Oxidants, including singlet oxygen (1O2*) and organic triplet excited states (3C*) formed from the photoexcitation of brown carbon (BrC), drive many chemical processes in atmospheric waters. However, due to the chemical complexity of atmospheric BrC, many questions remain about the specific BrC chromophores and physicochemical properties that primarily control 1O2* and 3C* production. In this study, we present a framework for apportioning photosensitizers and predicting the production of 1O2* and 3C* based on measurable physicochemical properties of BrC. This is achieved by combining photochemical experiments with absorbance and fluorescence measurements and statistical modeling of a year-long data set of PM2.5 extracts from Hong Kong SAR, China. Parallel Factor and Non-negative Matrix Factorization analyses of the fluorescence data revealed that highly oxygenated organic aerosols were the main contributors to 1O2* production, whereas less oxygenated organic aerosols were the main contributors to 3C* production. Next, we developed Orthogonal Partial Least Squares-Multiple Linear Regression models that successfully predicted 1O2* and 3C* steady-state concentrations (1O2*ss and 3C*ss) and quantum yields ( ΦO2*1 and Φ3C*) from standard optical measurements. These models revealed that while 1O2*ss and 3C*ss depended on parameters that reflected the quantities of BrC chromophores, ΦO2*1 and Φ3C* were influenced by the specific types (i.e., quality) of BrC chromophores present. Overall, this combined approach provides a powerful tool for identifying key BrC chromophore components and specific physicochemical properties that drive 1O2* and 3C* production.
Lyu et al. (Sat,) studied this question.
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