Exposure model assessment

EPA, 1996, is the third edition of EML/DVIES on CD-ROM for distributing exposure models, documentation, and the IMES about many computer models used for exposure assessment and other fate and transport studies as developed by the EPA s Office of Research and Development (ORD). 

Because the significance of exposure has only been considered over the past few years, there is not as wide a selection of exposure models available as that for fate models. The latter have been applied for several decades to the calculation of ambient exposure levels compared with some standard values. Papers illustrative of human exposure assessments in this symposium include one on airborne pollutant exposure assessments by Anderson (2), a generic approach to estimating exposure in risk studies by Fiksel (5), and a derivation of pollutant limit values in soil or water based on acceptable doses to humans by Rosenblatt, Small and Kainz (6). 

Field Applicability Testing (FAT) Workshop. In March 1982, the EPA Office of Research and Development convened a workshop with the specific objectives to (1) assess the state of knowledge on determining the field applicability of laboratory bioassay tests, toxicity studies, microcosm studies, and mathematical chemical exposure models (i.e., the extent to which these methods have been tested/compared with field data), and (2) recommend research objectives and priorities to advance the current level of field testing. Workshop attendees included representatives from EPA research laboratories, universities, and private industry. 

Working groups were organized with specific responsibility to assess the utility and limits of four different methods (or tools) currently used by EPA and industry for evaluating hazards posed by toxic chemicals (1) laboratory toxicity data, (2) microcosm test data, (3) site-specific data, and (4) chemical fate and exposure model results. The Exposure Modeling Committee (3.) report presented an assessment of the current extent of field model testing and recommendations for future testing efforts. 

Fate and exposure analyses. The multimedia transport and transformation model is a dynamic model that can be used to assess time-varying concentrations of contaminants that are placed in soil layers at a time-zero concentration or contaminants released continuously to air, soil, or water. This model is used for determining the distribution of a chemical in the environmental compartments. An overview of the partitioning among the liquid, solid and/or gas phases of individual compartments is presented in Fig. 7. The exposure model encompasses... 

There are many models for assessing risks to human health and/or the environment. Some of them are multimedia models, which assess the exposure and risks in different environmental matrices, such as soil, air, water, and food chains with different degrees of complexity within each medium. Conversely, others are more specific with regard to a medium or a system (e.g., river or food chain). Other models assess only human health risks or environmental risks, while some assess both risks. Based on the type of scenario that is studied, an appropriate model will be chosen. 

Analyst to conduct multipathway human health risk assessments and food-web based ecological risk assessment modeling. BREEZE risk analyst combines databases, GIS functionality, fate, transport, and exposure modeling equations into one software application... 

Besides the LCA approach, also risk assessment can be performed analysing the chemical compounds or modelling via predictive exposure models. Both types of approaches have their justification to measure environmental concentrations of chemicals in the environment with laboratory measurement is still the most reliable way for determination. But it goes along with the disadvantage of high investments concerning time and money. Besides that laboratory approaches are limited in terms of space and time, and in consequence, the survey of many micro-pollutants and their... 

The next step is impact prediction that requires detailed quantitative information about the sources of risk agents, exposure models, the receptors and possible changes in the state of these receptors caused by the defined agents. If the CLL concept was selected for assessment ecosystem effects it should firstly be utilized for impact baseline studies or assessing the do-nothing scenario. In this context CLL calculation includes the following steps (Bashkin, 2002) ... 

Under this project, an IPCS Harmonization Project Document on the Principles of Characterizing and Applying Human Exposure has been published (WHO/IPCS 2005). This document sets out the characteristics of exposure assessment models that should be described to aid in model selection by exposure assessors. The document summarizes current practice in exposure modeling and principles for evaluating exposure models, but does not provide a comprehensive list of existing exposure models. The focus of the document is on the discussion of general properties of exposure models and how they should be described. The characteristics of different modeling frameworks are examined, and 10 principles are recommended for characterization, evaluation, and use of exposure models in order to help model users select and apply the most appropriate models. The report also discusses issues such as validation, input data needs, time resolution, and extrapolation of the model results to different populations and scenarios. 

The European Commission s Joint Research Centre (on behalf of DG S ANCO) has started a project known as European Information System on Risks from Chemicals Released from Consumer Products/Articles (EIS-ChemRisks) (EU 2004), which is designed as a network to collect exposure data, exposure factors, exposure models, and health-related data. The overall objective is to develop tools and reference data to enable harmonized exposure assessment procedures in the EU. A toolbox has been designed to collect exposure information from four reference systems to systematically support exposure assessors in the EU ... 

When the project was started in 2002, European exposure factor data were scattered within numerous national and international institutions. ExpoFacts has created no new data, but instead compiled the existing data into one Internet database, where it can be easily found, screened, and downloaded from. Data were collected from the EU countries, candidate countries to EU, and EFTA countries. As a result, the ExpoFacts database contains data from 30 European countries. In addition to the population time use patterns and exposure route information, e.g., dietary statistics, the database contains socio-demographic and physiologic information to enable database use as a tool for population-wide exposure modeling and risk assessment. 

