Daniels William S, Jia Meng, Hammerling Dorit M
Department of Applied Mathematics and Statistics, Colorado School of Mines, Golden, Colorado 80401, United States.
Energy Emissions Modeling and Data Lab, The University of Texas at Austin, Austin, Texas 78712, United States.
Environ Sci Technol Lett. 2024 Oct 28;11(11):1187-1192. doi: 10.1021/acs.estlett.4c00687. eCollection 2024 Nov 12.
We propose a method for estimating methane emission durations on oil and gas sites, referred to as the Probabilistic Duration Model (PDM), that uses concentration data from continuous monitoring systems (CMS). The PDM probabilistically addresses a key limitation of CMS: nondetect times, or the times when wind blows emitted methane away from the CMS sensors (resulting in no detections). Output from the PDM can be used to bound the duration of emissions detected by survey-based technologies, such as plane or satellites, that have limited ability to characterize durations due to the typically low temporal frequency (e.g., quarterly) at which they observe a given source. Linear regression indicates that the PDM has a bias of -4.9% (R = 0.80) when evaluated on blinded controlled releases at the Methane Emissions Technology Evaluation Center (METEC), with 86.8% of estimates within a factor of 2× error from the true duration. We apply the PDM to a typical production site in the Appalachian Basin and use it to bound the duration of survey-based measurements. We find that failing to account for CMS nondetect times results in underestimated emission durations of up to a factor of 65× (6400%) on this site.
我们提出了一种估算油气田甲烷排放持续时间的方法，称为概率持续时间模型（PDM），该方法使用来自连续监测系统（CMS）的浓度数据。PDM概率性地解决了CMS的一个关键限制：未检测到的时间，即风将排放的甲烷吹离CMS传感器（导致未检测到）的时间。PDM的输出可用于界定基于调查的技术（如飞机或卫星）检测到的排放持续时间，这些技术由于观测给定源的时间频率通常较低（例如每季度一次），在表征持续时间方面能力有限。线性回归表明，在甲烷排放技术评估中心（METEC）对盲法控制释放进行评估时，PDM的偏差为-4.9%（R = 0.80），86.8%的估计值与真实持续时间的误差在2倍以内。我们将PDM应用于阿巴拉契亚盆地的一个典型生产场地，并使用它来界定基于调查的测量的持续时间。我们发现，在该场地，若不考虑CMS的未检测到时间，会导致排放持续时间被低估高达65倍（6400%）。
