Develop a hybrid life cycle assessment model to evaluate transport infrastructure projects
Not specified
May 31, 2026
United Kingdom
individual
About This Opportunity
This PhD research opportunity at the University of Leeds focuses on developing a hybrid Life Cycle Assessment (LCA) model to evaluate transport infrastructure projects. The project aims to investigate the environmental effects of major transport projects from changes to infrastructure and demand. A key aspect is expanding traditional LCA boundaries to include travel time analysis, integrate cost-benefit analysis, and cross transport modes with demand prediction. The research will address the limitation that travel time savings, one of the most important benefits of improved highway networks, is often structurally excluded from LCA. The project will explore how to evaluate future savings in travel time projected over a project's lifetime, as well as delay costs associated with construction and maintenance. Due to the complexity of estimating travel time, alternative measures of valuation and network effects will be considered. The research will obtain data from literature and specific locations to make informed assumptions for a range of infrastructure types and operation efficiencies. Through case studies, the project will demonstrate how assumptions can be validated despite uncertainties and data constraints, developing a LCA model that aims to optimize resource use and minimize emissions. The research addresses the recognized problem of burden shifting in the infrastructure sector, which has been explored by very few studies. This PhD position is based at the Institute for Transport Studies and is supervised by Professor Richard Batley and Dr Yue Huang.
Who Can Apply
- Region
- United Kingdom
- Project in
- United Kingdom
- Applicants
- individual
- Priority for
- women_in_stem, racial_minorities, lgbtq, disabled
Application Details
Stages
- 1 single_stage
Required documents
External Application
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- Award Amount
- Not specified
- Application Deadline
-
May 31, 2026 at 23:59 UTCDue in 88 days
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