Six interaction profiles for simple mixtures

The Agency for Toxic Substances and Disease Registry (ATSDR) has a program for chemical mixtures that encompasses research on chemical mixtures toxicity, health risk assessment, and development of innovative computational methods. ATSDR prepared a guidance document that instructs users on how to conduct health risk assessment on chemical mixtures (Guidance Manual for the Assessment of Joint Toxic Action of Chemical Mixtures). ATSDR also developed six interaction profiles for chemical mixtures. Two profiles were developed for persistent environmental chemicals that are often found in contaminated fish and also can be detected in human breast milk. The mixture included chlorinated dibenzo-p-dioxins, hexachlorobenzene, dichlorodiphenyl dichloroethane, methyl mercury, and polychlorinated biphenyls. Two profiles each were developed for mixtures of metals and mixtures of volatile organic chemicals (VOCs) that are frequently found at hazardous waste sites. The two metal profiles dealt with (a) lead, manganese, zinc, and copper; and (b) arsenic, cadmium, chromium, and lead; the two VOCs mixtures dealt with (a) 1,1,1-trichloroethane, 1,1-dichloroethane, trichloroethylene, and tetrachloroethylene; and (b) benzene, ethylbenzene, toluene, and xylenes (BTEX). Weight-of-evidence methodology was used to assess the joint toxic action for most of the mixtures. Physiologically based pharmacokinetic modeling was used for BTEX. In most cases, a target-organ toxicity dose modification of the hazard index approach is recommended for conducting exposure-based assessments of noncancer health hazards.     

Assessing single and joint effects of chemicals on the survival and reproduction of Folsomia candida (Collembola) in soil

Chemicals are often found in the environment as complex mixtures. There has been a large effort in the last decade to assess the combined effect of chemicals, using the conceptual models of Concentration Addition and Independent Action, but also including synergistic, antagonistic, dose-level and dose-ratio dependent deviations from these models. In the present study, single and mixture toxicity of atrazine, dimethoate, lindane, zinc and cadmium were studied in Folsomia candida, assessing survival and reproduction. Different response patterns were observed for the different endpoints and synergistic patterns were observed when pesticides were present. Compared with the previously tested Enchytraeus albidus and Porcellionides pruinosus, the mixture toxicity pattern for F. candida was species specific. The present study highlights the importance of studying toxicity of chemicals mixtures due to the observed potentiation of effects and confirms that for an adequate ecologically relevant risk assessment different organisms and endpoints should be included.     

化学物质对发光菌的联合毒性评价方法

毒性单位法(TU)的理论基础来源于剂量加和模型(DA),目前仅在二元联合毒性评价中广泛应用。为了确定TU模型适合评价的混合物类型,实验选取5种剂量效应曲线类型不同的物质,采用微板光度计测试了一元、二元混合物对发光菌青海弧菌-Q67(Vibrio-qinghaiensis sp.-Q67)的急性毒性。根据物质的剂量效应曲线形状将物质分为A、B、C 3类,利用毒性单位法(TU)和联合作用定义法分别对AA类、AB类、AC类、BC类混合物进行分析。结果表明,TU法仅适合于由剂量效应曲线接近直线的物质组成的混合物进行联合毒性的评价。以效应为基准、TU模型为框架建立了TU’模型,该模型可以满足对任何类型已知成分的混合物或者未知成分的实际水样之间的多元联合作用的评价。     

Joint action and lethal levels of toluene, ethylbenzene, and xylene on midge (Chironomus plumosus) larvae

Aquatic ecosystems are vulnerable to the exposure with petrochemicals such as toluene, ethylbenzene, and xylene (o-, m-, and p-xylene) (TEX) and their adverse effects. Considering the widespread use, occurrence, and high toxicity of TEX, the aim of this work was to investigate the differential toxicity of TEX against midge (Chironomus plumosus) larvae and reveal the joint action of binary and ternary mixtures of TEX using the predictive concentration addition model. More importantly, this research can afford the basic toxicity data and scientific reference for the establishment of water quality criteria or benchmark, water pollution control, and aquatic risk assessment. Single and joint toxic effects of TEX on C. plumosus larvae were investigated using a semi-static bioassay, and the type of joint effects of TEX was ascertained. In the single toxicant experiments, the toxicity of the three pollutants could be sequenced as ethylbenzene > xylene > toluene. Specifically, LC_50s of T, E, and X after a 48-h exposure were 64.9, 37.8, and 42.0 mg/L, respectively. In the binary mixture experiments, the interaction between toluene and ethylbenzene, ethylbenzene and xylene, and toluene and xylene was largely in conformity with partial additive or additive effect as determined by isobologram representation and toxic unit models. In the ternary mixture experiments, the interaction was basically dependent on the use of additive index and mixture toxicity index methods. However, the antagonistic and synergistic actions were not significant. Thus, the tertiary mixture interaction could be regarded as additive action. The concentration addition model could successfully predict the joint action of TEX mixtures on C. plumosus larvae. Particularly, the additive action of TEX on C. plumosus larvae can be further recommended to evaluate water quality criteria of TEX.     

