Benefit-Cost Analysis for Groundwater Remediation Considering Socio-Economic Measures

Management of contaminated groundwater resources has been a challenge due to limited resources committed to monitor and remediate a large number of contaminated sites. Therefore, there is an important question on the optimal allocation of resources for additional data collection and remedial measures. In this work, we extended the risk assessment methodology under subsurface heterogeneity and population variability proposed by others to estimate individuals' willingness-to-pay (WTP) for a proposed risk reduction by adding socio-economic measures. We introduced one of the early applications of welfare measures namely, health state, utility, and WTP concepts to study the benefits and costs of collecting additional data to reduce uncertainty for groundwater remediation. The proposed framework considered uncertainty due to subsurface heterogeneity and public health risk through a utility theory based approach that can be used in decision-making. Our framework replaced costly contingent valuation approaches and used a meta analysis which considered a theoretical structure on population age, income, and health state, and used empirical estimates from previous contingent valuation methods. We also performed sensitivity analysis on important variables such as WTP and utility levels. Our findings showed that health state and age have vital impacts on WTP. The predictions of WTP trends are consistent with patterns expected in economic theory. We illustrated the proposed framework by evaluating two scenarios of gathering additional information to better describe subsurface heterogeneity. In this example we considered a small addition of data at a correlation scale of 112 m versus a large addition of data at a correlation scale of 22 m. The results showed the two scenarios have annual individuals' WTP of $258 and $330, respectively indicating a 28% increase in individuals' WTP for additional information.