Editing IPCC:AR6/WGI/Chapter-6 (section)

==== 6.2.2.6 Open Biomass Burning Emissions ====

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Emissions from open biomass burning (including forest, grassland, peat fires and agricultural waste burning) represent about 30%, 10%, 15% and 40% of present-day global emissions of CO, NO <sub>x</sub> , BC and OC, respectively ( [[#van%20Marle--2017|van Marle et al., 2017]] ; [[#Hoesly--2018|Hoesly et al., 2018]] ). Wildfires also play an important role in several atmospheric chemistry–climate feedback mechanisms ( [[#Bowman--2009|Bowman et al., 2009]] ; [[#Fiore--2012|Fiore et al., 2012]] ) and fire events occurring near populated areas induce severe air pollution episodes ( [[#Marlier--2020|Marlier et al., 2020]] ; [[#Rooney--2020|Rooney et al., 2020]] ; [[#Yu--2020|Yu et al., 2020]] ).

For the last two decades, model-based emissions estimates are constrained by remote-sensing capacity to detect active fires and area burned. In AR5, biomass burning emissions were derived from a satellite product ( [[#Lamarque--2010|Lamarque et al., 2010]] ). Since then, improvements in detection of small fires has enhanced the agreement with higher-resolution and ground-based data on burned area in several regions ( [[#Randerson--2012|Randerson et al., 2012]] ; [[#Mangeon--2015|Mangeon et al., 2015]] ), especially for areas subjected to agricultural waste burning ( [[#Chuvieco--2016|Chuvieco et al., 2016]] , 2019). The updated emissions factors and the contribution of forest versus savanna fires lead to significantly higher global emissions of NO <sub>x</sub> and lower emissions of OC and CO in CMIP6, compared with CMIP5. A recent compilation and assessment of emissions factors ( [[#Andreae--2019|Andreae, 2019]] ) indicates that the emissions factors from [[#Akagi--2011|Akagi et al. (2011)]] , primarily used to produce the CMIP6 datasets, differ by ±50% for CO, OC, BC and NO <sub>x</sub> , depending on the biome, and would imply, for example, up to 10–30% higher OC and BC emissions from tropical forest fires.

The historical (pre-satellite era) dataset for CMIP6 considers advances in knowledge of past fire dynamics (new fire proxy datasets, such as charcoal in sediments and levoglucosan in ice cores) and visibility records from weather stations ( [[#Marlon--2016|Marlon et al., 2016]] ; [[#van%20Marle--2017|van Marle et al., 2017]] ). At a global level, CMIP5 and CMIP6 emissions trends are similar, however, there are substantial differences at the regional level, especially for the USA, South America (south of Amazonia) and Southern Hemisphere Africa ( [[#van%20Marle--2017|van Marle et al., 2017]] ).

Globally, the CMIP5 estimates ( [[#Lamarque--2010|Lamarque et al., 2010]] ), indicated a gradual decline of open biomass burning emissions from 1920 to about 1950 and then steady, and stronger than CMIP6, increase towards 2000. In contrast, CMIP6 biomass burning emissions ( [[#van%20Marle--2017|van Marle et al., 2017]] ) increase only slightly over 1750–2015 – they peak during the 1990s after which they decrease gradually, which is consistent with the assessment of fire trends in Chapter 5. Therefore, the CMIP6 evolution has a smaller difference between pre-industrial and present-day emissions than CMIP5, resulting in a lower radiative forcing of biomass burning SLCFs, possibly leading to a lower effect on climate ( [[#van%20Marle--2017|van Marle et al., 2017]] ).

Climate warming, especially through change in temperature and precipitation, will generally increase the risk of fire ( [[#Jia--2019|Jia et al., 2019]] , see also Chapter 12) and can also affect the fire injection and plume height ( [[#Veira--2016|Veira et al., 2016]] ), but occurrence of fires and their emissions in the future strongly depends on anthropogenic factors, such as population density, land use and fire management ( [[#Veira--2016|Veira et al., 2016]] ). Consequently, future emissions vary widely with increases and decreases amongst the SSP scenarios due to different land-use change scenarios.

In summary, there has been an improvement in the knowledge of biomass burning emissions by reducing key uncertainties highlighted in AR5. However, systematic assessment of remaining uncertainties is limited, with a lower limit of uncertainties due to emissions factors of 30%, and larger uncertainties due to burning-activity estimates, especially at regional level. Overall, a ''medium confidence'' in current global biomass burning SLCF emissions and their evolution over the satellite era is assessed. There is ''low'' to ''medium confidence'' in SLCF emissions from biomass burning from the pre-industrial period to the 1980s, which rely on the incorporation of several proxy data, with limited spatial representativeness. Nevertheless, uncertainties in the absolute value of pre-industrial emissions remain high, limiting confidence in radiative forcing estimates.

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