Estimating Methane Emission Durations Using Continuous Monitoring Systems

We propose a method for estimating methane emission durations on oil and gas sites, referred to as the Probabilistic Duration Model (PDM), that uses concentration data from continuous monitoring systems (CMS). The PDM probabilistically addresses a key limitation of CMS: nondetect times, or the times when wind blows emitted methane away from the CMS sensors (resulting in no detections). Output from the PDM can be used to bound the duration of emissions detected by survey-based technologies, such as plane or satellites, that have limited ability to characterize durations due to the typically low temporal frequency (e.g., quarterly) at which they observe a given source. Linear regression indicates that the PDM has a bias of -4.9% (R<sup>2</sup> = 0.80) when evaluated on blinded controlled releases at the Methane Emissions Technology Evaluation Center (METEC), with 86.8% of estimates within a factor of 2× error from the true duration. We apply the PDM to a typical production site in the Appalachian Basin and use it to bound the duration of survey-based measurements. We find that failing to account for CMS nondetect times results in underestimated emission durations of up to a factor of 65× (6400%) on this site.

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Publication Details

Journal
Environmental Science & Technology Letters
Published
2024-10-28
DOI
https://doi.org/10.1021/acs.estlett.4c00687
Citations
7
Primary Topic
Atmospheric and Environmental Gas Dynamics
Type
article
Field-Weighted Citation Impact
1.98

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article

Estimating Methane Emission Durations Using Continuous Monitoring Systems

William Daniels, Meng Jia, Dorit Hammerling
7 citations
Environmental Science & Technology Letters
Atmospheric and Environmental Gas Dynamics
1.98
article

Estimating Methane Emission Durations Using Continuous Monitoring Systems

William Daniels, Meng Jia, Dorit Hammerling
article en
7 citations

Abstract

We propose a method for estimating methane emission durations on oil and gas sites, referred to as the Probabilistic Duration Model (PDM), that uses concentration data from continuous monitoring systems (CMS). The PDM probabilistically addresses a key limitation of CMS: nondetect times, or the times when wind blows emitted methane away from the CMS sensors (resulting in no detections). Output from the PDM can be used to bound the duration of emissions detected by survey-based technologies, such as plane or satellites, that have limited ability to characterize durations due to the typically low temporal frequency (e.g., quarterly) at which they observe a given source. Linear regression indicates that the PDM has a bias of -4.9% (R<sup>2</sup> = 0.80) when evaluated on blinded controlled releases at the Methane Emissions Technology Evaluation Center (METEC), with 86.8% of estimates within a factor of 2× error from the true duration. We apply the PDM to a typical production site in the Appalachian Basin and use it to bound the duration of survey-based measurements. We find that failing to account for CMS nondetect times results in underestimated emission durations of up to a factor of 65× (6400%) on this site.

Environmental Science & Technology LettersVol. 11(11)
Colorado School of Mines (US), The University of Texas at Austin (US)
U.S. Department of Energy
Affordable and clean energy
Openalex Percentile: Top 14%
Atmospheric and Environmental Gas Dynamics
1.98
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Estimating Methane Emission Durations Using Continuous Monitoring Systems — William Daniels, Meng Jia, et al. · Environmental Science & Technology Letters (2024) | TGRS Research Map | TGRS