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An increasing number of pharmaceuticals found in the environment potentially impose adverse effects on organisms such as fish. Physiologically based kinetic (PBK) models are essential risk assessment tools, allowing a mechanistic approach to understanding chemical effects within organisms. However, fish PBK models have been restricted to a few species, limiting the overall applicability given the countless species. Moreover, many pharmaceuticals are ionizable, and fish PBK models accounting for ionization are rare. Here, we developed a generalized PBK model, estimating required parameters as functions of fish and chemical properties. We assessed the model performance for five pharmaceuticals (covering neutral and ionic structures). With biotransformation half-lives (HLs) from EPI Suite, 73 and 41% of the time-course estimations were within a 10-fold and a 3-fold difference from measurements, respectively. The performance improved using experimental biotransformation HLs (87 and 59%, respectively). Estimations for ionizable substances were more accurate than any of the existing species-specific PBK models. The present study is the first to develop a generalized fish PBK model focusing on mechanism-based parameterization and explicitly accounting for ionization. Our generalized model facilitates its application across chemicals and species, improving efficiency for environmental risk assessment and supporting an animal-free toxicity testing paradigm.

We aimed to identify patterns in the internal distribution of persistent organic pollutants (POPs) and assess contributing factors using sea turtles and their offspring as a case study of a long-lived wildlife species. We systematically synthesized 40 years of data and developed a lipid database to test whether lipid-normalized POP concentrations are equal among tissues as expected under steady state for lipophilic compounds. Results supported equal partitioning among tissues with high blood flow or perfusion including the heart, kidney, muscle, and lung. Observed differences in the brain, fat, and blood plasma, however, suggest the physiological influence of the blood-brain barrier, limited perfusion, and protein content, respectively. Polybrominated diphenyl ethers partitioned comparably to legacy POPs. Polycyclic aromatic hydrocarbons, meanwhile, partitioned more into the lung, colon, and muscle compared to the liver under chronic and acute field exposure. Partitioning ratios of individual POPs among tissues were significantly related to the lipophilicity of compounds (as estimated by K ow ) in half of the observed cases, and significant differences between juveniles and adults underscore physiological differences across life stages. The comprehensive tissue partitioning patterns presented here provide a quantitative basis to support comparative assessments of POP pollution derived from biomonitoring among multiple tissues.

The densely populated North Sea region encompasses catchments of rivers such as Scheldt and Meuse. Herein, agricultural, industrial, and household chemicals are emitted, transported by water, and deposited in sediments, posing ecological risks. Though sediment monitoring is often costly and time-intensive, modeling its toxicity to biota has received little attention. Due to high complexity of interacting variables that induce overall toxicity, monitoring data only sporadically validates current models. Via a range of concepts, we related bio-physicochemical constituents of sediment in Flanders to results from toxicity bioassays performed on the ostracod Heterocypris incongruens . Depending on the water body, we explain up to 90% of the variance in H. incongruens growth. Though variable across Flanders' main water bodies, organotin cations and ammonia dominate the observed toxicity according to toxic unit (TU) assessments. Approximately 10% relates to testing conditions/setups, species variabilities, incoherently documented pollutant concentrations, and/or bio-physicochemical sediment properties. We elucidated the influence of organotin cations and ammonia relative to other metal(oxides) and biocides. Surprisingly, the tributylin cation appeared ∼1000 times more toxic to H. incongruens as compared to "single-substance" bioassays for similar species. We inferred indirect mixture effects between organotin, ammonia, and phosphate. Via chemical speciation calculations, we observed strong physicochemical and biological interactions between phosphate and organotin cations. These interactions enhance bioconcentration and explain the elevated toxicity of organotin cations. Our study aids water managers and policy makers to interpret monitoring data on a mechanistic basis. As sampled sediments differ, future modeling requires more emphasis on characterizing and parametrizing the interactions between bioassay constituents. We envision that this will aid in bridging the gap between testing in the laboratory and field observations.

Simultaneous presence of metals and parasites in fish might lead to potential risks to human health. Parasites might influence metal accumulation and disturb detoxification in fish, thereby affecting biomarkers of fish responses as well as metal biomagnification in humans. It is, therefore, of importance to take into account parasite infection when investigating metal accumulation in fish. However, mechanisms of metal accumulation and distribution in fish-parasite systems are not integrated into current approaches. The present study proposes a new physiologically based pharmacokinetic model for mechanistic simulation of metal partitioning between intestinal parasites and their hosts. As a particular case, Ag accumulation in the system of chub Squalius cephalus and the acanthocephalan Pomphorhynchus tereticollis was investigated. As a novelty, fish cardiac output and organ-specific blood flow distribution were incorporated in our model. This approach distinguishes the current model from the ones developed previously. It also facilitates model extrapolation and application to varying conditions. In general, the model explained Ag accumulation in the system well, especially in chub gill, storage (including skin, muscle, and carcass), and liver. The highest concentration of Ag was found in the liver. The accumulation of Ag in the storage, liver, and gill compartments followed a similar pattern, i.e., increasing during the exposure and decreasing during the depuration. The model also generated this observed trend. However, the model had a weaker performance for simulating Ag accumulation in the intestine and the kidney. Silver accumulation in these organs was less evident with considerable variations.

