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Title: Characterizing Regional Methane Emissions from Natural Gas Liquid Unloading

Abstract

A “bottom-up” probabilistic model was developed using engineering first-principles to quantify annualized throughput normalized methane emissions (TNME) from natural gas liquid unloading activities for 18 basins in the United States in 2016. For each basin, six discrete liquid-unloading scenarios are considered, consisting of combinations of well types (conventional and unconventional) and liquid-unloading systems (nonplunger, manual plunger lift, and automatic plunger lift). Analysis reveals that methane emissions from liquids unloading are highly variable, with mean TNMEs ranging from 0.0093% to 0.38% across basins. Automatic plunger-lift systems are found to have significantly higher per-well methane emissions rates relative to manual plunger-lift or non-plunger systems and on average constitute 28% of annual methane emissions from liquids unloading over all basins despite representing only ~0.43% of total natural gas well count. While previous work has advocated that operational malfunctions and abnormal process conditions explain the existence of super-emitters in the natural gas supply chain, this work finds that super-emitters can arise naturally due to variability in underlying component processes. Additionally, average cumulative methane emissions from liquids unloading, attributed to the natural gas supply chain, across all basins are ~4.8 times higher than those inferred from the 2016 Greenhouse Gas Reporting Program (GHGRP). Our newmore » model highlights the importance of technological disaggregation, uncertainty quantification, and regionalization in estimating episodic methane emissions from liquids unloading. These insights can help reconcile discrepancies between “top-down” (regional or atmospheric studies) and “bottom-up” (component or facility-level) studies.« less

Authors:
 [1]; ORCiD logo [1];  [1]; ORCiD logo [1];  [2];  [3];  [4];  [1]
  1. National Energy Technology Lab. (NETL), Pittsburgh, PA, (United States)
  2. National Oceanic and Atmospheric Administration (NOAA), Boulder, CO (United States). Earth System Research Lab.; Univ. of Colorado, Boulder, CO (United States). Cooperative Inst. for Research in Environmental Sciences
  3. Cheniere Energy, Inc., Houston, TX (United States)
  4. AECOM, Austin, TX (United States)
Publication Date:
Research Org.:
National Energy Technology Laboratory (NETL), Pittsburgh, PA, Morgantown, WV, and Albany, OR (United States)
Sponsoring Org.:
USDOE Office of Fossil Energy (FE)
OSTI Identifier:
1505013
Alternate Identifier(s):
OSTI ID: 1508755
Grant/Contract Number:  
FE0025912
Resource Type:
Published Article
Journal Name:
Environmental Science and Technology
Additional Journal Information:
Journal Volume: 53; Journal Issue: 8; Journal ID: ISSN 0013-936X
Publisher:
American Chemical Society (ACS)
Country of Publication:
United States
Language:
English
Subject:
03 NATURAL GAS

Citation Formats

Zaimes, George G., Littlefield, James A., Augustine, Daniel J., Cooney, Gregory, Schwietzke, Stefan, George, Fiji C., Lauderdale, Terri, and Skone, Timothy J. Characterizing Regional Methane Emissions from Natural Gas Liquid Unloading. United States: N. p., 2019. Web. doi:10.1021/acs.est.8b05546.
Zaimes, George G., Littlefield, James A., Augustine, Daniel J., Cooney, Gregory, Schwietzke, Stefan, George, Fiji C., Lauderdale, Terri, & Skone, Timothy J. Characterizing Regional Methane Emissions from Natural Gas Liquid Unloading. United States. doi:10.1021/acs.est.8b05546.
Zaimes, George G., Littlefield, James A., Augustine, Daniel J., Cooney, Gregory, Schwietzke, Stefan, George, Fiji C., Lauderdale, Terri, and Skone, Timothy J. Mon . "Characterizing Regional Methane Emissions from Natural Gas Liquid Unloading". United States. doi:10.1021/acs.est.8b05546.
@article{osti_1505013,
title = {Characterizing Regional Methane Emissions from Natural Gas Liquid Unloading},
author = {Zaimes, George G. and Littlefield, James A. and Augustine, Daniel J. and Cooney, Gregory and Schwietzke, Stefan and George, Fiji C. and Lauderdale, Terri and Skone, Timothy J.},
abstractNote = {A “bottom-up” probabilistic model was developed using engineering first-principles to quantify annualized throughput normalized methane emissions (TNME) from natural gas liquid unloading activities for 18 basins in the United States in 2016. For each basin, six discrete liquid-unloading scenarios are considered, consisting of combinations of well types (conventional and unconventional) and liquid-unloading systems (nonplunger, manual plunger lift, and automatic plunger lift). Analysis reveals that methane emissions from liquids unloading are highly variable, with mean TNMEs ranging from 0.0093% to 0.38% across basins. Automatic plunger-lift systems are found to have significantly higher per-well methane emissions rates relative to manual plunger-lift or non-plunger systems and on average constitute 28% of annual methane emissions from liquids unloading over all basins despite representing only ~0.43% of total natural gas well count. While previous work has advocated that operational malfunctions and abnormal process conditions explain the existence of super-emitters in the natural gas supply chain, this work finds that super-emitters can arise naturally due to variability in underlying component processes. Additionally, average cumulative methane emissions from liquids unloading, attributed to the natural gas supply chain, across all basins are ~4.8 times higher than those inferred from the 2016 Greenhouse Gas Reporting Program (GHGRP). Our new model highlights the importance of technological disaggregation, uncertainty quantification, and regionalization in estimating episodic methane emissions from liquids unloading. These insights can help reconcile discrepancies between “top-down” (regional or atmospheric studies) and “bottom-up” (component or facility-level) studies.},
doi = {10.1021/acs.est.8b05546},
journal = {Environmental Science and Technology},
number = 8,
volume = 53,
place = {United States},
year = {2019},
month = {3}
}

Journal Article:
Free Publicly Available Full Text
Publisher's Version of Record
DOI: 10.1021/acs.est.8b05546

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