Abstract

Abstract. A new parameter model for α-pinene secondary organic aerosol (SOA) is presented, based on simulations with the detailed model BOREAM (Biogenic hydrocarbon Oxidation and Related Aerosol formation Model). The parameterisation takes into account the influence of temperature, type of oxidant, NOx-regime, photochemical ageing and water uptake, and is suitable for use in global chemistry transport models. BOREAM is validated against recent photooxidation smog chamber experiments, for which it reproduces SOA yields to within a factor of 2 in most cases. In the simple chemical mechanism of the parameter model, oxidation of α-pinene generates peroxy radicals, which, upon reaction with NO or HO2, yield products corresponding to high or low-NOx conditions, respectively. The model parameters – i.e. the temperature-dependent stoichiometric coefficients and partitioning coefficients of 10 semi-volatile products – are obtained from simulations with BOREAM, including a prescribed diurnal cycle for the radiation, oxidant and emission levels, as well as a deposition sink for the particulate and gaseous products. The effects of photooxidative ageing are implicitly included in the parameterisation, since it is based on near-equilibrium SOA concentrations, obtained through simulations of a two-week period. In order to mimic the full BOREAM model results both during SOA build-up and when SOA has reached an equilibrium concentration, the revolatilisation of condensable products due to photochemical processes is taken into account through a fitted pseudo-photolysis reaction of the lumped semi-volatile products. Modelled SOA mass yields are about ten times higher in low-NOx than in high-NOx conditions, with yields of more than 50% in the low-NOx OH-initiated oxidation of α-pinene, considerably more than in previous parameterisations based on smog chamber experiments. Sensitivity calculations indicate that discrepancies between the full model and the parameterisation due to variations in assumed oxidant levels are limited, but that changes in the radiation levels can lead to larger deviations. Photolysis of species in the particulate phase is found to strongly reduce SOA yields in the full model. Simulations of ambient conditions at 17 different sites (using oxidant, radiation and meteorological data from a global chemistry-transport model) show that overall, the parameterisation displays only little bias (2%) compared with the full model, whereas averaged relative deviations amount to about 11%. Water uptake is parameterised using fitted activity coefficients, resulting in a good agreement with the full model.

Highlights

  • Aerosols play an important role in the Earth’s atmosphere through their impact on climate (Solomon et al, 2007) and air quality (Pope III et al, 2002; Krewski et al, 2009)

  • Several volatile organic compounds (VOC) have been identified as important secondary organic aerosol (SOA) precursors through smog chamber experiments, such as aromatic compounds, mostly of anthropogenic origin (Ng et al, 2007b), and biogenic species such as the monoterpenes, sesquiterpenes (Ng et al, 2007a), isoprene (Kroll et al, 2006) and dicarbonyls (Volkamer et al, 2009)

  • Numerous smog chamber studies have been conducted, aimed at monitoring SOA yields and elucidating the gas phase and aerosol phase composition and chemical mechanisms, which were either “dark ozonolysis” or “photooxidation” experiments

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Summary

Introduction

Aerosols play an important role in the Earth’s atmosphere through their impact on climate (Solomon et al, 2007) and air quality (Pope III et al, 2002; Krewski et al, 2009). In the most recent global modelling studies (e.g. Farina et al, 2010; Pye et al, 2010) the impact of long-term ageing was ignored for biogenic VOCs. Whereas Tsigaridis et al (2006) only considered ozonolysis as a significant SOA source, photooxidation experiments, such as Ng et al (2007a) indicated that high SOA yields are found in the OH-initiated oxidation of α-pinene, especially under low-NOx conditions. A similar approach was adopted recently in Xia et al (2011), in which a reduced mechanism consisting in a volatility basis set with further ageing reactions was designed, based on simulations with the detailed MCM mechanism for α-pinene Another reduced-size model designed to reproduce SOA production of a larger model (in this case the MCM v3.1) is the Common Representative Intermediates mechanism for both anthropogenic and biogenic VOC oxidation and SOA formation (Utembe et al, 2009).

Gas phase chemistry mechanism
Generic chemistry
Heterogeneous and aerosol phase chemistry
Partitioning between gas phase and aerosol phase
Model comparison against photooxidation smog chamber experiments
Parameter model
Parameter adjustment results
NOx dependence
Importance of aerosol photolysis for SOA ageing
Influence of assumed OH and HO2 concentrations
Sensitivity to generic chemistry parameters in BOREAM
Comparison with parameterised models based on experimental yields
Treatment of water uptake and water activity
Findings
Conclusions
Full Text
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