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<p>High-rate methane biofiltration (HMBF) offers a sustainable and efficient method for mitigating methane (CH₄)-rich waste gases at oil well and battery sites, serving as a viable alternative to flaring and venting. Conventionally, the performance of these systems is assessed by manually measuring CH₄ input and output, a method that, while accurate, only provides periodic snapshots. However, HMBF performance is inherently dynamic, fluctuating with environmental conditions such as ambient temperature, necessitating the use of advanced measurement techniques for continuous, long term monitoring. This study introduces a novel approach that uses temperature as a proxy for CH₄ oxidation in remote, field-deployed HMBF systems. Since CH₄ oxidation is an exothermic process, changes in the filter-bed temperature directly correlate with the rate of microbial activity. We developed a dynamic, physically based model to estimate CH₄ oxidation rates using inputs such as inlet gas flow, filter-bed temperature, and ambient air temperature. The model provides critical outputs, including daily CH₄ oxidation rates, cumulative CO₂-equivalent reductions, and real-time assessments of filter-bed moisture and porosity. The model was calibrated and validated using 420&#xa0;days of operational data from an actively aerated HMBF system installed at an oil battery site in Hanna, Alberta. The model’s accuracy was tested across a range of conditions, including high and low flow rates, varying oxygen availability, and extended operational periods. This innovative approach not only enhances the understanding of HMBF performance under real-world conditions but also provides a robust tool for optimizing methane mitigation strategies in the oil and gas sector.</p>

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Dynamic modeling of methane oxidation in high-rate biofilters: a temperature-based approach for continuous performance evaluation

  • 期刊论文

  • 发表日期：

    2026年4月2日

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  • Samadhi Gunasekera,
  • Joseph Patrick A. Hettiaratchi,
  • Seniru Ruwanpura

摘要

High-rate methane biofiltration (HMBF) offers a sustainable and efficient method for mitigating methane (CH₄)-rich waste gases at oil well and battery sites, serving as a viable alternative to flaring and venting. Conventionally, the performance of these systems is assessed by manually measuring CH₄ input and output, a method that, while accurate, only provides periodic snapshots. However, HMBF performance is inherently dynamic, fluctuating with environmental conditions such as ambient temperature, necessitating the use of advanced measurement techniques for continuous, long term monitoring. This study introduces a novel approach that uses temperature as a proxy for CH₄ oxidation in remote, field-deployed HMBF systems. Since CH₄ oxidation is an exothermic process, changes in the filter-bed temperature directly correlate with the rate of microbial activity. We developed a dynamic, physically based model to estimate CH₄ oxidation rates using inputs such as inlet gas flow, filter-bed temperature, and ambient air temperature. The model provides critical outputs, including daily CH₄ oxidation rates, cumulative CO₂-equivalent reductions, and real-time assessments of filter-bed moisture and porosity. The model was calibrated and validated using 420 days of operational data from an actively aerated HMBF system installed at an oil battery site in Hanna, Alberta. The model’s accuracy was tested across a range of conditions, including high and low flow rates, varying oxygen availability, and extended operational periods. This innovative approach not only enhances the understanding of HMBF performance under real-world conditions but also provides a robust tool for optimizing methane mitigation strategies in the oil and gas sector.