4.7 Article

A new perspective on human health risk assessment: Development of a time dependent methodology and the effect of varying exposure durations

Journal

SCIENCE OF THE TOTAL ENVIRONMENT
Volume 431, Issue -, Pages 221-232

Publisher

ELSEVIER
DOI: 10.1016/j.scitotenv.2012.05.030

Keywords

Cancer risk; Stochastic; Uncertainty; Variability; Kinetic; Arsenic

Funding

  1. DOE NETL [DE-FE0002059]
  2. EPA STAR [RD-83438701-0]
  3. Golden Energy Computing Organization at the Colorado School of Mines
  4. National Science Foundation
  5. National Renewable Energy Laboratory
  6. US Environmental Protection Agency's Science to Achieve Results (STAR) program [RD-83438701-0]

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We present a new Time Dependent Risk Assessment (TDRA) that stochastically considers how joint uncertainty and inter-individual variability (JUV) associated with human health risk change as a function of time. In contrast to traditional, time independent assessments of risk, this new formulation relays information on when the risk occurs, how long the duration of risk is, and how risk changes with time. Because the true exposure duration (ED) is often uncertain in a risk assessment, we also investigate how varying the magnitude of fixed size durations (ranging between 5 and 70 years) of this parameter affects the distribution of risk in both the time independent and dependent methodologies. To illustrate this new formulation and to investigate these mechanisms for sensitivity, an example of arsenic contaminated groundwater is used in conjunction with two scenarios of different environmental concentration signals resulting from rate dependencies in geochemical reactions. Cancer risk is computed and compared using environmental concentration ensembles modeled with sorption as 1) a linear equilibrium assumption (LEA) and 2) first order kinetics (Kin). Results show that the information attained in the new time dependent methodology reveals how the uncertainty in other time-dependent processes in the risk assessment may influence the uncertainty in risk. We also show that individual susceptibility also affects how risk changes in time, information that would otherwise be lost in the traditional, time independent methodology. These results are especially pertinent for forecasting risk in time, and for risk managers who are assessing the uncertainty of risk. (C) 2012 Elsevier B.V. All rights reserved.

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