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EPA-Expo-Box (A Toolbox for Exposure Assessors)

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Indirect Estimation
(Scenario Evaluation)

Calculating Exposure and Dose

Methods

Approaches for quantifying exposure vary depending on the level of refinement or complexity required. Directly related to the level of refinement incorporated into an assessment is whether the results of the assessment are a point estimate or a distribution of possible values.

  • Deterministic exposure assessments use point estimates (or, single values) to quantify the amount of exposure that is likely to occur for potential receptors. They produce an exposure estimate that is also a point estimate and can provide an estimate of central tendency or high-end exposures within a defined population. Deterministic approaches are used in screening-level assessments partly because of the economical and straightforward nature of the approach. Characterization of uncertainty and variability is limited when using deterministic approaches, but can be increased with multiple deterministic calculations. In other words, by calculating multiple exposure estimates using different point values for key parameters in the exposure equation, an assessor can identify which parameters most influence the exposure estimate and can attempt to describe or quantify the variability and uncertainty associated with those parameters better. Deterministic exposure assessments are discussed further in the Deterministic and Probabilistic Module in the Tiers and Types Tool Set of EPA-Expo-Box.
  • Probabilistic exposure assessment approaches use distributions of data (either probability or frequency distributions) for various parameters to generate a distribution of possible exposure estimates as opposed to a single point. Probability distributions describe the range of values for certain variables and estimate the relative likelihood (probability) that any of those values might occur in the given population (U.S. EPA, 2001). The probability distribution therefore helps to account for variability within the population. A widely-used approach to estimating exposure with probability distributions is the Monte Carlo simulation. Probabilistic exposure assessments are discussed further in the Deterministic and Probabilistic Module in the Tiers and Types Tool Set of EPA-Expo-Box.
  • Aggregate exposure assessment considers combined exposures to a single chemical across multiple routes and multiple pathways. Aggregate exposure assessments often include a summation of all potential exposure pathways. This is a conservative, health-protective approach that assumes that a single person will be exposed to the chemical through all possible exposure pathways (U.S. EPA, 2002). Aggregate exposure assessments are discussed further in the Aggregate and Cumulative Module in the Tiers and Types Tool Set of EPA-Expo-Box.
  • Cumulative exposure assessment is the evaluation of multiple stressors and multiple exposure pathways. The aim of this approach is to assess the cumulative, overall impact on human health of multiple chemicals that act by a common mechanism of toxicity. It is important to remember that the presence of multiple stressors does not necessarily mean that all of those stressors will cause or contribute to an adverse effect. Cumulative exposure assessment considers multiple chemicals and multiple pathways of exposure, but the result is not necessarily the simple sum of multiple, aggregate exposure assessments. Cumulative exposure assessments are discussed further in the Aggregate and Cumulative Module in the Tiers and Types Tool Set of EPA-Expo-Box.

The Tiers and Types Tool Set of EPA-Expo-Box provides further discussion and links to resources related to screening-level and refined assessments.

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Exposure Descriptors

Exposure descriptors are estimates for a specific point on the exposure distribution (e.g., mean, median, 95th percentile, maximum) for individual or population exposures. Exposures vary due to differences among individuals, populations, spatial and temporal scales, and other factors. According to U.S. EPA’s (2004) Example Exposure Scenarios, this "variability can be addressed by estimating exposure for the various descriptors of exposure (i.e., central tendency, high-end, or bounding) to estimate points on the distribution of exposure." Exposure descriptors are also useful when characterizing exposure and can help exposure assessors communicate with risk managers.

Exposure Descriptors
Exposure Descriptors

Source: (U.S. EPA, 1992)

Bounding Estimates

Exposure scenarios can be developed to derive a bounding estimate that captures the highest possible exposure, or theoretical upper bound, for a given exposure pathway. Bounding estimates are often used to perform screening-level assessments because if the highest possible exposure is evaluated and found to be not of concern, other potential lower exposures will also not be of concern.

To calculate an upper bound, the values selected as input parameters to the exposure or dose equation are individually higher than those expected to occur in the actual population. The combination of these assumptions results in a highly conservative exposure estimate. If exposures for a particular pathway estimated using this conservative approach are not determined to be significant, then the assessor might be able to justify eliminating that pathway from the assessment.

The scenarios developed for bounding estimates are sometimes referred to as “worst case” scenarios in which “everything that can plausibly happen to maximize exposure, dose, or risk does in fact happen. This worst case may occur (or even be observed) in a given population, but since it is usually a very unlikely set of circumstances, in most cases, a worst-case estimate will be somewhat higher than occurs in a specific population” (U.S. EPA, 1992).

High-End Estimates

Exposure scenarios can be developed to derive high-end estimates of exposure, which are generally considered to be more realistic or more likely to occur compared with bounding estimates and often are calculated using a combination of high and central inputs for exposure parameters. High-end estimates of exposure are, by definition, intended to fall within the actual distribution, rather than above it. Estimates above the distribution are bounding estimates (U.S. EPA, 1992).

The following descriptors all account for individuals at the high end of the exposure distribution (at or above the 90th percentile):

  • Reasonable maximum exposure (RME) – the highest exposure reasonably likely to occur, generally assumed to be in the range of the 90th and 99.9th percentiles (U.S. EPA, 2001)
  • Reasonable worst-case exposure – the lower part of the high-end exposure range, which is above the 90th percentile but below the 98th percentile (U.S. EPA, 1992)
  • Maximum exposure – the range above the 98th percentile (U.S. EPA, 1992)

These terms all refer to exposures that are within the population distribution and not outside the distribution; the terms are expected to describe "an individual who exists, or is thought to exist, in the population." The worst-case scenario, by contrast, describes a situation of exposure that is "a statistical possibility that may or may not occur in the population" (U.S. EPA, 1992).

As the exposure estimate moves higher within the percentile range, the level of uncertainty increases. These high-end estimates are intended to assess exposures that are higher than average, but still within a realistic, reasonable anticipated range.

Central Tendency Estimates

Exposure scenarios can be developed to derive a central tendency estimate that represents the exposure of the average or typical individual in a population, usually the mean or median of the population distribution.

The arithmetic mean uses average values for all of the factors that comprise the exposure of interest. This value may not necessarily be representative of a single receptor or group, but it falls within the actual distribution and is useful for characterizing exposure for the average population. This value is sometimes called the "average estimate," but terminology varies from assessment to assessment.

The median is another useful descriptor of central tendency, especially when data on the receptor or exposure of interest are skewed as they are in a log normal distribution. This is often called the "typical case," but terminology can vary.

If both the arithmetic mean and median exposure estimates are available, but vary substantially from each other, it is useful to provide both values to risk assessors to provide greater context about the exposure scenario and resulting exposure estimates.

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Tools

A variety of tools are available for calculating the doses of contaminants to which populations may be exposed. These tools have typically been developed for specific situations or programs but may be tailored to meet the needs of the user.

Also see the Routes Tool Set in EPA-Expo-Box for information and tools on calculating dose.

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