Simulations of organic aerosol concentrations in Mexico City using the WRF-CHEM model during the MCMA-2006/MILAGRO campaign

摘要

Organic aerosol concentrations are simulated using theWRF-CHEM model in Mexico City during the period from 24 to 29 March in association with the MILAGRO-2006 campaign. Two approaches areemployed to predict the variation and spatial distribution of the organicaerosol concentrations: (1) a traditional 2-product secondary organic aerosol(SOA) model with non-volatile primary organic aerosols (POA); (2) anon-traditional SOA model including the volatility basis-set modeling methodin which primary organic components are assumed to be semi-volatile andphotochemically reactive and are distributed in logarithmically spacedvolatility bins. The MCMA (Mexico City Metropolitan Area) 2006 officialemission inventory is used in simulations and the POA emissions are modifiedand distributed by volatility based on dilution experiments for thenon-traditional SOA model. The model results are compared to the AerosolMass Spectrometry (AMS) observations analyzed using the Positive MatrixFactorization (PMF) technique at an urban background site (T0) and asuburban background site (T1) in Mexico City. The traditional SOA modelfrequently underestimates the observed POA concentrations during rush hoursand overestimates the observations in the rest of the time in the city. Themodel also substantially underestimates the observed SOA concentrations,particularly during daytime, and only produces 21% and 25% of theobserved SOA mass in the suburban and urban area, respectively. Thenon-traditional SOA model performs well in simulating the POA variation, butstill overestimates during daytime in the urban area. The SOA simulationsare significantly improved in the non-traditional SOA model compared to thetraditional SOA model and the SOA production is increased by more than100% in the city. However, the underestimation during daytime is stillsalient in the urban area and the non-traditional model also fails toreproduce the high level of SOA concentrations in the suburban area. In thenon-traditional SOA model, the aging process of primary organic componentsconsiderably decreases the OH levels in simulations and further impacts theSOA formation. If the aging process in the non-traditional model does nothave feedback on the OH in the gas-phase chemistry, the SOA production isenhanced by more than 10% compared to the simulations with the OHfeedback during daytime, and the gap between the simulations andobservations in the urban area is around 3 μg m?3 or 20% onaverage during late morning and early afternoon, within the uncertainty fromthe AMS measurements and PMF analysis. In addition, glyoxal andmethylglyoxal can contribute up to approximately 10% of the observed SOAmass in the urban area and 4% in the suburban area. Including the non-OHfeedback and the contribution of glyoxal and methylglyoxal, thenon-traditional SOA model can explain up to 83% of the observed SOA inthe urban area, and the underestimation during late morning and earlyafternoon is reduced to 0.9 μg m?3 or 6% on average.Considering the uncertainties from measurements, emissions, meteorologicalconditions, aging of semi-volatile and intermediate volatile organiccompounds, and contributions from background transport, the non-traditionalSOA model is capable of closing the gap in SOA mass between measurements andmodels.