Abstract
ABSTRACTNumerical simulation-based health risk assessment for contaminated groundwater is computationally costly. This study presents a meta-model-based statistical framework to create a series of rapid response for capturing the relations between remediation strategies (pumping rates at the wells) and remediation performance (contaminant concentrations). The meta-model is used to predict the naphthalene concentrations in groundwater under the assumption that remedial action would be implemented in 3, 5, 7, and 10 years of remediation, respectively. The simulation results from the meta-model are used as the input parameters for health risk assessment. This meta-analysis approach is applied to a naphthalene-contaminated aquifer located in a power plant in Anhui province, China. Results reveal that the exceeding level of the peak excess lifetime cancer risk is much greater than that of naphthalene concentration as compared with their environmental standards. It is also demonstrated that the proposed framework is particularly suitable to instant health risk assessment, which brings a bridge to assist in mathematically designing optimal groundwater remediation systems.
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