Harmonized global to regional gridded methane inventories in a discrete global grid framework

Mingke Li , Mozhou Gao, Steve H.L. Liang

Heterogeneous gridded environmental datasets are increasingly used in Earth system modeling, atmospheric studies, and spatial analytics, but differences in coordinate reference systems, spatial resolutions, sector classifications, reporting units, and data formats hinder interoperability and cross-dataset comparison. Conventional latitude–longitude grids further introduce unequal cell areas that bias aggregation and regional comparison. This study presents a framework for harmonizing heterogeneous gridded datasets within a Discrete Global Grid System (DGGS), using explicit grid-selection criteria, area-weighted mass-preserving conversion, cross-scheme sector mapping, and five measurable evaluation criteria. Using methane as a demanding case, we transformed 13 open-access inventories from global to subnational scales into the rearranged Hierarchical Equal-Area isoLatitude Pixelization (rHEALPix) DGGS, harmonizing 324 source variables from five classification schemes and standardizing values to megagrams per year per cell. Conversion preserved emission totals, with negligible differences for continental, national, and regional inventories and differences within 2% to 3% for global inventories. Cell area is constant by construction, aggregation along the hierarchy is exact, and inventories at different resolutions can be compared after aggregation. The framework is reproducible and extensible to other gridded spatial data.