Modeling the exposure of children and adults via diet to chemicals in the environment with crop-specific models

Exposure to chemicals via diet is a major uptake pathway for many compounds but is often estimated in a rather generic way. We use a new model framework (NMF) with crop-specific models to predict the dietary intake by 4-5-year-old children and 14-75-year-old women of three environmental compounds from their background concentrations in soil and air. Calculated daily intakes of benzo(a)pyrene and 2,3,7,8-TCDD are in good agreement with measured results from diet studies. The major source of both compounds in human diet is deposition from air. Inhalation of air and ingestion of soil play a minor role. Children take up more than twice the amount than adults per kg bodyweight, due to higher consumption per kg bodyweight. Contrary, the methods for indirect human exposure suggested in the Technical Guidance Document (TGD) for chemical risk assessment in the EU lead to overprediction, due to unrealistic consumption data and a false root model.     

Plant uptake and transport models for neutral and ionic chemicals

BACKGROUND: Models for predicting uptake and transport of chemicals in plants are applied in pesticide design, risk assessment, and environmental biotechnology. OBJECTIVE: This review considers the theoretical basics of the most popular models, and discusses what they have in common. The line is drawn between models for neutral compounds, and models for weak and strong electrolytes. MAIN FEATURES: Neutral Compounds. Neutral compounds undergo only very few processes inside plants (lipophilic interactions, metabolism), in contrast to weak electrolytes. The models developed for neutral compounds are widely applied in the risk assessment of environmental contaminants, but are not of much use for weak electrolytes, such as pesticides. Weak electrolytes. A very important process for weak electrolytes is the 'ion trap', which traps chemicals that dissociate inside plant cells. This is considered in the popular models of Kleier, Satchivi and Briggs. Other relevant processes for electrolytes are electrophilic interactions, speciation and complex formation. None of the currently used models considers these processes. CONCLUSIONS: The accuracy of models for neutral compounds is satisfactory, but the prediction of electrolyte behavior inside plants is still quite difficult due to gaps in knowledge.     

Coupled mother-child model for bioaccumulation of POPs in nursing infants

Bioaccumulation of persistent organic pollutants (POPs) leads to high levels in human milk and high doses of POPs for nursing infants. This is currently not considered in chemical risk assessment. A coupled model for bioaccumulation of organic chemicals in breast-feeding mother and nursing infant was developed and tested for a series of organic compounds. The bioaccumulation factors (BAFs) in mother, breast milk and child were predicted to vary with log K_OW and, for volatile compounds, with K_AW and concentration in air. The concentrations of POPs in the infant body increase the first half year to about factor 3 above mother and decline thereafter to lower levels. The predicted results are close to empirical data and to an empirical regression. The new mother–child model is compact due to its easy structure and the analytical matrix solution. It could be added to existing exposure and risk assessment systems, such as EUSES.     

A review of models for estimating terrestrial ecological receptor exposure to chemical contaminants

In instances where empirical measurements are not practicable, ecological risk assessments may rely on site-specific exposure models for estimating uptake of chemical contaminants. This paper presents, based on a review of the literature, a compilation of relatively simple quantitative models that can be combined to produce site- and species-specific first-order estimates of uptake of chemicals from abiotic media. These models have proved useful in providing order-of-magnitude estimates for screening and sample program design purposes. This paper intended as both a practical guide for choosing models to estimate terrestrial wildlife exposures and as a step toward development of a more comprehensive and standard approach to exposure assessment in terrestrial ecological receptors.     

Quantifying the sorption of organic chemicals on sediments

The use of a reference compound to quantify the sorption of nonpolar organic chemicals is proposed. This is because organic carbon normalized sorption coefficients (K_OC) do appear to be dependent on the type of sediment, and are thus not generally applicable to characterize the sorption properties of chemicals. Therefore, in this paper the hypothesis that nonpolar chemicals sorb in a constant ratio, independent of the sediment, has been investigated. Evidence for this hypothesis is shown with data from the literature. This enables one to compare sorption properties of nonpolar compounds on different sediments, if the differences between the sediments are normalized with a reference chemical rather than with the organic carbon content. Sediments with an organic carbon content of less than 0.1% seem to be unsuitable, because the compounds do not sorb mainly on the organic carbon, but also on other parts of the sediment. Sorption coefficients of compounds with aqueous solubilities in the μg per liter range or octan-1-ol water partition coefficients of more than 10⁵ are strongly influenced by the experimental techniques used. For these compounds the sorption coefficients measured by different techniques are less comparable. To enable comparison of sorption coefficients of hydrophobic chemicals, the use of a chlorobenzene as a reference compound in sorption experiments is suggested.     

