**5. Summery**

A model inter-comparison of secondary pollutant simulations over urban areas in Japan, J-STREAM Phase I, was performed, in which a total of 32 simulations were conducted by combining CMAQ, CAMx, and WRF-Chem.

Simulated hourly concentrations of the primary pollutants NO and NO2, which are precursors of PM2.5, generally showed good agreemen<sup>t</sup> with the observed concentrations, at the same level as the MICS case. However, some di fferences between observations and simulations and CTMs may be considered to be caused by the di fferences in meteorological conditions and NOx chemistries of each CTM. Furthermore, most of the CTMs using the same input emissions tended to overestimate SO2 concentrations, although the models showed good performance for PM2.5 SO4 2−. The di fferent emission inventory, EAGrid produced better results for SO2; therefore, it appears that the emission input can be improved. However, it was likely to be unrealistic that just the modifications of the emissions could fully resolve the overestimation of SO2.

Simulated concentrations of PM2.5 and its components were evaluated via a comparison with daily observed concentrations by using the filter pack method at selected AAPMSs for a period of at least two weeks for each season in this project. In general, most of the models showed good agreemen<sup>t</sup> with the observed concentration of total PM2.5 mass for each season, within goal or criteria levels of model ensemble statistics especially in warmer seasons. This agreemen<sup>t</sup> was associated with the reproducibility of some of dominant particulates.

Among individual PM2.5 components, most model results for SO4 2− and NH4 + showed good agreemen<sup>t</sup> with daily concentration levels and day-to-day variations, with good model ensemble statistics, particularly for the warmer seasons. However, for SO4 2−, a problem in the WRF-Chem model and novel, improved mechanisms for SO4 2− formation in most CTMs were found through this model inter-comparison. Additionally, we found that the di fferences in the Asian scale precipitation patterns between precipitation parametrizations a ffected the simulated water-soluble PM2.5 concentrations. Additional improvements for SO4 2− were expected, particularly for the winter [11]. All participant models showed a strong tendency to overestimate NO3 − in warmer seasons, with the model ensemble NMB reaching 651%. However, in winter, most of the models reproduced the day-to-day variations, with underestimations for elevated NO3 − levels. These tendencies di ffered from a previous model inter-comparison, UMICS, which concluded that the participant models overestimated NO3 − levels in both summer and winter [11,12]. This di fference between two model inter-comparison studies is attributed to variations in the number of observations applied for verification. Thus, a su fficient amount of observation data on PM2.5 components is needed to evaluate and improve CTMs. The EC levels simulated by most models were considerably lower than the observed levels for all seasons; however, some models employing EAGrid emissions produced higher EC levels than the other models. The models reproduced concentrations for some elevated OC values in the warmer seasons, but clearly underestimated the OC levels in autumn and winter. In addition, some models employing the VBS model and the newly updated SOA yield mechanisms produced higher OC levels and even overestimated the observed OC concentration in some cases.

This study has identified some effective approaches for improving PM2.5 simulations for urban areas in Japan based on a model inter-comparison. First, improvements in emissions are expected to increase the reproducibility of primary pollutants that are precursors of PM2.5 and EC concentrations. For SO4<sup>2</sup><sup>−</sup>, NO3<sup>−</sup>, and OC, additional formation pathways can help to reduce underestimations. The recent model updates (e.g., CMAQ Version 5.3) improved the chemical pathways and are expected to simulate the secondary PM2.5 components well. Simulated meteorological fields will be important for the Asian scale PM2.5 concentration levels and the elevated PM2.5 concentrations during the days with high amounts of pollution. In addition, special attention is needed for misjudgments in these models. Finally, additional accumulated observations are needed to evaluate the simulated concentrations. Future studies will include these modifications to realize reference air quality modeling in the next stages of J-STREAM.

**Author Contributions:** K.Y. managed the model inter-comparison (J-STREAM), prepared the initial, boundary, and meteorological inputs, and wrote this article. S.C. is the leader of J-STREAM project and prepared emission inputs. S.I. and H.H. are core members of J-STREAM in charge of inorganic aerosols. T.S. is a core member of J-STREAM in charge of photochemical gases. M.S., M.T., T.M. (Tazuko Morikawa), I.K., Y.M. (Yukako Miya), H.K., Y.M. (Yu Morino), K.K., T.N., H.S., K.U., and Y.F. are participants who conducted the model simulations. T.H. and T.M. (Takeshi Misaki) analyzed the submitted data. K.S. is in charge of global simulations. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research was funded by the Environment Research and Technology Development Fund (5-1601) of the Environmental Restoration and Conservation Agency, JSPS KAKENHI Grant Number 18H03369, and the Collaborative Research Program of Research Institute for Applied Mechanics, Kyushu University.

**Acknowledgments:** This project was supported by the Environment Research and Technology Development Fund (5-1601) of the Environmental Restoration and Conservation Agency. This work was also partially supported by JSPS KAKENHI Grant Number 18H03369. Monitoring data of APMSs were obtained from National Institute for Environmental Studies. This work was supported in part by the Collaborative Research Program of Research Institute for Applied Mechanics, Kyushu University.

**Conflicts of Interest:** The authors declare no conflict of interest.
