Methane is a potent greenhouse gas source attribution and emission quantification of which are critical to address managing natural and anthropogenic emissions. Substantial emissions arise from natural sources such as wetlands, thawing permafrost, gas hydrates, and various other large and diffuse areal sources. Methane is emitted from anthropogenic sources, including landfills and wastewater treatment facilities, and agricultural and industrial activities that are high-rate point sources. The convergence of multi-scale data sources and advances in data-driven methods provides a unique opportunity for using artificial intelligence for methane emission detection, quantification, and forecasting.

Topics include, but are not limited to:

• Remote sensing of methane emissions (including hyperspectral imaging)
• Geospatial AI methods for source identification and characterization
• Physics-informed AI methods for hybrid methane modelling
• Anthropogenic methane emission quantification
• Natural methane emission quantification
• Seasonal and spatiotemporal analysis of methane emissions
• Source attribution from mixed sources
• Validation studies against flux tower, aircraft, mobile measurement campaigns

• A - Atmospheric Sciences