Probabilistic, Measurement-Informed Greenhouse Gas Emissions from Global Liquefied Natural Gas Supply Chains Reveal Wide Country-Level Variation

29 July 2025, Version 1
This content is an early or alternative research output and has not been peer-reviewed by Cambridge University Press at the time of posting.

Abstract

Growth in liquefied natural gas (LNG) demand has been accompanied by debates about its greenhouse gas (GHG) emissions impact. Studies have shown that activity-based inventory accounting methods in the oil and gas sector significantly underestimates methane emissions. As a result, target-based policies and voluntary initiatives are moving towards adopting direct measurements to assess the GHG emissions intensity (EI) of LNG supply chains. Yet, most supply chain assessments of LNG do not incorporate measurement data. In this work, we develop a probabilistic, geospatial, and measurement informed life cycle assessment model to estimate the GHG EI of global LNG supply chains covering over 90% of LNG trade. We find a ~5x range in supply chain GHG EI from 8.6 g CO2e/MJ in Qatar to over 39 g CO2e/MJ in Algeria. Overall, our work suggests supply chain-weighted GHG EI of global LNG trade is underestimated by up to 31% compared to prior estimates that did not incorporate measurements. Probabilistic models of GHG EI of LNG exhibit a heavy tailed distribution, revealing the importance of low likelihood but high emitting supply chains. Incorporating direct measurements in supply chain assessments is necessary to avoid underestimation from activity-based inventories and increase confidence in target-based policies to address methane.

Keywords

LNG
Satellite
Measurement-Informed
Super-emitter
Supply Chain
MRV
Methane

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