|front |1 |2 |3 |4 |5 |6 |7 |8 |9 |10 |11 |12 |13 |14 |15 |16 |17 |18 |19 |20 |21 |22 |23 |24 |review|
aggregate or cumulative doses are considered, to date there appear to be primarily two
types of exposure estimation techniques available for use to quantify human exposures (see,
e.g., Dong et al., 1994a, 1994b; Dong and Ross, in press). Point-estimation,
otherwise known as deterministic analysis, and probabilistic analysis are the two major
types of techniques currently in use for estimating human exposure to environmental
Point-estimation is the conventional method in which high-end or otherwise conservative point estimate values are used for most parameters in an exposure algorithm. These upper-bound point estimates are typically extremely improbable and hence yield highly conservative uptake or intake potential that will most likely overestimate the risk involved.
The probabilistic analysis, also known as the stochastic analysis or Monte Carlo simulation, is considered a more realistic alternative wherein probabilistic distributions for the various key exposure factors (e.g., contact rate, body surface, environmental concentration, exposure duration, etc.) are used in the algorithm instead of their point estimates. The general distinction between the two exposure estimation techniques, along with a basic description of the Monte Carlo simulation process, has been discussed in the federal (USEPA, 1997b, 1998b) and state (OEHHA, 1996) guidance documents and by numerous investigators including Thompson et al. (1992), Whitmyre et al. (1992), Copeland et al. (1994), Finley and Paustenbach (1994), and Dong et al. (1994a, 1994b).