5.2 METHODS
5.2.3 Simulation configuration
The meteorological data and model parameter used in configuration file of ENVI-met are summarized in Table 5.2. The simulation area was subdivided into a 3-D grid. Its horizontal area consisted of 130 by 130 grids of 2m resolution. The vertical grid size was also 2 m. The horizontal area considered a total area of 6.76ha in this simulation. In the model, the boundary of domain shows a large variation according to the wind speed and wind direction. This influences the correct interpretation on
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the results. Therefore, the simulation domain is additionally secured by 20 m at each boundary. The configuration file value is initial modeling timing data. The analysis date is from 4:00 am on 3, August, 2018 to 8:00 am on 4, August, 2018, and the weather data is simulated for 28 hours at 1-h interval. In order to increase the accuracy of the model, the simulation was performed at 4:00 am, which is 4 hours before the actual measurement time. The results of the modeling were obtained at 1.4m agl.
Table 5.2 Description of the meteorological boundary and input parameter for model
Model parameter Run time: 28h
Main model area(x,y,z) 130, 130, 30 Grid size(dx,dy,dz) 2, 2, 2
Soil profiles Concrete & Asphalt pavement Building profiles Default(concrete) /
factory: Steel sandwich panel (Blue & gray) Position on earth Busan/south Korea, 37.17, 128.98
Model rotation out of north 4°
Meteorological data Date: 3.August. 2018
Wind speed (10 m .agl) 2.8m/s
Wind direction 340
Specific humidity (2,500m a.g.l) 7.0g/kg
Roughness length 0.1
Material emissivity Buildings: 0.90, concrete & asphalt: 0.90, grasslands: 0.95 trees: 0.95
a. Meteorological data
The meteorological data had been measured at three points(P1-P3) for two days of a clear sky (Figure 5.1). The field measurement was carried out for a total of 31 hours from 8 am on August 3 to 4 pm on August 4. All sensors recorded data every 1-min in each site and data were averaged hourly to use in simulation. The meteorological data of the simulation was taken from the P1 point measurement data.
Using weather devices, the following meteorological variables were measured: air temperature(Ta), Relative humidity(RH), Wind speed(WS), Wind direction(WD) and globe temperature(Tg). Sensors at each station were installed at height 1.5m from the ground.
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Ta and RH were recorded from HOBO temperature RH smart sensor with solar radiation shield. Tg measurement was conducted using a 40mm table tennis ball painted with grey color (RAL 7001) with a T-type copper-thermocouple sensor inside the middle of the ball(Thorsson et al. 2007). WS and WD were measured with other variables, but ENVI-met is used wind speed at 10m above ground. In this study, WS at 10m above ground and WD are derived from the Sa-sang AWS(Automatic weather station).
This station is located in about 4 km south-west away from the study area. The accuracy of each sensor for the measurements is as follows: ± 0.21℃ and ±1.0 for Ta and Tg, ± 2.5% for RH, and ± 1.1m/sec and ±7degrees for WS and WD, respectively.
b. Buildings material data
ENVI-met can describe specific building characteristic using 3-D input data. To consider the thermal effects on the building skin, the default value of concrete was applied to the residential buildings and the sandwich panel was applied to the factory buildings. The sandwich panel is a combination of stainless steel or aluminum on both sides of the insulation. In this study, reflectance, emissivity and thickness of sandwich panels were considered.
Emissivity and reflectance are major factors affecting surface temperature. The higher the emissivity and reflectivity, the lower the surface temperature. Emissivity and reflectivity of sandwich panels were obtained from the American Society for Testing and Materials (ASTM) (Lee, U., et al., 2012). In this study, stainless steel was considered as the material of the factory building, and light gray and blue color were applied to the wall and roof color. The emissivity was 0.9 and the reflectance was 0.33 (light gray) and 0.28 (blue) depending on the color. The wall and roof thicknesses were considered 100T and 150T, respectively. Materials were added to the material properties for the factory building in the Manage database of ENVI-met.
c. Green buffers planning
This study is applied to the scenarios based on the status of the green buffers surveyed in the previous study. Main planting species of buffered green area are composed of evergreen trees such as strobus pine, pine, zelkova, cherry, pine and acacia. Plant density is suggested to be 0.22 tree/m2 for arbor, 0.15 tree/m2 for arborescent and 0.67 tree/m2for bush(Han, B. H., et al. 2010). Na, Y., et al. (2015) presents the required planning criteria for construction of the green buffers. Green buffers should be secured height at least 4 m and the ratio of evergreen to deciduous tree is 8:2. However, this study did not consider tree density.
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Figure 5.2 The basic species in ENVI-met; Plant name and geometry(Image: VAN DEN BERK, 2018) This study area creates a buffered green zone with grassland and tree after removing the existing buildings, because there is no free space to create green buffers. In order to evaluate the effect of green buffers space, the width of 10m and 20m of green buffers are simulated. Vegetation species of green buffers considered the basic species provided in ENVI-met(Figure 5.2); pine, pinus pinea, robin pseudoacacia, Koelreuteria paniculate. The plant height is 10-15m and the crown diameter is 7-13m.