The decarbonization of transport infrastructure is pivotal for achieving climate neutrality and advancing Circular Economy (CE) goals. Conventional asphalt production, heavily reliant on energy-intensive methods and virgin materials, contributes significantly to greenhouse gas emissions. Integrating alternative materials and low-emission energy sources could offer a viable pathway to minimizing environmental impacts while preserving pavement performance and optimizing Life Cycle Costs (LCC). This study developed a multi-objective optimization model that combines Monte Carlo simulation with Pareto front analysis to identify optimal asphalt mixtures by jointly evaluating LCC, Global Warming Potential (GWP), and product quality. The model incorporated various parameters including mix design, Reclaimed Asphalt Pavement (RAP) content, bitumen, fuel types, heating energy, transport distance, and other influencing factors. The results reveal substantial variability in environmental and economic performance, with GWP ranging from 9.17 to 97.72 kg CO 2 -eq per ton and LCC between 2.75 and 13.67 €/ton, primarily driven by the type and amount of fuel consumed, with green hydrogen playing a particularly notable role despite its higher cost. Pareto-optimal solutions achieved average reductions of 35.7% in GWP and 11.7% in LCC, respectively. Analysis of Pareto-optimal solutions demonstrates that achieving low GWP does not inherently require high costs or reduced quality, nor does cost minimization necessarily lead to increased emissions or compromised performance. Overall, this research establishes a practical framework for simultaneously balancing economic, environmental, and technical criteria in asphalt production, thereby enabling more informed and sustainable decision-making in real-world applications.
Shokri et al. (2026) studied this question.