Assessing multimedia/multipathway exposures to inorganic arsenic at population and individual level using MERLIN-Expo

Modeling the migration of chemicals from food contact materials to food: The MERLIN-expo/VERMEER toolbox

Evaluating the migration of chemicals from food contact materials (FCM) into food is a key step in the safety assessment of such materials. In this paper, a simple mechanistic model describing the migration of chemicals from FCM to food was combined with quantitative property-property relationships (QPPRs) for the prediction of diffusion coefficients and FCM-Food partition coefficients. The aim of the present study was to evaluate the performance of these operational models in the prediction of a chemical's concentration in food in contact with a plastic monolayer FCM. A comparison to experimental migration values reported in literature was conducted. Deterministic simulations showed a good match between predicted and experimental values. The tested models can be used to provide insights in the amount and the type of toxicological data that are needed for the safety evaluation of the FCM substance. Uncertainty in QPPRs used for describing the processes of both diffusion in FCM and partition at the FCM-Food interface was included in the analysis. Combining uncertainty in QPPR predictions, it was shown that the third quartile (75th percentile) derived from probabilistic calculations can be used as a conservative value in the prediction of chemical concentration in food, with reasonable safety factors.

A probabilistic model for assessing uncertainty and sensitivity in the prediction of monochloramine loss in French river waters

Monochloramine (NH₂Cl) is increasingly used as alternative disinfectant to free chlorine in industrial plants. After use in cooling systems, the waters are released to the environment and residual NH₂Cl may be discharged into the receiving waters. As NH₂Cl is suspected to exhibit toxicity towards aquatic organisms, a proper risk assessment of its occurrence in environmental waters is needed to prevent adverse effects on wildlife. For this purpose, a comprehensive model simulating monochloramine loss in natural riverine waters was developed. This model incorporates the following processes: (i) autodecomposition; (ii) reaction with nitrite and bromide; (iii) oxidation with Dissolved Organic Carbon (DOC); (iv) oxidation with organic fraction of Suspended Particulate Matter (SPM); (v) reactions in bottom sediments and (vi) volatilization. The model was also designed to conduct uncertainty and sensitivity analysis. It was tested on several French rivers submitted to discharges of monochloraminated effluents and on several seasonal conditions. Uncertainty analysis allowed evaluation of confidence intervals related to NH₂Cl half-lives in natural waters. It was shown that simulation intervals are in good agreement with experimental data obtained on the same rivers. Sensitivity analysis using an EFAST variance decomposition approach allowed identification of the most influential parameters on half-life determination. It was shown that the kinetic rate describing rapid reaction of NH₂Cl with DOC is by far the most sensitive parameter, demonstrating the predominance of such reactions in the loss process. Variables or parameters involved in temperature dependence (temperature and activation energy) can also significantly influence model results. To a lesser extent, wind velocity is the most sensitive parameter explaining uncertainty in the prediction of volatilization, with a high level of interactions with other parameters, showing that loss through volatilization can be essential in some specific conditions only. This study then identified the most important research priorities for improving the prediction of NH₂Cl half-lives in natural rivers.

Arsenic toxicokinetic modeling and risk analysis: Progress, needs and applications

Arsenic (As) poses unique challenges in PBTK model development and risk analysis applications. Arsenic metabolism is complex, adequate information to attribute specific metabolites to particular adverse effects in humans is sparse, and measurement of relevant metabolites in biological media can be difficult. Multiple As PBTK models have been published and used or adapted for use in various exposure and risk analysis applications. These applications illustrate the broad utility of PBTK models for exposure and dose-response analysis, particularly for arsenic where multi-pathway, multi-route exposures and multiple toxic effects are of concern. Arsenic PBTK models have been used together with exposure reconstruction and dose-response functions to estimate risk of specific adverse health effects due to drinking water exposure and consumption of specific foodstuffs (e.g. rice, seafood), as well as to derive safe exposure levels and develop consumption advisories. Future refinements to arsenic PBTK models can enhance the confidence in such analyses. Improved estimates for methylation biotransformation parameters based on in vitro to in vivo extrapolation (IVIVE) methods and estimation of interindividual variability in key model parameters for specific toxicologically relevant metabolites are two important areas for consideration.

A comprehensive probabilistic approach for integrating and separating natural variability and parametric uncertainty in the prediction of distribution coefficient of radionuclides in rivers

A geochemical speciation model was developed to predict Distribution coefficients (K_ds) of radionuclides (RNs) in rivers. The model takes into account complexation of RNs with inorganic ligands, sorption of RNs with hydrous ferric oxides, complexation of RNs with dissolved and particulate organic carbon (DOC and POC) and sorption and/or co-precipitation of RNs to carbonates. A sorption model of Cs onto clay was also integrated. The tool is also designed to conduct uncertainty and sensitivity analysis. Sensitivity analysis follows a stepwise structured approach, starting from computationally 'inexpensive' Morris method to most costly variance-based EFAST method. A nested Monte Carlo approach was also implemented to separate natural variability and lack of knowledge in global uncertainty assessment. As case studies, K_d distributions were estimated for Co, Mn, Ag and Cs in seven French rivers. Uncertainty analysis allowed to quantify K_d ranges that can be expected when considering all the sensitive parameters together.

