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March 14, 2026Building Services Engineering Research and Technology0 citationsOpen Access

The inclusion of the urban heat island effect in design weather for net-zero buildings

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GLG.J. LevermoreUniversity of ManchesterJPJB ParkinsonUniversity of Manchester

Key Points

  • This analysis aims to evaluate how the urban heat island effect affects temperature estimates used in building design for net-zero buildings.
  • Compared weather data from Manchester city center with CIBSE Design Summer Year type 3 data.
  • Analyzed the discrepancies in night and winter temperature estimates.
  • Developed a simple algorithm to incorporate urban heat island data.
  • Found that existing DSY3 data underestimates city center night temperatures.
  • Discovered overestimation of winter minima temperatures due to lack of UHII data.
  • The new algorithm provides a more accurate representation of temperatures for urban building design.

Abstract

Dry bulb air temperatures are increasing especially in the UK. On top of this there is the urban heat island intensity (UHII), the temperature difference between rural and hotter urban temperatures. This is important as most new and existing buildings are in urban areas subject to the urban heat island (UHI)., In this paper is an analysis of weather data in Manchester city centre is compared to the CIBSE Design Summer Year type 3 (DSY 3) weather data. The latter, based on weather data from the Meteorological Office at a non-urban contains little if any UHII data. The DSY3 is based on a very warm year but the lack of the UHII data severely underestimates city centre night time temperatures and overestimates the winter minima temperatures. This underestimates the heating effect for net-zero design for urban buildings. A simple algorithm, which has been derived from Manchester and London data, is shown to give a useful method of adding in the UHII. Practical application For the weather data, including the urban heat island effect, for the design of buildings and plant.

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Cite This Study

Levermore et al. (2026) studied this question.

synapsesocial.com/papers/69b4fc6ab39f7826a300d3fehttps://doi.org/10.1177/01436244261422097
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