Comparative analysis of the energy performance in green and non-green office buildings in Dar Es Salaam, Tanzania

Abstract

The rate of energy use around the world in recent years has been alarming. In Africa, and Tanzania in particular, the energy demand for office building is increasing annually as a result of urbanisation, population growth and economic growth. Reducing office buildings’ ever-escalating energy use is a critical objective requiring scholarly attention. To contribute to achieving that objective, this study compared the energy performance of 2 green and 15 non-green office buildings in Dar es Salaam, Tanzania. The buildings were sampled purposively. The buildings’ consumption patterns were studied by examining their electricity bills over a five-year period (2015–2019). The buildings’ energy consumption data and elements of their designs were analysed using multiple regression models. The study examined four building sets (green buildings, non-green buildings with maximal glazing, non-green buildings with minimal glazing and traditional office buildings). The results indicate that the traditional office buildings, which contained the most climate-responsive design elements of the building types examined, consumed less energy than green-certified office buildings. The modern office buildings with minimal and maximal glass façades consumed the most energy. The buildings with single-split HVAC systems consumed less energy than those with multi/central systems. The study concluded that building classifications and HVAC type are the most significant predictors of energy use, followed by window-to-wall ratio. As East Africa urbanises rapidly, these findings will provide architects, engineers, property managers and policymakers with research-based, real-life data that are specific to their context. Those data can help enhance the performance of green and non-green buildings during their design and operation phases. The study recommends adopting a design strategy that considers both climatic and technical factors in order to optimise building design decisions to lower buildings’ energy use.