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STOCHASTIC COST-OPTIMIZATION AND RISK ASSESSMENT OF IN SITU CHEMICAL OXIDATION FOR DENSE NON-AQUEOUS PHASE LIQUID (DNAPL) SOURCE REMEDIATION
Kim, U., J.C. Parker, and R.C. Borden.
Stochastic Environmental Research and Risk Assessment 33(1):73-89(2019)
A computer program was developed to optimize in situ chemical oxidation (ISCO) design to meet specified source zone remediation objectives at DNAPL sites. In addition to the remediation objectives, the program determined optimal design parameters to meet remediation cost and took uncertainty in site characterization data and model predictions into consideration. The ISCO model was implemented in the Stochastic Cost Optimization Toolkit. ISCO design parameters considered for optimization include oxidant concentration and injection rate, frequency and number of soil or groundwater samples, and cleanup criteria for termination of subregion injection. Sensitivity studies and example applications are presented to demonstrate the benefits of the proposed stochastic optimization methodology. The Stochastic Cost Optimization Toolkit can be accessed via http://scotoolkit.csuohio.edu/aminated-Groundwater/Persistent-Contamination/ER-2310l .
Stochastic Environmental Research and Risk Assessment 33(1):73-89(2019)
A computer program was developed to optimize in situ chemical oxidation (ISCO) design to meet specified source zone remediation objectives at DNAPL sites. In addition to the remediation objectives, the program determined optimal design parameters to meet remediation cost and took uncertainty in site characterization data and model predictions into consideration. The ISCO model was implemented in the Stochastic Cost Optimization Toolkit. ISCO design parameters considered for optimization include oxidant concentration and injection rate, frequency and number of soil or groundwater samples, and cleanup criteria for termination of subregion injection. Sensitivity studies and example applications are presented to demonstrate the benefits of the proposed stochastic optimization methodology. The Stochastic Cost Optimization Toolkit can be accessed via http://scotoolkit.csuohio.edu/
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