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Research Grants Council (RGC) General Research Fund (GRF)

Implications of Optimising Prefabrication for the Life Cycle Carbon Emissions of High-Rise Residential Buildings in Hong Kong


Buildings in Hong Kong consume 90% of electricity and contribute 60% of carbon emissions. Due to the scarce developable land in Hong Kong, high-rise residential buildings are almost the norm. The prefabrication approach has been integrated into the building design and construction of public housing in Hong Kong. Prefabrication will help not only reduce the carbon footprint of materials and products, but improve the efficiency of construction processes and quality of constructed facilities which should lead to substantial carbon reductions over the life cycle of the building. However, prefabrication is not yet a recognised life cycle stage, and there is no consistent method of estimating life cycle carbon emissions from prefabricated buildings. Previous research has also overlooked the indirect effects of prefabrication use, which may also play a significant role in reducing carbon emissions. This project aims to examine the implications of prefabrication use for building life cycle carbon emissions and develop solutions for achieving maximum life cycle carbon emission reduction in high-rise public residential buildings in Hong Kong through optimal such use. 


  1. Teng, Y. & Pan, W. (2020). Estimating and minimizing embodied carbon of prefabricated high-rise residential buildings considering parameter, scenario and model uncertainties. Building and Environment, 106951.

  2. Teng, Y. & Pan, W. (2019). Systematic embodied carbon assessment and reduction of prefabricated high-rise public residential buildings in Hong Kong. Journal of Cleaner Production, 238, 117791.

  3. Pan, W., Li, K. & Teng, Y. (2018). Rethinking the System Boundaries of Life Cycle Carbon Assessment of Buildings. Renewable and Sustainable Energy Reviews, 90, July 2018, 379-390.

  4. Pan, W., Li, K. & Teng, Y. (2018). Life-cycle carbon assessment of prefabricated buildings: challenges and solutions. Institution of Civil Engineers-Engineering Sustainability (Vol. 172, No. 1, pp. 3-8).

  5. Teng, Y., Li, K., Pan, W. & Ng, T. (2018). Reducing Buildings’ Life Cycle Carbon Emissions through Prefabrication: Evidence from and Gaps in Empirical Studies. Building and Environment, 132 (15 March), 125-136.

  6. Teng, Y. & Pan, W., (2018). A framework for BIM-enabled embodied carbon assessment of prefabricated buildings. International Conference on Construction Futures (ICCF) 2018, Wolverhampton, UK, 19-20 December 2018.

  7. Wang, J., Yu, C. & Pan, W. (2018). Life cycle energy of high-rise office buildings in Hong Kong. Energy and Buildings, 167, 152-164.

  8. Pan, W., Li, K.J. & Teng, Y. (2017) Life Cycle Carbon Assessment of Prefabricated Buildings: Challenges, Fundamentals and Solutions. Proceedings of RISUD Annual International Symposium 2017 – New Frontiers in Urban Development, Hong Kong, 24-25 August 2017 (abstract only).

  9. Teng, Y., Pan, W., & Li, K. (2018). Comparing life cycle assessment databases for estimating carbon emissions of prefabricated buildings. Construction Research Congress (CRC) 2018, New Orleans, US, 2-5 April 2018. ASCE.

  10. Pan, W., Teng, Y., Li, K., & Yu, C. (2018). Implications of prefabrication for the life cycle carbon emissions of high-rise buildings in high-density urban environment. Construction Research Congress (CRC) 2018, New Orleans, US, 2-5 April 2018. ASCE.

  11. Teng, Y. & Pan, W. (2017) Building Life Cycle Carbon Emissions: A Review. Proceedings of the World Sustainable Built Environment Conference 2017 Hong Kong, 5-7 June 2017, ISBN 978-988-77943-0-1, pp.1095-1101.



This project is led and coordinated by Professor Wei Pan of Department of Civil Engineering of The University of Hong Kong (HKU), with project team members from HKU, HKPolyU and The Pennsylvania State University, and supporters from a wide range of government and industry organizations.  


This project is funded by the Hong Kong Research Grants Council (RGC) under the General Research Fund (GRF) (Project Number: 17207115).

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