Abstract
Characterizing black carbon (BC) on a fine scale globally is essential for understanding its climate and health impacts. However, sparse BC mass measurements in different parts of the world and coarse model resolution have inhibited evaluation of global BC emission inventories. Here, we apply globally distributed BC mass measurements from the Surface Particulate Matter Network (SPARTAN) and complementary measurement networks to evaluate contemporary BC emission inventories. We use a global chemical transport model (GEOS-Chem) in its high-performance configuration (GCHP) for high-resolution simulations to relate BC emissions to ambient concentrations for comparison with measurements. Here we find that simulations using the Community Emissions Data System (CEDS) emission inventory exhibit skill (r(2) = 0.73) in representing variability in SPARTAN measurements across primarily developed regions with low BC concentrations but exhibit pronounced discrepancy (r(2) = 0.00019) across high-BC regions in the Global South, underestimating BC by 38%. Alternative inventories (EDGAR, HTAP) yield similar results. These findings motivate renewed attention to the challenging task of characterizing BC emissions from low- and middle-income countries.