A novel lightweight CF decision-making approach for highway reconstruction and operation

Road infrastructure is a major emitter of greenhouse gases (GHGs), contributing significantly to the overall carbon emissions of many countries. Due to their importance in the life-cycle carbon footprint (CF) assessment of highway projects, highway reconstruction, rehabilitation, and operation have garnered increased attention. Existing highway CF studies have relied heavily on on-site data. They were often limited by a handful of operation or reconstruction scenarios. Most existing highway CF studies focused solely on mitigating the infrastructure CF and ignored the potential savings of highway traffic CF resulting from different traffic behaviour and technology options. A comprehensive CF saving potential comparison between the highway infrastructure and traffic for the city- or nation-wide policy decision-making is needed. Moreover, the loss of design and operation information for many existing highway projects with long operational periods necessitates a new approach to assess and manage the CF of highway reconstruction, rehabilitation, and operation. As a result, this study has proposed a new lightweight CF decision-making approach to help highway reconstruction, rehabilitation, and traffic operation management with informative stage-based highway decision-making supporting framework and digital platform that enable the comparison between highway infrastructure and traffic CF's potential savings. With the help of the developed framework and platform, the project decision-maker and government policymaker can leverage better information support and dynamically compare CF decision-making scenarios regarding different highway infrastructure and traffic options. This study contributes to knowledge in three ways: (1) evaluating and validating an informative highway CF decision-making framework for highway infrastructure and traffic assessment and management, (2) proving the applicability of using a lightweight data collection and model building method for highway infrastructure CF assessment and management practice, and (3) providing an applicable way of building a highway CF digital twins (DT) platform for visualisation, decisionmaking, and management of the highway infrastructure and traffic.