A stochastic LCA model for estimating greenhouse gas emissions from federal highway construction projects in Brazil

Abstract

In Brazil, the National Department of Transport Infrastructure (DNIT), responsible for the country's federal highways, lacks tools to assess and mitigate greenhouse gas (GHG) emissions from its projects, which can be addressed through the Life Cycle Assessment (LCA) methodology. Additionally, the scarcity of environmental data on key road materials, such as Portland cement, leads to using foreign databases in LCA studies conducted in Brazil, creating uncertainties in the results. The general objective of this research is to use national standards, LCA methodology, and uncertainty analysis techniques to evaluate the GHG emissions of a DNIT highway project with rigid concrete pavement. The research compares the use of environmental data from local Portland cement with its equivalent produced in the United States of America (USA) and Europe (EUR), using a calculation model developed in the study. The model covers the phases of material production, transport, and construction, presenting probabilistic results influenced by the quality of environmental data. The probabilistic analysis showed that using Brazilian cement led to the lowest mean global emissions and uncertainties among the results of the three scenarios. Environmental data from foreign types of cement resulted in increases of 7.38 % (EUR) and 12.93 % (USA) in the mean global emissions of the full project. However, the probabilistic approach to scenarios using European and American cement revealed that the qualitative parameters of their environmental data could lead to equivalent global emissions results, depending on the probability range considered in the analysis. The sensitivity analysis revealed that Portland cement plays a critical role in the full project results and individually in most of its disciplines, but this criticality can be altered depending on the qualitative properties of the environmental data. The disciplines of pavement (new and restored) and earthworks account for approximately 90 % of the project's global emissions in all scenarios. In conclusion, the research proposes a new approach to estimating GHG emissions in Brazilian federal highway projects, evaluating how variations in the quality of environmental data for a key road material affect the results of the LCA model. Finally, considerations are presented regarding improving and expanding the scope of the calculation model developed in this study, allowing for a more comprehensive and accurate analysis of the environmental impacts associated with the Brazilian federal road network.