Comparative study on carbon emissions based on scenario uncertainty analysis: A case of asphalt and composite...

To improve the accuracy of carbon emission accounting results during the construction of asphalt pavement and composite pavement, and clarify the differences in their carbon emission levels during the construction stage, this study developed a comparative life cycle assessment model based on scenario uncertainty analysis. The model identifies influential inputs through sensitivity analysis and evaluates them using a Pedigree Matrix to obtain data quality scores. It quantifies the uncertainty of influential inputs by combining the transformation relationship between quality scores and distribution functions. Based on Monte Carlo simulation, uncertainties are propagated from influential inputs to random results. Meanwhile, the impact of model uncertainties caused by different transformation relationships and distribution function selections on random results is considered. Taking a highway construction project in South China, this study verifies the proposed model. Comprehensive analysis of extensive simulation results across all scenarios shows that the carbon emission level of asphalt pavement construction is relatively lower: the average global warming potential of composite pavement is approximately 1.65 times that of asphalt pavement, with a maximum global warming potential ranging from 1.84 to 2.13 times that of asphalt pavement. Additionally, the global warming potential uncertainty of composite pavement is relatively higher. This work further establishes selection criteria of transformation methods and distribution functions for diverse data quality conditions. The research findings provide a comprehensive theoretical basis for improving the quality of accounting results, and provide methodological support for pavement life cycle assessment uncertainty analysis amid data scarcity. The model proposed in this study can also be applied to compare the carbon emission levels of other pavement systems.