Global trade in liquefied natural gas (LNG) is growing significantly, as is interest in the life-cycle greenhouse gas (GHG) emissions associated with LNG. Most assessments of lifecycle GHG emissions from LNG have employed national or regional average emission estimates; however, there is significant variability in emissions across different suppliers and across the natural gas supply chain. This work describes a framework for compiling supplier-specific GHG emission data for LNG, from the producing well to regasification at the destination port. A case study is presented for Cheniere Energy's Sabine Pass Liquefaction (SPL) LNG supply chain from production in the United States and delivered to China. GHG emission intensities are estimated to be 30−43% lower than other analyses employing national or regional average emission profiles. The segments driving these differences are gas production and gathering, transmission, and ocean transport. Extending the boundaries of this analysis to the power plant illustrates the effect of fuel switching from coal to natural gas; the effect of fuel switching in China is a 47−57% reduction in GHG emission intensity, cradle through power generation. This work highlights the important role customized life-cycle assessments can play to improve GHG emission estimates and differentiate supply chains to inform business and policy decisions related to the transition to a low carbon future.

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Government policies and corporate strategies aimed at reducing methane emissions from the oil and gas sector increasingly rely on measurement-informed, site-level emission inventories, as conventional bottom-up inventories poorly capture temporal variability and the heavy-tailed nature of methane emissions. This work is based on an 11-month methane measurement campaign at oil and gas production sites. We find that operator-level top-down methane measurements are lower during the end-of-project phase than during the baseline phase. However, gaps persist between end-of-project topdown measurements and bottom-up site-level inventories, which we reconcile with high-frequency data from continuous monitoring systems (CMS). Specifically, we use CMS to (i) validate specific snapshot measurements and determine how they relate to the temporal emission profile of a given site and (ii) create a measurement-informed, site-level inventory that can be validated with top-down measurements to update conventional bottom-up inventories. This work presents a real-world demonstration of how to reconcile CMS rate estimates and top-down snapshot measurements jointly with bottom-up inventories at the site level. More broadly, it demonstrates the importance of multiscale measurements when creating measurement-informed, site-level emission inventories, which is a critical aspect of recent regulatory requirements in the Inflation Reduction Act, voluntary methane initiatives such as the Oil and Gas Methane Partnership 2.0, and corporate strategies.

Government policies and corporate strategies aimed at reducing methane emissions from the oil and gas sector increasingly rely on measurement-informed emissions inventories, as conventional bottom-up inventories poorly capture temporal variability and the heavy-tailed nature of methane emissions. This work is based on an 11-month methane measurement campaign at oil and gas production sites. We find that basin- and operator-level top-down measurements show lower methane emissions during end-of-project than during baseline 9-months earlier. However, gaps persist between end-of-project top-down measurements and bottom-up inventories, which we reconcile with high-frequency data from continuous monitoring systems (CMS). Specifically, we use CMS to (i) assess the validity of snapshot measurements and determine how they relate to the temporal emissions profile of a given site and (ii) create a near-real time, measurement-informed inventory that can be cross-checked with top-down measurements to update conventional bottom-up inventories. This work presents a real-world demonstration of how CMS can be used to reconcile top-down snapshot measurements with bottom-up inventories at the site-level. More broadly, it demonstrates the importance of multi-scale measurements when creating measurement-informed emissions inventories, which is a critical aspect of recent regulatory requirements in the Inflation Reduction Act, voluntary methane initiatives such as OGMP 2.0, and corporate strategies.