Using Vertical Attachment Energies to Predict Dehalogenation Rates of Environmental Contaminants (SEER I)EPA Grant Number: R829422E02
Title: Using Vertical Attachment Energies to Predict Dehalogenation Rates of Environmental Contaminants (SEER I)
Investigators: Burrow, Paul D. , Comfort, S. D.
Institution: University of Nebraska at Lincoln
EPA Project Officer: Winner, Darrell
Project Period: August 5, 2002 through August 4, 2004 (Extended to August 4, 2005)
Project Amount: $177,831
RFA: EPSCoR (Experimental Program to Stimulate Competitive Research) (2001) RFA Text | Recipients Lists
Research Category: EPSCoR (The Experimental Program to Stimulate Competitive Research)
Zerovalent iron (Fe0) barriers are an established technology for remediating groundwater contaminated with halogenated hydrocarbons. Permeable reactive barriers (PRBs) are particularly attractive for in situ remediation because they provide long-term solutions with low operating costs. Despite the numerous advantages of PRBs, uncertainties exist in predicting the reaction rates of halogenated contaminants with Fe0. The reductive dehalogenation rates of many environmental contaminants resulting from Fe0 treatments may be related to the ability of the molecules to accept an additional electron while in the geometry of their ground electronic states. This project introduces a new experimental approach that utilizes vertical attachment energies (VAEs) as measures of the reductive properties of the contaminants and thus independent predictors of their reaction with Fe0. A major limitation in the proposed correlation is the large variability in currently published rate constants.
Project objectives are to: (i) determine internally consistent sets of kinetic rate constants for dehalogenation of several compound classes by Fe0 in aqueous media, (ii) measure the VAEs and dissociative electron attachment (DEA) cross sections of these compounds, and (iii) integrate molecular orbital and temporary anion properties (unoccupied molecular orbital energies, VAEs and DEA cross sections) into a predictive model for describing rates of dehalogenation by Fe0.
Internally consistent sets of kinetic data will be obtained by treating several classes of chlorinated organic contaminants with Fe0 in aqueous solution and tracking reductive dechlorination. Because dehalogenation rates on Fe0 can be drastically influenced by pH, redox, and many other variables, batch experiments will be conducted under strictly controlled conditions. Electron scattering equipment will be used to measure the VAEs and DEA cross sections for the same compounds. In addition, quantum-chemical software will be used to calculate LUMO energies and examine how they can be scaled to benchmark values of VAEs determined experimentally. Correlations between the reference dehalogenation rate constants and VAEs will then be examined.
Strong correlations between reference dehalogenation rate constants and VAEs are anticipated. The molecular descriptors discussed above can then be integrated into a model for predicting relative dehalogenation rates of environmental contaminants by Fe0. From regulatory and feasibility perspectives, the ability to predict reductive dehalogenation rates in PRBs will be enormously beneficial and greatly accelerate the use of this emerging technology.
Publications and Presentations:Publications have been submitted on this project: View all 1 publications for this project
Supplemental Keywords:cleanup, halocarbon, restoration, chemical reduction, environmental chemistry, physics., Scientific Discipline, Geographic Area, Waste, Water, Remediation, Contaminated Sediments, State, Ecology and Ecosystems, Environmental Engineering, Groundwater remediation, sediment treatment, predictive understanding, reductive treatment, remediation technologies, hazardous waste, zero valent iron, contaminated soil, chlorinated organic compounds, dehalogenation, permeable reactive barriers, contaminated groundwater, verticle attachment, halogenated hydrocarbons, water quality, contaminated aquifers, ecology assessment models
Progress and Final Reports:2003 Progress Report
2004 Progress Report