| Recent research has clearly demonstrated the importance of atmospheric aerosols to human health, visibility, and the radiative forcing of climate. We report on findings from the Mexico City Metropolitan Area field campaign that took place in April 2003 (MCMA-2003). Ambient particle-bound polycyclic aromatic hydrocarbons (PAH) were quantified for the first time using a real-time aerosol mass spectrometer, and for the first time PAHs were quantified with two different real-time methods alongside filter-based measurements in an extended field campaign. We developed a subtraction method that allows the removal of the contribution from non-PAH organics to the ion signals of the PAHs in ambient data. We report the mass concentrations of individual groups of PAHs, as well as the total PAH mass. The time series of the PAH measured with Photoelectric Aerosol Sensor and quadrupole-based Aerodyne Aerosol Mass Spectrometer (Q-AMS) during MCMA-2003 are well correlated. Comparison of Q-AMS PAH measurements to those from GC-MS analysis of filter samples shows that several groups of PAHs agree well, while the Q-AMS measurements are larger than the GC-MS ones for several others. Results suggest that labile PAHs decayed rapidly due to reaction occurring during filter sampling.;We use the case study during MCMA-2003 to evaluate three new SOA models: (1) updated aromatic SOA yields from recent chamber experiments; (2) the formation of SOA from glyoxal; and (3) the formation of SOA from primary semivolatile and intermediate volatility species (primary S/IVOC or P-S/IVOC). We also evaluate the effect of reduced partitioning of SOA into POA. Traditional SOA precursors (mainly high-yield aromatics) by themselves still fail to produce enough SOA to match the observations by a factor of ∼7. Glyoxal contributes several mug m-3 to SOA formation, with similar timing as the measurements. Gaseous P-S/IVOC species introduce a large amount of oxidizable carbon that was not in models before. Gaseous S/IVOC precursors have a high SOA yield, and this mechanism helps to close the gap in measured vs. modeled SOA mass for our case study. However the volatility of model SOA is too high and the O/C ratio is lower than observations. The sensitivities of the model to some key uncertain parameters are evaluated. |