European union system for the evaluation of substances: the second version

This publication presents major changes in the assessment of the risks of chemicals to human health and the environment as implemented in the second version of the European Union System for the Evaluation of Substances, EUSES 2.0. EUSES is a harmonised quantitative risk assessment tool for chemicals. It is the PC-implementation of the technical guidelines developed within the framework of EU chemical legislation for industrial chemicals and biocides. As such, it is designed to support decision making by risk managers in government and industry and to assist scientific institutions in the risk assessment for these substances. The development of EUSES 2.0 is a co-ordinated project of the European Chemicals Bureau, EU Member States and the European chemical industry. Several model concepts, the technical background and the user interface of EUSES have been improved considerably. Major changes in the environmental assessment such as the implementation of emission scenario documents for industrial chemicals and biocides, the addition of the marine risk assessment, the enhancement of the regional model to include global scales, and improvements in the secondary poisoning and environmental effects modelling will be discussed. The update of the human risk assessment module in EUSES focuses on the risk characterisation for both threshold and non-threshold substances with, among others, the introduction of assessment factors. The performance of EUSES is illustrated in an example showing the human and environmental risk assessment of a sanitation disinfectant for private use.     

Potential Impact on Standards for Toxic Air Contaminants

Since the Bhopal incident, the public has placed pressure on regulatory agencies to set community exposure limits for the dozens of chemicals that may be released by manufacturing facilities. More or less objective limits can be established for the vast majority of these chemicals through the use of risk assessment. However, each step of the risk assessment process (i.e., hazard identification, dose-response assessment, exposure assessment, and risk characterization) contains a number of pitfalls that scientists need to avoid to ensure that valid limits are established. For example, in the hazard identification step there has been little discrimination among animal carcinogens with respect to mechanism of action or the epidemiology experience. In the dose-response portion, rarely is the range of “plausible” estimated risks presented. Physiologically based pharmacokinetic (PB-PK) models should be used to understand the difference between the tissue doses and the administered dose, as well as the difference in target tissue concentrations of the toxicant between rodents and humans. Biologically-based models like the Moolgavkar-Knudson-Venzon (MKV) should be developed and used, when appropriate. The exposure assessment step can be significantly improved by using more sensitive and specific sampling and analytical methods, more accurate exposure parameters, and computer models that can account for complex environmental factors. Whenever possible, model predictions of exposure and uptake should be validated by biological monitoring of exposed persons (urine, blood, adipose) or by field measurements of plants, soil, fish, air, or water. In each portion of an assessment, the weight of evidence approach should be used to identify the most defensible value. In the risk characterization, the best estimate of the potential risk as well as the highest plausible risk should be presented. Future assessments would be much improved if quantitative uncertainty analyses were conducted. Procedures are currently available for making future assessments. By correcting some of these shortcomings in how health risk assessments have been conducted, scientists and risk managers should be better able to identify scientifically appropriate ambient air standards and emission limits.     

The current practice of health risk assessment: potential impact on standards for toxic air contaminants

