Estimates of greenhouse gases and particulate emissions are made with a high spatiotemporal resolution from the Kilmore East fire in Victoria, Australia, which burnt approximately 100,000 ha over a 12 h period. Altogether, 10,175 Gigagrams (Gg) of CO2 equivalent (CO2‐e) emissions occurred, with CO2 (∼68%) being the dominant chemical species emitted followed by CH4 (∼17%) and black carbon (BC) (∼15%). About 63% of total CO2‐e emissions were estimated to be from coarse woody debris, 22% were from surface fuels, 7% from bark, 6% from elevated fuels, and less than 2% from tree crown consumption. To assess the quality of our emissions estimates, we compared our results with previous estimates which used the Global Fire Emissions Database version 3.1 (GFEDv3.1) and the Fire INventory from the National Center for Atmospheric Research version 1.0 (FINNv1), as well as Australia's National Inventory System (and its revision). The uncertainty in emission estimates was addressed using truncated Monte Carlo analysis, which derived a probability density function for total emissions from the uncertainties in each input. The distribution of emission estimates from Monte Carlo analysis was lognormal with a mean of 10,355 Gigagrams (Gg) and a ±1 standard deviation (σ) uncertainty range of 7260–13,450 Gg. Results were in good agreement with the global data sets (when using the same burnt area), although they predicted lower total emissions by 15–37% due to underestimating fuel consumed. Emissions estimates can be improved by obtaining better estimates of fuel consumed and BC emission factors. Overall, this study presents a methodological template for high‐resolution emissions accounting and its uncertainty, enabling a step toward process‐based emissions accounting to be achieved.