A relatively simple but informative methodology is introduced to determine the characteristic travel distance (CTD) for airborne semivolatile organic pollutants. The CTD is derived from a moving Lagrangian cell (representing the air) and a nonmoving compartment (representing soil or vegetation). The methodology is expanded to a fugacity based steady-state multimedia environmental framework including air, vegetation, and soil. Chemical transformations in air as well as partitioning to, and transformation in, vegetation and soil are considered. Concentrations are determined by interactions among the compartments and transformation rates. This method is most appropriate for continuous, large nonpoint emissions (such as emissions from an urban airshed). A case study for 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) reveals that the CTD is on the same order of magnitude as the typical distance between urban centers. Vegetation is important for defining the regional transport processes for TCDD.

Stochastic environmental risk assessment considers the effects of numerous biological, chemical, physical, behavioral and physiological processes that involve elements of uncertainty and variability. A methodology for predicting health risks to individuals from contaminated groundwater is presented that incorporates the elements of uncertainty and variability in geological heterogeneity, physiological exposure parameters, and in cancer potency. An idealized groundwater basin is used to perform a parametric sensitivity study to assess the relative impact of (a) geologic uncertainty, (b) behavioral and physiological variability in human exposure and (c) uncertainty in cancer potency on the prediction of increased cancer risk to individuals in a population exposed to contaminants in household water supplied from groundwater. A twodimensional distribution (or surface) of human health risk was generated as a result of the simulations. Cuts in this surface (fractiles of variability and percentiles of uncertainty) are then used as a measure of relative importance of various model components on total uncertainty and variability. A case study for perchloroethylene or PCE, shows that uncertainty and variability in hydraulic

Abstract. A methodology and hypothetical case study are presented for incorporation of uncertainty and variability into calculations of human health risk appropriate for regional, or basin-scale, groundwater management problems. Uncertainty in well water concentration is introduced through complex contaminant migration patterns in the subsurface. Variability is considered in parameters related to individual behavior patterns and biological effects and to groundwater extraction and distribution networks. A joint uncertainty and variability (JUV) analysis is used to generate a two-dimensional distribution or risk surface that spans both transport uncertainty as well as individual variability. Cuts in this distributional surface (fractiles of variability and percentiles of uncertainty) are presented and discussed. Comparisons with alternative approaches based upon deterministic transport models are also made. In addition, important distinctions are made between the case where household water is derived from the nearest well and the case where household water is mixed from many wells in a distribution system. IntroductionGroundwater is an important natural resource in the United States, comprising 40% of all public supply water and over This paper develops a new integrated methodology of linkedgroundwater contaminant transport and human exposure that includes uncertainty and variability. This methodology explicitly addresses the variability in multipathway exposure and treats groundwater transport in regional scale, heterogeneous aquifers. Important physical features (such as wells and resultant well distribution systems) are included, as is the uncertainty in geophysical parameters. The methodology is also used to study parameter effects over a wide range of heterogeneity. An idealized groundwater contamination problem is then analyzed using the methodology, and insights regarding different water management strategies are described. BackgroundUnder the Safe Drinking Water Act (SDWA) of 1974, 1986, and 1995, the U.S. Environmental Protection Agency (USEPA) is required to regulate levels of contaminants in water supplies in order to protect public health. As part of this protection, the USEPA establishes a nonenforceable maximum contaminant goal level (MCGL) and an enforceable maximum contaminant level (MCL) for contaminants considered to have adverse health effects [Pontius, 1990a, b]. In addition, states may have their own standards. In planning the restoration or remedial action for contaminated groundwater, target cleanup levels may be established either in terms of 833

A simple yet representative method for determining the characteristic time a persistent organic pollutant remains in a multimedia environment is presented. The characteristic time is an important attribute for assessing long-term health and ecological impacts of a chemical. Calculating the characteristic time requires information on decay rates in multiple environmental media as well as the proportion of mass in each environmental medium. We explore the premise that using a steady-state distribution of the mass in the environment provides a means to calculate a representative estimate of the characteristic time while maintaining a simple formulation. Calculating the steadystate mass distribution incorporates the effect of advective transport and nonequilibrium effects resulting from the source terms. Using several chemicals, we calculate and compare the characteristic time in a representative multimedia environment for dynamic, steady-state, and equilibrium multimedia models, and also for a single medium model. We demonstrate that formulating the characteristic time based on the steady-state mass distribution in the environment closely approximates the dynamic characteristic time for a range of chemicals and thus can be used in decisions regarding chemical use in the environment.