Methane Emissions Attribution and Quantification Based on “Plus Mobile Monitoring” Approach

Mitigating methane emissions is widely regarded as one of the most cost-effective strategies for combating climate change. Achieving this goal requires a complementary and flexible combination of source attribution and quantification technologies with various minimum detection limits (MDLs) and spatial-temporal resolutions. Ground-based mobile monitoring (MOMO) offers advantages such as high temporal resolution, lower MDLs, and great source attribution capability in mixed-source environments. However, the lack of guidance on appropriate methodological choices have limited its integration into the broader “space–air–ground” methane monitoring framework, particularly for sources with diverse emission characteristics. Here, we present a comprehensive evaluation of MOMO techniques, including their advantages, limitations, quantification uncertainties, and MDLs. Building on this assessment, we propose a “Plus MOMO” strategy to address monitoring needs ranging from regional-scale source identification to source-level localization, while enabling discrimination between fossil-fuel and biogenic methane emissions. To support this approach, we developed a MOMO data integration and visualization platform designed to facilitate multi-source data fusion and interpretation. The “Plus MOMO” strategy has been applied in several in situ case studies, including methane leaks from rural natural gas usage in Beijing, emissions from high- and low-gas coal mines, and abandoned coal mines. Based on these applications, we advocate the development of standardized MOMO protocols and a “MOMO Plus” multi-source data integration framework to improve the accuracy and robustness of methane emission attribution and quantification.