85 Figure 6.18 Infrared surface temperatures (oC) on the north terrace buildings (horizontal axis) compared to the building just inside Gawler Place (vertical axis). 86 Figure 6.19 Temperatures (oC) measured in the air in Kent Town (BoM) (horizontal axis) versus the infrared surface temperature of building Y on King William Street (vertical axis).
Introduction to the Adelaide Urban Heat Island Study
- Climate change, the urban heat island, and social-economic connections
- Questions and issues for the urban heat island in Adelaide
- Project history: monitoring, modelling and understanding the Adelaide UHI
- Basic aspects of the urban heat island effect
The aim of this project was to establish the effects of the Adelaide parkland on urban heat island mitigation. Analytical models have been developed to interpret the distribution of Adelaide urban heat island intensity (Chapter 3).
Adelaide Urban Heat Island Observation Network
Fixed sensor network
The data set is virtually continuous and complete for all locations, apart from the permanent loss of one location in Victoria Park and sensor losses at two locations in the CBD, since replaced. The data from the two other organizations also covered a wider range of parameters, apart from sunshine, at different sampling intervals.
Mobile instrumentation and traverse data
The roof-mounted boom supports (1) a downward-facing surface temperature radiometer, (2) an air temperature thermocouple at 6 ft (1.8 m), (3) an upward-facing air temperature radiometer, (3) downward directional thermal radiation of the whole air, and (4) the air temperature at 0.3 m, mounted on the traversing vehicle. This combined with data from flights over the CBD by Airborne Research Australia, and the network data, have provided a basis for many of the results presented in various chapters of the report.
Timing aspects
Morphological examination of the urban heat island intensity in the Adelaide
Introduction
The portion of the sky that is visible compared to an unobstructed location is called the Sky-view factor. A value of one means that the surface can "see" the sky completely, while a value of zero indicates that the sky is completely blocked.
Warm spots in the Adelaide CBD and the diurnal and seasonal variations
This is because only rain-free days were used for Figure 3.4, while all days were used for spatial mapping. This was probably due to a warm air mass moving into the CBD towards the end of the picture year (evidence of this is shown in Figure 3.10 later).
Interpretation of CBD warm spots from urban forms
A fairly quantitative relationship between air temperature and surface brightness temperature for the CBD monitoring sites is shown in Figure 3.8, with air temperatures being about 3 warmer than surface temperatures. Although the park belt absorbs more solar energy during the day (Figure 3.11), it is cooler on average than the CBD (Figure 3.3).
Estimation of the urban heat island intensity from urban morphology
Thus, the equations given in Figure 3.13 can be used to estimate mean 10 PM air temperatures averaged over 100 meter pixel size. It should be noted that the equations shown in Figure 3.13 were derived from the CBD data.
Predicted changes to the UHII from changed building regulations
They are not suitable for estimating the UHII for the parklands where the surface is much more open. Thus, any interpretation of the park area portion of UHII maps in Figures 3.14 and 3.15 should be avoided. However, based on the results of Figure 3.13, the effect of any changes in building heights can be estimated using the shape-dependent solar exposure and the frontal area index resulting from the changes.
Conclusions
Unger Computation of Continuous Sky View Factors Using 3D Urban Raster and Vector Databases: Comparison and Application to Urban Climate", Theor. Sun Mapping of Mean Monthly Temperature over a Coastal Hilly Region Incorporating Terrain Aspect Effects", Journal of Hydrometeorology, in press Analysis of sky view factors - implications for temperature differences in urban air", Meteorol. The relationship between the urban heat island and the sky view factor approximated by a software tool on a 3D urban database", Int.
Influence of the Park Lands on the Adelaide CBD Thermal Environment
- Introduction
- Field data analysis
- Numerical experiments - setup
- Model results for the sensitivity of CBD temperatures to altered land-use
- Conclusions
Most of the parameters used by the urban canopy model (UCM) in this study are default values as there was no prior information about the study region. The effect of parks is analyzed in this chapter using 11 months of half-hourly data obtained from the temperature monitoring network established in the CBD and parks. Upmanis, H., Eliasson, I., Lindqvist, S., 1998, “Influence of green areas on nighttime temperatures in a high-latitude city (Gothenburg, Sweden)”, International Journal of Climatology.
