Uncertainties in SOA simulations due to meteorological uncertainties in Mexico City during MILAGRO-2006 field campaign
1Molina Center for Energy and the Environment, La Jolla, California, USA
2Department of Earth, Atmospheric and Planetary Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
3School of Human Settlements and Civil Engineering, Xi'an Jiaotong University, Xi'an, China
4Key Laboratory of Aerosol Science & Technology, SKLLQG, Institute of Earth Environment, Chinese Academy of Sciences, Xi'an, China
Abstract. The purpose of the present study is to investigate the uncertainties in simulating secondary organic aerosol (SOA) in Mexico City metropolitan area (MCMA) due to meteorological initial uncertainties using the WRF-CHEM model through ensemble simulations. The simulated periods (24 and 29 March 2006) represent two typical meteorological episodes ("Convection-South" and "Convection-North", respectively) in the Mexico City basin during the MILAGRO-2006 field campaign. The organic aerosols are simulated using a non-traditional SOA model including the volatility basis-set modeling method and the contributions from glyoxal and methylglyoxal. Model results demonstrate that uncertainties in meteorological initial conditions have significant impacts on SOA simulations, including the peak time concentrations, the horizontal distributions, and the temporal variations. The ensemble spread of the simulated peak SOA at T0 can reach up to 4.0 μg m−3 during the daytime, which is around 35% of the ensemble mean. Both the basin wide wind speed and the convergence area affect the magnitude and the location of the simulated SOA concentrations inside the Mexico City basin. The wind speed, especially during the previous midnight and the following early morning, influences the magnitude of the peak SOA concentration through ventilation. The surface horizontal convergence zone generally determines the area with high SOA concentrations. The magnitude of the ensemble spreads may vary with different meteorological episodes but the ratio of the ensemble spread to mean does not change significantly.