Aerosol mass spectrometer constraint on the global secondary organic aerosol budget
1School of Earth and Environment, University of Leeds, Leeds, LS2 9JT, UK
2Department of Chemistry and Biochemistry, and CIRES, University of Colorado, Boulder, CO, USA
3Aerodyne Research, Billerica, MA, USA
4Department of Physics, University of Helsinki, Finland
5Department of Environmental Toxicology, University of California, Davis, CA, USA
6Centre for Atmospheric Science, School of Earth, Atmospheric and Environmental Sciences, University of Manchester, Manchester, UK
Abstract. The budget of atmospheric secondary organic aerosol (SOA) is very uncertain, with recent estimates suggesting a global source of between 12 and 1820 Tg (SOA) a−1. We used a dataset of aerosol mass spectrometer (AMS) observations from 34 different surface locations to evaluate the GLOMAP global chemical transport model. The standard model simulation (which included SOA from monoterpenes only) underpredicted organic aerosol (OA) observed by the AMS and had little skill reproducing the variability in the dataset. We simulated SOA formation from biogenic (monoterpenes and isoprene), lumped anthropogenic and lumped biomass burning volatile organic compounds (VOCs) and varied the SOA yield from each precursor source to produce the best overall match between model and observations. We assumed that SOA is essentially non-volatile and condenses irreversibly onto existing aerosol. Our best estimate of the SOA source is 140 Tg (SOA) a−1 but with a large uncertainty range which we estimate to be 50–380 Tg (SOA) a−1. We found the minimum in normalised mean error (NME) between model and the AMS dataset when we assumed a large SOA source (100 Tg (SOA) a−1) from sources that spatially matched anthropogenic pollution (which we term antropogenically controlled SOA). We used organic carbon observations compiled by Bahadur et al. (2009) to evaluate our estimated SOA sources. We found that the model with a large anthropogenic SOA source was the most consistent with these observations, however improvement over the model with a large biogenic SOA source (250 Tg (SOA) a−1) was small. We used a dataset of 14C observations from rural locations to evaluate our estimated SOA sources. We estimated a maximum of 10 Tg (SOA) a−1 (10 %) of the anthropogenically controlled SOA source could be from fossil (urban/industrial) sources. We suggest that an additional anthropogenic source is most likely due to an anthropogenic pollution enhancement of SOA formation from biogenic VOCs. Such an anthropogenically controlled SOA source would result in substantial climate forcing. We estimated a global mean aerosol direct effect of −0.26 ± 0.15 Wm−2 and indirect (cloud albedo) effect of −0.6+0.24−0.14 Wm−2 from anthropogenically controlled SOA. The biogenic and biomass SOA sources are not well constrained with this analysis due to the limited number of OA observations in regions and periods strongly impacted by these sources. To further improve the constraints by this method, additional OA observations are needed in the tropics and the Southern Hemisphere.