Traditional risk assessments involve the use of point estimates of exposure with no regard for variability or uncertainty as input to the exposure models, and this may not be acceptable, as the exposure assessments have great impact on the outcome of the risk assessment. 

Probabilistic exposure models attempt to provide inputs to exposure models by representing variability or uncertainty via frequency or probability distributions. Probabilistic methods can be used in the exposure assessment because pertinent variables (e.g., concentration, intake rate, exposure duration, and body weight) have been identified, their distributions can be observed, and the formula for combining the variables to estimate the exposure is well defined. 

Predictive methods of exposure assessment often rely on single values for input parameters to the exposure model that represent one point on the distribution curve of all possible values for this parameter. This point value can range from a 50th percentile, mean, median, or typical value to a worst-case estimate. In the predictive exposure assessment, a number of parameters are integrated through an algorithm to produce an output such as the predicted environmental concentration (PEC). If many worst-case values are involved, this integration can result in a PEC that has a... 

Occupational and toxicological studies have demonstrated adverse health effects from exposure to toxic air contaminants. Data on outdoor levels of toxic air contaminants have not been available for most communities in the United States, making it difficult to assess the potential for adverse human health effects from general population exposures. Models and new experiments provide a great amount of new data (Woodruff et al., 1998). 

PM concentration fields coming from air quality models are estimations of outdoor microenvironments that combined with gridded population and microenvironments information can be used for exposure modelling and estimation of doses and health effects, integrating the source to dose assessment chain (recall Fig. 1). 

If field studies are conducted in which the variables are clearly delineated, it is possible that a model could be developed that would predict the maximum exposure under registered use conditions, and such a model would be of great value in the assessment of hazard to workers. This approach may be feasible for the orchard scenario because of the large number of studies that have been carried out. Some of the factors which should be taken into consideration in developing an exposure model and areas where there are insufficient data to make an accurate estimate will be discussed. 

Conceptual models link anthropogenic activities with stressors and evaluate the relationships among exposure pathways, ecological effects, and ecological receptors. The models also may describe natural processes that influence these relationships. Conceptual models include a set of risk hypotheses that describe predicted relationships between stressor, exposure, and assessment end point response, along with the rationale for their selection. Risk hypotheses are hypotheses in the broad scientific sense they do not necessarily involve statistical testing of null and alternative hypotheses or any particular analytical approach. Risk hypotheses may predict the effects of a stressor, or they may postulate what stressors may have caused observed ecological effects. 

Expand modeling approaches and case examples in which nonsteady-state biomonitoring data are simulated to explore the exposure conditions responsible for biomonitoring results this may provide exposure estimates that can be used in risk assessment (for example, Bayesian inference techniques and population behavior-exposure models). 

Recently, metapopulation models have been successfully applied to assess the risks of contaminants to aquatic populations. A metapopulation model to extrapolate responses of the aquatic isopod Asellus aquaticus as observed in insecticide-stressed mesocosms to assess its recovery potential in drainage ditches, streams, and ponds is provided by van den Brink et al. (2007). They estimated realistic pyrethroid concentrations in these different types of aquatic ecosystems by means of exposure models used in the European legislation procedure for pesticides. It appeared that the rate of recovery of Asellus in pyrethroid-stressed drainage ditches was faster in the field than in the isolated mesocosms. However, the rate of recovery in drainage ditches was calculated to be lower than that in streams and ponds (van den Brink et al. 2007). In another study, the effects of flounder foraging behavior and habitat preferences on exposure to polychlorinated biphenyls in sediments were assessed by Linkov et al. (2002) using a tractable individual-based metapopulation model. In this study, the use of a spatially and temporally explicit model reduced the estimate of risk by an order of magnitude as compared with a nonspatial model (Linkov et al. 2002). 

Exposure models use available information on concentrations of chemicals in exposure media along with information about when, where, and how individuals might contact the exposure media to estimate exposure. For population assessments, distributional data on exposure factors and environmental concentrations are used to estimate exposure distributions for a population. Examples of various exposure models are summarized in Table 6. 

In general, integration of the health and exposure assessments should include statements regarding the relevance of the route, timing, and duration of exposure modelled from the experimental... 

The complexity of exposure assessments necessarily varies, depending on their purpose. Quantitative approaches to exposure assessment have evolved over time as new methodologies have developed, which has led to increasing detail and transparency and the potential for greater harmony in the results obtained from different exposure models. 

To address these questions, an exposure assessment should begin with a definition of the assessment objective (section 2.2.1). From this follows the need to define and evaluate the conceptual exposure model (section 2.2.2). The goal of the conceptual model is to establish exposure links via exposure pathways to exposure routes and relative magnitude of uptake or intake by different exposure routes. These questions are discussed in more detail in section 5.4 with respect to interpretation of the results of a probabilistic exposure assessment. 

In exposure assessment, uncertainty arises from insufficient knowledge about relevant exposure scenarios, exposure models and model inputs. Each of these sources of uncertainty has factors that determine the magnitude of uncertainty and variation. For example, Mosbach-Schulz (1999) identified three factors related to the uncertainty and variability of input data ... 

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