Residential Comfort and Energy Efficiency in a Csb Mediterranean Climate: An Adaptive Comfort Study

Indoor thermal comfort safeguards occupant health and wellbeing and is a driver of energy consumption in buildings and greenhouse gas emissions. This paper assesses the indoor thermal conditions in a naturally ventilated middle-class residence in the Mediterranean climate of Cape Town. Data logged in two separate rooms was imputed into Ladybug, a building environmental design software, to execute a full-year adaptive comfort simulation for each room. It was found that indoor thermal comfort can be maintained by passive, psychological and behaviourial adaptive measures only without the need for artificial space conditioning. The upper indoor adaptive comfort limit for Cape Town was found to be 29°C. Indoor temperatures rarely exceeded this upper limit. Therefore, overheating is not a problem in the naturally ventilated residence. The lower adaptive comfort limit for Cape Town was found to be 19°C. In both rooms, a significant number of hours had temperatures below this threshold. The northwest-facing room was found to be excessively cold for 45% of the year. The southeast-facing room was found to be excessively cold for 75% of the year. At 55 percent, the hours of the year for which the logged indoor operative temperatures are within the bounds of comfort in the northwest-orientated room were found to be more than double those in southeast-orientated at 25 percent. Orientation has a significant impact on thermal comfort. In a sensitivity analysis, the above results proved to be robust for other cities in Csb Mediterranean regions in the southern and northern hemispheres. The above results signify that in Cape Town and similar Mediterranean climates, policies should drive practice to use orientation, indoor heat preservation and passive heating to improve comfort, safeguard health and save energy for both new and existing housing stock. Further research in Cape Town and other Csb climates is needed using larger sample sizes to generate more evidence, increase generalisability, and advance Energy Modelling for Policy Support (EMoPS).