Alternative Exposure Scenarios

4 Alternative Exposure Scenarios. In the scenarios for inadvertent intrusion at a radioactive waste disposal facility considered in Sections 7.1.3.1 through 7.1.3.3, intrusion is assumed to be a onetime event occurring at 100 y after disposal. This Section considers alternative scenarios and their impacts on classification of the Hanford waste. 

Another credible assumption is that permanent access to the site could occur at the end of the 100 y period of institutional control. This assumption has been used in establishing waste acceptance criteria at all DOE low-level waste disposal sites (DOE, 1988c 1999c), including the Hanford site, based on an acceptable dose from chronic exposure of an inadvertent intruder of 1 mSv y Therefore, the waste acceptance criteria for the Hanford site already take into account an acceptable dose to an inadvertent intruder from permanent site occupancy, so the waste is acceptable for near-surface disposal as low-hazard waste according to this scenario without the need for further analysis. 

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As an alternative to these calculations, the registrant may choose to make a generic release estimate. Here, conservative default values are used for identifying waste amounts and fractions entering into the three main waste streams. Furthermore, generic exposure scenarios can be selected containing default release factors and assumptions on implemented risk management in the processes. [19]. 

According to IPCS [18] an exposure model is a conceptual or mathematical representation of the exposure process, designed to reflect real-world human exposure scenarios and processes. There are many different ways to classify exposure models. A consensus appears to be developing around the following classification scheme proposed by the World Health Organization [19], which has been adopted in this chapter (a) mechanistic or empirical and (b) deterministic or stochastic (probabilistic). Table 1 lists these model categories. However, alternative classifications may be considered as well. 

The concept of a hypothetical inadvertent intruder at a nearsurface waste disposal site, including permanent occupants of a site after an assumed loss of institutional control, provides a suitable basis for defining exposure scenarios that would be used to calculate risks that arise from waste disposal and the boundaries between waste classes. For other dispositions of waste, alternative scenarios would need to be developed and evaluated. 

Here, the important aspect is that the QSAR models, from different sources, and also those developed within CAESAR, for instance, will be integrated, evaluating their possible use. Indeed, the final target of the registration is the overall information about the acceptability or otherwise of the chemical substance. It may happen that for a certain compound, the toxicity is not so critical because the exposure scenario reduces the concern, for instance. Thus, QSAR is only one component of a more complex strategy for the evaluation of the chemical substances. Multiple factors have to be considered, and also data from different sources. OSIRIS will be important because it will organize these multiple sources into a combined scheme, and thus provide practical examples of the use of QSAR. It is also important to notice that this means that the QSAR methods are tools that are suitable for integration with other approaches, not necessarily alternative, but supplementary tools. 

Calculation of Exposure. A great advantage of Risk Assistant is that it allows users to consider a wide range of factors that will influence quantitative exposure estimates (e.g., specific exposure factors for different populations, pathways, and scenarios) with a minimum of effort. Thus, a user can rapidly produce alternative exposure evaluations, including best estimates, reasonable worst-case exposure estimates, and worst case exposure estimates. Moreover, the system provides the user with information on the degree of uncertainty contributed by various assumptions used in the analysis, which can guide the user s future data collection efforts so that they result in maximum reduction of uncertainty. 

Another important reason for using multiple scenarios is to represent major sources of variability, or what-if scenarios to examine alternative assumptions about major uncertainties. This can be less unwieldy than including them in the model. Also, the distribution of outputs for each separate scenario will be narrower than when they are combined, which may aid interpretation and credibility. A special case of this occurs when it is desired to model the consequences of extreme or rare events or situations, for example, earthquakes. An example relevant to pesticides might be exposure of endangered species on migration. This use of multiple scenarios in ecological risk assessment has been termed scenario analysis, and is described in more detail in Ferenc and Foran (2000). 

The guidelines specify the preferred route of administration as gavage (orogastric intubation) to deliver the largest possible bolus dose in order to maximize the potential of the test agent to cause maternal and developmental toxicity, i.e., worst case scenario , and to control the delivered dose to the maternal animal. Use of other routes to simulate possible human exposure situations is becoming increasingly popular and is acceptable if scientifically defensible. These alternative routes include dosed feed, dosed water, inhalation by whole body or nose-only exposure, cutaneous application, injection by intravenous, subcutaneous, intraperitoneal, or intramuscular routes, or subcutaneous insertion (for implants or for minipumps for continuous infusion). 

Fortunately for the investment community, there are alternatives to calculating tracking error that give an accurate idea of where a portfolio s risks lie. These methods start with understanding the exposures of a portfolio relative to its benchmark, along several dimensions such as duration, term structure, rating, sector, and issuer. They then create interest rate and credit spread scenarios for different future time periods and perform a what-if analysis on the portfolio and the benchmark for these scenarios. These scenarios should encompass both expected and extreme conditions (best and worst case) in order to generate a return profile, both absolute and relative to the index, as well as to identify key thresholds. 

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