Abstract
Abstract. A simplified parameterization for secondary organic aerosol (SOA) formation in polluted air and biomass burning smoke is tested and optimized in this work, towards the goal of a computationally inexpensive method to calculate pollution and biomass burning SOA mass and hygroscopicity in global and climate models. A regional chemistry-transport model is used as the testbed for the parameterization, which is compared against observations from the Mexico City metropolitan area during the MILAGRO 2006 field experiment. The empirical parameterization is based on the observed proportionality of SOA concentrations to excess CO and photochemical age of the airmass. The approach consists in emitting an organic gas as lumped SOA precursor surrogate proportional to anthropogenic or biomass burning CO emissions according to the observed ratio between SOA and CO in aged air, and reacting this surrogate with OH into a single non-volatile species that condenses to form SOA. An emission factor of 0.08 g of the lumped SOA precursor per g of CO and a rate constant with OH of 1.25 × 10−11 cm3 molecule−1 s−1 reproduce the observed average SOA mass within 30 % in the urban area and downwind. When a 2.5 times slower rate is used (5 × 10−12 cm3 molecule−1 s−1) the predicted SOA amount and temporal evolution is nearly identical to the results obtained with SOA formation from semi-volatile and intermediate volatility primary organic vapors according to the Robinson et al. (2007) formulation. Our simplified method has the advantage of being much less computationally expensive than Robinson-type methods, and can be used in regions where the emissions of SOA precursors are not yet available. As the aged SOA/ΔCO ratios are rather consistent globally for anthropogenic pollution, this parameterization could be reasonably tested in and applied to other regions. The evolution of oxygen-to-carbon ratio was also empirically modeled and the predicted levels were found to be in reasonable agreement with observations. The potential enhancement of biogenic SOA by anthropogenic pollution, which has been suggested to play a major role in global SOA formation, is also tested using two simple parameterizations. Our results suggest that the pollution enhancement of biogenic SOA could provide additional SOA, but does not however explain the concentrations or the spatial and temporal variations of measured SOA mass in the vicinity of Mexico City, which appears to be controlled by anthropogenic sources. The contribution of the biomass burning to the predicted SOA is less than 10% during the studied period.
Highlights
The representation of sources and formation processes of organic aerosols (OA) in chemistry and climate models is currently highly uncertain
Our results suggest that the pollution enhancement of biogenic secondary organic aerosols (SOA) could provide additional SOA, but does not explain the concentrations or the spatial and temporal variations of measured SOA mass in the vicinity of Mexico City, which appears to be controlled by anthropogenic sources
Given the overall results and the relatively wide response surfaces of the statistical parameters, we chose as the optimum combination of parameters for simulating SOA from anthropogenically-dominated sources a VOCA/carbon monoxide (CO) emission ratio of 0.08 g g−1 and a rate constant of 1.25 × 10−11 cm3 molecules−1 s−1 (e-folding time constant ∼0.6 days in the typical Mexico City boundary layer)
Summary
The representation of sources and formation processes of organic aerosols (OA) in chemistry and climate models is currently highly uncertain. This leads to inaccurate estimates of OA mass and the radiative forcing associated with atmospheric aerosols (Kiehl, 2007), as well as the difficulty to distinguish between naturally and anthropogenically controlled OA (Carlton et al, 2010; Hoyle et al, 2011). Accurate predictions of OA mass and its sources are key to predicting aerosol evolution and radiative forcing under future climate and emission scenarios. The spatio-temporal distribution of OA concentrations depends on their primary emission sources, atmospheric transport and mixing, chemical processing, and removal by deposition. While significant uncertainties exist at all levels of OA processing, the largest unknowns reside in the representation of the formation and ageing of SOA (Hallquist et al, 2009)
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