Control of stochastic carcinogenic and noncarcinogenic risks in groundwater remediation through an integrated optimization design model

Abstract

This study presents an integrated optimal groundwater remediation design approach. It incorporates numerical simulation, health risk assessment, uncertainty analysis, and nonlinear optimization within a general framework. It is capable of dealing with not only health risk itself (generally caused by uncertainty), but also parameter uncertainty (e.g., slope factor and reference dose) in health risk assessment. This approach is applied to a contaminated site in western Canada for creating a set of optimal remediation strategies. Carcinogenic and noncarcinogenic risks associated with the strategies are further evaluated under four confidence levels (68.26, 90, 95 and 99.72 %). Results from the case study indicate that (i) the wells have varied contributions to groundwater remediation under different remediation periods and environmental standards; (ii) total pumping rate is mainly controlled by health risk constraints and a stringent health risk standard leads to a high total pumping rate; (iii) remediation period has a significant impact on health risk mitigation, but the marginal impact does not always increase; (iv) the impact of confidence level of slope factor on health risk is obvious, i.e., the larger the confidence level, the higher the health risk.