Dynamic biomass burning emission factors and their impact on atmospheric CO mixing ratios

Abstract

Biomass burning is a major source of trace gases and aerosols, influencing atmospheric chemistry and climate. To quantitatively assess its impact, an accurate representation of fire emissions is crucial for the atmospheric modeling community. So far, most studies rely on static emission factors (EF) which convert estimates of dry matter burned to trace gas and aerosol emissions. These EFs are often based on the arithmetic mean of field measurements stratified by biome, neglecting the variability in time and space. Here we present global carbon monoxide (CO) emission estimates from fires based on six EF scenarios with different spatial and temporal variability, using dry matter emission estimates from the Global Fire Emissions Database (GFED). We used the TM5 model to transport these different bottom-up estimates in the atmosphere and found that including spatial and temporal variability in EFs impacted CO mixing ratios substantially. Most scenarios estimated higher CO mixing ratios (up to 40% more CO from fires during the burning season) over boreal regions compared to the GFED standard run, while a decrease (~15%) was estimated over the continent of Africa. A comparison to atmospheric CO observations showed differences of 10-20 ppb between the scenarios and systematic deviations from local observations. Although temporal correlations of specific EF scenarios improved for certain regions, an overall "best" set of EFs could not be selected. Our results provide a new set of emission estimates that can be used for sensitivity analyses and highlight the importance of better understanding spatial and temporal variability in EFs for atmospheric studies in general and specifically when using CO or aerosols concentration measurements to top-down constrain fire carbon emissions. Key Points New biomass burning emission factor scenarios were developed New emission factor scenarios impacted CO mixing ratios substantially Better understanding of spatial and temporal variability in EFs is important © 2013. American Geophysical Union. All Rights Reserved.