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

Monte Carlo-based interval transformation analysis for multi-criteria decision analysis of groundwater management strategies under uncertain naphthalene concentrations and health risks

“…Because of the increasing water utilization for industrial, agricultural and domestic uses, as well as the inefficient and unsustainable resource exploitation, the quality and quantity of groundwater resources are deteriorating and shrinking at its weakest pace (Chang et al, 2007;Thiruvenkatachari et al, 2008;McKnight and Finkel, 2013;Mategaonkar and Eldho, 2014;Li et al, 2015). As one of important environmental problems, the management of contaminated groundwater has drawn great attention of the public since it is a time-consuming and costly challenge (Maqsood et al, 2005;Ko and Lee, 2010).…”

An Integrated Simulation, Inference and Optimization Approach for Groundwater Remediation with Two-Stage Health-Risk Assessment

“…In many urbanized and industrialized regions, groundwater has been destroyed owing to the leakage from underground storage tanks and pipelines for petroleum products [1][2][3]. Therefore, remediation of contaminated aquifers and development of appropriate management strategies are of great importance and attract considerable attention from academic, governmental, and industrial agencies [4,5].…”

“…The results indicated that complex uncertain features had significant impacts on modeling and risk-assessment outputs [25]. Li et al (2015) presented an integrated optimal groundwater remediation design approach that incorporated numerical simulation, health-risk assessment, uncertainty analysis, and non-linear optimization within a general framework [3]. It found that the impact of confidence level of slope factor on health risk was obvious, meaning that the larger the confidence level, the higher the health risk.…”