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

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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.

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Acknowledgments

This research was supported by the National Natural Science Foundation of China (41271540), Program for China National Funds for Excellent Young Scientists (51222906), New Century Excellent Talents in Universities of China (NCET-13-0791), and Fundamental Research Funds for the Central Universities.

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Authors and Affiliations

  1. School of Renewable Energy, North China Electric Power University, Beijing, 102206, China

    Jing Li, Li He, Hongwei Lu & Xing Fan

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  1. Jing Li
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  2. Li He
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  3. Hongwei Lu
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  4. Xing Fan
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Correspondence to Li He.

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Li, J., He, L., Lu, H. et al. Control of stochastic carcinogenic and noncarcinogenic risks in groundwater remediation through an integrated optimization design model. Stoch Environ Res Risk Assess 29, 2159–2172 (2015). https://doi.org/10.1007/s00477-015-1106-5

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  • DOI: https://doi.org/10.1007/s00477-015-1106-5

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