Emerging contaminants are defined as synthetic or naturally occurring chemicals or microorganisms that are not currently regulated but have the potential to enter the environment and cause adverse ecological and/or human health effects. With recent development in analytical techniques, emerging contaminants have been detected in wastewater, source water, and finished drinking water. These environmental occurrence data have raised public concern about the fate and ecological impacts of such compounds. Concerns regarding emerging contaminants and the many chemicals that are in use or production necessitate a task to assess their potential health effects and removal efficiency during water treatment.
Advanced oxidation processes (AOPs) are attractive and promising technologies for emerging contaminant control due to its capability of mineralizing organic compound via reactions with highly active hydroxyl radicals. However, the nonselective reactivity of hydroxyl radicals and the radical chain reactions make AOPs mechanistically complex processes. In addition, the diversity and complexity of the structure of a large number of emerging contaminants make it difficult and expensive to study the degradation pathways of each contaminant and the fate of the intermediates and byproducts. The intermediates and byproducts that are produced may pose potential effects to human and aquatic ecosystems. Consequently, there is a need to develop first-principle based mechanistic models that can enumerate reaction pathway, calculate concentrations of the byproducts, and estimate their human effects for both water treatment and reuse practices.
This dissertation develops methods to predict reaction rate constants for elementary reactions that are identified by a previously developed computer-based reaction pathway generator. Many intermediates and byproducts that are experimentally identified for HO* induced reactions with emerging contaminants include common lower molecular weight organic compounds on the basis of several carbons. These lower carbon intermediates and byproducts also react with HO* at relatively smaller reaction rate constants (i.e., k < 109 M-1s-1) and may significantly affect overall performance of AOPs. In addition, the structures of emerging contaminants with various functional groups are too complicated to model. As a consequence, the rate constant predictors are established based on the conventional organic compounds as an initial approch.
A group contribution method (GCM) predicts the aqueous phase hydroxyl radical reaction rate constants for compounds with a wide range of functional groups. The GCM is a first comprehensive tool to predict aqueous phase hydroxyl radical reaction rate constants for reactions that include hydrogen-atom abstraction from a C-H bond and/or a O-H bond by hydroxyl radical, hydroxyl radical addition to a C=C unsaturated bond in alkenes and aromatic compounds, and hydroxyl radical interaction with sulfur-, nitrogen-, or phosphorus-atom-containing compounds. The GCM shows predictability; factor of difference of 2 from literature-reported experimental values. The GCM successfully predicts the hydroxyl radical reaction rate constants for a limited number of emerging contaminants.
Linear free energy relationships (LFERs) bridge a kinetic property with a thermochemical property. The LFERs is a new proof-of-concept approach for Ab initio reaction rate constants predictors. The kinetic property represents literature-reported and our experimentally obtained hydroxyl radical reaction rate constants for neutral and ionized compounds. The thermochemical property represents quantum mechanically calculated aqueous phase free energy of activation. Various Ab initio quantum mechanical methods and solvation models are explored to calculate the aqueous phase free energy of activation of reactantas and transition states. The quantum mechanically calculcated aqueous phase free energies of activation are within the acceptable range when compared to those that are obtained from the experiments. These approaches may be applied to other reaction mechanisms to establish a library of rate constant predictions for the mechanistic modeling of AOPs. The predicted kinetic information enables one to identify important pathways of AOP mechanisms that are initiated by hydroxyl radical, and can be used to calculate concentration profiles of parent compounds, intermediates and byproducts. The mechanistic model guides the design of experiments that are used to examine the reaction mechanisms of important intermediates and byproducts and the application of AOPs to real fields.
| Identifer | oai:union.ndltd.org:GATECH/oai:smartech.gatech.edu:1853/37127 |
| Date | 22 November 2010 |
| Creators | Minakata, Daisuke |
| Publisher | Georgia Institute of Technology |
| Source Sets | Georgia Tech Electronic Thesis and Dissertation Archive |
| Detected Language | English |
| Type | Dissertation |
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