Ecological risks (ERs) of pollutants are typically assessed using species sensitivity distributions (SSDs), based on effect concentrations obtained from bioassays with unknown representativeness for field conditions. Alternatively, monitoring data relating breeding success in bird populations to egg concentrations may be used. In this study, we developed a procedure to derive SSDs for birds based on field data of egg concentrations and reproductive success. As an example, we derived field-based SSDs for p, p'-DDE and polychlorinated biphenyls (PCBs) exposure to birds. These SSDs were used to calculate ERs for these two chemicals in the American Great Lakes and the Arctic. First, we obtained field data of p, p'-DDE and PCBs egg concentrations and reproductive success from the literature. Second, these field data were used to fit exposure-response curves along the upper boundary (right margin) of the response's distribution (95th quantile), also called quantile regression analysis. The upper boundary is used to account for heterogeneity in reproductive success induced by other external factors. Third, the species-specific EC 10/50 s obtained from the field-based exposure-response curves were used to derive SSDs per chemical. Finally, the SSDs were combined with specific exposure data for both compounds in the two areas to calculate the ER. We found that the ERs of combined exposure to these two chemicals were a factor of 5-35 higher in the Great Lakes compared to Arctic regions. Uncertainty in the species-specific exposure-response curves and related SSDs was mainly caused by the limited number of field exposure-response data for bird species. With sufficient monitoring data, our method can be used to quantify field-based ecological risks for other chemicals, species groups, and regions of interest.

Species sensitivity distributions (SSDs) are commonly used in regulatory procedures and ecological risk assessments. Yet, most toxicity threshold and risk assessment studies are based on invertebrates and fish. In the present study, no observed effect concentrations (NOECs) specific to birds and mammals were used to derive SSDs and corresponding hazardous concentrations for 5% of the species (HC5 values). This was done for 41 individual substances as well as for subsets of substances aggregated based on their toxic Mode of Action (MoA). In addition, potential differences in SSD parameters (mean and standard deviation) were investigated in relation to MoA and end point (growth, reproduction, and survival). The means of neurotoxic and respirotoxic compounds were significantly lower than those of narcotics, whereas no differences were found between end points. The standard deviations of the SSDs were similar across MoA's and end points. Finally, the SSDs obtained were used in a case study by calculating Ecological Risks (ER) and multisubstance Potentially Affected Fractions of species (msPAF) based on 19 chemicals in 10 Northwestern European estuaries and coastal areas. The assessment showed that the risks were all below 2.6 × 10 -2 . However, the calculated risks underestimate the actual risks of chemicals in these areas because the potential impacts of substances that were not measured in the field or for which no SSD was available were not included in the risk assessment. The SSDs obtained can be used in regulatory procedures and for assessing the impacts of contaminants on birds and mammals from fish contaminants monitoring programs.

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.

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.

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.

In bioaccumulation models, biotransformation is one of the processes decreasing the concentration of chemicals in an organism. In order to be metabolized, a compound needs to bind to an enzyme. In this study, we derived relationships between binding affinity and lipophilicity, expressed as Log (1/K(m)) and Log K(ow), respectively. We focused on oxidations in mammals catalyzed by alcohol dehydrogenase (ADH), aldehyde dehydrogenase (ALDH), flavin-containing monooxygenase (FMO), and cytochrome P450 (CYP) enzymes. For all regressions, 1/K(m) increased with compound K(ow), which can be understood from the tendency to biotransform lipophilic compounds into more polar, thus more easily excretable metabolites. Lipophilicity was relevant to the binding of most of the substrate classes of ADH, ALDH, and CYP. The resulting slopes had 95% Confidence Intervals covering the value of 0.63, typically noted in protein-water distribution (Log K(pw)) and Log K(ow) regressions. A reduced slope (0.2-0.3) was found for FMO: this may be due to a different reaction mechanism involving a nucleophilic attack. The general patterns of metabolism were mechanistically interpreted in terms of partitioning theory. Information on the overall principles determining biotransformation may be helpful in predicting metabolic rates., (© 2012 American Chemical Society)

