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      • KCI등재

        Model Evaluation based on a Relationship Analysis between the Emission and Concentration of Atmospheric Ammonia in the Kanto Region of Japan

        Tatsuya SAKURAI,Takeru SUZUKI,Misato YOSHIOKA 한국대기환경학회 2018 Asian Journal of Atmospheric Environment (AJAE) Vol.12 No.1

        This study aims to evaluate the performance of the Air Quality Model (AQM) for the seasonal and spatial distribution of the NH3 concentration in the atmosphere. To obtain observational data for the model validation, observations based on biweekly sampling have been conducted using passive samplers since April 2015 at multiple monitoring sites in the Tokyo metropolitan area. AQM, built based on WRF/CMAQ, was applied to predict the NH3 concentration observed from April 2015 to March 2016. The simulation domain includes the Kanto region, which is the most densely populated area in Japan. Because the area also contains large amount of livestock, especially in its northern part, the density of the NH3 emissions derived from human activities and agriculture there are estimated to be the highest in Japan. In the model validation, the model overestimated the observed NH3 concentration in the summer season and underestimated it in the winter season. In particular, the overestimation in the summer was remarkable at a rural site (Komae) in Tokyo. It was found that the overestimation at Komae was caused by the transportation of NH3 emitted in the northern part of the Kanto region during the night. It is suggested that the emission input used in this study overestimated the NH3 emission from human sources around the Tokyo suburbs and agricultural sources in the northern part of the Kanto region in the summer season. In addition, the current emission inventories might overestimate the difference of the agricultural NH3 emissions among seasons. Because the overestimation of NH3 in the summer causes an overestimation of NO3 - in PM2.5 in the AQM simulation, further investigation is necessary for the seasonal variation in the NH3 emissions.

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