Fuel types and fire severity effects on atmospheric pollutant emissions in an extreme wind-driven wildfire

Abstract. In the Mediterranean area, wind-driven wildfires with crown fires are rising, causing an increment in atmospheric pollutant emissions. Quantifying gas emissions in these wildfires requires a better understanding of the components that contribute to the total emission estimate. Here, we aimed to analyze the differences in pre-fire available biomass distribution among layers of fuel types in Pinus halepensis and Quercus suber (hereafter, pine and oak) forests burned in one of the largest wildfires (“La Jonquera”, 10,264 ha) of the past decades. This was done in order to try to unravel the differences in fire severity linked to the percentage of available biomass consumed in each layer and pollutant emissions (CO₂, CO, CH₄, PM_2.5). We used field data (>100 post-fire plots) in which measures from crown, shrub and litter layers, fire severity and consumption assessments were combined with data from National Forest Inventories to quantify final atmospheric pollutant emissions.

Total pre-fire available biomass among pine and oak forests showed different vertical distribution. Pine forests had a higher percentage of crown fine and shrub biomass for all fuel types while oak had more litter biomass. The fuel types with large trees and low tree density, together with fuel types with has lower tree density and vertical continuity had the highest non-charred fire severity in pine and oak. The presence of Erica arborea caused higher fire severity in oak stands. Fuel types of pine were more resistant to the effects of surface fires because they had taller trees than oak. Percent biomass consumption was higher in pine and oak stands in low fire severities because the taller trees could withstand surface fire at high intensities without increasing fire severity. The wildfire analyzed was a large fire with massive crown and high-intensity surface fires, but only a small amount of the finest crown biomass and coarse surface fuels were consumed. Fire severity was the main factor determining different amount of emissions without significant influence of fuel types, and only emissions of CO₂ and CH₄ were higher in pine than in oak in low fire severities. Although remote sensing technologies are extremely useful for biomass and wildfire severity assessments, field data is essential to quantify biomass consumption, atmospheric pollutant emissions from different fuel types and fuel layers.