dissolution. The model solves simultaneous mass balance equations (MBE) using simple matrix algebra. The MBEs link all concentrations and transfer processes using first-order rate constants for all processes known to be relevant for ENPs. The first-order rate constants are obtained from the literature. The output of SB4N is mass concentrations of ENPs as free dispersive species, heteroaggregates with natural colloids, and larger natural particles in each compartment in time and at steady state. Known scenario studies for Switzerland were used to demonstrate the impact of the transport processes included in SB4N on the prediction of environmental concentrations. We argue that SB4N-predicted environmental concentrations are useful as background concentrations in environmental risk assessment.

Oral absorption efficiency is an important factor to consider in human risk assessment and varies widely between elements. Linking absorption efficiency to chemical properties facilitates the understanding of underlying processes and enables extrapolation across elements. In our study, oral absorption efficiency in humans was predicted for a number of elements based on their ionization energy and electronegativity. Data on oral absorption efficiency in humans were retrieved via a literature survey. A model was developed based on the assumption that ionic species readily react with biotic ligands. Accordingly, ionization energy was presumed to represent the reactivity and absorption of atoms in the gastrointestinal tract. The coefficients of the model were parameterized by fitting the quantitative relationship between absorption efficiency and ionization energy to data collected from well-standardized studies. Generally, absorption efficiency was strongly related to ionization energy, explaining 94% of the variability in absorption efficiency between elements reported by the International Commission on Radiological Protection (ICRP). In addition, the absorption efficiencies predicted based on ionization energy were within a factor of two of those given by the ICRP (ME = -0.05; RMSE = 0.31). However, the model is not applicable to alkaline metals and molybdenum because of the uniquely high solubility of their compounds or the flexible electron configuration of these elements. Approximately 56% of the variability in absorption efficiency between elements could be explained by electronegativity. These strong relationships between absorption efficiency and ionization energy and, to a lesser extent, electronegativity indicate potential for extrapolation across elements using atomic properties.

Wildlife organisms are exposed to a combination of chemical, biological and physical stressors. Information about the relative impact of each stressor can support management decisions, e.g., by the allocation of resources to counteract those stressors that cause most harm. The present paper introduces Eco-SpaCE; a novel receptor-oriented cumulative exposure model for wildlife species that includes relevant ecological processes such as spatial habitat variation, food web relations, predation, and life history. A case study is presented in which the predicted mortality due to cadmium contamination is compared with the predicted mortality due to flooding, starvation, and predation for three small mammal species (Wood mouse, Common vole, and European mole) and a predator (Little owl) living in a lowland floodplain along the river Rhine in The Netherlands. Results indicated that cadmium is the principal stressor for European mole and Little owl populations. Wood mouse and Common vole population densities were mainly influenced by flooding and food availability. Their estimated population sizes were consistent with numbers reported in literature. Predictions for cadmium accumulation and flooding stress were in agreement with field data. The large uncertainty around cadmium toxicity for wildlife leads to the conclusion that more species-specific ecotoxicological data is required for more realistic risk assessments. The predictions for starvation were subject to the limited quantitative information on biomass obtainable as food for vertebrates. It is concluded that the modelling approach employed in Eco-SpaCE, combining ecology with ecotoxicology, provides a viable option to explore the relative contribution of contamination to the overall stress in an ecosystem. This can help environmental managers to prioritize management options, and to reduce local risks., (Copyright 2009 Elsevier B.V. All rights reserved.)

Environmental risk assessment procedures often use bioaccumulation as a criterion for hazard identification of a polluted location. Field studies regarding metal concentrations in food chains, however, have provided widely different information, because accumulation is shown to vary between the extremes of bioreduction and biomagnification. Bioaccumulation models provide insight regarding species-specific uptake and elimination kinetics of metals and assist in the interpretation of field data. Here, we use the bioaccumulation model OMEGA (Optimal Modeling for Ecotoxicological Applications) to estimate cadmium accumulation in herbivorous voles and carnivorous shrews. In addition to model validation, a meta-analysis of cadmium accumulation data is performed, because earlier studies generally have focused on relationships between cadmium concentrations in either specific tissues (kidney and liver) or whole-body concentrations and total soil levels. Additionally, we included the food-small mammal relationship. Our results show that cadmium whole-body concentrations are significantly related to cadmium levels in food items such as earthworms and plants. In addition, a significant relationship is found between cadmium accumulation in the liver and kidney of small mammals and total soil levels. Cadmium concentrations in shrews typically are an order of magnitude higher than metal levels in voles as a result of higher metal accumulation in earthworms compared to plants. Model predictions for both voles and shrews are in good agreement with field observations; deviations generally are within a factor of five. Small mammals prevent cadmium toxicity by binding this metal to metallothionein, which likely results in low elimination rates. Comparison with empirical elimination rates shows that rate constants of loss are accurately predicted assuming that cadmium is only released via growth dilution.

