Atmospheric movements
; Gaussian distribution
; Nitrogen oxides
; Pollution
; Roads and streets
; Transportation
; Urban transportation
; Calpuff
; Dispersion Modelling
; Gaussian model
; Hybrid model
; SIRANE
; Street canyon
; Traffic emissions
; Air pollution
; nitrogen dioxide
; atmospheric modeling
; atmospheric pollution
; concentration (composition)
; dispersion
; Gaussian method
; nitrogen dioxide
; numerical model
; pollutant transport
; pollution exposure
; road
; street canyon
; traffic emission
; urban region
; air pollution
; Article
; atmospheric dispersion
; building
; canopy
; controlled study
; Gaussian puff model
; meteorology
; neighborhood
; population exposure
; priority journal
; simulation
; statistical model
; traffic
; urban area
; Neptunia
Scopus学科分类:
Environmental Science: Water Science and Technology
; Earth and Planetary Sciences: Earth-Surface Processes
; Environmental Science: Environmental Chemistry
英文摘要:
The development and use of dispersion models that simulate traffic-related air pollution in urban areas has risen significantly in support of air pollution exposure research. In order to accurately estimate population exposure, it is important to generate concentration surfaces that take into account near-road concentrations as well as the transport of pollutants throughout an urban region. In this paper, an integrated modelling chain was developed to simulate ambient Nitrogen Dioxide (NO2) in a dense urban neighbourhood while taking into account traffic emissions, the regional background, and the transport of pollutants within the urban canopy. For this purpose, we developed a hybrid configuration including 1) a street canyon model, which simulates pollutant transfer along streets and intersections, taking into account the geometry of buildings and other obstacles, and 2) a Gaussian puff model, which resolves the transport of contaminants at the top of the urban canopy and accounts for regional meteorology. Each dispersion model was validated against measured concentrations and compared against the hybrid configuration. Our results demonstrate that the hybrid approach significantly improves the output of each model on its own. An underestimation appears clearly for the Gaussian model and street-canyon model compared to observed data. This is due to ignoring the building effect by the Gaussian model and undermining the contribution of other roads by the canyon model. The hybrid approach reduced the RMSE (of observed vs. predicted concentrations) by 16%–25% compared to each model on its own, and increased FAC2 (fraction of predictions within a factor of two of the observations) by 10%–34%. � 2017 Elsevier Ltd
Department of Civil Engineering, University of Toronto, Galbraith Building, 35 St George Street, Toronto, Ontario, Canada
Recommended Citation:
Fallah-Shorshani M,, Shekarrizfard M,, Hatzopoulou M. Integrating a street-canyon model with a regional Gaussian dispersion model for improved characterisation of near-road air pollution[J]. Atmospheric Environment,2017-01-01,153