Evaluating the Effect of Variability in Biomass Burning Emissions Inventories on Modeled Smoke Concentrations: Insights from the 2021 Canadian Wildfire Season

Wildfire smoke is increasingly recognized as a significant source of air pollution that leads to public health issues. Over the past few decades, air pollution in Canada has been reduced due to effective regulations. However, fine particulate emissions (i.e., particles with an aerodynamic diameter of less than 2.5 μm (PM_2.5)) from wildfires have shown upward trends as climate change exacerbates the frequency and likelihood of wildfires. According to the Canadian Interagency Forest Fire Centre (CIFFC) in 2021, there were 18% more fire starts and nearly a 61% increase in the total area burned compared to the past 10-year average in Canada. The emissions inventories used for modeling the impact of fires on air quality and climate exhibit several discrepancies in emissions estimates, primarily due to the different types of satellite products used for identifying fires and measuring burned area, as well as differences in emission factors describing the vegetative fuels burned. This variability of fire emission inventories leads to uncertainties in  predicting air quality. Using the GEOS-Chem chemical transport model, we studied how differences in emissions estimates among three commonly used global biomass burning inventories—the Global Fire Emissions Database 4 (GFED4), the Global Fire Assimilation System (GFAS), and the Quick-Fire Emissions Database 2 (QFED2)—and a newly developed  regional biomass burning emission inventory, the Canadian Forest Fire Emissions Prediction System (CFFEPS), affect modeled concentrations of PM_2.5 during the 2021 wildfire season in Canada. To examine the sensitivity of simulated PM_2.5 to different biomass burning emission datasets, we compared them with ground based PM_2.5 data from 70 NAPS (National Air Pollution Surveillance) stations across Canada, from east to west. The simulated PM_2.5 concentrations showed significant variation in model performance based on the geographic location of the monitoring stations, particularly between the western and eastern regions of Canada. These findings indicate the importance of considering the strengths and weaknesses of each fire inventory, as some inventories may more accurately represent fire emissions in certain regions than others.