Multi-Year Simulations of the Global Atmosphere: The role of Biomass Burning Emissions Datasets

Wildfires are a significant source of trace gases and aerosols emitted into the atmosphere with the potential to influence the Earth’s radiative balance, and therefore climate. To assess their present-day influence on atmospheric composition, we conducted multi-year simulations using a range of emissions datasets over the period 2003-2015.  

In our study we employ TM5-MP Chemical Transport Model (CTM) and five biomass burning (BB) emissions datasets: GFED4.1s, GFASv1.2, FEERv1.0-G1.2, QFEDv2.4r1 and FINNv2.5, to drive the simulations. This intercomparison aims to assess the model's ability to simulate atmospheric composition and wildfire-driven changes in atmospheric tracers such as carbon monoxide (CO), nitrogen oxides (NOx), ozone, and aerosol abundances, distribution, seasonal cycles, and interannual variability (IAV), while examining the dependency of the results on the input wildfire emissions dataset. Hot-spots of wildfire influences are identified, and results are compared with satellite and ground-based observations, to examine where the model captures the role of biomass burning emissions in the atmosphere more accurately and where deficiencies are evident.  

Comparing results for CO, high IAV is captured in BB hotspots in the corresponding BB season, with simulations using FEER showing the lowest IAV of all datasets. Simulated Aerosol Optical Depth (AOD) shows pronounced IAV in Siberia (boreal spring/summer), South America (boreal summer/autumn) and Boreal North America (boreal summer), across all datasets, albeit, with different magnitudes. These patterns align with the seasonal burning in each region; when fire emissions are excluded, AOD IAV decreases significantly during the corresponding burning seasons.