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The Community Multiscale Air Quality modeling system clearly overestimated the concentration of fine particulate nitrate in the Greater Tokyo Area of Japan, which was attributed to overestimation of production of ammonium nitrate. Sensitivity analyses were conducted for factors associated with the model performance for nitrate. Ammonia emission and dry deposition of nitric acid and ammonia may be key factors for improvement of the model performance.

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The first phase of the Urban air quality Model InterComparison Study in Japan (UMICS) has been conducted to find ways to improve model performance with regard to elemental carbon (EC). Common meteorology and emission datasets are used with eight different models. All the models underestimate the EC concentrations observed in Tokyo Metropolitan Area in the summer of 2007. Sensitivity analyses are conducted using these models to investigate the causes of this underestimation. The results of the analyses reveal that emissions and vertical diffusion are dominant factors that affect the simulated EC concentrations. A significant improvement in the accuracy of EC concentrations could be realized by applying appropriate scaling factors to EC emissions and boundary concentrations. Observation data from Lidar and radiosonde suggest the possible overestimation of planetary boundary layer height, which is a vital parameter representing vertical diffusion. The findings of this work can help to improve air quality models to that they can be used to develop more effective strategies for reducing PM 2.5 concentrations.