Report

Description

Overheating of cities is causing serious energy, environmental and health problems and it has a serious impact on the whole economic and cultural life of cities. To counterbalance the impact of high urban temperatures several mitigation technologies have been proposed, developed and implemented. Monitoring of several large-scale urban projects involving the application of mitigation technologies has demonstrated the possibility decreasing the peak ambient temperature of the precincts up to 2.5 °C.

Analysis reveals that the magnitude of the overheating depends on many parameters of which the more important are: The layout and the characteristics of the buildings and open spaces, the type of the materials used, the released anthropogenic heat, the land use, the climatic conditions, etc. Several studies have been performed to understand and evaluate the impact of some of the above parameters; however, detailed studies to investigate the impact of the precincts’ layout and characteristics on the urban overheating are not widely available.

The present study aimed to provide answers to the following research questions:

  1. What is the impact of building height, street width, aspect ratio, built area ratio, orientation and dimensions of open spaces to the distribution of the ambient and surface temperature as well as on thermal comfort conditions in open spaces?
  2. What is the exact impact of the above parameters on the energy consumption of buildings in a precinct?
  3. How is the cooling potential of the common mitigation technologies influenced by the layout and characteristics of precincts?
  4. Is it possible to decrease the amplitude of urban overheating through the proper design of buildings and precincts and what is the exact cooling potential?

To respond to the above research questions the methodology described below was followed:

  1. A total of 14 residential typologies have been used to provide a logical categorisation of residential areas that can support micro-climatic and energy consumption analyses. The typologies are suggested by the Urban Taskforce Australia, and follows the approach applied by the Local Climates Zones (LCZs), which is a standardised and widely applied scheme for analysis of urban overheating conditions within urban areas. Seven housing types were profiled for this study and for the Sydney metropolitan area (SMA) based on building height as per the building typologies defined by the Department of Planning and Environment New South Wales (NSW).
  2. Mesoscale climatic models have been used to simulate the climatic conditions in the Sydney area for the actual land use and climatic conditions, as well as for the future climate and land use in 2050. In parallel, the expected future climatic conditions in Sydney considering a full implementation of mitigation measures are simulated. Simulations have been performed for a full summer month on an hourly basis.
  3. Hourly climatic files for all the above climatic scenarios were prepared for use in energy and microscale climatic simulations.
  4. Microscale simulations to predict the distribution of the main climatic parameters, ambient temperature, wind speed, surface temperature, outdoor thermal comfort, in the 14 different precincts were carried out for representative days of the summer period using the previously defined climatic data for the scenario of 2050 under non-mitigation and full mitigation conditions. Simulations were performed for two scenarios: a) Considering that mitigation technologies, greenery, evaporation, cool materials, are implemented everywhere in the precinct, and b) no mitigation measures are used in the precinct.
  5. The results of the previously described simulations during the peak daytime temperature conditions, were thoroughly analysed and conclusions drawn regarding the distribution of the main climatic parameters and the outdoor thermal comfort, and the impact of the main parameters defined in the research questions.
  6. The results of the microscale simulations for each precinct were used to prepare detailed climatic input files to be used in energy simulation models.
  7. Detailed energy simulations were performed to identify the impact of the parameters defined in the research questions on the energy consumption of the buildings in a precinct.
  8. Conclusions were reached about the impact of the precincts’ layout and characteristics of the defined precincts.

