Global identification of solid waste methane super emitters using hyperspectral satellites

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Authors

Xin Zhang, Joannes D. Maasakkers, Javier Roger, Luis Guanter, Shubham Sharma, Srijana Lama, Paul Tol, Daniel J. Varon , Daniel H Cusworth, Kate Howell, Andrew Thorpe, Phillip G Brodrick, Ilse Aben 

Abstract

Solid waste disposal facilities are the third largest anthropogenic source of methane, and mitigating their emissions is crucial for addressing global climate change. We combine three high-resolution (30–60 m) hyperspectral satellite imagers (EMIT, EnMAP, and PRISMA) to quantify and monitor emissions from 38 disposal sites. These facilities are selected based on urban methane hot spots identified by the TROPOspheric Monitoring Instrument (TROPOMI). Comparisons show the three imagers give consistent emissions estimates, with EMIT and EnMAP having a better sensitivity to landfill methane emissions than PRISMA. Total observed methane emissions from the 38 facilities add up to 230 ± 15 t h-1, representing 5% of global solid waste emissions reported in inventories. Our estimates for these landfills exceed the facility-level Climate TRACE and city-level WasteMAP inventories by factors of 1.8 and 6.3, respectively. On the other hand, we only find emission plumes from 9 of the 20 highest-emitting landfills in the Climate TRACE dataset, suggesting that site-specific practices affect emissions in ways that are difficult to capture by inventories. We further show that multi-month hyperspectral observations allow us to explore potential spatial and temporal emission variations, as well as possible links to landfill operations. With an estimated 1 t h-1 detection limit, our hyperspectral system could detect and quantify up to 60% of global landfill methane emissions, according to the Climate TRACE distribution of landfill emissions. This highlights hyperspectral imaging's potential to monitor global landfill methane, expanding upon current satellite capabilities designed for methane observation.

DOI

https://doi.org/10.31223/X57132

Subjects

Atmospheric Sciences, Environmental Sciences

Keywords

methane, Hyperspectral, landfill, satellite, remote sensing

Dates

Published: 2024-11-01 06:56

Last Updated: 2024-11-01 13:56

License

CC BY Attribution 4.0 International

Additional Metadata

Data Availability (Reason not available):
Retrieval and emission data will be available on Zenodo: https://doi.org/10.5281/zenodo.13643544.