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Smoke from biomass and peat burning has a notable impact on ambient airquality and climate in the Southeast Asia (SEA) region. We modeled a largefire-induced haze episode in 2006 stemming mostly from Indonesia using theWeather Research and Forecasting model coupled with chemistry (WRF-Chem). Wefocused on the evolution of the fire plume composition and its interactionwith the urbanized area of the city state of Singapore, and on comparisons ofmodeled and measured aerosol and carbon monoxide (CO) concentrations. Two simulations were runwith WRF-Chem using the complex volatility basis set (VBS) scheme toreproduce primary and secondary aerosol evolution and concentration. Thefirst simulation referred to as WRF-FIRE included anthropogenic, biogenicand biomass burning emissions from the Global Fire Emissions Database (GFED3)while the second simulation referred to as WRF-NOFIRE was run withoutemissions from biomass burning. To test model performance, we used threeindependent data sets for comparison including airborne measurements ofparticulate matter (PM) with a diameter of 10 μm or less (PM10) inSingapore, CO measurements in Sumatra, and aerosol optical depth (AOD) columnobservations from four satellite-based sensors. We found reasonable agreementbetween the model runs and both ground-based measurements of CO andPM10. The comparison with AOD was less favorable and indicated the modelunderestimated AOD, although the degree of mismatch varied between differentsatellite data sets. During our study period, forest and peat fires inSumatra were the main cause of enhanced aerosol concentrations from regionaltransport over Singapore. Analysis of the biomass burning plume showed highconcentrations of primary organic aerosols (POA) with values up to600 μg m−3 over the fire locations. The concentration of POAremained quite stable within the plume between the main burning region andSingapore while the secondary organic aerosol (SOA) concentration slightlyincreased. However, the absolute concentrations of SOA (up to 20 μg m−3) were much lower than those from POA, indicating a minor role ofSOA in these biomass burning plumes. Our results show that about 21% of thetotal mass loading of ambient PM10 during the July–October study periodin Singapore was due to biomass and peat burning in Sumatra, but thiscontribution increased during high burning periods. In total, our modelresults indicated that during 35 days aerosol concentrations in Singaporewere above the threshold of 50 μg m−3 day−1 indicatingpoor air quality. During 17 days this was due to fires, based on thedifference between the simulations with and without fires. Local pollution incombination with recirculation of air masses was probably the main cause ofpoor air quality during the other 18 days, although fires from Sumatra andprobably also from Kalimantan (Indonesian part of the island of Borneo) added tothe enhanced PM10 concentrations. The model versus measurementcomparisons highlighted that for our study period and region the GFED3biomass burning aerosol emissions were more in line with observations thanfound in other studies. This indicates that care should be taken when usingAOD to constrain emissions or estimate ground-level air quality. This studyalso shows the need for relatively high resolution modeling to accuratelyreproduce the advection of air masses necessary to quantify the impacts andfeedbacks on regional air quality

Importance of transboundary transport of biomass burning emissions to regional air quality in Southeast Asia during a high fire event