The performance of a building’s envelope has a significant influence on the energy performance and other functions of a building. As a solution for efficiency issues of building envelopes, plants have been used on rooftops, called green roofs, not only to enhance roof energy performance but also to reduce building energy consumption. Many studies have used computer simulation software, such as EnergyPlus, which is the most popular software, and computer modeling has become a predictive analysis tool for evaluating the design and decision-making for regional green building development. The main objective of this project was to examine the critical parameters influencing energy consumption when establishing roof energy efficiency technology, especially green roof systems. The results and...[ Read more ]

The performance of a building’s envelope has a significant influence on the energy performance and other functions of a building. As a solution for efficiency issues of building envelopes, plants have been used on rooftops, called green roofs, not only to enhance roof energy performance but also to reduce building energy consumption. Many studies have used computer simulation software, such as EnergyPlus, which is the most popular software, and computer modeling has become a predictive analysis tool for evaluating the design and decision-making for regional green building development. The main objective of this project was to examine the critical parameters influencing energy consumption when establishing roof energy efficiency technology, especially green roof systems. The results and observations presented here could contribute toward formulating a database of parameters and deriving the order of priority of green roof simulation parameters for practitioners in predicting whether a green roof would be beneficial.

First, the existing green roof standards and codes around the world that play a role in the roof greening development were reviewed, with a concentration on how biodiversity directly or indirectly might be affected in three regions, including Singapore, Hong Kong, and the selected typical mainland city Guangzhou with their standards and guideline developments.

Second, this study reviewed the published literature related to green roof energy performance, the analysis of parameters used in simulations, and how these parameters influence green roof energy performance. There are four parameter classifications, including parameters related to vegetation, substrate, buildings, and climate conditions. After classification, sensitivity analyses were done, and the parameters directly related to green roof systems in Hong Kong ranked.

Finally, after analyzing the important parameters, the abilities of green roofs to influence energy and indoor thermal performances were demonstrated using EnergyPlus software to simulate the top of a building at the HKUST campus. The simulated building was also placed into the other five cities with various climate conditions, including Harbin, Beijing, Shanghai, and Kunming, as representative cities in each climate zone, and the parameters altered for each green roof. Moreover, conventional and white roof models were established to compare them with green roof systems, which provided useful suggestions based on simulation results. Using EnergyPlus software, the analysis also tested some improvement opportunities offered with some key lessons from modeling in the use of these innovative techniques. In terms of energy savings, recommended settings for green roofs were suggested.

This study provided green roof system stakeholders with a better appreciation of roof energy consumption options. More importantly, the study results served as a source of reference for both policymakers as well as designers when formulating green roof systems in different climate conditions in China. In addition, the methodology used in this study could be used for evaluating energy efficiency when establishing a green roof system rooftop.