Closing the gap: Explaining persistent underestimation by US oil and natural gas production-segment methane inventories

Abstract

Methane (CH4) emissions from oil and natural gas (O&NG) systems are an important contributor to greenhouse gas emissions. In the United States (US), recent synthesis studies of field measurements of CH4 emissions at different spatial scales are ~1.5x-2x greater compared to official Environmental Protection Agency (EPA) greenhouse gas inventory (GHGI) estimates. Site-level field studies have isolated the production-segment as the dominant contributor to this divergence. Based on an updated synthesis of measurements from component-level field studies, we develop a new inventory-based model for CH4 emissions using bootstrap resampling that agrees within error with recent syntheses of site-level field studies and allows for isolation of differences between our inventory and the GHGI at the equipment-level. We find that venting and malfunction-related emissions from tanks and other equipment leaks are the largest contributors to divergence with the GHGI. To further understand this divergence, we decompose GHGI equipment-level emission factors into their underlying component-level data. This decomposition shows that GHGI inventory methods are based on measurements of emission rates that are systematically lower compared with our updated synthesis of more recent measurements. If our proposed method were adopted in the US and other jurisdictions, inventory estimates could become more accurate, helping to guide methane mitigation policy priorities.

LNG Supply Chains: A Supplier-Specific Life-Cycle Assessment for Improved Emission Accounting

“…Another sensitivity analysis is conducted to assess potential sources of under-reported emissions within the GHGRP, as identified in recent studies by Lyon et al and Rutherford et al , These analyses demonstrate how discrepancies in emission inventories and top-down studies can be reconciled in part with improved emission factors and assumptions on operations. Here, we investigate the sensitivity of the supply chain to production and G&B fugitive emission factors, emissions from tank thief hatches and other gas release points from tanks, and flaring efficiency in the Permian oil and gas production region in the U.S.…”

“…However, we recognize that there are limitations to the data and opportunities for future improvement. We address the known limitations of the GHGRP emission factors through a sensitivity analysis on modeled parameters. − The supplier-specific supply chain model is limited by the lag in data reporting from the GHGRP (data is generally published in the third or fourth quarter of the following year, i.e., 2018 data becomes available toward the end of 2019) as well as the unknown surrounding gas purchased from nonoperators (e.g., marketers). These volumes purchased from nonoperators are currently modeled using a US average intensity, but future efforts will focus on improving this understanding.…”

Comprehensive aerial survey quantifies high methane emissions from the New Mexico Permian Basin

“…The US Environmental Protection Agency (EPA) Greenhouse Gas Inventory (GHGI) estimates a national NG production loss rate of 1.5% (11,12). But the GHGI has been identified as a conservative estimate of methane emissions (11,13,14), and a recent alternative estimate of national finding an average loss rate of 2.3% NG production loss rate based on a synthesis of measurements from across the O&G supply chain (11). But note that the Permian findings are even higher than this adjusted national average.…”

Multi-scale Methane Measurements at Oil and Gas Facilities Reveal Necessary Framework for Improved Emissions Accounting

“…Empirical measurements of methane have also highlighted the limits of conventional inventory development using activity and emissions factors [19]. Analysis of recent field measurements across O&G production facilities in the US and Canada show that, on average, measured emissions are approximately 60% higher than official inventory estimates [20], [21].…”