SUP&R DSS: A sustainability-based decision support system for road pavements

Santos, J.; Bressi, S.; Cerezo, V.; Lo Presti, D.

Abstract

Road pavement community members are increasingly becoming aware of the need to incorporating the principles of sustainable development into the sector. Policies are also going in this direction and as a consequence in the recent years researchers and practitioners are coming up with new materials, technologies and practices designed to reduce the negative impacts of their activities in the surroundings. Within this framework the road pavements sector is witnessing a paradigm shift towards the development of pavement technologies incorporating high-content of recycled materials, as well as best practices to decrease the overall carbon footprint. These are all promising solutions that to the most can sound as sustainable practices. However the whole road pavement community is still investigating methodologies and tools to define what actually sustainable means and thereby performing a sustainable decision-making. It is within this context that the need of a sustainability-based decision support system (DSS) that could help road pavement engineers at the design stage was identified and is here presented. The Sustainable Pavements & Railways DSS (SUP&R DSS) relies on a multi-criteria decision analysis (MCDA) method to rank the sustainability of alternatives. It applies life cycle-based approaches to quantify the values of a set of indicators purposely and methodologically selected to capture the cause-effect link between the general concepts of the three wellbeing dimensions of sustainability, i.e., environmental, economic and social, and the infrastructure construction and maintenance practice. Furthermore, the system allows selecting different weighting for the indicators but offers also a default set of values derived from a survey conducted with over 50 stakeholders in Europe and beyond. Together with the development, structure and features of the SUP&R DSS, this paper present its applicability by means of a case study aiming at identifying the most sustainable asphalt mixture for wearing courses. Several promising options for flexible road pavements were selected, ranging from low to hot temperature asphalt. The results show that a foamed warm mix asphalt mixture with a reclaimed asphalt pavement content of 50% is the most sustainable among the competing alternatives. Furthermore, a sensitivity analysis conducted to investigate the influence of the indicators weights, the parameters of the MCDA method and the long-term performance of the alternative asphalt mixtures on the stability of the ranking showed that its first position in the ranking remained unaffected.

Citation

Santos, J., Bressi, S., Cerezo, V., & Lo Presti, D. (2019). SUP&R DSS: A sustainability-based decision support system for road pavements. Journal of Cleaner Production, 206, 524-540. doi:10.1016/j.jclepro.2018.08.308

• Journal Article Type: Article
• Acceptance Date: Aug 29, 2018
• Online Publication Date: Oct 1, 2018
• Publication Date: Jan 1, 2019
• Deposit Date: Nov 23, 2018
• Journal: Journal of Cleaner Production
• Print ISSN: 0959-6526
• Electronic ISSN: 1879-1786
• Publisher: Elsevier
• Peer Reviewed: Peer Reviewed
• Volume: 206
• Pages: 524-540
• DOI: https://doi.org/10.1016/j.jclepro.2018.08.308
• Keywords: Life cycle thinking; Multi-criteria decision analysis; Sustainability assessment; Sustainable design; Sustainable engineering; Sustainable pavements; Artificial intelligence; Asphalt mixtures; Carbon footprint; Decision making; Decision support systems; E
• Public URL: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85054805154&doi=10.1016%2fj.jclepro.2018.08.308&partnerID=40&md5=f5ef93161123190f1524753cc84a441f
• Publisher URL: https://www.sciencedirect.com/science/article/pii/S0959652618326696?via%3Dihub