To protect thousands of species from thousands of chemicals released in the environment, various risk assessment tools have been developed. Here, we link quantitative structure-activity relationships (QSARs) for response concentrations in water (LC50) to critical concentrations in organisms (C50) by a model for accumulation in lipid or non-lipid phases versus water Kpw. The model indicates that affinity for neutral body components such as storage fat yields steep Kpw-Kow relationships, whereas slopes for accumulation in polar phases such as proteins are gentle. This pattern is confirmed by LC50 QSARs for different modes of action, such as neutral versus polar narcotics and organochlorine versus organophosphor insecticides. LC50 QSARs were all between 0.00002 and 0.2Kow(-1). After calibrating the model with the intercepts and, for the first time also, with the slopes of the LC50 QSARs, critical concentrations in organisms C50 are calculated and compared to an independent validation data set. About 60% of the variability in lethal body burdens C50 is explained by the model. Explanations for differences between estimated and measured levels for 11 modes of action are discussed. In particular, relationships between the critical concentrations in organisms C50 and chemical (Kow) or species (lipid content) characteristics are specified and tested. The analysis combines different models proposed before and provides a substantial extension of the data set in comparison to previous work. Moreover, the concept is applied to species (e.g., plants, lean animals) and substances (e.g., specific modes of action) that were scarcely studied quantitatively so far.

Biota to sediment accumulation factors (BSAFs) are widely used to describe the potential accumulation of organic contaminants in organisms. From field studies it is known that these BSAFs can vary dramatically between sediments of different origin, which is possibly explained by the variation in bioavailability of organic contaminants in sediments. In the present study it is shown that the variability in BSAF values for different sediment samples obtained at two Dutch freshwater sites could largely be explained by the variation in Tenax-extractable concentrations in these sediments. Variations of a factor of about 50 could be explained. The ratio between concentrations in biota and Tenax-extractable concentrations in sediment varied slightly between sediments and contaminant class, but was close to the theoretically expected value of 2. This is a strong indication that Tenax-extractable concentrations of contaminants in sediments are an excellent indicator of available concentrations.

In this study, biotransformation rate constants are estimated for a large set of organic compounds. Biotransformation (km) is considered part of the total elimination, further consisting of physico-chemical elimination to water (kw), depuration by feces (kf) and growth dilution (gamma). Existing models are used to estimate kw and kf, and gamma. The difference between measured elimination rate constants and the sum of predicted elimination rate constants for water, feces and growth indicates the ration of biotransformation in the total elimination. In all examined animal classes, polycyclic aromatic hydrocarbons seem to be metabolized at an intermediate rate. Because of the relative low hydrophobicity of some of the studied compounds, their physico-chemical elimination rate constant is relatively high, and the relative contribution of metabolism to total elimination of these compounds is therefore relatively low. Fish seem to be capable of metabolizing chlorodibenzo-p-dioxins and -furans, DDT, chloroanilines and phenol.

Most of the thousands of substances and species that risk assessment has to deal with are not investigated empirically because of financial, practical, and ethical constraints. To facilitate extrapolation, we have developed a model for concentration kinetics of inorganic substances as a function of the exposure concentration of the chemical and the weight and trophic level of the species. The ecological parameters and the resistances that substances encounter during diffusion in water layers were obtained from previous reviews. The other chemical parameters (the resistances for permeation of lipid layers) were calibrated in the present study on 1,062 rate constants for absorption from water, for assimilation from food, and for elimination. Data on all elements and species were collected, but most applied to aquatic species, in particular mollusks and fish, and to transition metals, in particular group IIB (Zn, Cd, Hg). Their ratio was validated on 92 regressions and nine geometric averages, representing thousands of (near-)equilibrium accumulation ratios from laboratory and field studies. Rate constants for absorption and elimination decreased with species weight at an exponent of about -0.25, known from ecological allometry. On average, uptake-rate constants decreased with about the reciprocal square root of the exposure concentration. About 71 and 30% of the variation in absorption and elimination was explained by the model, respectively. The efficiency for assimilation of elements from food appeared to be determined mainly by the food digestibility and the distribution over egested and digested fractions. (Near-)equilibrium accumulation and magnification ratios also decreased with the reciprocal square root of the exposure concentration. The level of the organism-solids concentrations ratios roughly varied between one and two orders of magnitude, depending on the number of elements and species groups investigated. Metal concentrations did not increase at higher trophic levels, with the exception of (methyl-)mercury. Organism-solids concentration ratios for terrestrial species tended to be somewhat lower than those for their aquatic equivalents. Food web accumulation, expressed as organism-organic solids and organism-food concentrations ratios, can therefore be only partly explained by ecological variables. The model is believed to facilitate various types of scientific interpretation as well as environmental risk assessment.

