Abstract
Abstract. Organic aerosol (OA) is an important fraction of submicron aerosols. However, it is challenging to predict and attribute the specific organic compounds and sources that lead to observed OA loadings, largely due to contributions from secondary production. This is especially true for megacities surrounded by numerous regional sources that create an OA background. Here, we utilize in situ gas and aerosol observations collected on board the NASA DC-8 during the NASA–NIER KORUS-AQ (Korea–United States Air Quality) campaign to investigate the sources and hydrocarbon precursors that led to the secondary OA (SOA) production observed over Seoul. First, we investigate the contribution of transported OA to total loadings observed over Seoul by using observations over the Yellow Sea coupled to FLEXPART Lagrangian simulations. During KORUS-AQ, the average OA loading advected into Seoul was ∼1–3 µg sm−3. Second, taking this background into account, the dilution-corrected SOA concentration observed over Seoul was ∼140 µgsm-3ppmv-1 at 0.5 equivalent photochemical days. This value is at the high end of what has been observed in other megacities around the world (20–70 µgsm-3ppmv-1 at 0.5 equivalent days). For the average OA concentration observed over Seoul (13 µg sm−3), it is clear that production of SOA from locally emitted precursors is the major source in the region. The importance of local SOA production was supported by the following observations. (1) FLEXPART source contribution calculations indicate any hydrocarbons with a lifetime of less than 1 day, which are shown to dominate the observed SOA production, mainly originate from South Korea. (2) SOA correlated strongly with other secondary photochemical species, including short-lived species (formaldehyde, peroxy acetyl nitrate, sum of acyl peroxy nitrates, dihydroxytoluene, and nitrate aerosol). (3) Results from an airborne oxidation flow reactor (OFR), flown for the first time, show a factor of 4.5 increase in potential SOA concentrations over Seoul versus over the Yellow Sea, a region where background air masses that are advected into Seoul can be measured. (4) Box model simulations reproduce SOA observed over Seoul within 11 % on average and suggest that short-lived hydrocarbons (i.e., xylenes, trimethylbenzenes, and semi-volatile and intermediate-volatility compounds) were the main SOA precursors over Seoul. Toluene alone contributes 9 % of the modeled SOA over Seoul. Finally, along with these results, we use the metric ΔOA/ΔCO2 to examine the amount of OA produced per fuel consumed in a megacity, which shows less variability across the world than ΔOA∕ΔCO.
Highlights
In 2007, the human population living in urban areas had increased to over 50 %, and it is predicted that nearly two-thirds of the human population will be living in urban areas by 2050 (Monks et al, 2009; UNDESA, 2015; Baklanov et al, 2016)
We evaluate the observed SOA production over the Seoul metropolitan area (SMA) with source analysis models, correlation of secondary gas-phase species with SOA, an oxidation flow reactor, and box modeling to constrain local versus transport contributions
The fact that organic aerosol (OA) concentrations are greater than POA concentrations at the youngest photochemical ages may be due to (1) very rapid SOA production, (2) sunrise occurring 3– 4 h prior to sampling air over Seoul in the morning, and (3) the imperfect characterization provided by the average photochemical age when fresh emissions have been recently injected into an air parcel
Summary
Prior to 1950, 30 % of the human population resided in urban areas (UNDESA, 2015). In 2007, the human population living in urban areas had increased to over 50 % (making it the first time in human history that more people reside in urban than rural areas), and it is predicted that nearly two-thirds of the human population will be living in urban areas by 2050 (Monks et al, 2009; UNDESA, 2015; Baklanov et al, 2016). It has been recently shown that historical chamber SOA yields are biased low due to unaccounted-for partitioning of S/IVOCs to walls (Matsunaga and Ziemann, 2010; Zhang et al, 2014; Krechmer et al, 2016, 2017) These missing or underrepresented compounds and low-biased yields, along with uncertain emission inventories for SOA precursors (Shrivastava et al, 2008; Woody et al, 2016; Murphy et al, 2017), led SOA modeling efforts over urban areas using pre-2007 models to underpredict observed SOA concentrations (de Gouw et al, 2005, 2009; Volkamer et al, 2006; Dzepina et al, 2009; Freney et al, 2014; Woody et al, 2016). These results are discussed and placed into the context of improving our knowledge about SOA production and sources in urban environments
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