Methane is a powerful greenhouse gas, but its sources remain uncertain in many regions. The isotope fingerprints of methane are diagnostic of its sources, yet their source end-members are poorly constrained for South Asia. Here we determined the methane isotope signal for major sources in South Asia and found these to differ from global averages. Improved regional-specific isotope source fingerprints will help to improve top-down assessments of methane budgets and climate mitigation strategies.

This study uses data and machine learning to better estimate methane emissions from a major landfill in South Korea. By considering local weather conditions like temperature and rain, the research improves how landfill methane is tracked over time. The results help us understand how climate affects emissions and provide tools that can be used worldwide to improve greenhouse gas monitoring and climate action planning.