Protecting Arctic ecosystems against potential adverse effects from anthropogenic activities is recognized as a top priority. In particular, understanding the accumulation and effects of persistent organic pollutants (POPs) in these otherwise pristine ecosystems remains a scientific challenge. Here, we combine more than 20,000 tissue concentrations, a food web bioaccumulation model, and time trend analyses to demonstrate that the concentrations of legacy-POPs in the Barents/Norwegian Sea fauna decreased 10-fold between 1985 and 2010, which reflects regulatory efforts to restrict these substances. In contrast, concentrations of fossil fuel derived PAHs in lower trophic levels (invertebrates and fish) increased 10 to 30 fold over the past 25 years and now dominate the summed POP burden (25 POPs, including 11 PAHs) in these biota. Before 2000, PCBs dominated the summed POP burden in top predators. Our findings indicate that the debate on the environmental impacts of fossil fuel burning should move beyond the expected seawater temperature increase and examine the possible environmental impact of fossil fuel derived PAHs.

Potential contamination of polar regions due to increasing oil exploitation and transportation poses risks to marine species. Risk assessments for polar marine species or ecosystems are mostly based on toxicity data obtained for temperate species. Yet, it is unclear whether toxicity data of temperate organisms are representative for polar species and ecosystems. The present study compared sensitivities of polar and temperate marine species to crude oil, 2-methyl-naphthalene, and naphthalene. Species sensitivity distributions (SSDs) were constructed for polar and temperate species based on acute toxicity data from scientific literature, reports, and databases. Overall, there was a maximum factor of 3 difference in sensitivity to oil and oil components, based on the means of the toxicity data and the hazardous concentrations for 5 and 50% of the species (HC₅ and HC₅₀) as derived from the SSDs. Except for chordates and naphthalene, polar and temperate species sensitivities did not differ significantly. The results are interpreted in the light of physiological characteristics, such as metabolism, lipid fraction, lipid composition, antioxidant levels, and resistance to freezing, that have been suggested to influence the susceptibility of marine species to oil. As a consequence, acute toxicity data obtained for temperate organisms may serve to obtain a first indication of risks in polar regions.

To perform life-cycle assessment studies, data on the production and use of the products is required. However, often only few data or measurements are available. Estimation of properties can be performed by applying scaling relationships. In many disciplines, they are used to either predict data or to search for underlying patterns, but they have not been considered in the context of product assessments hitherto. The goal of this study was to explore size scaling for commonly used energy conversion equipment, that is, boilers, engines, and generators. The variables mass M, fuel consumption Q, and costs C were related to power P. The established power-law relationships were M = 10(0.73.. 1.89)P(0.64.. 1.23) (R(2) ≥ 0.94), Q = 10(0.06.. 0.68)P(0.82.. 1.02) (R(2) ≥ 0.98) and C = 10(2.46.. 2.86)P(0.83.. 0.85) (R(2) ≥ 0.83). Mass versus power and costs versus power showed that none of the equipment types scaled isometrically, that is, with a slope of 1. Fuel consumption versus power scaled approximately isometrically for steam boilers, the other equipments scaled significantly lower than 1. This nonlinear scaling behavior induces a significant size effect. The power laws we established can be applied to scale the mass, fuel consumption and costs of energy conversion equipments up or down. Our findings suggest that empirical scaling laws can be used to estimate properties, particularly relevant in studies focusing on early product development for which generally only little information is available.

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.

Ecotoxicogenomics might help solving open questions that cannot be answered by standard ecotoxicity tests currently used in environmental risk assessment. Changes in gene expression are claimed to serve potentially as early warning indicators for environmental effects and as sensitive and specific ecotoxicological end points. Ecotoxicogenomics focus on the lowest rather than the highest levels of biological organization. Our aim was to explore the links between gene expression responses and population level responses, both mechanistically (conceptual framework) and correlatively (Species Sensitivity Distribution). The effects of cadmium on aquatic species were compared for gene level responses (Lowest Observed Effect Concentrations) and individual level responses (median Lethal Concentrations, LC(50), and No Observed Effect Concentrations, NOEC). Responses in gene expression were on average four times above the NOEC and eleven times below the LC(50) values. Currently, use of gene expression changes as early warning indicators of environmental effects is not underpinned due to a lack of data. To confirm the sensitivity claimed by ecotoxicogenomics more testing at low concentrations is needed. From the conceptual framework, we conclude that for a mechanistic gene population link in risk management, research is required that includes at least one meaningful end point at each level of organization.