Assessment of combined antiandrogenic effects of binary parabens mixtures in a yeast-based reporter assay

To date, toxicological studies of endocrine disrupting chemicals (EDCs) have typically focused on single chemical exposures and associated effects. However, exposure to EDCs mixtures in the environment is common. Antiandrogens represent a group of EDCs, which draw increasing attention due to their resultant demasculinization and sexual disruption of aquatic organisms. Although there are a number of in vivo and in vitro studies investigating the combined effects of antiandrogen mixtures, these studies are mainly on selected model compounds such as flutamide, procymidone, and vinclozolin. The aim of the present study is to investigate the combined antiandrogenic effects of parabens, which are widely used antiandrogens in industrial and domestic commodities. A yeast-based human androgen receptor (hAR) assay (YAS) was applied to assess the antiandrogenic activities of n-propylparaben (nPrP), iso-propylparaben (iPrP), methylparaben (MeP), and 4-n-pentylphenol (PeP), as well as the binary mixtures of nPrP with each of the other three antiandrogens. All of the four compounds could exhibit antiandrogenic activity via the hAR. A linear interaction model was applied to quantitatively analyze the interaction between nPrP and each of the other three antiandrogens. The isoboles method was modified to show the variation of combined effects as the concentrations of mixed antiandrogens were changed. Graphs were constructed to show isoeffective curves of three binary mixtures based on the fitted linear interaction model and to evaluate the interaction of the mixed antiandrogens (synergism or antagonism). The combined effect of equimolar combinations of the three mixtures was also considered with the nonlinear isoboles method. The main effect parameters and interaction effect parameters in the linear interaction models of the three mixtures were different from zero. The results showed that any two antiandrogens in their binary mixtures tended to exert equal antiandrogenic activity in the linear concentration ranges. The antiandrogenicity of the binary mixture and the concentration of nPrP were fitted to a sigmoidal model if the concentrations of the other antiandrogens (iPrP, MeP, and PeP) in the mixture were lower than the AR saturation concentrations. Some concave isoboles above the additivity line appeared in all the three mixtures. There were some synergistic effects of the binary mixture of nPrP and MeP at low concentrations in the linear concentration ranges. Interesting, when the antiandrogens concentrations approached the saturation, the interaction between chemicals were antagonistic for all the three mixtures tested. When the toxicity of the three mixtures was assessed using nonlinear isoboles, only antagonism was observed for equimolar combinations of nPrP and iPrP as the concentrations were increased from the no-observed-effect-concentration (NOEC) to effective concentration of 80 %. In addition, the interactions were changed from synergistic to antagonistic as effective concentrations were increased in the equimolar combinations of nPrP and MeP, as well as nPrP and PeP. The combined effects of three binary antiandrogens mixtures in the linear ranges were successfully evaluated by curve fitting and isoboles. The combined effects of specific binary mixtures varied depending on the concentrations of the chemicals in the mixtures. At low concentrations in the linear concentration ranges, there was synergistic interaction existing in the binary mixture of nPrP and MeP. The interaction tended to be antagonistic as the antiandrogens approached saturation concentrations in mixtures of nPrP with each of the other three antiandrogens. The synergistic interaction was also found in the equimolar combinations of nPrP and MeP, as well as nPrP and PeP, at low concentrations with another method of nonlinear isoboles. The mixture activities of binary antiandrogens had a tendency towards antagonism at high concentrations and synergism at low concentrations.     

