Removing Shadows from Consequential LCA through a Time-Dependent Modeling Approach: Policy-Making in the Road Pavement Sector

Lack of dynamic accounting in consequential life cycle assessment (CLCA) can keep policy-makers from having an accurate analysis of emission flows over time. In this study, we propose a dynamic CLCA framework to assess the environmental consequences of pavements. Dynamic changes in the demand vector and technosphere matrices were computed using relevant time horizons of affected supply technologies and incorporating time-dependent parameters. A Monte Carlo simulation was then conducted to propagate the variability, model uncertainty, and parameter uncertainty sources of LCI to the damage results. The results show that simplifying pavement CLCA framework through neglecting real-time changes results in notable diversions in the damage results. The environmental benefits of substituting asphalt with concrete are underestimated by 7, 17, and 77% for climate change, human health and resources categories, respectively. A divergence of 114% was also observed in ecosystem quality when using the static framework. Moreover, the lack of accounting for a temporal profile for GHG emissions using static characterization factors leads to a divergence of the GWP benefits of substituting asphalt with concrete of 473 t CO_2eq (105%). The uncertainty results show 41–71% contribution of the variance in the damage categories is caused by the variability sources and is primarily attributed to monthly temperature accounting and service life.