Journal
JOURNAL OF CLEANER PRODUCTION
Volume 254, Issue -, Pages -Publisher
ELSEVIER SCI LTD
DOI: 10.1016/j.jclepro.2020.120046
Keywords
Life-cycle assessment; Life-cycle cost analysis; Pavement management; Sustainable development; Probabilistic analysis; Managerial flexibilities
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Sustainable development requires decision-making systems based on sustainability criteria and over-passing just economic and financial criteria. Integration of life-cycle cost analysis (LCCA) and life-cycle assessment (LCA) to select pavement alternative is a solution to address economic and environmental issues simultaneously. While most of current methods related to sustainable design of pavements consider environmental parameters as economic factors i.e. cost, this paper takes the two criteria of carbon emissions and energy consumption into account. Moreover the presented method considers the embedded managerial flexibilities which are available due to existing uncertainties in pavement project valuation procedure. Agency costs, user costs, carbon emissions, and energy consumption are considered as the main criteria, and Monte Carlo simulation (MCS) technique is used with a recursive procedure for analyzing flexibility in each time step of pavement life-cycle. For making the best decision in each time step and the best overall alternative, technique for order of preference by similarity to ideal solution (TOPSIS) is used, and the best alternatives are reported. The model is applied in a highway project in Iran to demonstrate its capabilities to analyze the sustainability of different asphalt and concrete alternatives for pavement projects. Various alternatives of the two pavement types are compared and it is clarified that the best asphalt alternative has lower life-cycle costs but more carbon emissions and much more energy consumption. Selection of concrete pavement instead of asphalt pavement in last decade in Iran, will approximately 35% increase related costs but it will result in about 2,000,000 tons of carbon emissions reduction and 700,000 GJ reduction in energy consumption annually. (C) 2020 Elsevier Ltd. All rights reserved.
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