Comparison of the Gaussian plume and puff atmospheric dispersion models on oil and gas facilities

Jia, Meng; Daniels, William; Hammerling, Dorit

doi:10.26434/chemrxiv-2023-hc95q

Cited by 3 publications

(2 citation statements)

References 21 publications

(24 reference statements)

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“…We use the Gaussian puff atmospheric dispersion model to forward simulate. 13 Create information mask. Next we identify periods during which we expect the wind to blow methane toward the sensors (periods of "information") and between the sensors (periods of "no information").…”

Section: Methodsmentioning

confidence: 99%

Estimating methane emission durations using continuous monitoring systems

Daniels,

Jia,

Hammerling

2024

Preprint

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A small number of large emissions contribute a significant portion of total emitted methane from the oil and gas sector, making them a critical pathway toward emission reduction. These large emissions are often detected by snapshot measurements from aerial or satellite platforms, which have limited ability to characterize emission duration due to the relatively low frequency at which they observe a given source. Duration estimates are necessary for computing the total methane emitted by a given release and will be required for all emissions >100 kg/hr under proposed updates to the EPA's Greenhouse Gas Reporting Program (GHGRP). Continuous monitoring systems (CMS) are a monitoring technology that measure methane concentrations in near-real time and hence can complement snapshot measurements by bounding the duration of detected emissions. However, CMS will not record concentration enhancements during an emission if wind blows emitted methane away from the sensors. We propose a method for estimating emission durations using CMS that accounts for these non-detect times. The method has an average error of 6.3% when evaluated on controlled releases, with 88.5% of estimates within a factor of 2x error from the true duration (i.e., percent error within [-50%, 100%]). We apply the method to a typical production site in the Appalachian Basin and use it to bound the duration of snapshot measurements. We find that failing to account for CMS non-detect times on this site results in underestimated emission durations of up to a factor of 71x (7,000%).

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Section: Methodsmentioning

confidence: 99%

Estimating methane emission durations using continuous monitoring systems

Daniels,

Jia,

Hammerling

2024

Preprint

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“…At a high level, the framework simulates methane concentrations from all potential sources on a given site using the Gaussian puff atmospheric dispersion model. 44 The simulation predictions are then pattern matched against the actual CMS concentration observations to determine the most likely emission source and rate. Quantification uncertainty is provided by resampling the available data many times, pattern matching on each sample, and then taking the 5 th and 95 th percentiles of the resulting sample-specific rate estimates.…”

Section: Continuous Monitoring Systemsmentioning

confidence: 99%

Toward Multiscale Measurement-Informed Methane Inventories: Reconciling Bottom-Up Site-Level Inventories with Top-Down Measurements Using Continuous Monitoring Systems

Daniels

Wang

Ravikumar

et al. 2023

Environ. Sci. Technol.

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Government policies and corporate strategies aimed at reducing methane emissions from the oil and gas sector increasingly rely on measurement-informed, site-level emission inventories, as conventional bottom-up inventories poorly capture temporal variability and the heavy-tailed nature of methane emissions. This work is based on an 11-month methane measurement campaign at oil and gas production sites. We find that operator-level top-down methane measurements are lower during the end-of-project phase than during the baseline phase. However, gaps persist between end-of-project topdown measurements and bottom-up site-level inventories, which we reconcile with high-frequency data from continuous monitoring systems (CMS). Specifically, we use CMS to (i) validate specific snapshot measurements and determine how they relate to the temporal emission profile of a given site and (ii) create a measurement-informed, site-level inventory that can be validated with top-down measurements to update conventional bottom-up inventories. This work presents a real-world demonstration of how to reconcile CMS rate estimates and top-down snapshot measurements jointly with bottom-up inventories at the site level. More broadly, it demonstrates the importance of multiscale measurements when creating measurement-informed, site-level emission inventories, which is a critical aspect of recent regulatory requirements in the Inflation Reduction Act, voluntary methane initiatives such as the Oil and Gas Methane Partnership 2.0, and corporate strategies.

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Detection, localization, and quantification of single-source methane emissions on oil and gas production sites using point-in-space continuous monitoring systems

Daniels,

Jia,

Hammerling

2024

Elem Sci Anth

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We propose a modular framework for methane emission detection, localization, and quantification on oil and gas production sites that uses concentration and wind data from point-in-space continuous monitoring systems. The framework leverages a gradient-based spike detection algorithm to estimate emission start and end times (event detection) and pattern matches simulated and observed concentrations to estimate emission source location (localization) and rate (quantification). The framework was evaluated on a month of non-blinded, single-source controlled releases ranging from 0.50 to 8.25 h in duration and 0.18 to 6.39 kg/h in size. All controlled releases are detected and 82% are localized correctly; 5.5% of estimated events are false positives. For emissions ≤1 kg/h, the framework underestimates the emission rate by −3.9% on average, with 90% of rate estimates falling within a percent difference of [−74.9%, 195.2%] from the true rate. For emissions >1 kg/h, the framework overestimates the emission rate by 4.3% on average, with 90% of rate estimates falling within a percent difference of [−49.3%, 78.8%] from the true rate. Potential uses for the proposed framework include near real time alerting for rapid emission mitigation and emission quantification for use in measurement-informed inventories on production sites.

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Comparison of the Gaussian plume and puff atmospheric dispersion models on oil and gas facilities

Cited by 3 publications

References 21 publications

Estimating methane emission durations using continuous monitoring systems

Estimating methane emission durations using continuous monitoring systems

Toward Multiscale Measurement-Informed Methane Inventories: Reconciling Bottom-Up Site-Level Inventories with Top-Down Measurements Using Continuous Monitoring Systems

Detection, localization, and quantification of single-source methane emissions on oil and gas production sites using point-in-space continuous monitoring systems

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