Optimal In Situ Bioremediation Design of Groundwater Contaminated with Dissolved Petroleum Hydrocarbons

Abstract

Aquifers are one of the main water supply resources for drinking, agricultural, and industrial purposes. Therefore, it is crucial to study and evaluate different remediation methodologies that can be used to enhance the quality of groundwater. In situ bioremediation is one of the most efficient and cost-effective cleanup methodologies to treat groundwater pollution. This methodology relies on the microorganisms of a contaminated aquifer to treat polluted groundwater. This paper presents a multiobjective simulation-optimization (S-O) model to achieve the best in situ bioremediation system design for a groundwater with contaminated dissolved hydrocarbons. Minimizing the design and operational costs along with the sum of squared cleanup standard violations (SCSV) are the two main objectives of this study. The results of optimization are presented in the form of Pareto possibility frontiers. A model from the literature and a nondominated sorting genetic algorithm are used for groundwater simulation and optimization, respectively, in this work. Single-objective and multiobjective cleanup optimized designs were obtained. The results of the single-objective design confirmed the capability and accuracy of the developed S–O model. The multiobjective optimization results yielded a Pareto frontier that can be used by regulators to select the best design tradeoff between the cleanup standard requirements and the financial resources. For example, an optimal option that reduces total cost about 51.3% increases the SCSV about 1.9%. Moreover, the option that increases the SCSV by about 12.6% decreases the total cost equal to 76.2%. A sensitivity analysis was performed for some of the bioremediation parameters such as hydraulic conductivity, initial oxygen concentration, injected oxygen concentration, remediation time, and the ratio of oxygen to hydrocarbon consumed. The results show that the hydraulic conductivity and remediation time had the most impact on the effectiveness of the bioremediation operation.