Mechanism-based structure-activity relationship investigation on hydrolysis kinetics of atmospheric organic nitrates

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作者
Qiaojing Zhao
Hong-Bin Xie
Fangfang Ma
Wei Nie
Chao Yan
Dandan Huang
Jonas Elm
Jingwen Chen
机构
[1] Dalian University of Technology,Key Laboratory of Industrial Ecology and Environmental Engineering (Ministry of Education), School of Environmental Science and Technology
[2] Nanjing University,Joint International Research Laboratory of Atmospheric and Earth System Sciences, School of Atmospheric Sciences
[3] Shanghai Academy of Environmental Sciences,State Environmental Protection Key Laboratory of Formation and Prevention of Urban Air Pollution Complex
[4] Aarhus University,Department of Chemistry, iClimate
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Organic nitrates are key components of atmospheric organic aerosols. Hydrolysis is one of their main transformation pathways, affecting atmospheric nitrogen cycle and the properties of organic aerosols. Studying hydrolysis using experiments is hindered by limited authentic chemical standards. To advance our understanding on the hydrolysis of organic nitrates, we apply quantum chemistry methods here to establish a structure-activity relationship of the mechanisms and kinetics by selecting eight organic nitrates as model compounds. The results indicate that an acid-catalyzed mechanism is dominant for the most considered organic nitrates at pH corresponding to ambient organic aerosol (pH < 5). More importantly, a hydrolysis pathway driven by the shift of hydrogen or methyl cation is unveiled. Based on the revealed mechanisms, quaternary C at the α-site, tertiary/quaternary C at the β-site, and –C=C at the β/γ-site of the −ONO2 group are determined to be the key structural factors for the fast hydrolysis kinetics. An important feature for the hydrolysis of organic nitrates with such structural factors is proceeding via a carbocation intermediate. The formed carbocation could further mediate the organic aerosol chemistry, affecting the composition and properties of organic aerosols. This study provides a basis to further develop predictive models for hydrolysis kinetics of organic nitrates.
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