Since the Bhopal incident, the public has placed pressure on regulatory agencies to set community exposure limits for the dozens of chemicals that may be released by manufacturing facilities. More or less objective limits can be established for the vast majority of these chemicals through the use of risk assessment. However, each step of the risk assessment process (i.e., hazard identification, dose-response assessment, exposure assessment, and risk characterization) contains a number of pitfalls that scientists need to avoid to ensure that valid limits are established. For example, in the hazard identification step there has been little discrimination among animal carcinogens with respect to mechanism of action or the epidemiology experience. In the dose-response portion, rarely is the range of "plausible" estimated risks presented. Physiologically based pharmacokinetic (PB-PK) models should be used to understand the difference between the tissue doses and the administered dose, as well as the difference in target tissue concentrations of the toxicant between rodents and humans. Biologically-based models like the Moolgavkar-Knudson-Venzon (MKV) should be developed and used, when appropriate. The exposure assessment step can be significantly improved by using more sensitive and specific sampling and analytical methods, more accurate exposure parameters, and computer models that can account for complex environmental factors. Whenever possible, model predictions of exposure and uptake should be validated by biological monitoring of exposed persons (urine, blood, adipose) or by field measurements of plants, soil, fish, air, or water. In each portion of an assessment, the weight of evidence approach should be used to identify the most defensible value. In the risk characterization, the best estimate of the potential risk as well as the highest plausible risk should be presented. Future assessments would be much improved if quantitative uncertainty analyses were conducted. Procedures are currently available for making future assessments. By correcting some of these shortcomings in how health risk assessments have been conducted, scientists and risk managers should be better able to identify scientifically appropriate ambient air standards and emission limits.     

Setting the most robust effluent level under severe uncertainty: Application of information-gap decision theory to chemical management

Decisions in ecological risk management for chemical substances must be made based on incomplete information due to uncertainties. To protect the ecosystems from the adverse effect of chemicals, a precautionary approach is often taken. The precautionary approach, which is based on conservative assumptions about the risks of chemical substances, can be applied selecting management models and data. This approach can lead to an adequate margin of safety for ecosystems by reducing exposure to harmful substances, either by reducing the use of target chemicals or putting in place strict water quality criteria. However, the reduction of chemical use or effluent concentrations typically entails a financial burden. The cost effectiveness of the precautionary approach may be small. Hence, we need to develop a formulaic methodology in chemical risk management that can sufficiently protect ecosystems in a cost-effective way, even when we do not have sufficient information for chemical management. Information-gap decision theory can provide the formulaic methodology. Information-gap decision theory determines which action is the most robust to uncertainty by guaranteeing an acceptable outcome under the largest degree of uncertainty without requiring information about the extent of parameter uncertainty at the outset. In this paper, we illustrate the application of information-gap decision theory to derive a framework for setting effluent limits of pollutants for point sources under uncertainty. Our application incorporates a cost for reduction in pollutant emission and a cost to wildlife species affected by the pollutant. Our framework enables us to settle upon actions to deal with severe uncertainty in ecological risk management of chemicals.     

Comparison of RBCA and CalTOX for setting risk-based cleanup levels based on inhalation exposure

Risk-based corrective action (RBCA) and CalTOX (California EPA) are often used to develop risk-based soil cleanup levels. The determination of the entry parameters, including slope factors, degradation assumption, methodologies, and dispersion models for these two approaches greatly affect the onsite/offsite cleanup levels, risk distribution, and ranking of the influential factors. The subsurface soil-to-ambient air was considered as the only significant exposure pathway in this study. RBCA and CalTOX apply analytical equations and multimedia fugacity model, respectively, to simulate the transport of contaminants from subsurface soil to ambient air. Nine carcinogenic organic contaminants were selected as the target compounds. Environmental monitoring data collected from a contaminated site in southern Taiwan was used as model inputs. In this study, degradation assumption had greater influence on CalTOX evaluation than slope factors. The cleanup soil levels of all target chemicals developed by both models were close under the same slope factors and degradation assumptions, except for vinyl chloride and hexachlorobenzene. Furthermore, RBCA generally had larger offsite dispersion ratios than CalTOX, especially for long distances. The risk distribution obtained by RBCA was much board than by CalTOX. When 95th percentile was considered as the starting point, the SSTLs derived by RBCA were much stricter than by CalTOX. The ranking of influential factors in the onsite risk assessment for these two models were completely different because of their distinct model methodologies.     

