Reduction rate constants for nitroaromatic compounds estimated from adiabatic electron affinities
Kathy L Phillips1, Pei C Chiu, Stanley I Sandler
1Department of Chemical Engineering, University of Delaware, Center for Molecular and Engineering Thermodynamics, 150 Academy Street, Newark, Delaware 19716, USA.
Environmental Science & Technology
|September 9, 2010
Summary
Predicting the environmental fate of nitroaromatic compounds (NACs) is crucial. This study establishes new linear free energy relationships (LFERs) linking electron affinities (EA) to reduction rate constants (k), enabling accurate prediction of NAC reactivity.
Area of Science:
- Environmental Chemistry
- Computational Chemistry
- Chemical Kinetics
Background:
- Nitroaromatic compounds (NACs) are widespread environmental contaminants.
- Predicting the environmental fate and reactivity of NACs is essential.
- Previous studies used linear free energy relationships (LFERs) based on reduction potentials (E(o)(H)).
Purpose of the Study:
- To develop new LFERs correlating electron affinity (EA) with reduction rate constants (k) for NACs.
- To assess the predictive power of EA-based LFERs for NAC environmental fate.
- To estimate reduction rate constants for NACs where experimental data is lacking.
Main Methods:
- Quantum mechanical calculations to determine adiabatic electron affinities (EA) of NACs.
- Examination of NAC reduction mediated by various environmental reductants (quinones, natural organic matter, Fe(II), radicals).
- Development and application of new LFERs relating EA and log k.
Main Results:
- Strong linear correlations between EA and log k were observed for monosubstituted nitrobenzenes.
- EA-based LFERs provided accurate estimates of reduction rate constants (k).
- Estimates for 169 rate constants across 23 compounds in nine systems were generated, with deviations within an order of magnitude for complex structures.
Conclusions:
- Electron affinity (EA) is a reliable predictor of nitroaromatic compound (NAC) reactivity.
- New LFERs based on EA offer a powerful tool for assessing environmental fate and predicting reduction rates.
- This approach facilitates the estimation of kinetic data for environmental risk assessment.
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