Catalytic combustion for reduction of fugitive methane emissions from natural gas compressor stations

Author(s):  
R LITTO ◽  
R HAYES ◽  
B LIU
2014 ◽  
Vol 49 (1) ◽  
pp. 641-648 ◽  
Author(s):  
David T. Allen ◽  
David W. Sullivan ◽  
Daniel Zavala-Araiza ◽  
Adam P. Pacsi ◽  
Matthew Harrison ◽  
...  

1999 ◽  
Vol 47 (1-4) ◽  
pp. 115-121 ◽  
Author(s):  
D. Klvana ◽  
J. Kirchnerová ◽  
J. Chaouki ◽  
J. Delval ◽  
W. Yaı̈ci

2018 ◽  
Vol 52 (17) ◽  
pp. 10205-10213 ◽  
Author(s):  
Marc L. Fischer ◽  
Wanyu R. Chan ◽  
Woody Delp ◽  
Seongeun Jeong ◽  
Vi Rapp ◽  
...  

Elem Sci Anth ◽  
2018 ◽  
Vol 6 ◽  
Author(s):  
Tara I. Yacovitch ◽  
Bruno Neininger ◽  
Scott C. Herndon ◽  
Hugo Denier van der Gon ◽  
Sander Jonkers ◽  
...  

The Groningen natural gas field in the Netherlands – one of Europe’s major gas fields – deploys a “production cluster” infrastructure with extraction, some processing and storage in a single facility. This region is also the site of intensive agriculture and cattle operations. We present results from a multi-scale measurement campaign of methane emissions, including ground and airborne-based estimates. Results are compared with inventory at both the facility and regional level. Investigation of production cluster emissions in the Groningen gas field shows that production volume alone is not a good indicator of whether, and how much, a site is emitting methane. Sites that are nominally shut down may still be emitting, and vice-versa. As a result, the inventory emission factors applied to these sites (i.e. weighted by production) do a poor job of reproducing individual site emissions. Additional facility-level case studies are presented, including a plume at 150 ± 50 kg CH4 hr–1 with an unidentified off-shore emission source, a natural gas storage facility and landfills. Methane emissions in a study region covering 6000 km2 and including the majority of the Groningen field are dominated by biogenic sources (e.g. agriculture, wetlands, cattle). Total methane emissions (8 ± 2 Mg hr–1) are lower than inventory predictions (14 Mg hr–1) but the proportion of fossil fuel sources is higher than indicated by the inventory. Apportionment of methane emissions between thermogenic and biogenic source types used ethane/methane ratios in aircraft flasks and ground-based source characterization. We find that emissions from the oil and gas sector account for 20% of regional methane, with 95% confidence limits of (0%, 51%). The experimental uncertainties bound the inventory apportionment of 1.9%, though the central estimate of 20% exceeds this result by nearly 10 times. This study’s uncertainties demonstrate the need for additional research focusing on emissions apportionment, inventory refinement and offshore platforms.


Atmosphere ◽  
2020 ◽  
Vol 11 (7) ◽  
pp. 716 ◽  
Author(s):  
Hugh Z. Li ◽  
Mumbi Mundia-Howe ◽  
Matthew D. Reeder ◽  
Natalie J. Pekney

The United States Environmental Protection Agency Greenhouse Gas Inventory only recently updated the emission factors of natural gas gathering pipelines in April 2019 from the previous estimates based on a 1990s study of distribution pipelines. Additional measurements are needed from different basins for more accurate assessments of methane emissions from natural gas midstream industries and hence the overall climate implications of natural gas as the interim major energy source for the next decade. We conducted an unmanned aerial vehicle (UAV) survey and a ground-based vehicle sampling campaign targeting gathering pipeline systems in the Utica Shale from March to April in 2019. Out of 73 km of pipeline systems surveyed, we found no leaks on pipelines and two leaks on an accessory block valve with leak rates of 3.8 ± 0.4 and 7.6 ± 0.8 mg/s. The low leak frequency phenomenon was also observed in the only existing gathering pipeline study in Fayetteville Shale. The UAV sampling system facilitated ease of access, broadened the availability of pipelines for leak detection, and was estimated to detect methane leaks down to 0.07 g/s using Gaussian dispersion modeling. For future UAV surveys adopting similar instrument setup and dispersion models, we recommend arranging controlled release experiments first to understand the system’s detection limit and choosing sampling days with steady and low wind speeds (2 m/s).


Sign in / Sign up

Export Citation Format

Share Document