Predicting Secondary Organic Aerosol Formation From Terpenoid Ozonolysis With Varying Yields In Indoor Environments

INDOOR AIR(2012)

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摘要
The ozonolysis of terpenoids generates secondary organic aerosol (SOA) indoors. Models of varying complexity have been used to predict indoor SOA formation, and many models use the SOA yield, which is the ratio of the mass of produced SOA and the mass of consumed reactive organic gas. For indoor simulations, the SOA yield has been assumed as a constant, even though it depends on the concentration of organic particles in the air, including any formed SOA. We developed two indoor SOA formation models for single terpenoid ozonolysis, with yields that vary with the organic particle concentration. The models have their own strengths and were in agreement with published experiments for d-limonene ozonolysis. Monte Carlo analyses were performed, which simulated different residential and office environments to estimate ranges of SOA concentrations and yields for d-limonene and a-pinene ozonolysis occurring indoors. Results indicate that yields are highly variable indoors and are most influenced by background organic particles for steady-state formation and indoor ozone concentration for transient peak formation. Additionally, a review of ozonolysis yields for indoor-relevant terpenoids in the literature revealed much uncertainty in their values at low concentrations typical of indoors. Practical Implications The results in this study suggest important factors that govern indoor secondary organic aerosol (SOA) formation and yields, in typical residential and office spaces. This knowledge informs the development and comparison of control strategies to reduce indoor-generated SOA. The ranges of SOA concentrations predicted indoors allow the quantification of the effects of sorptive interactions of semi-volatile organic compounds or reactive oxygen species with SOA, filter loading owing to SOA formation, and impacts of SOA on health, if links are established.
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关键词
Fine and ultrafine particles, d-Limonene, a-Pinene, Oxidation, Modeling, Monte Carlo
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