Degradation characteristics of toluene,benzene, ethylbenzene,and xylene by Stenotrophomonas maltophilia T3-c

Stenotrophomonas maltophilia T3-c, isolated from a biofilter for the removal of benzene, toluene, ethylbenzene, and xylene (BTEX), could grow in a mineral salt medium containing toluene, benzene, or ethylbenzene as the sole source of carbon. The effect of environmental factors such as initial toluene mass, medium pH, and temperature on the degradation rate of toluene was investigated. The cosubstrate interactions in the BTEX mixture by the isolate were also studied. Within the range of initial toluene mass (from 23 to 70 pmol), an increased substrate concentration increased the specific degradation of toluene by S. maltophilia T3-c. The toluene degradation activity of S. maltophilia T3-c could be maintained at a broad pH range from 5 to 8. The rates at 20 and 40 degrees C were 43 and 83%, respectively, of the rate at 30 degrees C. The specific degradation rates of toluene, benzene, and ethylbenzene by strain T3-c were 2.38, 4.25, and 2.06 micromol/g-DCW/hr. While xylene could not be utilized as a growth substrate by S. maltophilia T3-c, the presence of toluene resulted in the cometabolic degradation of xylene. The specific degradation rate of toluene was increased by the presence of benzene, ethylbenzene, or xylene in binary mixtures. The presence of toluene or xylene in binary mixtures with benzene increased the specific degradation rate of benzene. The presence of ethylbenzene in binary mixtures with benzene inhibited benzene degradation. The presence of more than three kinds of substrates inhibited the specific degradation rate of benzene. All BTEX mixtures, except tri-mixtures of benzene, ethylbenzene, and xylene or mixtures of all four substrates, had little effect on the degradation of ethylbenzene by S. maltophilia T3-c. The utilization preference of the substrates by S. maltophilia T3-c was as follows: ethylbenzene was degraded fastest, followed by toluene and benzene. However, the specific degradation rates of substrates, in order, were benzene, toluene, and ethylbenzene.     

Assessing joint toxicity of chemicals in Enchytraeus albidus (Enchytraeidae) and Porcellionides pruinosus (Isopoda) using avoidance behaviour as an endpoint

Contamination problems are often characterized by complex mixtures of chemicals. There are two conceptual models usually used to evaluate patterns of mixture toxicity: Concentration Addition (CA) and Independent Action (IA). Deviations from these models as synergism, antagonism and dose dependency also occur. In the present study, single and mixture toxicity of atrazine, dimethoate, lindane, zinc and cadmium were tested in Porcellionides pruinosus and Enchytraeus albidus, using avoidance as test parameter. For both species patterns of antagonism were found when exposed to dimethoate and atrazine, synergism for lindane and dimethoate exposures (with the exception of lower doses in the isopod case study) and concentration addition for cadmium and zinc occurred, while the exposure to cadmium and dimethoate showed dissimilar patterns.This study highlights the importance of dose dependencies when testing chemical mixtures and that avoidance tests can also be used to asses the effects of mixture toxicity.     

Hydrophobicity of complex organic mixtures

Hydrophobicity is an important property in risk assessment of chemicals. A group parameter that reflects the hydrophobicity of technical mixtures is not yet available. However, many substances are complex organic mixtures, for which it is practically impossible to determine each component separately. An experimental procedure to measure the hydrophobicity of organic mixtures without knowledge of the individual components was developed and tested for a mixture of benzene and twelve chlorobenzenes. This procedure is based on separation of the mixture into fractions of increasing hydrophobicity by reversed-phase HPLC, after which the total molar concentration in each fraction is determined by vapour pressure osmometry. The obtained information on hydrophobicity can be used for assessing bioaccumulation and sediment sorption after emission of the mixture to water has occurred.     

Novel approach to predicting hormetic effects of antibiotic mixtures on Vibrio fischeri

The determination of the hormetic effects of a mixture is quite difficult because of the moderate simulation and the complexity of measurement in low doses. In the present study, two typical models for mixture toxicity prediction, concentration additive (CA) and independent action (IA), were used to predict the hormetic effects of mixtures. The predictive power of those models was validated by the hormetic effects (24-h exposure) of antibiotic’s binary mixtures to Vibrio fischeri. The results showed that CA and IA were unable to predict the hormetic dose-response of mixture, especially those of the interactive mixtures. As an alternative, a novel model, which was named as “six-point” and developed based on the quantitative features in the determined dose-response curve and on the Quantitative Structure Activity Relationships (QSARs) approach, was proposed for predicting the hormetic effects of mixtures in low dose. The results indicated that the “six-point” model can accurately predict the mixture hormetic effects in low dose, not only for non-interactive mixtures but also for interactive mixtures. Therefore, the “six-point” model is a powerful tool to predict the mixture hormetic effects at low dose, and may offer an important approach in the environment risk assessment of mixtures.     

