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Building energy efficiency labeling programme in Singapore

Author

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  • Lee, Siew Eang
  • Rajagopalan, Priyadarsini

Abstract

The use of electricity in buildings constitutes around 16% of Singapore's energy demand. In view of the fact that Singapore is an urban city with no rural base, which depends heavily on air-conditioning to cool its buildings all year round, the survival as a nation depends on its ability to excel economically. To incorporate energy efficiency measures is one of the key missions to ensure that the economy is sustainable. The recently launched building energy efficiency labelling programme is such an initiative. Buildings whose energy performance are among the nation's top 25% and maintain a healthy and productive indoor environment as well as uphold a minimum performance for different systems can qualify to attain the Energy Smart Office Label. Detailed methodologies of the labelling process as well as the performance standards are elaborated. The main strengths of this system namely a rigorous benchmarking database and an independent audit conducted by a private accredited Energy Service Company (ESCO) are highlighted. A few buildings were awarded the Energy Smart Office Label during the launching of the programme conducted in December 2005. The labeling of other types of buildings like hotels, schools, hospitals, etc. is ongoing.

Suggested Citation

  • Lee, Siew Eang & Rajagopalan, Priyadarsini, 2008. "Building energy efficiency labeling programme in Singapore," Energy Policy, Elsevier, vol. 36(10), pages 3982-3992, October.
    • Handle: RePEc:eee:enepol:v:36:y:2008:i:10:p:3982-3992
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    Citations

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    Cited by:

    1. Donghyun Rim & Stefano Schiavon & William W Nazaroff, 2015. "Energy and Cost Associated with Ventilating Office Buildings in a Tropical Climate," PLOS ONE, Public Library of Science, vol. 10(3), pages 1-14, March.
    2. Ageliki Konstantoglou & Dimitris Folinas & Thomas Fotiadis, 2020. "Exploring the Multi-Function Nature of Packaging in the Food Industry," Logistics, MDPI, vol. 4(3), pages 1-14, September.
    3. Agarwal, Sumit & Satyanarain, Rengarajan & Sing, Tien Foo & Vollmer, Derek, 2016. "Effects of construction activities on residential electricity consumption: Evidence from Singapore's public housing estates," Energy Economics, Elsevier, vol. 55(C), pages 101-111.
    4. Cagno, Enrico & Franzò, Simone & Storoni, Elena & Trianni, Andrea, 2022. "A characterisation framework of energy services offered by energy service companies," Applied Energy, Elsevier, vol. 324(C).
    5. Nilsa Duarte da Silva Lima & Irenilza de Alencar Nääs & João Gilberto Mendes dos Reis & Raquel Baracat Tosi Rodrigues da Silva, 2020. "Classifying the Level of Energy-Environmental Efficiency Rating of Brazilian Ethanol," Energies, MDPI, vol. 13(8), pages 1-16, April.
    6. Yan, Chengchu & Wang, Shengwei & Xiao, Fu & Gao, Dian-ce, 2015. "A multi-level energy performance diagnosis method for energy information poor buildings," Energy, Elsevier, vol. 83(C), pages 189-203.
    7. Mardiana, A. & Riffat, S.B., 2013. "Review on physical and performance parameters of heat recovery systems for building applications," Renewable and Sustainable Energy Reviews, Elsevier, vol. 28(C), pages 174-190.
    8. Chan, Edwin H.W. & Qian, Queena K. & Lam, Patrick T.I., 2009. "The market for green building in developed Asian cities--the perspectives of building designers," Energy Policy, Elsevier, vol. 37(8), pages 3061-3070, August.
    9. Arjunan, Pandarasamy & Poolla, Kameshwar & Miller, Clayton, 2020. "EnergyStar++: Towards more accurate and explanatory building energy benchmarking," Applied Energy, Elsevier, vol. 276(C).
    10. Chung, William, 2011. "Review of building energy-use performance benchmarking methodologies," Applied Energy, Elsevier, vol. 88(5), pages 1470-1479, May.
    11. Melo, A.P. & Cóstola, D. & Lamberts, R. & Hensen, J.L.M., 2014. "Development of surrogate models using artificial neural network for building shell energy labelling," Energy Policy, Elsevier, vol. 69(C), pages 457-466.
    12. Zhang, Bin & Lu, Danting & He, Yan & Chiu, Yung-ho, 2018. "The efficiencies of resource-saving and environment: A case study based on Chinese cities," Energy, Elsevier, vol. 150(C), pages 493-507.

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