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<p>Addressing methane emissions from the oil and gas supply chain has emerged as a key near-term mitigation target. The past decade of research has improved our understanding of methane emissions, with a primary focus on quantifying emissions without describing their underlying causal mechanisms. Here, we integrate source-specific methane emissions measurements from multiple large-area aerial surveys with source-tracked cause analyses to identify and analyze causal mechanisms that underlie observed emission patterns. Overall, 53% of all observed emissions can be attributed to specific causal categories, with the rest comprising normal operational emissions. While abnormal tank emissions are the most common cause, unloading events exhibit the highest average emission rate. Importantly, we find that large release events are not driven by fundamentally different causal mechanisms than those of small emitters, indicating that escalation due to specific operational conditions, rather than fundamentally distinct causes, drives high-magnitude emissions. In addition, we observe statistically significant temporal and inter-operator variability in the prevalence of different causal categories, reinforcing the need for adaptive, operator-specific mitigation strategies. These findings support a shift in methane mitigation from generalized leak detection with one-size-fits-all solutions toward risk-targeted, process-informed mitigation.</p>

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Cause-informed framework for risk-targeted methane emission mitigation in oil and gas operations

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年5月4日

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  • Abdulmuiz A. Adekomi,
  • Shuting Lydia Yang,
  • Shannon Stokes,
  • Arvind P. Ravikumar

摘要

Addressing methane emissions from the oil and gas supply chain has emerged as a key near-term mitigation target. The past decade of research has improved our understanding of methane emissions, with a primary focus on quantifying emissions without describing their underlying causal mechanisms. Here, we integrate source-specific methane emissions measurements from multiple large-area aerial surveys with source-tracked cause analyses to identify and analyze causal mechanisms that underlie observed emission patterns. Overall, 53% of all observed emissions can be attributed to specific causal categories, with the rest comprising normal operational emissions. While abnormal tank emissions are the most common cause, unloading events exhibit the highest average emission rate. Importantly, we find that large release events are not driven by fundamentally different causal mechanisms than those of small emitters, indicating that escalation due to specific operational conditions, rather than fundamentally distinct causes, drives high-magnitude emissions. In addition, we observe statistically significant temporal and inter-operator variability in the prevalence of different causal categories, reinforcing the need for adaptive, operator-specific mitigation strategies. These findings support a shift in methane mitigation from generalized leak detection with one-size-fits-all solutions toward risk-targeted, process-informed mitigation.