An investigation into uncertainties within Human Health Risk Assessment to gain an insight into plans to mitigate impacts of arsenic contamination

Abstract

The topical research on Human Health Risk Assessment (HHRA) is investigated in this paper but in the context of uncertainty using Monto Carlo Simulation (MCS) tools. This study aims to capture some of the inherent uncertainties by implementing MCS in two dimensions: Dimension 1 considers the variability within the prescribed parameters; and Dimension 2 captures the uncertainty due to functional definitions of some of the moments of the selected distributions and interdependency of correlated parameters at a higher level. The 2D MCS model of HHRA is applied to risk assessment of a study area contaminated by arsenic, a challenging case in which arsenic has a geogenic origin but the risk is triggered by human activities. The results indicate that (i) the uncertainty in the results for the site reflects a probability distribution of risk with a positive skew; and (ii) the uncertainty increases by increasing arsenic concentration, as indicated by whisker box diagrams. The study sheds light on identifying remedial strategies since risk corresponding to Reasonable Maximum Exposure (RME Risk) is higher than the concern level of risk recommended by USEPA. The risk corresponding to the central tendency exposure is also higher than the concern level of risk in most of the samples. The paper investigates current water supply sources in the residential areas and their risk values and accordingly identifies a set of possible action plans to mitigate risk. However, the formulated 2D MCS can be extended by employing local data for deriving probability distributions and different uncertainty techniques.