Effects of Air-Fuel Ratio on Composition of Hydrocarbon Exhaust from Toluene,Toluene-n Heptane Mixture and Isooctane

This study describes the variations in the chemical composition of the exhaust at various air-fuel ratios when toluene, toluene-n-heptane mixture, and isooctane are used as fuels in a Labeco single cylinder engine. The exhaust products from toluene are divided into three groups: those which decrease as the equivalence ratio is increased: toluene, benzene, methane, and dimethylacetylene; those which increase with increasing equivalence ratio: benzaldehyde, and products which exhibit a maximum at an equivalence ratio of 1, then decrease: acetylene, ethyl acetylene, ethyl benzene, and styrene. Combustion of the mixture of 25 volume percent n-heptane in toluene reveals interesting information, compared to emissions from pure toluene: concentrations of ethyl benzene, styrene, and dimethylacetylene surprisingly are increased by factors of 1.9, 1.9, and 2.1 respectively, probably because reactive radicals derived from heptane interact with toluene to form unsaturated molecules. Ethyl acetylene, benzene, and benzaldehyde remained unchanged but the fractional mole concentration of unreacted toluene decreased. These results show that fuels rich in aromatics may produce less unsaturates than when diluted with aliphatic fuels. For isooctane fuel, methane, and isooctane in the exhaust decrease as the equivalence ratio is increased, while isobutylene, propylene, ethylene, and propadiene concentrations exhibit maxima at an equivalence ratio of 1.     

A comparison of mixture toxicity assessment: examining the chronic toxicity of atrazine, permethrin and chlorothalonil in mixtures to Ceriodaphnia cf. dubia

Pesticides predominantly occur in aquatic ecosystems as mixtures of varying complexity, yet relatively few studies have examined the toxicity of pesticide mixtures. Atrazine, chlorothalonil and permethrin are widely used pesticides that have different modes of action. This study examined the chronic toxicities (7-d reproductive impairment) of these pesticides in binary and ternary mixtures to the freshwater cladoceran Ceriodaphnia cf. dubia. The toxicity of the mixtures was compared to that predicted by the independent action (IA) model for mixtures, as this is the most appropriate model for chemicals with different modes of action. Following this they were compared to the toxicity predicted by the concentration addition (CA) model for mixtures. According to the IA model, the toxicity of the chlorothalonil plus atrazine mixture conformed to antagonism, while that of chlorothalonil and permethrin conformed to synergism. The toxicity of the atrazine and permethrin mixture as well as the ternary mixture conformed to IA implying there was either no interaction between the components of these mixtures and/or in the case of the ternary mixture the interactions cancelled each other out to result in IA. The synergistic and antagonistic mixtures deviated from IA by factors greater than 3 and less than 2.5, respectively. When the toxicity of the mixtures was compared to the predictions of the CA model, the binary mixture of chlorothalonil plus atrazine, permethrin plus atrazine and the ternary mixture all conformed to antagonism, while the binary mixture of chlorothalonil plus permethrin conformed to CA. Using the CA model provided estimates of mixture toxicity that did not markedly underestimate the measured toxicity, unlike the IA model, and therefore the CA model is the most suitable to use in ecological risk assessments of these pesticides.     

The joint effects of sulfonamides and their potentiator on Photobacterium phosphoreum: differences between the acute and chronic mixture toxicity mechanisms

