Development of Roughness Prediction Models for Life Cycle Assessment Studies of Recycled Pavement Projects

Eugene A. Amarh*, Gerardo W. Flintsch, Joao Santos, Brian K. Diefenderfer

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

1 Citation (Scopus)
91 Downloads (Pure)


The few existing life cycle assessment studies considering pavement recycling techniques usually omit the stages of maintenance and rehabilitation (M&R) and use. The reason for this omission is the lack of information about how the pavement’s performance evolves over time and absence of methods to determine the M&R frequency and service life for completed projects. As a result, the deterioration of pavement recycling projects in the long term is not clearly understood. Few projects have available data, the majority of which are on low volume primary and secondary roads. This paper describes an approach to develop a family of roughness models for recycling projects in Colorado using functional data analysis, and individual models for selected projects in Virginia to support ongoing life cycle assessment (LCA) studies. In the case of Colorado, full depth reclamation (FDR) projects will most likely deteriorate following an average group rate of 1.4 in./mi/year, with an initial international roughness index (IRI) between 52 and 70 in./mi. For the individual roughness models developed for Virginia projects, the initial IRI values and the rate of change for the treatments analyzed were found to range between 49 and 107 in./mi and between 0.7 and 5.2 in./mi/year, respectively, depending on the recycling method and type of stabilization treatment. The results of an LCA case study show that, in addition to recycling, Virginia Department of Transportation can achieve statewide emission reduction goals if focus is placed on achieving smoother roads while measures are taken to keep the annual rates of deterioration low.
Original languageEnglish
Pages (from-to)449-463
Number of pages15
JournalTransportation research record
Issue number12
Early online date8 Aug 2021
Publication statusPublished - 1 Dec 2021


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