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UK building thermal performance from industrial and governmental perspectives

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  • Ling-Chin, J.
  • Taylor, W.
  • Davidson, P.
  • Reay, D.
  • Nazi, W.I.
  • Tassou, S.
  • Roskilly, A.P.

Abstract

Current policies have implied that improving thermal performance of the built environment would be included in a strategy to reduce the greenhouse gas emissions in the UK and meet the national targets of the Climate Change Act by 2050. However, the perceptions of the industrial stakeholders in this matter have not, to date, been clear. This study aimed to uncover stakeholder perspectives on thermal performance of the built environment and investigate whether their perspectives aligned well with the national policies. Focusing on attributes of the built environment, technology and innovation, barriers and reflections on reality, technical feedback was gathered from experienced industrial stakeholders via a one-day workshop and emails. The analysis showed that despite being familiar with the national policies, the perspectives of the industrial stakeholders did not fully align with the national policies in most aspects. However, the industry had no objection to employing low carbon technology alternatives in the future. The study concluded that consultation with industry should be carried out continuously to assist in the formation of future national policies to significantly improve the thermal performance of the built environment. Future research should be extended to comparing the stakeholder viewpoints and national policies from environmental and economic perspectives on a European/global scale.

Suggested Citation

  • Ling-Chin, J. & Taylor, W. & Davidson, P. & Reay, D. & Nazi, W.I. & Tassou, S. & Roskilly, A.P., 2019. "UK building thermal performance from industrial and governmental perspectives," Applied Energy, Elsevier, vol. 237(C), pages 270-282.
    • Handle: RePEc:eee:appene:v:237:y:2019:i:c:p:270-282
    DOI: 10.1016/j.apenergy.2018.12.077
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    2. Seyedzadeh, Saleh & Pour Rahimian, Farzad & Oliver, Stephen & Rodriguez, Sergio & Glesk, Ivan, 2020. "Machine learning modelling for predicting non-domestic buildings energy performance: A model to support deep energy retrofit decision-making," Applied Energy, Elsevier, vol. 279(C).

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