Remediation of Aromatic Hydrocarbons in Low Permeability Soils: Updating the Remediation Decision Tree (Synthesis Study)

Because of the large number of technologies for in situ remediation, the very different types of contaminants to which these technologies are applicable, and the wide range of field conditions, it can be difficult to choose an optimal technology for a specific site. Sorting and prioritizing the various factors which contribute to the success of a particular clean-up can be daunting. Furthermore, non-technical factors, such as those in the legal, political, or financial realm, may also influence which technology is ultimately chosen. Most in situ treatment methods are effective in permeable soil. However, much of Indiana soil is low-permeability, so applicability of these methods is limited. One of the few currently viable options is massive (and expensive) excavation and disposal. The purpose of the study is to develop decision-support tools for use by INDOT staff involved with site remediation. The decision-support tools include remediation decision-trees for choosing technologies or combinations of technologies appropriate for specific types of sites, including sites with low-permeability soil. In order to develop decisiontrees, it is necessary to conduct a comprehensive analysis of remediation technologies, with a focus on investigations of aromatic hydrocarbons and low-permeability soils. An additional objective is to construct a database of remediated sites in the region. The types of sites will be screened so that they are as similar as possible to sites of interest to INDOT. In particular, information from sites that have been successfully remediated will be chosen. This project will expand the scientific basis for the development and application of innovative treatment for contaminated sites owned and operated by INDOT. Potential benefits include a more effective means of remediating benzene and other fuel hydrocarbons without having to excavate and dispose of contaminated soil. The use of a remediation decision tree may decrease the time needed to choose an effective technology