A national-scale dataset for neighbourhood-level urban building energy modelling for England and Wales

Buildings are significant contributors to global greenhouse gas emissions, accounting for 26% of global energy sector emissions in 2022. Meeting net-zero goals requires a rapid reduction in building emissions, both directly from the buildings and indirectly from the production of electricity and heat used in buildings. National energy planning for net zero demands both detailed and comprehensive building energy consumption data. However, geo-located building-level energy data is rarely available in Europe, with analysis typically relying on anonymised, simulated or low-resolution data. To address this problem, we introduce a dataset of Neighbourhood Energy, Buildings, and Urban Landscapes (NEBULA) for modelling domestic energy consumption for small neighbourhoods (5-150 households). NEBULA integrates data on building characteristics, climate, postcode area, housing density, environment, and socio-demographics, comprising 613,290 samples across England and Wales. It is designed to support evidence-based policymaking across housing, environment, and energy justice domains through integrated spatial-demographic analysis.

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Publication Details

Journal
Scientific Data
Published
2026-06-26
DOI
https://doi.org/10.1038/s41597-026-07621-5
Primary Topic
Building Energy and Comfort Optimization
Type
article
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article

A national-scale dataset for neighbourhood-level urban building energy modelling for England and Wales

Ronita Bardhan, Jonathan Cullen, Grace Beaney Colverd
Scientific Data
Building Energy and Comfort Optimization
article

A national-scale dataset for neighbourhood-level urban building energy modelling for England and Wales

Ronita Bardhan, Jonathan Cullen, Grace Beaney Colverd
article en

Abstract

Buildings are significant contributors to global greenhouse gas emissions, accounting for 26% of global energy sector emissions in 2022. Meeting net-zero goals requires a rapid reduction in building emissions, both directly from the buildings and indirectly from the production of electricity and heat used in buildings. National energy planning for net zero demands both detailed and comprehensive building energy consumption data. However, geo-located building-level energy data is rarely available in Europe, with analysis typically relying on anonymised, simulated or low-resolution data. To address this problem, we introduce a dataset of Neighbourhood Energy, Buildings, and Urban Landscapes (NEBULA) for modelling domestic energy consumption for small neighbourhoods (5-150 households). NEBULA integrates data on building characteristics, climate, postcode area, housing density, environment, and socio-demographics, comprising 613,290 samples across England and Wales. It is designed to support evidence-based policymaking across housing, environment, and energy justice domains through integrated spatial-demographic analysis.

Scientific Data
University of Cambridge (GB)
Affordable and clean energy
Openalex Percentile: Top 11%
Building Energy and Comfort Optimization
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A national-scale dataset for neighbourhood-level urban building energy modelling for England and Wales — Ronita Bardhan, Jonathan Cullen, et al. · Scientific Data (2026) | TGRS Research Map | TGRS