Evaluation and uncertainty investigation of the NO2, CO and NH3 modeling over China under the framework of MICS-Asia III

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 (<span classCombining double low line"inline-formula">NO2</span>), carbon monoxide (CO) and ammonia (<span classCombining double low line"inline-formula">NH3</span>) 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&thinsp;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 <span classCombining double low line"inline-formula">NO2</span> concentrations in the NCP region well, though <span classCombining double low line"inline-formula">NO2</span> levels were slightly underestimated. Relatively poor performance in <span classCombining double low line"inline-formula">NO2</span> 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&thinsp;% and 61.4&thinsp;% 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 <span classCombining double low line"inline-formula">NO2</span> and CO concentrations, all models failed to reproduce the observed monthly variations in <span classCombining double low line"inline-formula">NH3</span> 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 <span classCombining double low line"inline-formula">NH3</span> emissions and the <span classCombining double low line"inline-formula">NH3</span> 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 <span classCombining double low line"inline-formula">NH3</span> simulations. This suggests that for some highly active and/or short-lived primary pollutants, like <span classCombining double low line"inline-formula">NH3</span>, 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.