Micro-climate modelling of the Adelaide Urban Heat Island
- Introduction
- Model and Sites
- The Envi-Met model
- City locations
- The initial atmospheric model conditions
- Results from the traverse measurements
- Results from modelling
- Victoria Square
- CBD city centre zone
- Northern CBD zone
- Conclusions
In Figure 5.5, the corrected temperature data from the traverse is shown as colored dots, each color specifying a temperature range around the displayed isolines' temperature from the iButton data field. The view shown in Figure 5.10 at 00:00 CStdT shows a cool spot in the northern part of the Victoria Square, consistent with the modeled result for the Victoria Square zone alone, shown in figure 5.7. Taylor, J.K., Thomson, BP and Shepherd, RG, 1974, “The Soils and Geology of the Adelaide Area”, Bulletin 46. Department of Mines, Geological Survey of South Australia, Adelaide, South Australia.
Infrared Thermographic Analysis of the Urban Environment and its Individual
Introduction
Thermal characteristics of the Adelaide CBD
Using this focal center, Figure 6.2 shows the variation in mean surface temperatures in the thermal image with distance from. Higher surface temperatures are located around the center of the CBD, with temperatures gradually decreasing into the park area. Contributing factors such as low-albedo surfaces, enclosed urban geometry and more impervious surfaces are all present in the high-temperature inner-city areas.
Infrared sky temperatures
In Figure 6.4, the top graph shows the air temperature (between 6 and 14 degrees Celsius) and the bottom graph shows the infrared sky temperature. The infrared sky has much lower temperatures because a clear sky is very cold (in contrast, the 'random' hot spots where the sensor was under trees - which are much warmer than the clear sky). Although the infrared sky has much lower temperatures, the variation is important and remarkable.
Building surface temperatures at night in the city
This effect turns out not to be measurable under cloudy skies, but is often seen on clear mornings. In this case, a 10 m wide street with adjacent 25 m high buildings does not show significant radiative cooling until a height of 15 m above street level is reached. Warm temperatures exist below a height of 15 m, above which cooling to the clear sky becomes effective.
Urban landscape component analysis
Since the construction layer is used to calculate the zonal statistics of the thermal image, it is important that the construction layer is aligned with the correct pixels of the thermal image. To correct this difference, the building floor plan for each individual building was moved and modified to match the roof of the building.). The higher temperature areas in the city center have a lower building to area ratio, with the 27.5 - 28 °C temperature range having 6 buildings per ha, indicating larger buildings in these CBD areas.
External infrared building temperatures
The horizontal scale of the graph is expressed in pixels along the line in the image. The temperatures before pixel 96 follow the line in the figure of the very cold air through the exposed parts of the left building. In this case the averages of the temperatures are very similar, but the dispersion is high.
Diurnal surface temperature variation of buildings
By way of contrast, Figure 6.21 shows the heating of the south facade of the same building X between 0955 and 1659 hours. The temperature gradient (7-10oC) between the top and bottom of the building is greater than that observed for the western facade (2-3oC), which is most likely due to the canyon effect on the south side of the building. These results indicate that the orientation of a building's facades has a substantial influence on their thermal behavior, including maximum temperature and heating rate, as does the geometry of the surrounding city.
Strategies to reduce UHI effects in relation to buildings
Including cool surfaces in building regulations is a simple way to ensure that new buildings or any new works use high albedo materials (Taha et al, 1992). High albedo surfaces could be used for many of these surfaces to reduce urban temperatures. But cool surfaces should be emphasized first because they are more efficient than trees and cost little if high-albedo surfaces are included in regular maintenance programs.