Most of the thousands of substances and species that risk assessment has to deal with are not investigated empirically because of financial, practical, and ethical constraints. To facilitate extrapolation, we have developed a model for accumulation kinetics of organic substances as a function of the octanol-water partition ratio (Kow) of the chemical and the weight, lipid content, and trophic level of the species. The ecological parameters were obtained from a previous review on allometric regressions. The chemical parameters, that is, resistances that substances encounter in water and lipid layers of organisms, were calibrated on 1,939 rate constants for absorption from water for assimilation from food and for elimination. Their ratio was validated on 37 laboratory bioconcentration and biomagnification regressions and on 2,700 field bioaccumulation data. The rate constant for absorption increased with the hydrophobicity of the substances with a Kow up to about 1,000 and then leveled off, decreasing with the weight of the species. About 39% of the variation was explained by the model, while deviations of more than a factor of 5 were noted for labile, large, and less hydrophobic molecules as well as for algae, mollusks, and arthropods. The efficiency for assimilation of contaminants from food was determined mainly by the food digestibility and thus by the trophic level of the species. A distinction was made between substances that are stable, that is, with a minimum elimination only, and those that are labile, that is, with an excess elimination probably largely due to biotransformation. The rate constant for minimum elimination decreased with the hydrophobicity of the substance and the weight of the species. About 70% of the variation was explained by the model, while deviations of more than a factor of 5 were noted for algae, terrestrial plants, and benthic animals. Labile substances were eliminated faster than isolipophilic stable compounds, but differences in laboratory elimination and accumulation were small compared with those in field accumulation. Excess elimination by vertebrates was faster than by invertebrates. Differences between terrestrial and aquatic species were attributed to water turnover rates, whereas differences between trophic levels were due to the food digestibility. Food web accumulation, expressed as organism-organic solids and organism-food concentrations ratios could be largely explained by ecological variables only. The model is believed to facilitate various types of scientific interpretation as well as environmental risk assessment.

Implementing the variation within populations in ecological modeling of risk and effects of toxicants could contribute to a more sophisticated way of modeling. To give insight into the magnitude and spread in sensitivity within test populations the variation in sensitivity of individuals expressed as the slope of a concentration-effect curve (Sm) within more than 300 test populations from toxicity tests with 36 species and 116 substances is analyzed. The overall average variation from this study is 0.65 (Sm) and corresponds to an EC50/EC5 ratio of 2.9. The mode of action is often suggested as an explanation for the different slopes of concentration-effect curves. For metals, indeed, significant different median slope values are observed compared with organic substances. However, within the group of organic substances no distinction between the slope values of narcotic substances and substances with a specific mode of action could be made. Between species groups, significant differences in the amount of variation could be demonstrated. The median slopes for all toxicants within the data set of 96-h tests specified for fishes and mollusks are significantly steeper (median slopes of 0.38 and 0.37, respectively) than those for algae and crustaceans (1.2 and 0.72, respectively). Experimental factors that might explain these differences are discussed. The results from this study provide insight into the variation within a test population and can be used to estimate sensitivity parameters for risk and effect modeling.

From our experience, risk assessment for environmental management and research purposes is in need of models that apply to many of the species we want to protect from many of the microcontaminants released. The traditional one-compartment model serves as such a tool during interpretation and extrapolation of information on concentration kinetics. Unfortunately, its non-steady parameters are specific for a combination of a compound and a species. So, one must seriously face the prospect that their values will never be measured for most compounds and species due to experimental, ethical and financial constraints. It was therefore considered worthwhile to relate the main non-steady state parameter, viz. the outflow (elimination, clearance, depuration) rate, to common characteristics of compounds and species. The outflow rate (kout) for persistent organic microcontaminants was correlated to the octanol-water partition ratio of the compound (Kow) and the size of the species (z). The regressions for aquatic invertebrates, fish and warm-blooded animals were kout = (1/(4*10(-3)*Kow + 7*10(-8)) + 5*10(-3))*z-0.36 (n = 53, r2 = 0.45), kout = (1/(4*10(-4)*Kow + 5) + 4*10(-3))*z-0.19 (n = 140, r2 = 0.68) and kout = (1/(3*10(-4)*Kow + 2*10(-5)) + 8*10(-3))* z-0.86 (n = 51, r2 = 0.48) respectively. The correlation was less strong if Kow or z were omitted. In addition to the minimum loss rate for persistent compounds, one may distinguish an excess outflow rate (mainly caused by biotransformation) for less persistent organic microcontaminants. The order of magnitude difference is explored and ways to refine these estimations are discussed briefly. Outflow rates for cadmium and mercury are linked to species size with the same type of function. The internal consistency of the model was verified by calculating inflow rates from calibrated outflow rates and comparing these to independent measurements. Moreover, the constants in the regressions are explained physically and their value is compared with those obtained in ecology for consumption, production and respiration. The exponent that scales these rates to the species size is similar to the regressions for outflow rates obtained here. The model allows estimations for fairly unknown substances or species and it is thought to help refining risk evaluations without extensive experimental or desk studies. As this paper shows that joint application of chemical (Kow) and ecological (z) information yields more accurate estimations, this study contributes to the often advocated integration of both disciplines in ecotoxicology.