Field Testing of a Mixed Potential IoT Sensor Platform for Methane Quantification

Halley, Sleight; Ramaiyan, Kannan; Smith, James; Ian, Robert; Agi, Kamil; Garzon, Fernando; Tsui, Lok-kun

doi:10.1149/2754-2726/ad23df

Title: Field Testing of a Mixed Potential IoT Sensor Platform for Methane Quantification

Journal Article · 09 February 2024 · ECS Sensors Plus

DOI: https://doi.org/10.1149/2754-2726/ad23df · OSTI ID:2294129

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University of New Mexico, Albuquerque, NM (United States)
Sensorcomm Technologies, Inc., Albuquerque, NM (United States)

Emissions of CH₄ from natural gas infrastructure must urgently be addressed to mitigate its effect on global climate. With hundreds of thousands of miles of pipeline in the US used to transport natural gas, current methods of surveying for leaks are inadequate. Mixed potential sensors are a low cost, field deployable technology for remote and continuous monitoring of natural gas infrastructure. We demonstrate for the first time a field trial of a mixed potential sensor device coupled with machine learning and internet-of-things platform at Colorado State University's Methane Emissions Technology Evaluation Center (METEC). Emissions were detected from a simulated buried underground pipeline source. Sensor data was acquired and transmitted from the field test site to a remote cloud server. Quantification of concentration as a function of vertical distance is consistent with previously reported transport modelling efforts and experimental surveys of methane emissions by more sophisticated CH₄ analyzers.

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Research Organization:: Univ. of New Mexico, Albuquerque, NM (United States)

Sponsoring Organization:: USDOE Office of Fossil Energy (FE), Oil & Natural Gas; USDOE

Grant/Contract Number:: FE0031864

OSTI ID:: 2294129

Alternate ID(s):: OSTI ID: 2283249; OSTI ID: 2298924

Journal Information:: ECS Sensors Plus, Vol. 3, Issue 1; ISSN 2754-2726

Publisher:: IOP ScienceCopyright Statement

Country of Publication:: United States

Language:: English

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