Explicit modeling of organic chemistry and secondary organic aerosol partitioning for Mexico City and its outflow plume

The evolution of organic aerosols (OA) in Mexico City and its outflow is investigated with the nearly explicit gas phase photochemistry model GECKO-A (Generator of Explicit Chemistry and Kinetics of Organics in the Atmosphere), wherein precursor hydrocarbons are oxidized to numerous intermediate species for which vapor pressures are computed and used to determine gas/particle partitioning in a chemical box model. Precursor emissions included observed C3-10 alkanes, alkenes, and light aromatics, as well as larger n-alkanes (up to C25) not directly observed but estimated by scaling to particulate emissions according to their volatility. Conditions were selected for comparison with observations made in March 2006 (MILAGRO). The model successfully reproduces the magnitude and diurnal shape for both primary (POA) and secondary (SOA) organic aerosols, with POA peaking in the early morning at 15-20 µg m⁻³, and SOA peaking at 10-15 µg m⁻³ during mid-day. The majority (≥75%) of the model SOA stems from reaction products of the large n-alkanes, used here as surrogates for all emitted hydrocarbons of similar volatility, with the remaining SOA originating mostly from the light aromatics. Simulated OA elemental composition reproduces observed H/C and O/C ratios reasonably well, although modeled ratios develop more slowly than observations suggest. SOA chemical composition is initially dominated by δ-hydroxy ketones and nitrates from the large alkanes, with contributions from peroxy acyl nitrates and, at later times when NOx is lower, organic hydroperoxides. The simulated plume-integrated OA mass continues to increase for several days downwind despite dilution-induced particle evaporation, since oxidation chemistry leading to SOA formation remains strong. In this model, the plume SOA burden several days downwind exceeds that leaving the city by a factor of >3. These results suggest significant regional radiative impacts of SOA.