Biomass burning combustion efficiency observed from space using measurements of CO and NO<sub>2</sub> by the TROPOspheric Monitoring Instrument (TROPOMI)

Abstract

Abstract. The global fire emission inventories depend on ground and airborne measurements of species-specific emission factors (EFs), which translate dry matter losses due to fires to actual trace gas and aerosol emissions. The EFs of nitrogen oxides (NOx) and carbon monoxide (CO) can function as a proxy for combustion efficiency to distinguish flaming from smoldering combustion. The uncertainties in these EFs remain large as they are limited by the spatial and temporal representativeness of the measurements. The global coverage of satellite observations has the advantage of filling this gap, making these measurements highly complementary to ground-based or airborne data. We present a new analysis of biomass burning pollutants using space-borne data to investigate the spatiotemporal efficiency of fire combustion. Column measurements of nitrogen dioxide and carbon monoxide (XNO2 and XCO) from the TROPOspheric Monitoring Instrument (TROPOMI) are used to quantify the relative atmospheric enhancements of these species over different fire-prone regions around the world. We find spatial and temporal patterns in the ΔXNO2 ∕ ΔXCO ratio that point to distinct differences in biomass burning behavior. Such differences are induced by the burning phase of the fire (e.g., high-temperature flaming vs. low-temperature smoldering combustion) and burning practice (e.g., the combustion of logs, coarse woody debris and soil organic matter vs. the combustion of fine fuels such as savanna grasses). The sampling techniques and the signal-to-noise ratio of the retrieved ΔXNO2 ∕ ΔXCO signals were quantified with WRF-Chem experiments and showed similar distinct differences in combustion types. The TROPOMI measurements show that the fraction of surface smoldering combustion is much larger for the boreal forest fires in the upper Northern Hemisphere and peatland fires in Indonesia. These types of fires cause a much larger increase (3 to 6 times) in ΔXCO relative to ΔXNO2 than elsewhere in the world. The high spatial and temporal resolution of TROPOMI also enables the detection of spatial gradients in combustion efficiency at smaller regional scales. For instance, in the Amazon, we found higher combustion efficiency (up to 3-fold) for savanna fires than for the nearby tropical deforestation fires. Out of two investigated fire emission products, the TROPOMI measurements support the broad spatial pattern of combustion efficiency rooted in GFED4s. Meanwhile, TROPOMI data also add new insights into regional variability in combustion characteristics that are not well represented in the different emission inventories, which can help the fire modeling community to improve their representation of the spatiotemporal variability in EFs.

Vast CO2 release from Australian fires in 2019–2020 constrained by satellite

“…Under clear-sky conditions it also maintains high sensitivity up to the planetary boundary layer, where fire emissions have the largest impact. The instrument has been used previously to improve understanding of fires, their combustion characteristics and the atmospheric transport of emitted pollutants 27,28 . Here we use it in a regional inverse analysis to improve estimates of CO and CO 2 emission on a day-to-day basis for the Southeast Australian fires (see Supplementary Information).…”

Carbon Monoxide in Optically Thick Wildfire Smoke: Evaluating TROPOMI Using CU Airborne SOF Column Observations

“…Data from the ultraviolet–visible (UV–vis) detector on TROPOMI have been used to derive biomass burning trace gas emissions and lifetimes, , proxies for combustion efficiency, and to study direct emissions of CO (e.g., Borsdorff et al and Vellalassery et al). However, to the best of our knowledge, direct comparisons of TROPOMI CO columns with aircraft column measurements for biomass burning events have not yet been performed and hold the potential to improve the characterization of global wildfire emissions.…”

Atmospheric Trends of CO and CH4 from Extreme Wildfires in Portugal Using Sentinel-5P TROPOMI Level-2 Data

“…The Monchique area, in particular Serra de Monchique, is characterized by a Mediterranean climate surrounded by eucalyptus (Eucalyptus globulus) (40%) and shrubs (40%), reflecting its high propensity to wildfires (Figure S1 in the supplementary data) and as expected, affected the spread of the Monchique fire. The wildfire started to spread to the west, on the left bank of the Ribeira de Odelouca, where it was limited by low fuel accumulated as a consequence of a significant wildfire in 2016 (a more detailed description of the area and wildfire details is available in the Monchique Fire Assessment report [24]).…”

“…Additionally, Rooney et al [23] conducted a comprehensive investigation of air quality impacts, regarding PM 2.5 emissions on the Camp Fire using a combined analysis of ground-based and space-borne observations and WRF-Chem simulations. A year after, Van der Velde et al [24] examined different fire-prone regions around the world by means of an analysis of the biomass burning pollutants through the column measurements of nitrogen dioxide and carbon monoxide provided by TROPOMI, by using space-borne data to investigate the spatiotemporal efficiency of fire combustion.…”