Results

Impact on the Climate of the Precincts:

  1. To evaluate the cooling potential of each of the 14 considered precincts, a new parameter called ‘Gradient of the Temperature Decrease along the Precinct Axis’, GTD, was developed. The parameter measures the average temperature decrease along the X or the Y axis of the canyon.
  2. In precincts with mitigation the Gradient of Temperature decrease, GTD, varies between 0.01 K/m to 0.004 K/m.
  3. In precincts without mitigation, GTD varies between 0.0093 K/m to 0.0024 K/m.
  4. The maximum expected temperature difference between precincts of about 40000 m2, employing the same mitigation measures, caused by different layout and characteristics of the buildings and open spaces may be close to 0.9 °C for a reference ambient temperature of 32 °C, and a wind speed of about 2 m/sec.
  5. The maximum expected temperature difference between precincts of about 40000 m2, without any mitigation measure, is close to 1.5 °C, for a reference ambient temperature of 33 °C, and a wind speed of about 2 m/sec.
  6. The cooling potential caused only because of the layout of the precincts is decreasing when mitigation technologies are used, compared with the cooling potential of the same precinct without mitigation, because the utilisability factor is lower.
  7. Analysis of the results shown that advection is the major mechanism to transfer heat to the precincts and there is a strong relation between the flux of heat, because of the wind, and the GTD values.
  8. There is a strong correlation between the GTD of all the precincts with and without mitigation, and the corresponding average aspect ratio, (Height of buildings to Width of streets), of the precincts. The higher the aspect ratio of the precinct the lower the Cooling Capacity This is expected, as: a) the application of cool roofs in high rise buildings has a lower impact and b) wind speed in canyons of high aspect ratios is quite higher and corresponds to a much higher advection rate.
  9. The cooling contribution of the specific layout of the precincts is more important when advection to the precinct is low and decreases as advection is rising.
  10. The higher the Built Area Ratio, the lower the contribution of the mitigation techniques to the cooling rate of the precincts. This is logical as less space is allocated to install mitigation measures.
  11. Two prediction methods of sufficient accuracy are proposed to calculate the GTD of the mitigated and non-mitigated precincts. The average relative prediction error of both methods for the mitigated precincts is close to 10 %. For the non-mitigated precincts, the average prediction error of the method based on the aspect ratio is close to 17 %, while the corresponding error of the method based on the estimation of the advection rate is close to 12 %.
  12. There is a strong correlation between the ratio of the average wind speed in the precinct, V(average), and the incident wind speed in the limits of the precinct, Vinc, with the average aspect ratio of the precinct, H/W.
  13. The advection rate in the precincts depends highly on the orientation and the characteristics of its canyons. Canyons with an axis vertical or oblique to the wind direction may present a lower wind speed compared to the canyon with their axis parallel to the wind direction. This depends highly on the aspect ratio. For canyons vertical or oblique to the wind direction, a high h/w value > 0.8 signifies that the flow is under skimming regime and corresponds to a local vortex inside the canyon, and a bypass of the flowing air above the height of the buildings. For h/w values between 0.8 and 0.3, the flow is wake inference, and for lower values is isolated roughness.
  14. For all canyons of the precincts with an axis vertical or slightly oblique to the wind direction, a strong correlation of the average wind speed in the canyon, V(veraverage) and the aspect ratio, (h/w), is found.
  15. For all canyon with their axis parallel to wind direction, a strong correlation is established between the length of the canyon and the product of the entry wind speed and width of the canyon as, well as with the product of the product of the exit wind speed with the width of the canyon.

Impact on Energy:

  1. The layout and the characteristics of the precincts may affect the cooling energy consumption of a building of same orientation and same thermal and faced characteristics by up to 6 %.
  2. The layout and the characteristics of the precincts may affect the total cooling energy consumption per square meter, of all buildings in a precinct, with different orientation and façade and thermal characteristics up to 53 % when buildings are extremely well shaded, or up to 93 % when the shading coefficient is average.
  3. There is a general trend that the lower cooling energy consumption is presented in precincts with a lower aspect ratio, (H/W). This trend is stronger for the OT precincts than the CT precincts.
  4. The global cooling energy consumption in a precinct may be up to 4800 % higher than in another precinct of the similar plot. This is of course very much influenced by the total built area, orientation, building characteristics, etc.
Publication Details
Language: 
English
Peer Reviewed: 
Yes
Published year only: 
2019
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