Publication details
Journal: Journal of Cleaner Production, vol. 574, 148943, 1–14, August 1st 2026
Doi: doi.org/10.1016/j.jclepro.2026.148943
Arkiv: hdl.handle.net/11250/5539480
Archive: nva.sikt.no/registration/019fcc683c8c-44b35ba9-5411-43f0-8577-248031347633
Summary:
This study combines established methods – parametric LCA, probabilistic pavement lifetime modelling, traffic-volume characterization, and Monte Carlo simulation – into a service-based decision-support framework for asphalt pavement assessment. The framework evaluates environmental impacts not only per unit mass, but also in relation to pavement service life and traffic exposure, expressed as impact/(yr·AADT). Results indicate that binder type, asphalt plant efficiency, and transport distances are dominant contributors to environmental impacts. Incorporating probabilistic lifetimes and traffic loads reshapes environmental rankings, revealing that longer lifetimes do not always equate to lower burdens. These findings provide data-driven insights for reducing the environmental impacts of road construction and maintenance.