Decarbonising the building sector is vital for net-zero targets. In 2022, buildings produced around one-third of global energy-related CO₂ emissions—26% from operations and 7% from construction-related embodied emissions (IEA, 2023). Among which, residential buildings generated nearly 60% of the sector’s operational emissions, highlighting the importance of housing decarbonisation in climate mitigation (IEA, 2023).
Technological retrofitting, like installing heat pumps and insulation, is key for reducing energy use and CO2 emissions. Its effectiveness depends on occupant behaviours, such as heating, ventilation, and appliance use, which need behavioural interventions like feedback and education. These behaviours influence how retrofits are adopted and maintained, causing performance gaps, rebound effects, or synergies (Ekim, Mattsson and Bernardo, 2023; Massié and Belaïd, 2024). Capturing such interactions is crucial for designing effective retrofits.
Assessing housing decarbonisation potential requires detailed emissions accounting for retrofit and operational phases (Shibata, Sierra and Hagras, 2023). Retrofit involves materials like heat pumps, insulation, and ventilation, which generate embodied emissions. Post-retrofit emissions depend on energy system transitions (e.g., grid decarbonisation, and socio-economic factors including population growth and housing evolution (Mastrucci et al., 2021; van Heerden et al., 2025). A robust assessment requires a life-cycle perspective linked to future energy and socio-economic scenarios.
Two major gaps are identified. First, most studies assess technological and behavioural interventions separately or quantify their combined effects without analysing interactions with occupant behaviour. Second, existing retrofit life‑cycle assessments examine single measures under static conditions, lacking a system-level view and integration with future energy and socio-economic scenarios. Considering these scenarios is crucial because, amid global climate change and the net-zero transition, energy production and use will shift significantly, impacting housing emissions. Additionally, demographic changes like population decline will affect housing demand and occupancy, influencing the sector’s long-term decarbonisation.
This project will address these gaps by evaluating technological and behavioural interventions and their interactions with occupant behaviour using a framework integrating life-cycle assessment and future scenario modelling, applied to the UK case study. Achieving net-zero by 2050 will require about £250 billion in housing retrofits, offering transferable insights for other regions. The work will expand globally to assess broader implications.
Figure 1: Research framework integrating retrofit interventions, occupant behaviour, LCA and IAM to assess housing decarbonisation pathways.
This project is a CENTA Flagship Project.
This project is suitable for CASE funding
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This project will integrate several inter-disciplinary methods:
1) Occupant behaviour modelling will characterise occupant behaviours (e.g., heating schedules, appliance use, technology acceptability) to quantify performance gaps, rebound effects, and synergies arising from interactions with interventions.
2) Life Cycle Assessment (LCA) will quantify total CO2 impacts of interventions, including supply chains emissions from retrofit activities and operational energy use.
3) Integrated Assessment Models (IAMs) will combine behaviour-adjusted LCA results with long‑term energy system and socio‑economic scenarios to project future housing CO2 emissions.
This study will use the UK housing sector as a case study. LCA will use English Housing Survey the archetypes and operational energy demand from EnergyPlusbased housing stock models. Occupant behaviour will be calibrated using DifferenceinDifferences results from the INHABIT project (coled by Prof. Shi and Prof. Shan), providing empirical retrofit impact estimates. IAMs (e.g., GCAM, UK-TIMES, MESSAGEix-Buildings) will be selected to ensure UK-specific energy system and socioeconomic consistency.
DRs will be awarded CENTA Training Credits (CTCs) for participation in CENTA-provided and ‘free choice’ external training. One CTC can be earned per 3 hours training, and DRs must accrue 100 CTCs across the three and a half years of their PhD.
The student will be trained with subject-specific skills, research management, and engagement and impact from the supervisors (including emission accounts provided by Prof. Shan). Cross-college institutes with strong GEES (School of Geography, Earth and Environmental Sciences) links (e.g., BISCA (Birmingham Institute for Sustainability and Climate Action), School of Psychology, School of Health Sciences) will provide multidisciplinary insights on the project.
In addition to a wide range of training from CENTA3 and UoB, the student will seek internal and external opportunities to attend various training courses related to this project, including LCA, IAMs, climate modelling and environmental sustainability development.
EQUANS, a leading provider of sustainable regeneration, housing refurbishment, and repairs & maintenance services, acts as the CASE partner for this project. EQUANS will host a 3 –18 month placement, offering structured guidance and training, retrofit and sustainability programmes engagements, and professional development opportunities. They will provide co-supervision, quarterly feedback, and industry insight to ensure the research aligns with real retrofit challenges. Through this collaboration, the doctoral researcher will gain valuable transferable skills and professional experience. This collaboration is expected to deliver evidence-based solutions for net-zero housing retrofits and contribute to the UK’s transition towards a low-carbon built environment.
Year 1: Literature review and research design
Conduct a comprehensive literature review on housing retrofit-related LCA, IAM applications, and technology–behaviour interactions; Identify research gaps, refine research questions, and design the modelling framework; Collect baseline data on UK housing stock, technological and behaviour interventions, and occupant behaviour patterns.
Draft Chapter 1 (Introduction) and Chapter 2 (Literature Review) of PhD dissertation.
Year 2: Model development and data collection
Develop occupant behaviour models using statistical methods; Build and calibrate the LCA model for retrofit interventions (embodied + operational emissions); Acquire and process IAM scenario outputs (grid carbon intensity, fuel mix, population, housing stock).
Draft Chapter 3 (Methodology – Behaviour & LCA), Chapter 4 (Occupant Behaviour Analysis), and Chapter 5 (LCA Results).
Year 3 – Model Integration and scenario analysis
Integrate behaviour models, LCA, and IAM into a single assessment framework; Design and run baseline, technologyonly, behaviouronly, and combined scenarios; Conduct sensitivity and uncertainty analyses; assess policy implications.
Draft Chapter 3 (Methodology – IAM) and Chapter 6 (Integrated Scenario Results).
Year 3.5: Thesis writing
Integrate results and write up the thesis. Prepare for the viva.
Ekim, Z., Mattsson, P. and Bernardo, R. (2023) ‘Assessments of users’ interactions with energy-efficient solutions: A systematic review’, Building and Environment, 242, p. 110522. doi: 10.1016/j.buildenv.2023.110522.
van Heerden, R. et al. (2025) ‘Demand-side strategies enable rapid and deep cuts in buildings and transport emissions to 2050’, Nature Energy, 10(3), pp. 380–394. doi: 10.1038/s41560-025-01703-1.
IEA (2023) Tracking Clean Energy Progress 2023 – Analysis, IEA. Available at: https://www.iea.org/reports/tracking-clean-energy-progress-2023 (Accessed: 7 August 2025).
Massié, C. and Belaïd, F. (2024) ‘Estimating the direct rebound effect for residential electricity use in seventeen European countries: Short and long-run perspectives’, Energy Economics, 134, p. 107571. doi: 10.1016/j.eneco.2024.107571.
Mastrucci, A. et al. (2021) ‘Global scenarios of residential heating and cooling energy demand and CO2 emissions’, Climatic Change, 168(3), p. 14. doi: 10.1007/s10584-021-03229-3.
Shibata, N., Sierra, F. and Hagras, A. (2023) ‘Integration of LCA and LCCA through BIM for optimized decision-making when switching from gas to electricity services in dwellings’, Energy and Buildings, 288, p. 113000. doi: 10.1016/j.enbuild.2023.113000.
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Applications must be submitted by 23:59 GMT on Wednesday 7th January 2026.