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Air pollution is one of the world’s largest health and environmental problem, claiming more than 7 million deaths each year. Even the novel viruses like COVID19, SARS have shown a more detrimental effect in the areas of high pollution. Cities are found more polluted as compared to rural counterparts. 55% of the population, which translates to 4.4 billion lives in the urban setting. This makes it important to have an air quality management plan for cities. Munich is chosen as a study area and NO2 as a criteria pollutant. NO2 is mainly released from road transport and is a matter of concern in Europe and around the world. Statistical and deterministic modeling is done to predict the NO2 concentration at a local urban scale. The statistical result indicated that the weekend has less pollution as compared to weekdays due to fewer vehicles on the roads. Morning and evening peak are also seen, which corresponds to peak traffic hours. Landshuter Alle found to be the most polluted station with an average NO2 concentration of 64.47 (μg/m3). The station even showed the peak value NO2 value of 210(μg/m3) which is five times more than the European Standard. Spatial Interpolation is done on the 44 NO2 collectors of the city using a kriging approach. Spatial maps of pollution are developed for the year 2018 and 19. The result showed that the overall pollution in the city decreased in 2019 compared to 18. The road traffic emission inventory is developed by downscaling the national grid emission to create a spatial road map. The pollution rose, and calendar graphs are developed to understand the relation of meteorology on the ambient air quality. Hotspot of pollution in the city are identified using Getis-Ord General G statistics.
Keywords: Air quality modeling, AERMOD, Nitrogen di oxide, Downscaling, Kriging, hotspot analysis
