Peer-Reviewed LNG Lifecycle Assessment Released

Cheniere’s Sabine Pass LNG liquefaction plant.
Source: Cheniere

Cheniere Energy, Inc. announced the publication of an updated life cycle assessment (LCA) study for greenhouse gas (GHG) emissions intensities of the company's liquefied natural gas (LNG). This peer-reviewed study includes a novel gas-pathing algorithm that further improves the modeling of GHG emissions across Cheniere’s supply chain, utilizing actual operational data. The study also leverages the company’s multi-year Quantification, Monitoring, Reporting and Verification (QMRV) program by integrating measurement data from the company’s facilities and collaborations with natural gas producers, midstream providers, shippers and experts at leading academic institutions. The enhanced study has been published in the American Chemical Society’s Sustainable Chemistry & Engineering Journal, and builds upon Cheniere’s first LCA study, published in 2021.

The updated study deploys an algorithm that models natural gas pathways throughout Cheniere’s supply chain in 2022, from the natural gas production basin, through the transmission network, to the company’s Sabine Pass and Corpus Christi liquefaction facilities in the Gulf Coast region, utilizing data on gas purchases, transportation capacity and gas flows. This analysis enhances the understanding of supply chain emissions and improves the quality of GHG emissions intensity estimates for Cheniere’s LNG.

The study models cases with conventional emissions inventory inputs and measurement data. It finds in all cases that the 2022 GHG emissions intensity of Cheniere’s delivered LNG is lower than those presented in the U.S. Department of Energy’s National Energy Technology Laboratory (NETL) 2019 study. By incorporating emissions measurement data from across the supply chain into the LCA, the study finds the emissions intensities of Cheniere’s LNG, when used in importing countries for power generation, are 20-28% lower than the NETL study. The study also finds that integration of measurement data into LCAs is critical to accurately characterize the differences in GHG emissions from natural gas supply chains.

The updated study is co-authored by individuals from the University of Texas at Austin’s Energy Emissions Modeling and Data Lab, Queen Mary University of London’s School of Engineering and Materials Science, Colorado School of Mines’ Payne Institute for Public Policy, Rystad Energy, KeyLogic Systems and Cheniere.