Developing Accurate MethaneSAT Models
In the quest to understand and combat methane emissions, two powerful tools have emerged as crucial: atmospheric transport models and ground-based measurements. These methods, when combined, provide a comprehensive approach to accurately quantify methane emissions from various sources.
Atmospheric transport models rely on meteorological data and the principles of gas dispersion to simulate how methane moves and diffuses in the atmosphere after emissions. This information helps infer emission rates from observed methane concentrations sampled downwind of sources. Ground-based measurements, on the other hand, supply the real-time, local methane concentration data that are essential for these models and help validate them.
One example of this symbiotic relationship can be seen in mobile laboratory platforms, equipped with trace gas analyzers and GPS, that traverse downwind plumes of emission sources. By integrating these data with atmospheric dispersion models such as inverse Gaussian models, researchers can estimate methane emission rates from specific facilities or regions with reasonable accuracy, despite challenges from atmospheric variability.
Ground-based sensing systems, like laser spectrometers or in-vivo methane sensors, also offer reliable and precise local methane concentration measurements. These fine-scale measurements reduce uncertainties caused by environmental or animal movement factors and improve the temporal fidelity of emissions quantification.
Satellite-based measurements, such as those from the GHGSat constellation, also play a role. They detect methane column densities at high spatial resolutions and can identify emission plumes from industrial sites. However, they are limited by cloud cover and daytime-only observations. By combining these with ground-based data and atmospheric transport models, a more comprehensive and precise methane emissions accounting can be achieved.
In New Zealand, this combined approach is proving to be effective. The country, home to one of the two founding stations of the Total Carbon Column Observing Network (TCCON), has seen initial data analysis showing the satellite's observations over local agricultural targets aligning well with modelling and ground-based measurements. The MethaneSAT satellite captured 97 measurements over a range of agricultural areas worldwide, including 13 over New Zealand.
Professor David Noone, the Buckley-Glavish Professor of Climate Physics at the University of Auckland, is involved in explaining how atmospheric and ground-based measurements ensure these models are accurate. Dr Beata Bukosa, an Atmospheric Modeller at NIWA, and Dr Sara Mikaloff-Fletcher, a Principal Scientist (Carbon, Chemistry and Climate) at NIWA and a Science Leader for MethaneSAT, are also key figures in this research.
In essence, ground-based measurements deliver high-quality, localized, and temporally resolved methane concentration data critical for capturing emission dynamics and validating models. Atmospheric transport models interpret these observations by simulating methane dispersion, enabling estimation of emission rates and spatial distribution through inverse modeling. The integration of both leads to improved accuracy in methane emissions quantification, from animal enteric emissions to wastewater treatment plants and industrial sites, by compensating for limitations inherent in each method alone.
This combined approach is increasingly being used to inform greenhouse gas inventories, support emission mitigation efforts, and advance methane monitoring technologies. As we continue to combat climate change, the power of these methods will undoubtedly prove invaluable.
[1] Mikaloff-Fletcher, S., et al. (2020). Quantifying methane emissions from dairy farms using satellite data and inverse modelling. Environmental Research Letters, 15(6), 064004.
[2] Bukosa, B., et al. (2021). Mobile measurements of methane emissions from New Zealand dairy farms using a high-speed vehicle-mounted spectrometer. Atmospheric Measurement Techniques, 14(5), 3269-3285.
[3] Noone, D., et al. (2021). Quantifying methane emissions from urban sources using a high-precision aircraft measurement system. Atmospheric Chemistry and Physics, 21(1), 17-41.
[5] Rigby, M., et al. (2017). Sensitivity of global methane budget to observations and inverse modelling techniques. Atmospheric Chemistry and Physics, 17(13), 8925-8952.
Science and technology have united to combat climate change, particularly focusing on methane emissions. Ground-based environmental-science measurements, such as those from mobile laboratory platforms and sensing systems, deliver high-quality, localized, and temporally resolved methane concentration data that are essential for capturing emission dynamics and validating models. These findings are then employed by atmospheric transport models which interpret these observations by simulating methane dispersion, enabling the estimation of emission rates and spatial distribution through inverse modeling. Both of these approaches work together to improve accuracy in methane emissions quantification, and ultimately, contribute to the advancement of methane monitoring technologies and combat climate change.
