Abstract. Despite the significant progress in improving
chemical transport models (CTMs), applications of these modeling endeavors
are still subject to large and complex model uncertainty. The Model
Inter-Comparison Study for Asia III (MICS-Asia III) has provided the
opportunity to assess the capability and uncertainty of current CTMs in East
Asian applications. In this study, we have evaluated the multi-model
simulations of nitrogen dioxide (NO2), carbon monoxide (CO) and ammonia
(NH3) over China under the framework of MICS-Asia III. A total of 13
modeling results, provided by several independent groups from different
countries and regions, were used in this study. Most of these models used the same
modeling domain with a horizontal resolution of 45 km and were driven by
common emission inventories and meteorological inputs. New observations over the
North China Plain (NCP) and Pearl River Delta (PRD) regions were also
available in MICS-Asia III, allowing the model evaluations over highly
industrialized regions. The evaluation results show that most models
captured the monthly and spatial patterns of NO2 concentrations in the
NCP region well, though NO2 levels were slightly underestimated. Relatively
poor performance in NO2 simulations was found in the PRD region, with
larger root-mean-square error and lower spatial correlation coefficients,
which may be related to the coarse resolution or inappropriate spatial
allocations of the emission inventories in the PRD region. All models
significantly underpredicted CO concentrations in both the NCP and PRD
regions, with annual mean concentrations that were 65.4 % and 61.4 %
underestimated by the ensemble mean. Such large underestimations suggest
that CO emissions might be underestimated in the current emission inventory. In
contrast to the good skills for simulating the monthly variations in NO2
and CO concentrations, all models failed to reproduce the observed monthly
variations in NH3 concentrations in the NCP region. Most models
mismatched the observed peak in July and showed negative correlation
coefficients with the observations, which may be closely related to the
uncertainty in the monthly variations in NH3 emissions and the NH3
gas–aerosol partitioning. Finally, model intercomparisons have been
conducted to quantify the impacts of model uncertainty on the simulations of
these gases, which are shown to increase with the reactivity of species. Models
contained more uncertainty in the NH3 simulations. This suggests that
for some highly active and/or short-lived primary pollutants, like NH3,
model uncertainty can also take a great part in the forecast uncertainty
in addition to the emission uncertainty. Based on these results, some
recommendations are made for future studies.