An integrated urban air quality modeling system is established by coupling a computational fluid dynamics (CFD) model with mesoscale meteorological and chemistry-transport models. The mesoscale models used are the weather research and forecasting (WRF) model and the community multiscale air quality (CMAQ) model, which provide the initial and time-dependent boundary conditions for the CFD model. For the consistency of chemical processes in the CFD and CMAQ models, the same chemical mechanism used in the CMAQ model is implemented in the CFD model. Urban air quality simulations are performed from 0900 to 1800 LT on 3 June 2010 in a high-rise building area of Seoul, Republic of Korea, where mobile emission sources are concentrated. The NO2 and O-3 concentrations in the CFD simulation are evaluated with data measured at a roadside air quality monitoring station, showing better agreements than those in the CMAQ simulation. The NO2 and O-3 concentration fields exhibit high spatial variabilities in the high-rise building area. The spatial variabilities near the surfaces are strongly associated with the heterogeneity of mobile emission on roads, whereas the spatial variabilities near the top of high-rise buildings are strongly associated with the heterogeneity of building geometry. The average NO2 and O-3 concentrations (46 and 30 ppb, respectively, at z = 30 m) near the surfaces are considerably different from the NO2 and O-3 concentrations in the CMAQ simulation (17 and 44 ppb, respectively, at z = 30 m), implying the insufficient urban surface representation in the CMAQ simulation. The heterogeneity of building geometry is found to enhance the vertical pollutant transport, whereas the heterogeneity of mobile emission is found to confine emitted pollutants near the surfaces. When the vertical mixing is efficient, the O-3 concentration decreases in substantial vertical ranges with the same amount of NO emission. The integrated urban air quality modeling system realistically simulates the spatial variabilities associated with the local influences of building geometry and mobile emission. This is a promising modeling approach that accounts for multiscale influences on urban air quality. (C) 2014 Elsevier Ltd. All rights reserved.
