Abstract
Abstract. The influence of losses of organic vapors to chamber walls during secondary organic aerosol (SOA) formation experiments has recently been established. Here, the influence of such losses on simulated ambient SOA concentrations and properties is assessed in the University of California at Davis / California Institute of Technology (UCD/CIT) regional air quality model using the statistical oxidation model (SOM) for SOA. The SOM was fit to laboratory chamber data both with and without accounting for vapor wall losses following the approach of Zhang et al. (2014). Two vapor wall-loss scenarios are considered when fitting of SOM to chamber data to determine best-fit SOM parameters, one with “low” and one with “high” vapor wall-loss rates to approximately account for the current range of uncertainty in this process. Simulations were run using these different parameterizations (scenarios) for both the southern California/South Coast Air Basin (SoCAB) and the eastern United States (US). Accounting for vapor wall losses leads to substantial increases in the simulated SOA concentrations from volatile organic compounds (VOCs) in both domains, by factors of ∼ 2–5 for the low and ∼ 5–10 for the high scenarios. The magnitude of the increase scales approximately inversely with the absolute SOA concentration of the no loss scenario. In SoCAB, the predicted SOA fraction of total organic aerosol (OA) increases from ∼ 0.2 (no) to ∼ 0.5 (low) and to ∼ 0.7 (high), with the high vapor wall-loss simulations providing best general agreement with observations. In the eastern US, the SOA fraction is large in all cases but increases further when vapor wall losses are accounted for. The total OA ∕ ΔCO ratio captures the influence of dilution on SOA concentrations. The simulated OA ∕ ΔCO in SoCAB (specifically, at Riverside, CA) is found to increase substantially during the day only for the high vapor wall-loss scenario, which is consistent with observations and indicative of photochemical production of SOA. Simulated O : C atomic ratios for both SOA and for total OA increase when vapor wall losses are accounted for, while simulated H : C atomic ratios decrease. The agreement between simulations and observations of both the absolute values and the diurnal profile of the O : C and H : C atomic ratios for total OA was greatly improved when vapor wall-losses were accounted for. These results overall demonstrate that vapor wall losses in chambers have the potential to exert a large influence on simulated ambient SOA concentrations, and further suggest that accounting for such effects in models can explain a number of different observations and model–measurement discrepancies.
Highlights
Particulate organic matter, or organic aerosol (OA), is derived from primary emissions or from secondary chemical production in the atmosphere from the oxidation of volatile organic compounds (VOCs)
The parameters used in the current work have been determined by fitting them to time-dependent data from secondary organic aerosol (SOA) formation experiments conducted in the Caltech chamber both with and without accounting for vapor wall losses during the fitting process; references for the specific experiments considered are provided in Table S1 in the Supplement
The spatial distribution of the statistical oxidation model (SOM)-no model SOA concentrations is shown for South Coast Air Basin (SoCAB) and the eastern United States (US) using the average from the simulations carried out using the low- and high-NOx parameterizations (Fig. 1a–b; again, the low- and high-NOx designations here refer only to the experimental conditions under which the SOM parameters were determined, not the actual NOx conditions in the UCD/CIT model)
Summary
Particulate organic matter, or organic aerosol (OA), is derived from primary emissions or from secondary chemical production in the atmosphere from the oxidation of volatile organic compounds (VOCs). Odum et al, 1996) Such SOA yield measurements form the basis of most parameterizations of SOA formation in regional air quality and global chemical-transport and climate models (Tsigaridis et al, 2014). There have been various efforts to account for model–measurement disparities including, most notably, (i) the addition of new SOA precursors in the form of so-called semi-volatile and intermediate volatility organic compounds, S/IVOCs, including treating primary organic aerosol as semi-volatile (Robinson et al, 2007); (ii) the addition of ad hoc “ageing” schemes on top of existing parameterizations of SOA from VOCs (Lane et al, 2008b; Tsimpidi et al, 2010; Dzepina et al, 2011); (iii) updating of aromatic SOA yields (Dzepina et al, 2009); and (iv) production of SOA in the aqueous phase in aerosol– water, clouds and fogs (Ervens et al, 2011). The influence of erroneously low SOA yields due to vapor wall losses on simulated SOA concentrations in threedimensional (3-D) regional models and properties is the focus of the current work
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