Developing an Activity-Based Model for City-Scale Cross-Sectoral Energy and Carbon Emissions Management

Emerging working patterns (such as home-based and flexible working) are becoming increasingly prevalent worldwide, reshaping how urban residents allocate their time and interact with the built environment. These structural shifts are changing the spatial and temporal distribution of energy demand in cities, posing new challenges and opportunities for sustainable urban energy management. In response to the global climate emergency and the transformative effects of emerging working patterns, this thesis introduces a novel activity-based urban energy modelling framework that integrates the building and transport sectors. Acknowledging the limitations of conventional models that treat these sectors in isolation, the study develops a unified approach grounded in utility-maximisation theory, capturing the spatiotemporal dynamics of residents’ activity chains. The framework comprises three sub-models: activity generation, spatial-temporal distribution, and energy demand simulation. Each subject to explicit time and budget constraints. This enables estimations of end-use energy demand across different locations and sectors, particularly in light of the behavioural shifts associated with flexible and remote working. Empirical applications in Shanghai and Manchester reveal regional disparities in the adoption of flexible working patterns and their energy implications. In Manchester, home-based working reduces both travel and building energy demand, while in Shanghai, it results in increased residential energy use and transport activity. These findings highlight the complex interdependencies between urban form, human behaviour, and energy systems. The model also reveals how changes in activity chains redistribute energy loads across building types and times of day, with important implications for peak demand management. This study develops a novel framework that captures new working influences in urban energy. By bridging behavioural dynamics with inter-sectoral energy modelling, this research provides a robust tool for policymakers to assess the systemic impacts of lifestyle shifts. The study offers actionable insights for designing integrated, context-sensitive strategies to support net-zero transitions in diverse urban environments.

Name dc:type.qualificationname

Doctor of Philosophy (PhD)

Level dc:type.qualificationlevel

Doctoral

Grantor dc:publisher.institution

University of Cambridge

Year dc:date.issued

2025

Author dc:creator

• Wang, Qiancheng

Advisor dc:contributor.advisor

• Wan, Li

• activity pattern
• building sector
• energy demand
• time use
• transport sector

Licence

• https://www.repository.cam.ac.uk/bitstreams/bc344e7a-31e7-412b-9db3-51c31b2cddea/download
• http://purl.org/NET/rdflicense/allrightsreserved

DOI dc:identifier.doi

https://doi.org/10.17863/CAM.119831

OAI identifier oai:identifier

oai:www.repository.cam.ac.uk:1810/386752