Evaluation and comparison of multimedia mass balance models of chemical fate: application of EUSES and ChemCAN to 68 chemicals in Japan

The European Union System for Evaluation of Substances (EUSES) and the ChemCAN chemical fate model are applied to describe the fate of 68 chemicals on two spatial scales in Japan. Emission information on the chemicals has been obtained from Japan's Pollutant Release and Transfer Registry and available monitoring data gathered from government reports. Environmental concentrations calculated by the two models for the four primary environmental media of air, water, soil and sediment agree within a factor of 3 for over 70% of the data, and within a factor of 10 for over 87% of the data. Reasons for certain large discrepancies are discussed. Concentrations calculated by the models are generally consistent with the lower range of concentrations that are observed in the environment. Agreement between modeled and observed concentrations is considerably improved by including an estimate of the advective input of chemicals in air from outside Japan. The agreement between the EUSES and ChemCAN models suggests that results of individual chemical assessments are not likely to be significantly affected by the choice of chemical fate model. Primary sources of discrepancy between modeled and observed concentrations are believed to be uncertainties in emission rates, degradation half-lives, and the lack of data on advective inflow of contaminants in air.     

Modeling Short Range Air Dispersion from Area Sources of Non-buoyant Toxics

A model based on K-theory has been developed for describing the short range air dispersion from area sources of non-buoyant toxics. Model parameter estimation is via boundary layer theory. Lateral dispersion by plume meander is considered but ail other sources of horizontal dispersion are neglected. The model can be applied on and near area sources and it can be adapted for predictions of downwind concentrations with a wide variety of meteorological Inputs.

The model has been evaluated by simulating the data obtained during atmospheric tracer studies and by comparison to vinyl chloride concentrations near the BKK landfill in southern California. The model appears to represent a useful and accurate tool for regulatory planning and risk assessment close to area sources of toxics.     

QSAR modeling for predicting mutagenic toxicity of diverse chemicals for regulatory purposes

The safety assessment process of chemicals requires information on their mutagenic potential. The experimental determination of mutagenicity of a large number of chemicals is tedious and time and cost intensive, thus compelling for alternative methods. We have established local and global QSAR models for discriminating low and high mutagenic compounds and predicting their mutagenic activity in a quantitative manner in Salmonella typhimurium (TA) bacterial strains (TA98 and TA100). The decision treeboost (DTB)-based classification QSAR models discriminated among two categories with accuracies of >96% and the regression QSAR models precisely predicted the mutagenic activity of diverse chemicals yielding high correlations (R ²) between the experimental and model-predicted values in the respective training (>0.96) and test (>0.94) sets. The test set root mean squared error (RMSE) and mean absolute error (MAE) values emphasized the usefulness of the developed models for predicting new compounds. Relevant structural features of diverse chemicals that were responsible and influence the mutagenic activity were identified. The applicability domains of the developed models were defined. The developed models can be used as tools for screening new chemicals for their mutagenicity assessment for regulatory purpose.

     

Evaluation of the STP model: comparison of modelled and experimental results for ten polycyclic aromatic hydrocarbons (PAHs)

Screening level risk assessment models are used by many countries to assess the treatability of organic chemicals during the sewage treatment process, especially those that are new to commerce. The performance of one such model, the sewage treatment plant model, is evaluated in the current study by comparing model predictions with actual measurement data collected at various stages of a typical full-scale activated sludge type sewage treatment plant. A suite of ten polycyclic aromatic hydrocarbons (PAHs) with widely varying physico–chemical properties were monitored for the comparison. Model predicted removal efficiencies were in very good agreement with those measured for all ten PAHs. Observed chemical concentrations and their trends at various stages of the sewage treatment process were also well simulated by the model. Results also suggest that a reasonable first approximation estimate of a range for the biodegradation half-life needed for the model may be obtained by dividing reported aqueous biodegradation half-life by scaling factors of 50 and 150.     

Evaluation of the STP model: Comparison of modelled and experimental results for ten polycyclic aromatic hydrocarbons (PAHs)

Screening level risk assessment models are used by many countries to assess the treatability of organic chemicals during the sewage treatment process, especially those that are new to commerce. The performance of one such model, the sewage treatment plant model, is evaluated in the current study by comparing model predictions with actual measurement data collected at various stages of a typical full-scale activated sludge type sewage treatment plant. A suite of ten polycyclic aromatic hydrocarbons (PAHs) with widely varying physico–chemical properties were monitored for the comparison. Model predicted removal efficiencies were in very good agreement with those measured for all ten PAHs. Observed chemical concentrations and their trends at various stages of the sewage treatment process were also well simulated by the model. Results also suggest that a reasonable first approximation estimate of a range for the biodegradation half-life needed for the model may be obtained by dividing reported aqueous biodegradation half-life by scaling factors of 50 and 150.     