Organisms are typically exposed to mixtures of chemicals over long periods of time; thus, chronic mixture toxicity analysis is the best way to perform risk assessment in regards to organisms. However, most studies focus on the acute mixture toxicity. To investigate the difference between chronic mixture toxicity and acute mixture toxicity, Photobacterium phosphoreum were exposed to chronic (24 h exposure) and acute (15 min exposure) toxicity of single sulfonamide (SA) and their potentiator (trimethoprim, TMP), both individually and mixtures (SA with TMP). A comparison of chronic vs. acute mixture toxicity revealed the presence of an interesting phenomenon, that is, that the joint effects vary with the duration of exposure; the acute mixture toxicity was antagonistic, whereas the chronic mixture toxicity was synergistic. Based on the approach of Quantitative Structure Activity Relationships (QSARs) and molecular docking, this phenomenon was proved to be caused by the presence of two points of dissimilarity between the acute and chronic mixture toxicity mechanism: (1) the receptor protein of SAs in acute toxicity was Luc, while in chronic toxicity it was Dhps, and (2) there is a difference between actual concentration of binding-Luc in acute toxicity and individual binding-Dhps in chronic toxicity. This deep insight into the difference between chronic and acute mixture toxicity will benefit environmental science, medical science, and other disciplines. The existence of these differences poses a challenge for the assessment of routine combinations in medicine, risk assessment, and mixture pollutant control, in which, previously, only a synergistic effect has been observed between SA and their potentiator.     

Individual and mixture toxicity of three pesticides; atrazine,chlorpyrifos, and chlorothalonil to the marine phytoplankton species Dunaliella tertiolecta

This study analyzed the toxicity of three pesticides (the herbicide atrazine, the insecticide chlorpyrifos and the fungicide chlorothalonil) individually, and in two mixtures (atrazine and chlorpyrifos; atrazine and chlorothalonil) to the marine phytoplankton species Dunaliella tertiolecta (Chlorophyta). A standard 96 h static algal bioassay was used to determine pesticide effects on the population growth rate of D. tertiolecta. Mixture toxicity was assessed using the additive index approach. Atrazine and chlorothalonil concentrations > or = 25 microg/L and 33.3 microg/L, respectively, caused significant decreases in D. tertiolecta population growth rate. At much higher concentrations (> or = 400 microg/L) chlorpyrifos also elicited a significant effect on D. tertiolecta population growth rate, but toxicity would not be expected at typical environmental concentrations. The population growth rate EC50 values determined for D. tertiolecta were 64 microg/L for chlorothalonil, 69 microg/L for atrazine, and 769 microg/L for chlorpyrifos. Atrazine and chlorpyrifos in mixture displayed additive toxicity, whereas atrazine and chlorothalonil in mixture had a synergistic effect. The toxicity of atrazine and chlorothalonil combined was approximately 2 times greater than that of the individual chemicals. Therefore, decreases in phytoplankton populations resulting from pesticide exposure could occur at lower than expected concentrations in aquatic systems where atrazine and chlorothalonil are present in mixture. Detrimental effects on phytoplankton population growth rate could impact nutrient cycling rates and food availability to higher trophic levels. Characterizing the toxicity of chemical mixtures likely to be encountered in the environment may benefit the pesticide registration and regulation process.     

A novel method dependent only on the mixture information (MIM) for evaluating the toxicity of mixture

Compound contamination and toxicity interaction necessitate the development of models that have an insight into the combined toxicity of chemicals. In this paper, a novel and simple model dependent only on the mixture information (MIM), was developed. Firstly, the concentration-response data of seven groups of binary and multi-component (pseudo-binary) mixtures with different mixture ratios to Vibrio qinghaiensis sp.-Q67 were determined using the microplate toxicity analysis. Then, a desirable non-linear function was selected to fit the data. It was found that there are good linear correlations between the location parameter (α) and mixture ratio (p) of a component and between the steepness (β) and p. Based on the correlations, a mixture toxicity model independent of pure component toxicity profiles was built. The model can be used to accurately estimate the toxicities of the seven groups of mixtures, which greatly simplified the predictive procedure of the combined toxicity.     

Influence factors of multicomponent mixtures containing reactive chemicals and their joint effects

Organic chemicals usually coexist as a mixture in the environment, and the mixture toxicity of organic chemicals has received increased attention. However, research regarding the joint effects of reactive chemicals is lacking. In this study, we examined two kinds of reactive chemicals, cyanogenic toxicants and aldehydes and determined their joint effects on Photobacterium phosphoreum. Three factors were found to influence the joint effects of multicomponent mixtures containing reactive chemicals, including the number of components, the dominating components and the toxic ratios. With an increased number of components, the synergistic or antagonistic effects (interactions) will weaken to the additive effects (non-interactions) if the added component cannot yield a much stronger joint effect with an existing component. Contrarily, the joint effect of the mixture may become stronger instead of weaker if the added components can yield a much stronger joint effect than the existing joint effect of the multicomponent mixture. The components that yield the strongest interactions in their binary mixture can be considered the dominating components. These components contribute more to the interactions of multicomponent mixtures than other components. Moreover, the toxic ratios also influence the joint effects of the mixtures. This study provides an insight into what are the main factors and how they influence the joint effects of multicomponent mixtures containing reactive chemicals, and thus, the findings are beneficial to the study of mixture toxicology.     

