Daniels William S, Kidd Spencer G, Yang Shuting Lydia, Stokes Shannon, Ravikumar Arvind P, Hammerling Dorit M
Department of Applied Mathematics and Statistics, Colorado School of Mines, Golden, Colorado 80401, United States.
Department of Petroleum and Geosystems Engineering, The University of Texas at Austin, Austin, Texas 78712, United States.
ACS EST Air. 2025 Mar 18;2(4):564-577. doi: 10.1021/acsestair.4c00298. eCollection 2025 Apr 11.
We compare continuous monitoring systems (CMS) from three different vendors on six operating oil and gas sites in the Appalachian Basin using several months of data. We highlight similarities and differences between the three CMS solutions when deployed in the field and compare their output to concurrent top-down aerial measurements and to site-level bottom-up inventories. Furthermore, we compare vendor-provided emission rate estimates to estimates from an open-source quantification algorithm applied to the raw CMS concentration data. This experimental setup allows us to separate the effect of the sensor platform (i.e., sensor type and arrangement) from the quantification algorithm. We find that 1) localization and quantification estimates rarely agree between the three CMS solutions on short time scales (i.e., 30 min), but temporally aggregated emission rate distributions are similar between solutions, 2) differences in emission rate distributions are generally driven by the quantification algorithm, rather than the sensor platform, 3) agreement between CMS and aerial rate estimates varies by CMS solution but is close to parity when CMS estimates are averaged across solutions, and 4) similar sites with similar bottom-up inventories do not necessarily have similar emission characteristics. These results have important implications for developing measurement-informed inventories and for incorporating CMS-inferred emission characteristics into emission mitigation efforts.
我们使用数月的数据，在阿巴拉契亚盆地的六个运营中的石油和天然气站点，对来自三家不同供应商的连续监测系统（CMS）进行了比较。我们突出了这三种CMS解决方案在实地部署时的异同，并将它们的输出与同期的自上而下的空中测量结果以及站点层面的自下而上的清单进行了比较。此外，我们将供应商提供的排放率估算值与应用于原始CMS浓度数据的开源量化算法得出的估算值进行了比较。这种实验设置使我们能够将传感器平台（即传感器类型和布置）的影响与量化算法区分开来。我们发现：1）在短时间尺度（即30分钟）内，这三种CMS解决方案的定位和量化估算值很少一致，但各解决方案之间随时间汇总的排放率分布相似；2）排放率分布的差异通常由量化算法驱动，而非传感器平台；3）CMS与空中排放率估算值之间的一致性因CMS解决方案而异，但当对各解决方案的CMS估算值进行平均时，接近均等；4）具有相似自下而上清单的相似站点不一定具有相似的排放特征。这些结果对于开发基于测量的清单以及将CMS推断的排放特征纳入减排工作具有重要意义。
