This paper evaluates the current status of global modeling of the organic aerosol (OA) in the troposphere and analyzes the differences between models as well as between models and observations. Thirty-one global chemistry transport models (CTMs) and general circulation models (GCMs) have participated in this intercomparison, in the framework of AeroCom phase II. The simulation of OA varies greatly between models in terms of the magnitude of primary emissions, secondary OA (SOA) formation, the number of OA species used (2 to 62), the complexity of OA parameterizations (gas-particle partitioning, chemical aging, multiphase chemistry, aerosol microphysics), and the OA physical, chemical and optical properties. The diversity of the global OA simulation results has increased since earlier AeroCom experiments, mainly due to the increasing complexity of the SOA parameterization in models, and the implementation of new, highly uncertain, OA sources. Diversity of over one order of magnitude exists in the modeled vertical distribution of OA concentrations that deserves a dedicated future study. Furthermore, although the OA / OC ratio depends on OA sources and atmospheric processing, and is important for model evaluation against OA and OC observations, it is resolved only by a few global models. The median global primary OA (POA) source strength is 56 Tg a⁻¹ (range 34–144 Tg a⁻¹) and the median SOA source strength (natural and anthropogenic) is 19 Tg a⁻¹ (range 13–121 Tg a⁻¹). Among the models that take into account the semi-volatile SOA nature, the median source is calculated to be 51 Tg a⁻¹ (range 16–121 Tg a⁻¹), much larger than the median value of the models that calculate SOA in a more simplistic way (19 Tg a⁻¹; range 13–20 Tg a⁻¹, with one model at 37 Tg a⁻¹). The median atmospheric burden of OA is 1.4 Tg (24 models in the range of 0.6–2.0 Tg and 4 between 2.0 and 3.8 Tg), with a median OA lifetime of 5.4 days (range 3.8–9.6 days). In models that reported both OA and sulfate burdens, the median value of the OA/sulfate burden ratio is calculated to be 0.77; 13 models calculate a ratio lower than 1, and 9 models higher than 1. For 26 models that reported OA deposition fluxes, the median wet removal is 70 Tg a⁻¹ (range 28–209 Tg a⁻¹), which is on average 85% of the total OA deposition. Fine aerosol organic carbon (OC) and OA observations from continuous monitoring networks and individual field campaigns have been used for model evaluation. At urban locations, the model–observation comparison indicates missing knowledge on anthropogenic OA sources, both strength and seasonality. The combined model–measurements analysis suggests the existence of increased OA levels during summer due to biogenic SOA formation over large areas of the USA that can be of the same order of magnitude as the POA, even at urban locations, and contribute to the measured urban seasonal pattern. Global models are able to simulate the high secondary character of OA observed in the atmosphere as a result of SOA formation and POA aging, although the amount of OA present in the atmosphere remains largely underestimated, with a mean normalized bias (MNB) equal to −0.62 (−0.51) based on the comparison against OC (OA) urban data of all models at the surface, −0.15 (+0.51) when compared with remote measurements, and −0.30 for marine locations with OC data. The mean temporal correlations across all stations are low when compared with OC (OA) measurements: 0.47 (0.52) for urban stations, 0.39 (0.37) for remote stations, and 0.25 for marine stations with OC data. The combination of high (negative) MNB and higher correlation at urban stations when compared with the low MNB and lower correlation at remote sites suggests that knowledge about the processes that govern aerosol processing, transport and removal, on top of their sources, is important at the remote stations. There is no clear change in model skill with increasing model complexity with regard to OC or OA mass concentration. However, the complexity is needed in models in order to distinguish between anthropogenic and natural OA as needed for climate mitigation, and to calculate the impact of OA on climate accurately.

The indirect effect of aerosols on climate is highly uncertain and limits our ability to assess anthropogenic climate change. The foundation of this uncertainty is uncertainty in the number of cloud condensation nuclei (CCN), which itself stems from uncertainty in aerosol nucleation, primary emission and growth rates. In this paper, we use a global general circulation model with aerosol microphysics to assess how the uncertainties in aerosol nucleation, emission and growth rates affect our prediction of CCN(0.2%) concentrations. Using several nucleation rate parameterizations that span six orders of magnitude of globally averaged nucleation rates, the tropospheric average CCN(0.2%) concentrations vary by 17% and the boundary layer average vary by 12%. This sensitivity of tropospheric average CCN(0.2%) to the nucleation parameterizations increases to 33% and 20% when the total primary emissions are reduced by a factor of 3 and the SOA condensation rates are increased by a factor of 3.5, respectively. These results show that it is necessary to better understand global nucleation rates when determining CCN concentrations. When primary emissions rates are varied by a factor of 3 while using a binary nucleation parameterization, tropospheric average CCN(0.2%) concentrations also vary by 17%, but boundary layer average vary by 40%. Using the fastest nucleation rate parameterization, these changes drop to 3% and 22%, respectively. These results show the importance of reducing uncertainties in primary emissions, which appear from these results to be somewhat more important for CCN than the much larger uncertainties in nucleation. These results also show that uncertainties in nucleation and primary emissions are more important when sufficient condensable material is available to grow them to CCN sizes. The percent change in CCN(0.2%) concentration between pre-industrial times and present day does not depend greatly on the nucleation rate parameterization used for our base case scenarios; however, because other factors, such as primary emissions and SOA, are uncertain in both time periods, this may be a coincidence.

The individual effects of various meteorological parameters on PM_2.5 concentrations in the Eastern US are examined using the PMCAMx chemical transport model so that these effects and their relative magnitudes can be better understood. A suite of perturbations in temperature, wind speed, absolute humidity, mixing height, cloud cover, and precipitation are imposed individually on base case conditions corresponding to periods in July 2001 and January 2002 in order to determine the sensitivities of PM_2.5 concentrations and composition to these separate meteorological parameters. Temperature had a major effect on average PM_2.5 in January (−170 ng m⁻³ K⁻¹) due largely to the evaporation of ammonium nitrate and organic aerosol at higher temperatures; increases in sulfate production with increased temperature counteracted much of this decrease in July. Changes in mixing height also had major effects on PM_2.5 concentrations: 73 ng m⁻³ (100 m)⁻¹ in January and 210 ng m⁻³ (100 m)⁻¹ in July. Changes in wind speed (30 to 55 ng m⁻³ %⁻¹) and absolute humidity (15 to 20 ng m⁻³ %⁻¹) also had appreciable effects on average PM_2.5 concentrations. Precipitation changes had large impacts on parts of the domain (a consequence of the base case meteorology), with sensitivities to changing area of precipitation in July up to 100 ng m⁻³ %⁻¹. Perturbations in cloud cover had the smallest effects on average PM_2.5 concentrations. The changes in PM_2.5 concentrations resulting from changing all eight meteorological parameters simultaneously were approximately within 25% or so of the sum of the changes to the eight individual perturbations. The sensitivities of PM_2.5 concentrations to changes in these meteorological parameters indicate that changes in climate could potentially have important impacts on PM_2.5 concentrations.