Conclusions
The Energetic Basis of the Urban Heat Island”, Kwartaallikse Tydskrif van die Royal Meteorological Society. 34;Urban Climates and Heat Islands: Albedo, Evapotranspiration, and Anthropogenic Heat", Energy & Buildings - Special Issue on Urban Heat Islands, Volume 25, Number 2 (1997), pp.
Response of Office Building Electricity Consumption to Urban Weather and its
- Introduction
- Temperature-dependent building electricity consumption
- Data and Methodology
- Results
- Electricity consumption and its response to air temperature
- Statistical modelling of the response of electricity consumption to weather
- Comparison of the Adelaide office building electricity consumption with overseas
- The response of Adelaide CBD office buildings to climate change and heat waves
- Conclusions
- Recommendations for future work
A preliminary examination of the data showed that the electricity consumption of the three buildings followed the patterns described in the previous section. Both air temperature and humidity are statistically significant in regressions for the interpretation of electricity consumption data. Three buildings in Adelaide behave differently in terms of baseline electricity consumption and temperature dependence.
Building Performance Modelling
Introduction
Increasing the height of surrounding buildings to the same height as the case study building to analyze the shading effect of other buildings. In addition, the building envelope was also modified to analyze the sensitivity of the building's energy consumption to the envelope design. For the building that is fully glazed, the envelope is modified so that only 35% of the facade is glass, while for the other two buildings, which are not currently fully glazed, the facade is modified to be 100% glazed.
Modelling Parameters
- Climate and weather data
- Site and adjacent structures
- Building envelopes
- Internal thermal loads, energy use profiles and settings
- HVAC systems and settings
Since the surrounding structures will shade a building, they must be accurately represented in each of the models. Lighting and fixture load densities are based on either data from the building, when available, or BCA's J6 specification in 2011. It is acknowledged that the models are not calibrated to actual occupancy densities, nor to lighting and load equipment density of current buildings as this is beyond the scope of the project.
Building Descriptions
- Building X
- Building Y
- Building Z
- Estimation of Greenhouse Gas Emissions
Occupancy Profile According to BCA 2010 Default Profiles (JV Specification) Equipment Profile According to BCA 2010 Default Profiles (JV Specification). If not specified, the other input parameters for this building are the same as for building X. The simulation results of the different scenarios are converted to greenhouse gas emission equivalent (GHG-e) values with the conversion coefficients as presented in Table 8.10.
Simulation Results
- Simulation Results – Base scenario for each building
- Simulation Results – Scenario 1
- Simulation Results – Scenario 2
- Simulation Results – Scenario 3
- Simulation Results – Scenario 4
Despite the common perception that an increase in external temperatures will increase building energy consumption due to the rise in cooling energy, the forecasts here show that the total energy consumption of the three buildings will actually decrease. The simulation is performed to predict the impact of the change in the urban form due to future developments. Such an increase in the height of the surrounding buildings is found to have a minimal impact on the HVAC energy use of the three buildings or on their GHG emissions.
Summary
Therefore, the modeled increase in cooling energy may not be as significant as this study suggests. However, increasing building height may instead have more impact on the increasing demand for heating energy, as buildings would now receive less solar heat gain in the cooler periods due to shading by other buildings, while still experiencing more heat loss due to the increased glass area . If changes in building density, height and envelope materials have a significant impact on the urban microclimate, this would in turn impact energy use for heating and cooling by buildings, and consequently greenhouse gas emissions from buildings.
Building X Modelling Results
Building Y Modelling Results
Building Z Modelling Results
Summary
The presence of an urban heat island consequently has repercussions on heating and cooling energy use in buildings to maintain comfort levels for occupants. In summer, when the interior of buildings usually requires cooling, the evidence provided by data on temperatures and energy use in buildings clearly shows that occasions of higher temperatures are associated with greater electrical energy consumption during the day. CBD office buildings, a 1 oC increase in daytime temperatures, together with an urban heat island, indicates increases of 1500 MWh per year in electrical energy consumption.