A new effect residual ratio (ERR) method for the validation of the concentration addition and independent action models

Background, aim, and scope  

Glutaraldehyde (GA) often acts as an effective sterilant, disinfectant, and preservative in chemical products. It was found that GA had clearly acute toxicity to aquatic organisms. Furthermore, GA in natural environment could not exist as single species but as complex mixtures. To explore the toxicity interaction between GA and the other environmental pollutant, it is necessary to determine the mixture toxicities of various binary mixtures including GA. Two reference models, concentration addition (CA) and independent action (IA), are often employed to evaluate the mixture toxicity, which can be finished by comparing the concentration–response curves (CRCs) predicted by the reference models with the experimental CRC of the mixture. However, the CRC-based method cannot effectively denote the degree of the deviations from the reference models, especially at very low effect levels. Though the model deviation ratio (MDR) can be used to quantitatively evaluate the deviation of a mixture at EC50 level from the reference model, it is difficult to evaluate the deviations at the lower effect levels. Therefore, the primary aim of this study was to develop a new effect residual ratio (ERR) method to validate the deviations from the reference models at various effect levels.     

等浓度配比法研究苯酚、硝基苯和问硝基苯胺对发光菌的联合毒性作用

分别测定了苯酚、硝基苯和间硝基苯胺对发光菌的单一毒性，以及等浓度配比和等毒性配比的二元及三元混合体系的联合毒性，采用相加指数法对其联合效应进行了评价。结果表明，等浓度比和等毒性比混合体系的联合作用结果一致：苯酚＋间硝基苯胺二元体系为协同作用，其他各体系为相加作用。为简化联合毒性实验方法，建议在研究相关系列化合物的联合毒性作用机制中，可采用等浓度配比方法。     

等浓度配比法研究苯酚、硝基苯和间硝基苯胺对发光菌的联合毒性作用

分别测定了苯酚、硝基苯和间硝基苯胺对发光菌的单一毒性,以及等浓度配比和等毒性配比的二元及三元混合体系的联合毒性,采用相加指数法对其联合效应进行了评价。结果表明,等浓度比和等毒性比混合体系的联合作用结果一致:苯酚+间硝基苯胺二元体系为协同作用,其他各体系为相加作用。为简化联合毒性实验方法,建议在研究相关系列化合物的联合毒性作用机制中,可采用等浓度配比方法。     

Evaluation on the toxicity of ionic liquid mixture with antagonism and synergism to Vibrio qinghaiensis sp.-Q67

Ionic liquids (ILs) are a fascinating group of new chemicals with the potential to replace the classical volatile organic solvents, stimulating many applications in chemical industry. In case ILs are released to the environment, possible combined toxicity should be taken into account and it is, however, often neglected up to now. In this paper, therefore, the concentration-response curves (CRCs) of four groups of IL mixtures with various mixture ratios to Vibrio qinghaiensis sp.-Q67 were determined using the microplate toxicity analysis and were compared to the CRCs predicted by an additive reference model, the concentration addition (CA) or independent action (IA), to identify the toxicity interaction. It is showed that most of the IL mixture rays displayed the classical addition while the remaining rays exhibited antagonism or synergism. Moreover, it is found that the pEC₅₀ values of the mixture rays exhibiting antagonism or synergism are well correlated with the mixture ratio of a certain IL therein.     

Environmental impact assessment (EIA): Equilibrium fugacity calculations and worst case approach

A mathematical model UNITRISK which can be used for screening purposes and risk ranking was set up to calculate relative risk values of single chemicals and mixtures of chemicals towards single or mixtures of organisms via contamination of air, water, soil and food dose. The concentration values are calculated by applying the fugacity concept or a dose must be defined. The dose-response is assumed to be linear versus concentration and degradative processes are not considered which is the worst case. The assumption that equilibria between the environmental phases exist is simplifying the model and is also representing the worst case. A mean risk factor is calculated which is 1 if the endpoint values (LC₅₀, LD₅₀, ADI, etc.) are exceeded for the investigated organisms and man.