Spray irrigation of landfill leachate: estimating potential exposures to workers and bystanders using a modified air box model and generalised source term

Generalised source term data from UK leachates and a probabilistic exposure model (BPRISC(4)) were used to evaluate key routes of exposure from chemicals of concern during the spraying irrigation of landfill leachate. Risk estimates secured using a modified air box model are reported for a hypothetical worker exposed to selected chemicals within a generalised conceptual exposure model of spray irrigation. Consistent with pesticide spray exposure studies, the key risk driver is dermal exposure to the more toxic components of leachate. Changes in spray droplet diameter (0.02-0.2 cm) and in spray flow rate (50-1000 l/min) have little influence on dermal exposure, although the lesser routes of aerosol ingestion and inhalation are markedly affected. The risk estimates modelled using this conservative worst case exposure scenario are not of sufficient magnitude to warrant major concerns about chemical risks to workers or bystanders from this practice in the general sense. However, the modelling made use of generic concentration data for only a limited number of potential landfill leachate contaminants, such that individual practices may require assessment on the basis of their own merits.     

Biodegradation of chemicals in a standardized test and in environmental conditions

The estimation of biodegradation rates is an important source of uncertainty in chemical risk assessment. The existing OECD tests for ready biodegradability have been developed to devise screening methods to determine whether a chemical is potentially easily biodegradable, rather than to predict the actual rate, of biodegradation in the environment. However, risk assessment needs degradation rates. In practice these rates are often estimated (default values) from ready biodegradability tests. These tests have many compromising arbitrary features compared to the situation in the real environment. One important difference is the concentration of the chemical. In wastewater treatment or in the environment many chemicals are present at ng l(-1) to microg l(-1) levels whereas in the tests the concentrations exceed 10-400 mg carbon per litre. These different concentrations of the chemical will lead to different growth kinetics and hence different biodegradation rates. At high concentrations the chemical, if it is degradable, can serve as a primary substrate and competent microorganisms will grow exponentially, resulting in a sigmoid biodegradation curve. At low environmental concentrations the chemical does not serve as a primary substrate, and therefore does not support significant growth of the degraders, and the substrate has a linear biodegradation rate. In this study the biodegradation rates of two reference chemicals, aniline and 4-chloroaniline, were compared in a standard method and in more realistic conditions at low concentrations, using 14C-labelled substances and different sources of inocula. Biomass evolution during the tests was monitored by adenosine triphosphate measurement and also on the basis of the residual 14C-activity in the particulate matter. The results partly support the thesis that low concentrations lead to different biodegradation kinetics compared to the concentrations used in the standard tests. Furthermore the biodegradation rates of the chemicals studied, particularly of 4-chloroaniline, in Finnish natural waters appeared to be lower than those reported in some other countries.     

A risk assessment tool for contaminated sites in low-permeability fractured media

A risk assessment tool for contaminated sites in low-permeability fractured media is developed, based on simple transient and steady-state analytical solutions. The discrete fracture (DF) tool, which explicitly accounts for the transport along fractures, covers different source geometries and history (including secondary sources) and can be applied to a wide range of compounds. The tool successfully simulates published data from short duration column and field experiments. The use for risk assessment is illustrated by three typical risk assessment case studies, involving pesticides, chlorinated solvents, benzene and MTBE. The model is compared with field data and with results from a simpler approach based on an Equivalent Porous Media (EPM). Risk assessment conclusions of the DF and EPM approaches are very different due to the early breakthrough, long term tailing, and lower attenuation due to degradation associated with fractured media. While the DF tool simulates the field data, it is difficult to conclude that the DF model is superior to an EPM model because of a lack of long term monitoring data. However, better agreement with existing field data by the DF model using observed physical fracture parameters favors the use of this model over the EPM model for risk assessments.