Comparison of truck fuel consumption measurements with results of existing models and implications for road pavement LCA

Perrotta, Federico; Parry, Tony; Neves, Lu�s C.; Buckland, Thomas; Benbow, Emma; Viner, Helen

Abstract

Life Cycle Assessment (LCA) is increasingly used to evaluate the impact of all lifecycle phases of road pavements on the environment. From the late ‘90s, this technique has continuously evolved and improved, however, there are still limitations and uncertainties in the framework. In this regard, Santero et al (2011) showed that gaps still exist in the road pavement LCA methodology. More recently, Trupia et al (2016) highlighted how existing models of the impact of the road pavement condition on vehicle rolling resistance and hence, fuel consumption, can lead to very different results. This study presents a comparison between real measurements of truck fuel consumption from fleet manager’s databases, and results of existing pavement models, MIRAVEC, a model recently developed within an ERA-NET ROAD action, funded by the 6th framework programme of the EU, and HDM-4, one of the most widely used models for estimating vehicle operating costs in road asset management. The paper shows how far results of the considered models can be from reality and opens a discussion of the implications of these differences on pavement LCA and strategic decisions of managers of the road infrastructure.

Citation

Perrotta, F., Parry, T., Neves, L. C., Buckland, T., Benbow, E., & Viner, H. (2018). Comparison of truck fuel consumption measurements with results of existing models and implications for road pavement LCA.

• Conference Name: The Sixth International Symposium on Life-Cycle Civil Engineering (IALCCE 2018)
• Start Date: Oct 28, 2018
• End Date: Oct 31, 2018
• Acceptance Date: Apr 15, 2018
• Publication Date: Oct 28, 2018
• Deposit Date: Apr 26, 2018
• Publicly Available Date: Oct 28, 2018
• Peer Reviewed: Peer Reviewed
• Keywords: Fuel Consumption, MIRAVEC, HDM-4, Big Data, LCA
• Public URL: https://nottingham-repository.worktribe.com/output/950669