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Unexpectedly Efficient Aging of Organic Aerosols Mediated by Autoxidation.
Zhang, Wen; Zhao, Zixu; Shen, Chuanyang; Zhang, Haofei.
  • Zhang W; Department of Chemistry, University of California, Riverside, California 92507, United States.
  • Zhao Z; Department of Chemistry, University of California, Riverside, California 92507, United States.
  • Shen C; Department of Chemistry, University of California, Riverside, California 92507, United States.
  • Zhang H; Department of Chemistry, University of California, Riverside, California 92507, United States.
Environ Sci Technol ; 57(17): 6965-6974, 2023 05 02.
Article en En | MEDLINE | ID: mdl-37083304
ABSTRACT
Multiphase oxidative aging is a ubiquitous process for atmospheric organic aerosols (OA). But its kinetics was often found to be slow in previous laboratory studies where high hydroxyl radical concentrations ([•OH]) were used. In this study, we performed heterogeneous oxidation experiments of several model OA systems under varied aging timescales and gas-phase [•OH]. Our results suggest that OA heterogeneous oxidation may be 2-3 orders of magnitude faster when [•OH] is decreased from typical laboratory flow tube conditions to atmospheric levels. Direct laboratory mass spectrometry measurements coupled with kinetic simulations suggest that an intermolecular autoxidation mechanism mediated by particle-phase peroxy radicals greatly accelerates OA oxidation, with enhanced formation of organic hydroperoxides, alcohols, and fragmentation products. With autoxidation, we estimate that the OA oxidation timescale in the atmosphere may be from less than a day to several days. Thus, OA oxidative aging can have greater atmospheric impacts than previously expected. Furthermore, our findings reveal the nature of heterogeneous aerosol oxidation chemistry in the atmosphere and help improve the understanding and prediction of atmospheric OA aging and composition evolution.
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Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Atmósfera Tipo de estudio: Prognostic_studies Idioma: En Año: 2023 Tipo del documento: Article

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Atmósfera Tipo de estudio: Prognostic_studies Idioma: En Año: 2023 Tipo del documento: Article