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MacKay K, Seymour SP, Li HZ, Zavala-Araiza D, Xie D. A Comprehensive Integration and Synthesis of Methane Emissions from Canada's Oil and Gas Value Chain. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2024; 58:14203-14213. [PMID: 39089680 PMCID: PMC11325636 DOI: 10.1021/acs.est.4c03651] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/04/2024]
Abstract
Methane emissions from the global oil and gas value chain are a major contributor to climate change, and their mitigation could avoid 0.1 °C of warming by 2050. Here, we synthesize nearly a decade of research encompassing thousands of multiscale methane measurements along the oil and gas value chain (production to end use) to better constrain estimates of methane emissions from Canada's energy sector and to identify research gaps contributing to uncertainty in current estimates. We find that total value chain methane emissions are 2,600 (2,100-3,700) kt, which broadly agrees with Canada's latest official inventory that now includes atmospheric measurement data in some of their oil and gas methane estimates. Accurate understanding of emission magnitudes is critical because Canada committed to a 75% reduction of oil and gas methane emissions by 2030. We also identify and discuss information gaps in both emissions and activity data, namely, from the midstream, downstream, and end-use sectors. While they make up a smaller portion of the total inventory, accurate quantification of these emissions is still important and could point to more cost-effective mitigation solutions. This work emphasizes the need for frequent, comprehensive measurements to better constrain the climate impacts of the oil and gas sector and to validate reductions and commitments pledged by industry and governments.
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Affiliation(s)
- Katlyn MacKay
- Environmental Defense Fund, New York , New York 10010, United States
| | - Scott P Seymour
- Environmental Defense Fund, New York , New York 10010, United States
| | - Hugh Z Li
- Environmental Defense Fund, New York , New York 10010, United States
| | | | - Donglai Xie
- Environmental Defense Fund, New York , New York 10010, United States
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Yu J, Hmiel B, Lyon DR, Warren J, Cusworth DH, Duren RM, Chen Y, Murphy EC, Brandt AR. Methane Emissions from Natural Gas Gathering Pipelines in the Permian Basin. ENVIRONMENTAL SCIENCE & TECHNOLOGY LETTERS 2022; 9:969-974. [PMID: 36398313 PMCID: PMC9648336 DOI: 10.1021/acs.estlett.2c00380] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/03/2022] [Revised: 08/24/2022] [Accepted: 08/25/2022] [Indexed: 06/16/2023]
Abstract
The rapid reduction of methane emissions, especially from oil and gas (O&G) operations, is a critical part of slowing global warming. However, few studies have attempted to specifically characterize emissions from natural gas gathering pipelines, which tend to be more difficult to monitor on the ground than other forms of O&G infrastructure. In this study, we use methane emission measurements collected from four recent aerial campaigns in the Permian Basin, the most prolific O&G basin in the United States, to estimate a methane emission factor for gathering lines. From each campaign, we calculate an emission factor between 2.7 (+1.9/-1.8, 95% confidence interval) and 10.0 (+6.4/-6.2) Mg of CH4 year-1 km-1, 14-52 times higher than the U.S. Environmental Protection Agency's national estimate for gathering lines and 4-13 times higher than the highest estimate derived from a published ground-based survey of gathering lines. Using Monte Carlo techniques, we demonstrate that aerial data collection allows for a greater sample size than ground-based data collection and therefore more comprehensive identification of emission sources that comprise the heavy tail of methane emissions distributions. Our results suggest that pipeline emissions are underestimated in current inventories and highlight the importance of a large sample size when calculating basinwide pipeline emission factors.
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Affiliation(s)
- Jevan Yu
- Stanford
University, Stanford, California 94305, United States
- Environmental
Defense Fund, Austin, Texas 78701, United States
| | - Benjamin Hmiel
- Environmental
Defense Fund, Austin, Texas 78701, United States
| | - David R. Lyon
- Environmental
Defense Fund, Austin, Texas 78701, United States
| | - Jack Warren
- Environmental
Defense Fund, Austin, Texas 78701, United States
| | - Daniel H. Cusworth
- Arizona
Institutes for Resilience, University of
Arizona, Tucson, Arizona 85721, United
States
- Carbon
Mapper, Pasadena, California 91105, United States
| | - Riley M. Duren
- Arizona
Institutes for Resilience, University of
Arizona, Tucson, Arizona 85721, United
States
- Carbon
Mapper, Pasadena, California 91105, United States
| | - Yuanlei Chen
- Stanford
University, Stanford, California 94305, United States
| | - Erin C. Murphy
- Environmental
Defense Fund, Austin, Texas 78701, United States
| | - Adam R. Brandt
- Stanford
University, Stanford, California 94305, United States
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Sekhavati J, Hashemabadi SH, Soroush M. Computational methods for pipeline leakage detection and localization: A review and comparative study. J Loss Prev Process Ind 2022. [DOI: 10.1016/j.jlp.2022.104771] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
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