Aerosol mass yields of selected biogenic volatile organic compounds – a theoretical study with nearly explicit gas-phase chemistry
In this study we modeled secondary organic aerosol (SOA) mass loadings from the oxidation (by O3, OH and NO3) of five representative biogenic volatile organic compounds (BVOCs): isoprene, endocyclic bond-containing monoterpenes (α-pinene and limonene), exocyclic double-bond compound (β-pinene) and a...
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Veröffentlicht in: | Atmospheric chemistry and physics 2019-11, Vol.19 (22), p.13741-13758 |
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Sprache: | eng |
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Zusammenfassung: | In this study we modeled secondary organic aerosol (SOA) mass loadings from
the oxidation (by O3, OH and NO3) of five representative biogenic
volatile organic compounds (BVOCs): isoprene, endocyclic bond-containing
monoterpenes (α-pinene and limonene), exocyclic double-bond compound
(β-pinene) and a sesquiterpene (β-caryophyllene). The
simulations were designed to replicate an idealized smog chamber and oxidative
flow reactors (OFRs). The Master Chemical Mechanism (MCM) together with the
peroxy radical autoxidation mechanism (PRAM) were used to simulate the
gas-phase chemistry. The aim of this study was to compare the potency of MCM
and MCM + PRAM in predicting SOA formation. SOA yields were in good
agreement with experimental values for chamber simulations when MCM + PRAM
was applied, while a stand-alone MCM underpredicted the SOA yields. Compared
to experimental yields, the OFR simulations using MCM + PRAM yields were in
good agreement for BVOCs oxidized by both O3 and OH. On the other hand,
a stand-alone MCM underpredicted the SOA mass yields. SOA yields increased
with decreasing temperatures and NO concentrations and vice versa. This
highlights the limitations posed when using fixed SOA yields in a majority
of global and regional models. Few compounds that play a crucial role
(>95 % of mass load) in contributing to SOA mass increase
(using MCM + PRAM) are identified. The results further emphasized that
incorporating PRAM in conjunction with MCM does improve SOA mass yield
estimation. |
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ISSN: | 1680-7324 1680-7316 1680-7324 |
DOI: | 10.5194/acp-19-13741-2019 |