Methane Emissions from Gathering Compressor Stations in the U.S.

Using results from a nationally representative measurement campaign at 180 gathering compressor stations conducted with nine industry partners, this study estimated emissions for the U.S. gathering sector, where sector-specific emission factors have not been previously available. The study drew from a partner station population of 1705 stations-a significantly larger pool than was available for prior studies. Data indicated that whole gas emission rates from components on gathering stations were comparable to or higher than emission factors utilized by the EPA's greenhouse gas reporting program (GHGRP) but less than emission factors used for similar components on transmission compressor stations. Field data also indicated that the national population of stations likely has a higher fraction of smaller stations, operating at lower throughput per station, than the data used to develop the per-station emission factor used in EPA's greenhouse gas inventory (GHGI). This was the first national study to incorporate extensive activity data reported to the GHGRP, including 319 basin-level reports, covering 15,895 reported compressors. Combining study emission data with 2017 GHGRP activity data, the study indicated statistically lower national emissions of 1290 [1246-1342] Gg methane per year or 66% [64-69%] of current GHGI estimates, despite estimating 17% [12-22%] more stations than the 2017 GHGI (95% confidence interval). Finally, we propose a replicable method that uses GHGRP activity data to annually update GHGI gathering and boost sector emissions.

Characterizing Regional Methane Emissions from Natural Gas Liquid Unloading.

A "bottom-up" probabilistic model was developed using engineering first-principles to quantify annualized throughput normalized methane emissions (TNME) from natural gas liquid unloading activities for 18 basins in the United States in 2016. For each basin, six discrete liquid-unloading scenarios are considered, consisting of combinations of well types (conventional and unconventional) and liquid-unloading systems (nonplunger, manual plunger lift, and automatic plunger lift). Analysis reveals that methane emissions from liquids unloading are highly variable, with mean TNMEs ranging from 0.0093% to 0.38% across basins. Automatic plunger-lift systems are found to have significantly higher per-well methane emissions rates relative to manual plunger-lift or non-plunger systems and on average constitute 28% of annual methane emissions from liquids unloading over all basins despite representing only ∼0.43% of total natural gas well count. While previous work has advocated that operational malfunctions and abnormal process conditions explain the existence of super-emitters in the natural gas supply chain, this work finds that super-emitters can arise naturally due to variability in underlying component processes. Additionally, average cumulative methane emissions from liquids unloading, attributed to the natural gas supply chain, across all basins are ∼4.8 times higher than those inferred from the 2016 Greenhouse Gas Reporting Program (GHGRP). Our new model highlights the importance of technological disaggregation, uncertainty quantification, and regionalization in estimating episodic methane emissions from liquids unloading. These insights can help reconcile discrepancies between "top-down" (regional or atmospheric studies) and "bottom-up" (component or facility-level) studies.

Aerially guided leak detection and repair: A pilot field study for evaluating the potential of methane emission detection and cost-effectiveness.

Novel aerial methane (CH4) detection technologies were used in this study to identify anomalously high-emitting oil and gas (O&G) facilities and to guide ground-based "leak detection and repair" (LDAR) teams. This approach has the potential to enable a rapid and effective inspection of O&G facilities under voluntary or regulatory LDAR programs to identify and mitigate anomalously large CH4 emissions from a disproportionately small number of facilities. This is the first study of which the authors are aware to deploy, evaluate, and compare the CH4 detection volumes and cost-effectiveness of aerially guided and purely ground-based LDAR techniques. Two aerial methods, the Kairos Aerospace infrared CH4 column imaging and the Scientific Aviation in situ aircraft CH4 mole fraction measurements, were tested during a 2-week period in the Fayetteville Shale region contemporaneously with conventional ground-based LDAR. We show that aerially guided LDAR can be at least as cost-effective as ground-based LDAR, but several variable parameters were identified that strongly affect cost-effectiveness and which require field research and improvements beyond this pilot study. These parameters include (i) CH4 minimum dectectable limit of aerial technologies, (ii) emission rate size distributions of sources, (iii) remote distinction of fixable versus nonfixable CH4 sources ("leaks" vs. CH4 emissions occurring by design), and (iv) the fraction of fixable sources to total CH4 emissions. Suggestions for future study design are provided. Implications: Mitigation of methane leaks from existing oil and gas operations currently relies on on-site inspections of all applicable facilities at a prescribed frequency. This approach is labor- and cost-intensive, especially because a majority of oil and gas-related methane emissions originate from a disproportionately small number of facilities and components. We show for the first time in real-world conditions how aerial methane measurements can identify anomalously high-emitting facilities to enable a rapid, focused, and directed ground inspection of these facilities. The aerially guided approach can be more cost-effective than current practices, especially when implementing the aircraft deployment improvements discussed here.