Limiting the propagation of error in probabilistic risk assessment modeling methylmercury as an example
- Brookhaven National Lab., Upton, NY (United States)
- USDOE, Washington, DC (United States)
Probabilistic risk assessment has as its goal the delineation of the distribution of risks likely to result from process or action. Such distributions not only display the expected value of risk (i.e., the most probable outcome given a model, a set of conditions, and the distributions of input parameters), but also the expected range of outcomes. Thus, one may estimate the consequences of the most and least probable scenarios according to the levels of risk that the user finds acceptable. This information is inherently more useful for policy setting than that obtained from comparison with absolute concentration or dose levels deemed to be safe. In this paper, we compare risks estimated by using the 95th percentiles of each parameter. In general, we find that the frequency distribution of model outputs is controlled by the relative width of the distribution of the most widely dispersed of the inputs and that adding additional parameters that are less widely dispersed has little or no effect on the relative dispersion of outcomes. We use the health risks of methylmercury (MeHg) resulting from coal combustion as a case in point. The only important exposure pathway for MEHg is through consumption of contaminated fish. Coal combustion (and other local point sources of Hg) can only contribute significant risks through atmospheric deposition into fresh water sources of food fish on local or regional scales. The complete risk assessment model is defined.
- Research Organization:
- Brookhaven National Lab., Upton, NY (United States)
- Sponsoring Organization:
- USDOE, Washington, DC (United States)
- DOE Contract Number:
- AC02-76CH00016
- OSTI ID:
- 245563
- Report Number(s):
- BNL--62838; CONF-960647--8; ON: DE96008894
- Country of Publication:
- United States
- Language:
- English
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