Comparison of Advanced Detection Techniques of Methane Leaks in Industrial Gas Systems

References

[1] Lee, J. H., Kim, Y., Kim, I., Hong, S. B., & Yun, H. S. (2023). Comparative analysis of ultrasonic and traditional gas-leak detection systems in the process industries: a Monte Carlo approach. Processes, 12(1), 67.

[2] Aldhafeeri, T., Tran, M. K., Vrolyk, R., Pope, M., & Fowler, M. (2020). A review of methane gas detection sensors: Recent developments and future perspectives. Inventions, 5(3), 28.

[3] Kemp, C. E., Ravikumar, A. P., & Brandt, A. R. (2016). Comparing natural gas leakage detection technologies using an open-source “virtual gas field” simulator. Environmental science & technology, 50(8), 4546-4553.

[4] Hollenbeck, D., Zulevic, D., & Chen, Y. (2021). Advanced leak detection and quantification of methane emissions using sUAS. Drones, 5(4), 117.

[5] Kamieniak, J., Randviir, E. P., & Banks, C. E. (2015). The latest developments in the analytical sensing of methane. TrAC Trends in Analytical Chemistry, 73, 146-157.

[6] Kwaśny, M., & Bombalska, A. (2023). Optical methods of methane detection. Sensors, 23(5), 2834.

[7] Ravikumar, A. P., Wang, J., & Brandt, A. R. (2017). Are optical gas imaging technologies effective for methane leak detection?. Environmental science & technology, 51(1), 718-724.

[8] Zimmerle, Daniel, Timothy Vaughn, Clay Bell, Kristine Bennett, Parik Deshmukh, and Eben Thoma. "Detection limits of optical gas imaging for natural gas leak detection in realistic controlled conditions." Environmental science & technology 54, no. 18 (2020): 11506-11514.

[9] Meribout, Mahmoud. "Gas leak-detection and measurement systems: Prospects and future trends." IEEE Transactions on Instrumentation and Measurement 70 (2021): 1-13.

[10] Maazallahi H, Delre A, Scheutz C, Fredenslund AM, Schwietzke S, Denier van der Gon H, Röckmann T. Intercomparison of detection and quantification methods for methane emissions from the natural gas distribution network in Hamburg, Germany. Atmospheric Measurement Techniques Discussions. 2022 May 9;2022:1-29.

[11] Fasasi, S.T., Adebowale, O.J. and Nwokediegwu, Z.Q.S., 2023. Advancing methane leak detection technologies to support energy sector decarbonization. International Journal of Scientific Research in Computer Science, Engineering and Information Technology, 9(6), pp.500-511.

[12] Menon, Shyam Kumar, Adesh Kumar, and Surajit Mondal. "Advancements in hydrogen gas leakage detection sensor technologies and safety measures." Clean Energy 9.1 (2025): 263-277.

[13] Schwietzke, S., Harrison, M., Lauderdale, T., Branson, K., Conley, S., George, F.C., Jordan, D., Jersey, G.R., Zhang, C., Mairs, H.L. and Pétron, G., 2019. Aerially guided leak detection and repair: A pilot field study for evaluating the potential of methane emission detection and cost-effectiveness. Journal of the Air & Waste Management Association, 69(1), pp.71-88.

[14] Iwaszenko, S., Kalisz, P., Słota, M., & Rudzki, A. (2021). Detection of natural gas leakages using a laser-based methane sensor and UAV. Remote Sensing, 13(3), 510.

[15] Fasasi, S. T., Adebowale, O. J., Abdulsalam, A. B. D. U. L. M. A. L. I. Q., & Nwokediegwu, Z. Q. S. (2019). Benchmarking performance metrics of methane monitoring technologies in simulated environments. Iconic Research and Engineering Journals, 3(3), 193-202.

[16] Sun, S., Ma, L., & Li, Z. (2021). Methane emission estimation of oil and gas Sector: A review of measurement technologies, Data Analysis Methods and uncertainty estimation. Sustainability, 13(24), 13895.

[17] Lu, H., Xie, D., & Cheng, Y. F. (2025). Methane emissions from the oil and gas supply chain: Characteristics and mitigation. Nexus.

[18] Ravikumar, A. P., Sreedhara, S., Wang, J., Englander, J., Roda-Stuart, D., Bell, C., ... & Brandt, A. R. (2019). Single-blind inter-comparison of methane detection technologies–results from the Stanford/EDF Mobile Monitoring Challenge. Elem Sci Anth, 7, 37.

[19] Wang, J., Tchapmi, L. P., Ravikumar, A. P., McGuire, M., Bell, C. S., Zimmerle, D., ... & Brandt, A. R. (2020). Machine vision for natural gas methane emissions detection using an infrared camera. Applied Energy, 257, 113998.

[20] Brandt, A. R., Heath, G. A., & Cooley, D. (2016). Methane leaks from natural gas systems follow extreme distributions. Environmental science & technology, 50(22), 12512-12520.

