Volker Berding

Probabilistic uncertainty analysis of the European Union System for the evaluation of substances multimedia regional distribution model

The European Union System for the Evaluation of Substances (EUSES) is a computerized model system to facilitate and harmonize health and environmental risk assessment of previously notified and new substances. For calculation of regional background exposure, a multimedia distribution model is used. In the present study, the uncertainty of this regional model is analyzed. Environmental parameters were collected for North Rhine Westphalia (Germany), which resembles the standard region of EUSES. Probability distribution functions of various types (uniform, triangular, normal, log normal) depending on data availability were derived for environmental input parameters, including geometric parameters. Generic log-normal distribution functions with fixed standard deviations were chosen for solubility in air, water, and n-octanol as well as for degradation half-lives. Monte Carlo simulations were carried out for 10 reference substances having different properties. Contribution of environmental parameter uncertainty to total output uncertainties is higher than that of substance parameters. Range of output uncertainty, defined as the ratio of the logarithms of the 90th and 10th percentiles of the cumulative probability distribution function, shows an increase from air and water to soil. The highest-occurring range is 1.4 orders of magnitude, which means that total uncertainty of the regional model is relatively low and, usually, is lower than the range of measured values. The median of output probability distributions lies above the point estimate. Influence of input parameters was estimated as their rank correlation coefficients to output uncertainty. Substance and environmental parameters contribute differently to output variance depending on individual substance properties and environmental compartment. Hence, the present study underlines the need to perform uncertainty analyses instead of either using a set of simple rules or just looking at certain parameters.

Aquatic fate assessment of the polycyclic musk fragrance HHCB: Scenario and variability analysis in accordance with the EU risk assessment guidelines

By means of the environmental fate and distribution models laid down in the Technical Guidance Documents (TGD) and implemented in the European Union System for the Evaluation of Substances (EUSES) environmental concentrations of the polycyclic musk fragrance HHCB (1,3,4,6,7,8-hexahydro-4,6,6,7,8,8-hexamethyl-cyclopenta-[g]-2- benzopyrane; trade name: e.g. Galaxolide) were calculated for the aquatic environment under consideration of various scenarios. The results were then compared to monitoring data from the region of North Rhine-Westphalia (River Ruhr). An uncertainty analysis was carried out to determine sensitive parameters, to integrate environmental variability and to confirm the models calculations. The standard scenario of EUSES overestimates the measured concentrations, which confirms the conservative nature of the calculations. The regional-specific scenarios lead to lower deviations from the measured values than the standard scenario. Deviations range from one to two orders of magnitude in the effluent of sewage treatment plants; they amount to one order of magnitude for surface water concentrations on a local scale and conform to monitoring data on a regional scale. The use of measured bioconcentration factors for fish instead of estimated ones reduces deviations remarkably. The investigation reveals that unrealistic worst-case calculations of HHCB can at best be ameliorated by the application of more realistic emission rates and measured bioconcentration factors. The use of regional-specific parameters also diminishes the deviations of the calculations from the measured concentrations.

European scenarios for EUSES regional distribution model

The regional multimedia distribution model incorporated into EUSES 1.0 is used for the estimation of regionally predicted environmental concentrations in different European scenarios: a scenario representing a typical region in the north of Europe (high fraction connected to sewer systems, lower environmental temperature, high fractions of surface water and natural soil and a low fraction for agricultural soil) and another scenario representing a typical region in the south of Europe (low fraction connected to sewer systems, higher environmental temperature, low fractions for surface water and natural soil, and a high fraction for agricultural soil). The two scenarios are based on average data of countries in Northern and Southern Europe, but are not realistic for any specific country located in these regions. Scenario calculations were carried out using these two scenarios in addition to the generic standard region, given in EUSES 1.0 as a default scenario, and the North-Rhine Westphalian region. The substance properties, including emissions, were left unchanged for all scenarios. For a number of substances, the calculated concentrations in both the North and the South of Europe turned out to be higher than those calculated with the standard generic scenario. Thus, the standard scenario cannot be considered as a ‘worst case’ scenario per se. Uncertainties due to the regional heterogeneity within Europe are high. It is recommended to use these two additional scenarios for an improved estimation of possible concentration ranges in Europe.

