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Source sensitivity and source apportionment are two major indicators representing source–receptor relationships, which serve as essential information when considering effective strategies to accomplish improved air quality. This study evaluated source sensitivities and apportionments of ambient ozone and PM2.5 concentrations over Japan with multiple numerical techniques embedded in regional chemical transport models, including a brute-force method (BFM), a high-order decoupled direct method (HDDM), and an integrated source apportionment method (ISAM), to update the source–receptor relationships considering stringent emission controls recently implemented in Japan and surrounding countries. We also attempted to understand the differences among source sensitivities and source apportionments calculated by multiple techniques. While a part of ozone concentrations was apportioned to domestic sources, their sensitivities were small or even negative; ozone concentrations were exclusively sensitive to transport from outside Japan. Although the simulated PM2.5 concentrations were significantly lower than those reported by previous studies, their sensitivity to transport from outside Japan was still relatively large, implying that there has been a reduction in Japanese emissions, similar to surrounding countries including China, due to implementation of stringent emission controls. HDDM allowed us to understand the importance of the non-linear responses of PM2.5 concentrations to precursor emissions. Apportionments derived by ISAM were useful in distinguishing various direct and indirect influences on ozone and PM2.5 concentrations by combining with sensitivities. The results indicate that ozone transported from outside Japan plays a key role in exerting various indirect influences on the formation of ozone and secondary PM2.5 components. While the sensitivities come closer to the apportionments when perturbations in emissions are larger in highly non-linear relationships – including those between NH3 emissions and NH4+ concentrations, NOx emissions and NO3- concentrations, and NOx emissions and ozone concentrations – the sensitivities did not reach the apportionments because there were various indirect influences including other sectors, complex photochemical reactions, and gas–aerosol partitioning. It is essential to consider non-linear influences to derive strategies for effectively suppressing concentrations of secondary pollutants.

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.

Source sensitivity and source apportionment are two major indicators representing source-receptor relationships, which serve as essential information when considering effective strategies to accomplish improved air quality. This study evaluated source sensitivities to and apportionments of ambient ozone and PM2.5 concentrations over Japan with multiple numerical techniques embedded in regional chemical transport models, including a brute forth method (BFM), a high-order decoupled direct method (HDDM), and an integrated source apportionment method (ISAM), to update the source-receptor relationships considering stringent emission controls recently implemented in Japan and surrounding countries. We also attempted to understand the differences among source sensitivities and apportionments calculated by multiple techniques. While domestic sources had certain source apportionments to ozone concentrations, transport from outside Japan dominated the source sensitivities. Although the PM2.5 concentrations and absolute magnitudes of their source sensitivities were significantly lower than those reported by previous studies, transport from outside Japan still has relatively large contributions to PM2.5 concentrations, implying that there has been a reduction in Japanese emissions, similar to surrounding countries including China, due to implementation of stringent emission controls. HDDM allowed us to effectively understand the importance of the nonlinear responses of PM2.5 concentrations to precursor emissions. Apportionments derived by ISAM were useful in distinguishing various direct and indirect influences on ozone and PM2.5 concentrations. It was suggested that that ozone transported from outside Japan plays a key role in exerting various indirect influences on the formation of ozone and secondary PM2.5 components. This study demonstrated that a combination of sensitivities and apportionments derived by the BFM, HDDM, and ISAM can provide critical information to identify key emission sources and processes in the atmosphere, which are vital for the development of effective strategies for improved air quality.

Despite significant progress in improving chemical transport models (CTMs), applications of these modeling endeavours are still subject to the large and complex model uncertainty. Model Inter-Comparison Study for Asia III (MICS-Asia III) provides the opportunity to assess the capability and uncertainty of current CTMs in East Asia applications. In this study, we evaluated the multi-model simulations of nitrogen dioxide (NO2), carbon monoxide (CO) and ammonia (NH3) over China under the framework of MICS-Asia III. Compared with MICS-Asia II, modeling results were provided by a larger number of independent groups from different countries/regions and covered a longer period of time (one-full year). Furthermore, most of these groups used a common emission inventory, common meteorological inputs, and the same modeling domain and horizontal resolutions. New observations over North China Plain (NCP) and Peral River Delta (PRD) were also available in MICS-Asia III, allowing model evaluations over highly industrialized regions. The results show that most models well captured the monthly and spatial patterns of NO2 in NCP though NO2 levels were slightly underestimated. Relatively poor performance in NO2 simulations was found in PRD with larger root mean square error and lower spatial correlation coefficients, possibly due to the relative coarse model resolutions. All models significantly underpredicted CO concentrations both in NCP and PRD, with annual mean concentrations 65.4 % and 61.4 % underestimated by the ensemble mean respectively. Such large underestimations suggest that CO emissions might be underestimated in current emission inventory. In contrast to the good skills in simulating the monthly variations of NO2 and CO concentrations, all models failed to reproduce the observed monthly variations of NH3 concentrations in NCP. Most models mismatched the observed peak in July and showed negative correlation coefficients with observations, which may be closely related to the uncertainty in the monthly variations of NH3 emissions and the NH3 gas-aerosol partitioning. Finally, inter-comparisons of these model results were conducted to quantify the impacts of model uncertainty on the simulations of these gases, which are shown 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.