A total of 14 chemical transport models (CTMs) participated in the first topic of the Model Inter-Comparison Study for Asia (MICS-Asia) phase III. These model results are compared with each other and an extensive set of measurements, aiming to evaluate the current CTMs' ability in simulating aerosol concentrations, to document the similarities and differences among model performance, and to reveal the characteristics of aerosol components in large cities over East Asia. In general, these CTMs can well reproduce the spatial–temporal distributions of aerosols in East Asia during the year 2010. The multi-model ensemble mean (MMEM) shows better performance than most single-model predictions, with correlation coefficients (between MMEM and measurements) ranging from 0.65 (nitrate, ${\mathrm{NO}}_{\mathrm{3}}^{-}$ ) to 0.83 (PM_2.5). The concentrations of black carbon (BC), sulfate (${\mathrm{SO}}_{\mathrm{4}}^{\mathrm{2}-}$ ), and PM₁₀ are underestimated by MMEM, with normalized mean biases (NMBs) of −17.0 %, −19.1 %, and −32.6 %, respectively. Positive biases are simulated for ${\mathrm{NO}}_{\mathrm{3}}^{-}$ (NMB = 4.9 %), ammonium (${\mathrm{NH}}_{\mathrm{4}}^{+}$ ) (NMB = 14.0 %), and PM_2.5 (NMB = 4.4 %). In comparison with the statistics calculated from MICS-Asia phase II, frequent updates of chemical mechanisms in CTMs during recent years make the intermodel variability of simulated aerosol concentrations smaller, and better performance can be found in reproducing the temporal variations of observations. However, a large variation (about a factor of 2) in the ratios of SNA (sulfate, nitrate, and ammonium) to PM_2.5 is calculated among participant models. A more intense secondary formation of ${\mathrm{SO}}_{\mathrm{4}}^{\mathrm{2}-}$ is simulated by Community Multi-scale Air Quality (CMAQ) models, because of the higher SOR (sulfur oxidation ratio) than other models (0.51 versus 0.39). The NOR (nitric oxidation ratio) calculated by all CTMs has larger values (∼0.20) than the observations, indicating that overmuch ${\mathrm{NO}}_{\mathrm{3}}^{-}$ is simulated by current models. NH₃-limited condition (the mole ratio of ammonium to sulfate and nitrate is smaller than 1) can be successfully reproduced by all participant models, which indicates that a small reduction in ammonia may improve the air quality. A large coefficient of variation (CV > 1.0) is calculated for simulated coarse particles, especially over arid and semi-arid regions, which means that current CTMs have difficulty producing similar dust emissions by using different dust schemes. According to the simulation results of MMEM in six large Asian cities, different air-pollution control plans should be taken due to their different major air pollutants in different seasons. The MICS-Asia project gives an opportunity to discuss the similarities and differences of simulation results among CTMs in East Asian applications. In order to acquire a better understanding of aerosol properties and their impacts, more experiments should be designed to reduce the diversities among air quality models.

Spatiotemporal variations of ozone (O₃) and nitrogen oxide (NO_x) mixing ratios from 14 state-of-the-art chemical transport models (CTMs) are intercompared and evaluated with O₃ observations in East Asia, within the framework of the Model Inter-Comparison Study for Asia Phase III (MICS-Asia III). This study was designed to evaluate the capabilities and uncertainties of current CTMs simulations for Asia and to provide multi-model estimates of pollutant distributions. These models were run by 14 independent groups working in China, Japan, South Korea, the United States and other countries/regions. Compared with the previous phase of MICS-Asia (MICS-Asia II), the evaluation with observations was extended from 4 months to 1 full year across China and the western Pacific Rim. In general, model performance levels for O₃ varied widely by region and season. Most models captured the key patterns of monthly and diurnal variation of surface O₃ and its precursors in the North China Plain and western Pacific Rim but failed to do so for the Pearl River Delta. A significant overestimation of surface O₃ was evident from May to September/October and from January to May over the North China Plain, the western Pacific Rim and the Pearl River Delta. Comparisons drawn from observations show that the considerable diversity in O₃ photochemical production partly contributed to this overestimation and to high levels of inter-model variability in O₃ for North China. In terms of O₃ soundings, the ensemble average of models reproduced the vertical structure for the western Pacific, but overestimated O₃ levels to below 800 hPa in the summer. In the industrialized Pearl River Delta, the ensemble average presented an overestimation for the lower troposphere and an underestimation for the middle troposphere. The ensemble average of 13 models for O₃ did not always exhibit superior performance compared with certain individual models in contrast with its superior value for Europe. This finding suggests that the spread of ensemble-model values does not represent all of the uncertainties of O₃ or that most MICS-Asia III models missed key processes. This study improved the performance of modeling O₃ in March at Japanese sites compared with MICS-Asia II. However, it overpredicted surface O₃ concentrations for western Japan in July, which was not found by MICS-Asia II. Major challenges still remain with regard to identifying the sources of bias in surface O₃ over East Asia in CTMs.