Series: EU Risk Assessment Guidelines

An evaluation of the software quality of EUSES 1.00 (European Union System for the Evaluation of Substances) was carried out. Quality criteria for software products for the risk assessment of chemicals were developed. They were derived from common standards (described in ISO/IEC 12119), publications, and newly established requirements. Thus, a compilation of quality criteria emerged which can serve as a basis for the development of further similar programmes. After testing the software and reviewing the documentation, EUSES presents itself as a modern product which basically fulfils the postulated quality criteria.Particularly with regard to correctness and stability, no errors were found. EUSES contains some innovative features. However,numerous alterations are necessary. High complexity, low modularity, and incomplete documentation result in a lack of transparency and are emphasised as major points of criticism.

Visualisation of the complexity of EUSES.

The interdependencies of parameters applied in the models of EUSES are visualised in a directed connectivity graph. The parameters (inputs, defaults, state variables, outputs) are represented by boxes (nodes) and their relations by lines (edges). The visualisation, on the one hand, clarifies the complexity of the models in EUSES and, on the other hand, creates an overview and transparency. The parameters’ relations to each other can be recognised faster, and the models can be better understood. The complexity was quantified by the number (variety), kind (substance parameter, physico-chemical parameter, concentration, other parameters), and depth (dimension) of the parameter and the number of relations (connectivity). The variety of EUSES (without the modelsSimple Treat andSimple Box whose interior structure is not documented and without the effect and risk characterisation) amounts to 466, the connectivity to 961, and the maximal dimension is 21.

EU risk assessment guidelines, Part III. Scenario analysis of a Level III multimedia model using generic and regional data.

Regional PECs (Potential Environmental Concentrations) calculated with the software EUSES were compared with measured values using different emission and environmental distribution scenarios. The environmental data set recommended in EUSES (default data set) represents a generic standard region. In different scenarios the parameters of the generic region are replaced by concrete values, and estimated parameters (emissions, degradation rates and partition coefficients) are substituted by measured or investigated values. Deviations with regard to the measured values can be up to three orders of magnitude. Despite the basically conservative approximations, underestimations can occur. However, these are usually due to poor monitoring data or inappropriate input values. The use of regional data instead of default parameters only slightly ameliorates the results. The use of real emission and degradation rates alone can improve the results significantly.

Spatial Refinement of Regional Exposure Assessment

Using the European Union System for the Evaluation of Substances (EUSES) and the Geography-referenced Regional Exposure Assessment Tool for European Rivers (GREAT-ER) regional exposure assessments were performed for the polycyclic musk fragrance HHCB (1,3,4,6,7,8-hexahydro-4,6,6,7,8,8-hexamethyl-cyclopenta-[g]-2-benzopyrane; trade name: e.g. Galaxolide®), Starting with a generic standard region a spatial refinement was carried out for the German River Ruhr region. The refinement was realised in different scenarios by successively replacing EUSES default parameters with realistic regional values and then applying the selected region to GREAT-ER. The results were compared to monitoring data from the region of North Rhine-Westphalia (River Ruhr). It was shown that EUSES estimates the median of the measured values very well in every scenario. Spatial refinement leads to lower concentrations. Even underestimations are possible if realistic regional parameters are inserted and a ready biodegradability is assumed. The lowest deviations to measured values are the average concentrations calculated by GREAT-ER, however, much more data are needed to perform a reasonable regional assessment. Furthermore, assuming the same region, the predicted concentrations of EUSES and GREAT-ER do not differ by more than a factor of 5. In addition, GREAT-ER delivers realistic regional information with visualised concentration profiles and maps.

Evaluation Methodology for Fate and Exposure Models

The principles of model evaluation in terms of quality assurance, model validation, and software evaluation were elaborated and discussed with the intention to develop a suitable evaluation protocol for chemical risk assessment models. Since scientific theories and the mathematical models embedded therein cannot be proved as true, a pragmatic meaning of validation is required, of which the primary purpose is to increase the level of confidence that is placed in the model. The accuracy of the model outcome is a necessary, but insufficient criterion for the quality assurance of models. A wider approach is required which examines the scientific inference that can be made about models relative to their intended purpose. By reviewing the literature on the validation problem, it was found that all the facets of validation can be assigned to generic (internal) and task-specific (external) properties of a model. Appropriate and detailed quality criteria for fate and exposure assessment software have been recently developed. They are based on common standards for software supplemented by specific requirements for this field of application. Altogether, quality assurance of a model includes internal and external validation and addresses evaluation of the respective software. It should focus not only on the predictive capability of a model, but also on the strength of the theoretical underpinnings, the evidence supporting the model conceptualization, the database, and the software.