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Particle-Phase Photolysis of Organic Nitrates and Sulfur-Substituted Organic Nitrates: Constraints on Atmospheric Lifetimes and Loss Pathways.

Created on 11 Aug 2026

Authors

Xiang Zhang, Yuchen Wang, Zhijun Yang, Mingkai Liu, Wei Song, Xiangyu Zhang, Ruicheng Zhou, Tianli Xiong, Bin Yuan, Andrew T Lambe, Weiwei Hu, Xinming Wang

Published in

Environmental science & technology. Volume 60. Issue 31. Pages 21766-21778. Aug 11, 2026.

Abstract

Highly functionalized particle-phase organic nitrates (ONs) contribute substantially to secondary organic aerosol and influence NOx cycling through multiphase transformations. While photolysis of particle-phase inorganic nitrates is known to release nitrous acid to influence atmospheric oxidation, particle-phase ON photolysis remains poorly constrained. In this study, we determine suspended particle-phase photolysis rate constants for five synthetic multifunctional ONs and sulfur-substituted ONs (SONs) under dry conditions, using an oxidation flow reactor coupled to online aerosol measurements. The compounds include limonene- (LmSON, LmON), styrene- (SySON, SyON), and β-caryophyllene-derived (BcyON) species with additional carbonyl, sulfate, aromatic, or hydroxyl functionalities. We measure absorption cross-sections, infer quantum yields, and extrapolate to ambient solar conditions. The ambient particle-phase lifetimes range from 5.7 to 1.4 h, whereas no detectable photolysis for BcyON. Notably, carbonyl-nitrooxy conjugation enhances absorption at atmospherically relevant wavelengths and yields the fastest photolysis. We also observe net NOx production during photolysis, demonstrating its potential to influence NOx recycling. These results identify photolysis as an important sink for particle-phase ONs under dry conditions, with measurable effects on reactive nitrogen budgets. Given the functionalization typical of ambient ONs, particle-phase photolysis may be relatively rapid, highlighting the need to incorporate this pathway and its mechanistic controls into atmospheric models.

PMID:
42579099
Bibliographic data and abstract were imported from PubMed on 11 Aug 2026.

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