Reviews and syntheses: Spatiotemporal Dynamics, Drivers, and Uncertainties of Global Wildfire Carbon Dioxide Emissions

Abstract. Wildfire carbon dioxide emissions (WCEs) are increasingly recognized as a major and highly uncertain component of the global biogeochemical carbon cycle, reflecting limitations in constraining their historical evolution, future trajectories, and controlling mechanisms. This review synthesizes evidence from satellite-based emission products, fire-enabled model reconstructions and scenario projections, and paleoenvironmental archives (charcoal and ice-core black carbon) to evaluate global WCE dynamics from 1700 to 2100. Historical reconstructions indicate relatively stable global WCEs during 1700–1850, whereas pronounced divergence emerges during 1851–2000 due to differing representations of land-use change and industrialization. Contemporary satellite observations show declining WCEs over 2001–2020 (8.72 ± 0.67 Pg CO₂ yr⁻¹), with 83 % originating from tropical ecosystems because of large burned area and high combustion efficiency. Importantly, these fluxes represent a critical shift in the net carbon balance of tropical and boreal biomes. Multi-model projections suggest increases through the 2040s, followed by growing divergence under alternative socioeconomic pathways. Across datasets and models, annual WCE estimates differ by up to 40 %, driven by uncertainties in fire detection, combustion completeness, emission factors, and fire–climate–human interactions. Despite regional heterogeneity, climate change emerges as the primary regulator of interannual variability in WCEs. Approximately 43 % of global vegetated areas have experienced increasing extreme wildfire seasons, particularly in northern high-latitude forests where recurrent burning amplifies carbon losses and weakens ecosystem carbon sinks. We conclude by identifying priorities for reducing uncertainty through tighter integration of multi-source observations with fire-enabled process models, improved representation of coupled fire–climate–carbon feedback and post-fire recovery, and the application of artificial intelligence to better constrain WCE spatiotemporal variability and enhance predictive capability under increasingly nonlinear fire–climate interactions.