OPTIMIZATION OF ENGINEERED INJECTION AND EXTRACTION FOR IN SITU REMEDIATION OF SORBING GROUNDWATER CONTAMINANTS

Due to the ever growing population and changing climate, the availability of non-contaminated groundwater has become increasingly crucial in order to meet the global drinking water demand. In situ remediation allows the groundwater contaminants to degrade in the aquifer, rather than pumping the contaminated groundwater to the surface for treatment, and shows potential to be both more cost effective and energy efficient than the current most common remediation practice, pump-and-treat.

In Engineered Injection and Extraction (EIE), a treatment solution is injected into the contaminant plume, and clean water is injected and extracted into and from the aquifer from various wells. EIE has shown to increase the contact between the aqueous contaminants and treatment solution, ultimately leading to more contaminant degradation. This work sought to optimize an EIE sequence for aqueous and sorbed groundwater contaminants using the genetic algorithm toolbox in Matlab. Constraints were added to the genetic algorithm to remove any unwanted features from the sequences, such as plume boundaries which kept uncontaminated areas of the aquifer from becoming contaminated. An initial population of sequences that did not violate any constraints and included the motivating sequences was produced to be used as the first generation. The genetic algorithm was performed for various scenarios such as instantaneous reaction and rate limited reaction; equilibrium and non-equilibrium sorption; and different partitioning coefficients.