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Intro -- The Handbook of Environmental Chemistry Also Available Electronically -- Series Preface -- Preface -- Acknowledgements -- Contents -- List of Abbreviations -- Evolution and Future of Human Health and Environmental Risk Assessment -- 1 What Is Human Health and Environmental Risk Assessment? -- 2 First Steps in Developing Risk Assessment Schemes -- 3 Human Health and Environmental Risk Assessment in the European Union -- Box 1: The Precautionary Principle in International and EU Treaties -- 4 Current Practices in Risk Assessment -- 5 Future Priorities and Challenges -- 5.1 Managing Uncertainty Analysis in Risk Assessment -- 5.2 Probabilistic and Sensitivity Analysis -- 5.3 Integrated Risk Assessment -- References -- SWOT Analysis of the MERLIN-Expo Tool and Its Relevance in Legislative Frameworks -- 1 Introduction -- 2 Methodology -- 2.1 Assessment Criteria -- 2.2 Relevance Criteria Importance for Regulatory Frameworks -- 2.3 Exposure Models -- 2.3.1 CalTOX -- 2.3.2 ESCAPE -- 2.3.3 EUSES -- 2.3.4 GLOBOX -- 2.3.5 GREATER-ER -- 2.3.6 MACRO -- 2.3.7 MERLIN-Expo -- 2.3.8 MODULERS -- 2.3.9 PBPK -- 2.3.10 PEARL -- 2.3.11 STEPS 1-2 -- 2.3.12 TOXSWA -- 2.3.13 USEtox -- 3 Comparative Assessment -- 4 SWOT Analysis of the MERLIN-Expo Model -- 5 Conclusion -- References -- Standard Documentation of Exposure Models: MERLIN-Expo Case Study -- 1 Background -- 1.1 Introduction -- 1.2 The Challenge faced by MERLIN-Expo -- 1.3 Standardisation -- 2 Standard Documentation Framework -- 2.1 Exploratory Research -- 2.2 MERLIN-Expo Standard Documentation Framework -- 3 CEN Workshop -- 3.1 CEN Workshop ``MERLIN-Expo´´ -- 3.2 The CEN Workshop Agreement CWA 16938 -- References -- Modelling the Fate of Chemicals in Surface Waters -- 1 Introduction -- 2 Sorption/Desorption Between Water and Particles -- 2.1 Process Description.

This volume focuses on modelling the fate of chemicals in the environment and the human body to arrive at an integrated exposure assessment. It covers five broad topics, namely: future challenges in exposure assessment; the evolution of human health and environmental risk assessment; standard documentation for exposure models; modelling different environmental components (i.e. surface waters, atmosphere, soil, groundwater, plants, aquatic organisms and mammals); and the fate of contaminants in humans. This work draws on the authors' and editors' extensive experience and a range of different research activities, including case studies, that have led to the development of MERLIN-Expo, a standardised software package for simulating the fate of chemicals in the main environmental systems and in the human body in an integrated manner. It will be of considerable interest to researchers and students, risk managers, and policy- and decision-makers whose work involves environmental protection and human health

We report on model simulations performed using the newly developed exposure tool, MERLIN-Expo, in order to assess lead (Pb) exposure to pre-school children resulting from past emissions by non-ferrous smelters in Belgium (Northern Campine area). Exposure scenarios were constructed to estimate internal Pb exposure in children living in the vicinity of the former industrial sites as compared to children living in adjacent areas and a reference area. Model simulations at individual level are compared with biomonitoring data from a Belgian monitoring campaign (Flemish Government, 2008; Van Holderbeke et al., 2008) in order to verify the model performance of MERLIN-Expo when simulating complex scenarios that account for subject mobility, i.e., duration at the different considered locations (both indoors and outdoors) with varying exposure levels, and individual food consumption patterns. Adopting an assessment approach at individual level improves on more commonly performed generic exposure assessments at population level, by including intake of Pb from local and purchased food products, and taking into account the mobility of the participants, which results in a more comprehensive assessment of individual recent intake of lead. Also, the accuracy of the model predictions as compared to Pb biomonitoring data has been tested via different accuracy approaches and metrics. We calculated a Probability of detection (or true positive rate) of 0.93, reflecting that almost all blood levels above a chosen trigger value of 2.25 mg.L-1 are predicted as such by the model; a Bias of 1.87, i.e. reflecting a slight overestimation of the model, and F1 and F2 scores of 0.65 and 0.8, respectively, confirming that most of the measured positives are detected as such by the model (high F2 score) with a slight overestimation (lower F1 score). Although the model predictions for individual children slightly overpredict the biomonitoring data, they overlap with the prediction interval calculated by MERLIN-Expo based on population averages ...

We report on model simulations performed using the newly developed exposure tool, MERLIN-Expo, in order to assess lead (Pb) exposure to pre-school children resulting from past emissions by non-ferrous smelters in Belgium (Northern Campine area). Exposure scenarios were constructed to estimate internal Pb exposure in children living in the vicinity of the former industrial sites as compared to children living in adjacent areas and a reference area. Model simulations at individual level are compared with biomonitoring data from a Belgian monitoring campaign (Flemish Government, 2008; Van Holderbeke et al., 2008) in order to verify the model performance of MERLIN-Expo when simulating complex scenarios that account for subject mobility, i.e., duration at the different considered locations (both indoors and outdoors) with varying exposure levels, and individual food consumption patterns. Adopting an assessment approach at individual level improves on more commonly performed generic exposure assessments at population level, by including intake of Pb from local and purchased food products, and taking into account the mobility of the participants, which results in a more comprehensive assessment of individual recent intake of lead. Also, the accuracy of the model predictions as compared to Pb biomonitoring data has been tested via different accuracy approaches and metrics. We calculated a Probability of detection (or true positive rate) of 0.93, reflecting that almost all blood levels above a chosen trigger value of 2.25 mg.L-1 are predicted as such by the model; a Bias of 1.87, i.e. reflecting a slight overestimation of the model, and F1 and F2 scores of 0.65 and 0.8, respectively, confirming that most of the measured positives are detected as such by the model (high F2 score) with a slight overestimation (lower F1 score). Although the model predictions for individual children slightly overpredict the biomonitoring data, they overlap with the prediction interval calculated by MERLIN-Expo based on population averages (Fierens et al., 2016). Modelling exposure at individual level allows risk assessors to attribute the relative contribution of different exposure routes at various locations, reconstructing the exposure history for each individual in a complex site-specific exposure scenario. The slight overprediction of the actual observed Pb blood levels with a factor 2 is compatible with conservative decision-making.