The rapid and unsustainable urbanization process causes a serious existing thermal environmental problem that aggravates climatic change and generates a higher temperature in urban area than in rural area. Based on literature review, this is the first research that uses field measurement methodology to investigate the urban heat island (UHI) effect in Hangzhou and Ningbo cities of Zhejiang Province. This study aims to investigate reciprocal interaction of UHI effect with urban building energy based on the air temperature and relative humidity measurement in research area.
There are three main factors including vegetation cover, urban building configuration and surface material properties, and human activities, contributing to the UHI development. Through using ENVI-met simulation, the study has investigated how the West Lake and the Xixi Wetland ecological areas in the city act as passive thermal comfort systems in improving the outdoor built environment and mitigating UHI effect. However, according to the observation, the UHI effect in Hangzhou is still more intense than that in Ningbo. The monthly average UHII values in Hangzhou ranged between 1℃ and 4℃, whilst the highest monthly average UHII in Ningbo is only as high as 1.5℃.
Additionally, the study has evaluated that the UHI effect is most pronounce in winter days, because there is serious air pollution, high concentration of Particulate Matter (PM) and low wind speed in winter days in China. The result has also proved that the night time UHI effect is significantly more intense than the day time UHI effect. It has been validated in the study that UHI effect can be mitigated by three effective strategies, such as the application of cool materials on urban surfaces, modifying urban geometry to improve wind flow and expanding green space in urban areas.
Owing to the hourly air temperature and relative humidity collected from strategically selected sites around the city, modified TMY weather dataset has been established. The research employed a case study of China Telecom Business Office Building in Hangzhou to evaluate the impact of UHI on urban building energy consumption. It implies that there is about 20% cooling demand underestimated in the hot months and about 25% heating demand overestimated in the cold months for the office building located in the urban city of Hangzhou, if the building is designed based on currently available weather dataset without considering UHI effect.
Based on the application of artificial neural network (ANN) and genetic programming (GP) techniques, the research has provided algorithms to link factors such as “Distance from City Centre”, “Surrounding Albedo”, “Land Use of the Area (residential, commercial, industrial, recreational etc.)”, “Sky View Factor” to predict the UHI intensity for any site compared to a reference site.
|Date of Award
|8 Oct 2015
- Univerisity of Nottingham
|Jo Darkwa (Supervisor) & David Chow (Supervisor)