A long-term, robust observational record of atmospheric black carbon (BC) concentrations at Fukue Island for 2009–2019 was produced by unifying the data from a continuous soot monitoring system (COSMOS) and a Multi-Angle Absorption Photometer (MAAP). This record was then used to analyze emission trends from China. We identified a rapid reduction in BC concentrations of ($-\mathrm{5.8}\pm \mathrm{1.5}$ ) % yr⁻¹ or −48 % from 2010 to 2018. We concluded that an emission change of ($-\mathrm{5.3}\pm \mathrm{0.7}$ ) % yr⁻¹, related to changes in China of as much as −4.6 % yr⁻¹, was the main underlying driver. This evaluation was made after correcting for the interannual meteorological variability (IAV) by using the regional atmospheric chemistry model simulations from the Weather Research and Forecasting (WRF) and Community Multiscale Air Quality (CMAQ) models (collectively WRF/CMAQ) with the constant emissions. This resolves the current fundamental disagreements about the sign of the BC emissions trend from China over the past decade as assessed from bottom-up emission inventories. Our analysis supports inventories reflecting the governmental clean air actions after 2010 (e.g., MEIC1.3, ECLIPSE versions 5a and 6b, and the Regional Emission inventory in ASia (REAS) version 3.1) and recommends revisions to those that do not (e.g., Community Emissions Data System – CEDS). Our estimated emission trends were fairly uniform across seasons but diverse among air mass origins. Stronger BC reductions, accompanied by a reduction in carbon monoxide (CO) emissions, occurred in regions of south-central East China, while weaker BC reductions occurred in north-central East China and northeastern China. Prior to 2017, the BC and CO emissions trends were both unexpectedly positive in northeastern China during winter months, which possibly influenced the climate at higher latitudes. The pace of the estimated emissions reduction over China surpasses the Shared Socioeconomic Pathways (SSPs with reference to SSP1, specifically) scenarios for 2015–2030, which suggests highly successful emission control policies. At Fukue Island, the BC fraction of fine particulate matter (PM_2.5) also steadily decreased over the last decade. This suggests that reductions in BC emissions started without significant delay when compared to other pollutants such as NO_x and SO₂, which are among the key precursors of scattering PM_2.5.

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 PM_2.5 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 PM_2.5 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 PM_2.5 concentrations to precursor emissions. Apportionments derived by ISAM were useful in distinguishing various direct and indirect influences on ozone and PM_2.5 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 PM_2.5 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 ${\mathrm{NH}}_{\mathrm{4}}^{+}$ concentrations, NO_x emissions and ${\mathrm{NO}}_{\mathrm{3}}^{-}$ concentrations, and NO_x 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.

The Model Inter-Comparison Study for Asia (MICS-Asia) phase III was conducted to promote understanding of regional air quality and climate change in Asia, which have received growing attention due to the huge amount of anthropogenic emissions worldwide. This study provides an overview of acid deposition. Specifically, dry and wet deposition of the following species was analyzed: S (sulfate aerosol, sulfur dioxide (SO₂), and sulfuric acid (H₂SO₄)), N (nitrate aerosol, nitrogen monoxide (NO), nitrogen dioxide (NO₂), and nitric acid (HNO₃)), and A (ammonium aerosol and ammonia (NH₃)). The wet deposition simulated by a total of nine models was analyzed and evaluated using ground observation data from the Acid Deposition Monitoring Network in East Asia (EANET). In the phase III study, the number of observation sites was increased from 37 in the phase II study to 54, and southeast Asian countries were newly added. Additionally, whereas the analysis period was limited to representative months of each season in MICS-Asia phase II, the phase III study analyzed the full year of 2010. The scope of this overview mainly focuses on the annual accumulated deposition. In general, models can capture the observed wet deposition over Asia but underestimate the wet deposition of S and A, and show large differences in the wet deposition of N. Furthermore, the ratio of wet deposition to the total deposition (the sum of dry and wet deposition) was investigated in order to understand the role of important processes in the total deposition. The general dominance of wet deposition over Asia and attributions from dry deposition over land were consistently found in all models. Then, total deposition maps over 13 countries participating in EANET were produced, and the balance between deposition and anthropogenic emissions was calculated. Excesses of deposition, rather than of anthropogenic emissions, were found over Japan, northern Asia, and southeast Asia, indicating the possibility of long-range transport within and outside of Asia, as well as other emission sources. To improve the ability of models to capture the observed wet deposition, two approaches were attempted, namely, ensemble and precipitation adjustment. The ensemble approach was effective at modulating the differences in performance among models, and the precipitation-adjusted approach demonstrated that the model performance for precipitation played a key role in better simulating wet deposition. Finally, the lessons learned from the phase III study and future perspectives for phase IV are summarized.

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.