Cumulative energy demand has been used as a methodology to assess life cycle environmental impacts of commodity production since the early seventies, but has also been criticized because it focuses on energy only. During the past 30 years there has been much research into the development of more complex single-score life cycle impact assessment methodologies. However, a comprehensive analysis of potential similarities and differences between these methodologies and cumulative energy demand has not been carried out so far. Here we compare the cumulative energy demand of 498 commodities with the results of six frequently applied environmental life cycle impact assessment methodologies. Commodity groups included are metals, glass, paper and cardboard, organic and inorganic chemicals, agricultural products, construction materials, and plastics. We show that all impact assessment methods investigated often provide converging results, in spite of the different philosophies behind these methodologies. Fossil energy use is identified by all methodologies as the most important driver of environmental burden of the majority of the commodities included,with the main exception of agricultural products. We conclude that a wide range of life cycle environmental assessment methodologies point into the same environmental direction for the production of many commodities.

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.

The predictive power of bioaccumulation models may be limited when they do not accountfor strong sorption of organic contaminants to carbonaceous materials (CM) such as black carbon, and when they do not include metabolic transformation. We tested a food web accumulation model, including sorption to CM, on data from a model ecosystem experiment with historically contaminated sediment. In combination with measured CM contents of the sediment, the model gave good fits for the biota that are known not to metabolize PAHs (macrophytes, periphyton, floating algal biomass). The same model was applied to invertebrates and fish but now with optimization of their metabolic transformation rates (k(m)). For fish, these rates correlated empirically with log K(OW): Log k(m) = -0.8 log K(OW) + 4.5 (r2 adj = 0.73). For invertebrates, log k(m) did not correlate with logK(OW). Sensitivity analysis revealed that the model output is highly sensitive to sediment CM content and sorption parameters, moderately sensitive to metabolic transformation rates, and slightly sensitive to lipid fraction of the organism and diet-related parameters. It is concluded that CM-inclusive models yield a better assessment of accumulation than models without sorption to CM. Furthermore, inclusion of CM in a model enables metabolic transformation rates to be calculated from the remaining overestimation in the model results when compared to measured data.

Model estimations of bioaccumulation of polycyclic aromatic hydrocarbons (PAHs) have been higher than field or laboratory data. This has been explained by strong sorption to black carbon (BC). In this paper, eight previously published bioaccumulation datasets were reinterpreted in terms of additional BC sorption. Biota--Solids Accumulation Factors (BSAFs) of PAHs typically decreased by 1-2 orders of magnitude and were better in line with field data in marine, fresh water, and terrestrial ecosystems. Probabilistic BC-inclusive modeling showed that if BC content is not accurately known, uncertainty in BSAFs is 2-3 orders of magnitude (90 percentile confidence interval) due to uncertainty in the BC sorption term. When BC contents are measured, the deviation between model estimations and field measurements reduces to about a factor of 3. This implies that including routine measurements of BC contents is crucial in improving risk estimations of PAHs.

The appropriateness of the fossil Cumulative Energy Demand (CED) as an indicator for the environmental performance of products and processes is explored with a regression analysis between the environmental life-cycle impacts and fossil CEDs of 1218 products, divided into the product categories "energy production", "material production", "transport", and "waste treatment". Our results show that, for all product groups but waste treatment, the fossil CED correlates well with most impact categories, such as global warming, resource depletion, acidification, eutrophication, tropospheric ozone formation, ozone depletion, and human toxicity (explained variance between 46% and 100%). We conclude that the use of fossil fuels is an important driver of several environmental impacts and thereby indicative for many environmental problems. It maytherefore serve as a screening indicatorfor environmental performance. However, the usefulness of fossil CED as a stand-alone indicator for environmental impact is limited by the large uncertainty in the product-specific fossil CED-based impact scores (larger than a factor of 10 for the majority of the impact categories; 95% confidence interval). A major reason for this high uncertainty is nonfossil energy related emissions and land use, such as landfill leachates, radionuclide emissions, and land use in agriculture and forestry.

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.

Standard toxicity tests are performed at one constant, optimal temperature (usually 20 degrees C), while in the field variable and suboptimal temperatures may occur. Lack of knowledge on the interactions between chemicals and temperature hampers the extrapolation of laboratory toxicity data to ecosystems. Therefore, the aim of this study was to analyze the effects of temperature on cadmium toxicity to the waterflea Daphnia magna and to address possible processes responsible for temperature-dependent toxicity. This was investigated by performing standard toxicity tests with D. magna under a wide temperature range. Thermal effects on accumulation kinetics were determined by estimating uptake and elimination rates from accumulation experiments. To study temperature dependency of the intrinsic sensitivity of the daphnids to cadmium, the DEBtox model was used to estimate internal threshold concentrations (ITCs) and killing rates from the toxicity and accumulation data. The results revealed that increasing temperature lowered the ITC and increased the killing rate and the uptake rate of the metal. Enhanced sensitivity of D. magna was shown to be the primary factor for temperature-dependent toxicity. Since temperature has such a major impact on toxicity, a temperature correction may be necessary when translating toxicity data from the laboratory to the field.