[21] Ghasvari-Jahromi, H., Ekram, F., & Mokamati, S. (2024, September). Advancing Leak Detection in Natural Gas Pipelines: A Novel Approach Using Real-Time Transient Modeling for Methane Emissions Mitigation. In International Pipeline Conference (Vol. 88568, p. V003T04A029). American Society of Mechanical Engineers.

[22] Johnson, D. R., Covington, A. N., & Clark, N. N. (2015). Methane emissions from leak and loss audits of natural gas compressor stations and storage facilities. Environmental science & technology, 49(13), 8132-8138.

[23] Wainner, R. T., Frish, M. B., Green, B. D., Laderer, M. C., Allen, M. G., & Morency, J. R. (2006). High altitude aerial natural gas leak detection system. Physical Sciences Incorporated.

[24] Khandaker, S., Shaipuzaman, N., Hasan, M. M., Mohd Aspar, M. A. S., & Manap, H. (2024). A Comprehensive Review of State-of-the-art Optical Methods for Methane Gas Detection. Pertanika Journal of Science & Technology, 32(6).

[25] Cardoso-Saldaña, F. J. (2023). Tiered leak detection and repair programs at simulated oil and gas production facilities: Increasing emission reduction by targeting high-emitting sources. Environmental Science & Technology, 57(19), 7382-7390.

[26] Nisbet, E. G., Fisher, R. E., Lowry, D., France, J. L., Allen, G., Bakkaloglu, S., ... & Zazzeri, G. (2020). Methane mitigation: methods to reduce emissions, on the path to the Paris agreement. Reviews of Geophysics, 58(1), e2019RG000675.

[27] Golston, L. M., Aubut, N. F., Frish, M. B., Yang, S., Talbot, R. W., Gretencord, C., ... & Zondlo, M. A. (2018). Natural gas fugitive leak detection using an unmanned aerial vehicle: Localization and quantification of emission rate. Atmosphere, 9(9), 333.

[28] Zuo, J., Li, Z., Xu, W., Zuo, J., & Rong, Z. (2025). Automated Detection of Methane Leaks by Combining Infrared Imaging and a Gas-Faster Region-Based Convolutional Neural Network Technique. Sensors, 25(18), 5714.

[29] Ayaz, M., & Yüksel, H. (2019). Design of a new cost-efficient automation system for gas leak detection in industrial buildings. Energy and Buildings, 200, 1-10.

[30] Hendrick, M. F., Ackley, R., Sanaie-Movahed, B., Tang, X., & Phillips, N. G. (2016). Fugitive methane emissions from leak-prone natural gas distribution infrastructure in urban environments. Environmental Pollution, 213, 710-716.

[31] Aljameel, Sumayh S., Dina A. Alabbad, Dorieh Alomari, Razan Alzannan, Shatha Alismail, Aljwharah Alkhudir, Fatimah Aljubran, Elena Nikolskaya, and Atta-ur Rahman. "Oil and Gas Pipelines Leakage Detection Approaches: A Systematic Review of Literature." International Journal of Safety & Security Engineering 14, no. 3 (2024).

[32] Vrålstad, Torbjørn, Alf G. Melbye, Inge M. Carlsen, and David Llewelyn. "Comparison of leak-detection technologies for continuous monitoring of subsea-production templates." SPE Projects, Facilities & Construction 6, no. 02 (2011): 96-103.

@article{1713626,
      author = {Daniil Atamanov},
      title = {Comparison of Advanced Detection Techniques of Methane Leaks in Industrial Gas Systems},
      journal = {Iconic Research And Engineering Journals},
      year = {2026},
      volume = {9},
      number = {7},
      pages = {1257-1269},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1713626.pdf},
      abstract = {Methane leakage from industrial gas systems is an important safety and climate problem, and the detection of it should be quick and reliable under a variety of operating conditions. This article compares the advanced techniques for detecting methane leaks - ultrasonic sensors, optical gas imaging (OGI), unmanned aerial vehicles (UAV) equipped with special payloads, and laser-based sensors - based on the evidence from the approaches of virtual simulation of gas fields and reported field trials. Performance is measured against sensitivity, accuracy, range, cost and tolerance to the environment. Findings show that ultrasonic sensors are a practical and low-cost screening approach which could be limited due to noise and wind influence (Lee et al., 2023). OGI allows rapid localization of the visuals for conducting facility inspection and LDAR workflows, but the performance may be affected by adverse meteorological conditions (Ravikumar et al., 2017; Zimmerle et al., 2020). UAV-based monitoring allows coverage improvement and fewer workers exposed to risk in large assets (Hollenbeck et al., 2021), while laser-based sensing has the highest sensitivity for long-range detection (Kamieniak et al., 2015). The study concludes with the recommendations for deployment and future research.},
      keywords = {Methane leak detection; Optical gas imaging (OGI); Ultrasonic sensors; UAV monitoring; Laser-based sensing; Industrial gas systems},
      month = {January},
      doi = {https://doi.org/10.64388/IREV9I7-1713626}
  }