• Atmosphere
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• v.26 no.3
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• pp.423-433
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• 2016

In this study, performance of a computational fluid dynamics (CFD) model is assessed from analysis on air flow pattern which is observed in the artificial street canyon. Field observations focusing on flows were conducted at an artificial street canyon in Magok region. For the observation of three-dimensional airflow structures, twelve three-dimensional wind anemometers (hereafter, CSAT3) were installed inside the street canyon. The street canyon was composed of two rectangular buildings with 35-m length, 4-m width, and 7-m height. The street width (distance between the buildings) is 7 m, making the street aspect ratio (defined by the ratio of building height to street width) of 1. For the observation of above-building wind, a CSAT3 was installed above the northwest-side building. Southwesterly, westerly and northwesterly were dominant in the street canyon during the observations. Because wind direction is parallel to the street canyon in the southwesterly case, westerly and northwesterly were selected as inflow directions in numerical simulations using a computational fluid dynamics model developed through the collaborative research project between National Institute of Meteorological Sciences and Seoul National University (CFD_NIMR_SNU). The observations showed that a well-structured vortex flow (skimming flow) and an evidence of a small eddy at the corner of the downwind building and ground appeared. The CFD_NIMR_SNU reproduced both the observed flow patterns reasonably well, although wind speeds inside the street canyon were underestimated.

• Korean Journal of Remote Sensing
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• v.30 no.6
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• pp.755-767
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• 2014

In this study, detailed air flow characteristics in an urban areas were analyzed using GIS data and a Computational Fluid Dynamics (CFD) model. For this, a building construction algorithm optimized for Geographic Information System (GIS) data with a vector format (Los Angeles region imagery acquisition consortium 2 geographic information system, LARIAC2 GIS) was used. In the LARIAC2 GIS data, building vertices were expressed as latitude and longitude. Using the model buildings constructed by the algorithm as the surface boundary data in the CFD model, we performed numerical simulations for two building-congested areas in Los Angeles using inflow information provided by California Air Resources Board. Comparing with the inflow, there was a marked difference in wind speed and direction within the target areas, which was mainly caused by the secondarily induced local circulations such as street-canyon vortices, horse-shoe vortices, and recirculation zones. In street canyons parallel to the inflow direction, wind speed increased due to a channeling effect and, in street canyons perpendicular to the inflow direction, vertically well developed vortices were induced. In front of a building, a horse-shoe vortex was developed near the surface and, behind a building, a recirculation zone was developed. Near the surface in the areas where the secondarily induced local circulations, wind speed remarkably increased. Overall, wind direction little (largely) changed at the areas where wind speed largely increased (decreased).

• Korean Journal of Remote Sensing
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• v.36 no.6_3
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• pp.1653-1667
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• 2020

In this study, we coupled a computation fluid dynamics (CFD) model to the local data assimilation and prediction system (LDAPS), a current operational numerical weather prediction model of the Korea Meteorological Administration. We investigated the characteristics of fine particulate matter (PM2.5) distributions in a building-congested district. To analyze the effects of road emission on the PM2.5 concentrations, we calculated road emissions based on the monthly, daily, and hourly emission factors and the total amount of PM2.5 emissions established from the Clean Air Policy Support System (CAPSS) of the Ministry of Environment. We validated the simulated PM2.5 concentrations against those measured at the PKNU-AQ Sensor stations. In the cases of no road emission, the LDAPS-CFD model underestimated the PM2.5 concentrations measured at the PKNU-AQ Sensor stations. The LDAPS-CFD model improved the PM2.5 concentration predictions by considering road emission. At 07 and 19 LST on 22 June 2020, the southerly wind was dominant at the target area. The PM2.5 distribution at 07 LST were similar to that at 19 LST. The simulated PM2.5 concentrations were significantly affected by the road emissions at the roadside but not significantly at the building roof. In the road-emission case, the PM2.5 concentration was high at the north (wind speeds were weak) and west roads (a long street canyon). The PM2.5 concentration was low in the east road where the building density was relatively low.