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Estimating Methane Emission Durations Using Continuous Monitoring Systems.

William S Daniels1, Meng Jia1, Dorit M Hammerling1,2

  • 1Department of Applied Mathematics and Statistics, Colorado School of Mines, Golden, Colorado 80401, United States.

Environmental Science & Technology Letters
|November 18, 2024
PubMed
Summary
This summary is machine-generated.

Estimating methane emission durations from oil and gas sites is improved with the Probabilistic Duration Model (PDM). This method accounts for sensor nondetect times, significantly reducing underestimation errors in methane emission duration calculations.

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Area of Science:

  • Environmental Science and Engineering
  • Atmospheric Chemistry and Physics
  • Oil and Gas Operations

Background:

  • Continuous monitoring systems (CMS) for methane emissions face limitations due to nondetect times, where wind direction prevents sensor detection.
  • Survey-based technologies (e.g., aerial, satellite) have low temporal resolution, hindering accurate methane emission duration characterization.
  • Accurate methane emission duration is crucial for environmental impact assessment and regulatory compliance in the oil and gas industry.

Purpose of the Study:

  • To develop and validate a Probabilistic Duration Model (PDM) for estimating methane emission durations using CMS data.
  • To address the challenge of nondetect times in methane emission monitoring.
  • To provide a method for bounding emission durations detected by survey-based technologies.

Main Methods:

  • The Probabilistic Duration Model (PDM) probabilistically infers emission durations from CMS concentration data, specifically handling nondetect periods.
  • Model validation involved controlled methane releases at the Methane Emissions Technology Evaluation Center (METEC) using blinded data.
  • Application of the PDM to a production site in the Appalachian Basin to bound survey-based measurements.

Main Results:

  • The PDM demonstrated a low bias of -4.9% (R² = 0.80) in estimating methane emission durations during controlled releases.
  • 86.8% of PDM estimates were within a factor of 2× error of the true emission duration.
  • Analysis of a typical production site revealed that ignoring nondetect times can lead to underestimations of emission durations by up to 65× (6400%).

Conclusions:

  • The Probabilistic Duration Model (PDM) offers a robust method for accurately estimating methane emission durations from oil and gas sites.
  • Accounting for nondetect times is critical to avoid significant underestimation of methane emission durations, particularly when using survey-based data.
  • The PDM enhances the utility of CMS data for improving the accuracy of methane emission inventories and environmental monitoring.