How Accurate Is Your Carbon Footprint? Measuring the Uncertainty With Pedigree Matrix in the Design of an Oxyfuel Combustion Gas Turbine

Abstract Life Cycle Assessment (LCA) is a crucial tool for accurately analyzing the environmental impact associated with complex, energy-intensive processes and machinery, such as gas turbine technology. However, the uncertainty of the input data and process modeling used can significantly influence the results of quantified emissions impact, for example, the overall carbon footprint expressed in Kg CO2eq. This paper describes an original methodology to assess the overall uncertainty on the carbon footprint of a product/process calculated through LCA by combining the Pedigree Matrix (PM) of each process through a Monte Carlo approach. The PM associates with each process considered in the Life Cycle Inventory phase 5 different types of uncertainty (i.e., reliability and completeness of data and their temporal, geographic and technological correlation) and a numerical value (from 1 to 5) expressing the average uncertainty. The methodology was applied to a real-world scenario in the design of an oxyfuel combustion turbine. The results show that uncertainties in some of the input data can lead to significant variations in the results of more complex processes that are part of the total LCA of the product under study, suggesting approaches to extrapolate and potentially reduce the individual sources of error that are most costly.