In order to improve our understanding of air quality
in Southeast Asia, the anthropogenic emissions inventory
must be well represented. In this work, we apply different
anthropogenic emission inventories in the Weather Research
and Forecasting Model with Chemistry (WRF-Chem)
version 3.3 using Model for Ozone and Related Chemical
Tracers (MOZART) gas-phase chemistry and Global
Ozone Chemistry Aerosol Radiation and Transport (GOCART)
aerosols to examine the differences in predicted carbon
monoxide (CO) and ozone (O3) surface mixing ratios
for Southeast Asia in March and December 2008. The
anthropogenic emission inventories include the Reanalysis
of the TROpospheric chemical composition (RETRO),
the Intercontinental Chemical Transport Experiment-Phase
B (INTEX-B), the MACCity emissions (adapted from the
Monitoring Atmospheric Composition and Climate and
megacity Zoom for the Environment projects), the Southeast
Asia Composition, Cloud, Climate Coupling Regional Study
(SEAC4RS) emissions, and a combination of MACCity and
SEAC4RS emissions. Biomass-burning emissions are from
the Fire Inventory from the National Center for Atmospheric
Research (NCAR) (FINNv1) model. WRF-Chem reasonably
predicts the 2 m temperature, 10 m wind, and precipitation. In
general, surface CO is underpredicted by WRF-Chem while
surface O3 is overpredicted. The NO2 tropospheric column
predicted by WRF-Chem has the same magnitude as observations,
but tends to underpredict the NO2 column over the
equatorial ocean and near Indonesia. Simulations using different
anthropogenic emissions produce only a slight variability
of O3 and CO mixing ratios, while biomass-burning
emissions add more variability. The different anthropogenic
emissions differ by up to 30 % in CO emissions, but O3 and
CO mixing ratios averaged over the land areas of the model
domain differ by ∼ 4.5 % and ∼ 8 %, respectively, among the
simulations. Biomass-burning emissions create a substantial
increase for both O3 and CO by ∼ 29 % and ∼ 16 %, respectively,
when comparing the March biomass-burning period to
the December period with low biomass-burning emissions.
The simulations show that none of the anthropogenic emission
inventories are better than the others for predicting O3
surface mixing ratios. However, the simulations with different
anthropogenic emission inventories do differ in their predictions
of CO surface mixing ratios producing variations of
∼ 30 % for March and 10–20 % for December at Thai surface
monitoring sites.