A comprehensive probabilistic approach for integrating natural variability and parametric uncertainty in the prediction of trace metals speciation in surface waters

The main objectives of this study were to evaluate global uncertainty in the prediction of Distribution coefficients (Kds) for several Trace Metals (TM) (Cd, Cu, Pb, Zn) through the probabilistic use of a geochemical speciation model, and to conduct sensitivity analysis in speciation modeling in order to identify the main sources of uncertainty in Kd prediction. As a case study, data from the Loire river (France) were considered. The geochemical speciation model takes into account complexation of TM with inorganic ligands, sorption of TM with hydrous ferric oxides, complexation of TM with dissolved and particulate organic matter (i.e. dissolved and particulate humic acids and fulvic acids) and sorption and/or co-precipitation of TM to carbonates. Probability Density Functions (PDFs) were derived for physico-chemical conditions of the Loire river from a comprehensive collection of monitoring data. PDFs for model parameters were derived from literature review. Once all the parameters were assigned PDFs that describe natural variability and/or knowledge uncertainty, a stepwise structured sensitivity analysis (SA) was performed, by starting from computationally 'inexpensive' Morris method to most costly variance-based EFAST method. The most sensitive parameters on Kd predictions were thus ranked and their contribution to Kd variance was quantified. Uncertainty analysis was finally performed, allowing quantifying Kd ranges that can be expected when considering all the sensitive parameters together.

Ecological and human exposure assessment to PBDEs in Adige River

The interest for environmental issues and the concern resulting from the potential exposure to contaminants were the starting point to develop methodologies in order to evaluate the consequences that those might have over both the environment and human health. Considering the feature of POPs, including PBDEs, such as bioaccumulation, biomagnification, long-range transport and adverse effects even long time after exposure, risk assessment of POPs requires specific approaches and tools. In this particular context, the MERLIN-Expo tool was used to assess the aquatic environmental exposure of Adige River to PBDEs and the accumulation of PBDEs in humans through the consumption of possible contaminated local aquatic food. The aquatic food web models provided as output of the deterministic simulation the time trend of concentrations for twenty years of BDE-47 and total PBDEs, expressed using the physico-chemical properties of BDE-47, in aquatic organisms of the food web of Adige River. For BDE-47, the highest accumulated concentrations were detected for two benthic species: Thymallus thymallus and Squalius cephalus whereas the lowest concentrations were obtained for the pelagic specie Salmo trutta marmoratus. The trend obtained for the total PBDEs, calculated using the physico-chemical properties of BDE-47, follows the one of BDE-47. For human exposure, different BDE-47 and total PBDEs concentration trends between children, adolescent, adults and elderly were observed, probably correlated with the human intake of fish products in the daily diet and the ability to metabolize these contaminants. In detail, for the adolescents, adults and elderly a continuous accumulation of the target contaminants during the simulation's years was observed, whereas for children a plateau at the end of the simulation period was perceived.

Multimedia & PBPK modelling with MERLIN-Expo versus biomonitoring for assessing Pb exposure of pre-school children in a residential setting

This paper reports on a case study - conducted within the European FP7 project "4FUN" - focusing on exposure of pre-school children to lead resulting from past emissions by non-ferrous smelters in Belgium (Northern Campine area). Exposure scenarios were constructed and simulated with the MERLIN-Expo tool to estimate external Pb exposure as well as the Pb body burden in children living in the vicinity of the former industrial sites as compared to children living in adjacent areas and a reference area. Simulations were run for several scenarios ranging from very simple to rather complex in order to study the effect of different simulation approaches (e.g., deterministic vs. probabilistic, individual vs. aggregated population exposure) and different exposure scenarios (e.g., with vs. without considering local food consumption or time activity patterns) on the model outcomes (predicted concentrations of Pb in environmental and human matrices). This paper discusses the two most complex scenarios, namely exposure at the aggregated population level and at the individual level for a random sub-sample of subjects, respectively. In the final and most realistic exposure scenario, simulating individual lead exposure, model predictions were shown to be higher than the biomonitoring data. Blood Pb levels in children, irrespective of the area they lived in, were overpredicted by MERLIN-Expo with a factor of about 2 on average. The model predictions for individual children overlap with the prediction interval calculated by MERLIN-Expo based on population averages, demonstrating the use of probabilistic approaches in risk assessment. While these results constitute a first verification of the model performance of MERLIN-Expo dealing with inorganic pollutants in a complex real-world exposure scenario and a demonstration of the robustness of the modelling tool, further validation and benchmarking efforts are required for a larger number of inorganic pollutants and different exposure settings.

Potential for MERLIN-Expo, an advanced tool for higher tier exposure assessment, within the EU chemical legislative frameworks

MERLIN-Expo merges and integrates advanced exposure assessment methodologies, allowing the building of complex scenarios involving several pollution sources and targets. The assessment of exposure and risks to human health from chemicals is of major concern for policy and ultimately benefits all citizens. The development and operational fusion of the advanced exposure assessment methodologies envisaged in the MERLIN-Expo tool will have a significant impact in the long term on several policies dealing with chemical safety management. There are more than 30 agencies in Europe related to exposure and risk evaluation of chemicals, which have an important role in implementing EU policies, having especially tasks of technical, scientific, operational and/or regulatory nature. The main purpose of the present paper is to introduce MERLIN-Expo and to highlight its potential for being effectively integrated within the group of tools available to assess the risk and exposure of chemicals for EU policy. The main results show that the tool is highly suitable for use in site-specific or local impact assessment, with minor modifications it can also be used for Plant Protection Products (PPPs), biocides and REACH, while major additions would be required for a comprehensive application in the field of consumer and worker exposure assessment.