Quantifying CO emissions from boreal wildfires by assimilating TROPOMI and TCCON observations
2025
Voshtani, Sina | Jones, Dylan B. A. | Wunch, Debra | Pendergrass, Drew C. | Wennberg, Paul O. | Pollard, David F. | Morino, Isamu | Ohyama, Hirofumi | Deutscher, Nicholas M. | Hase, Frank | Sussmann, Ralf | Weidmann, Damien | Kivi, Rigel | García, Omaira | Té, Yao | Chen, Jack | Anderson, Kerry | Stevens, Robin | Kondragunta, Shobha | Zhu, Aihua | Worthy, Douglas | Racki, Senen | McKain, Kathryn | Makarova, Maria V. | Jones, Nicholas | Mahieu, Emmanuel | Cadena-Caicedo, Andrea | Cristofanelli, Paolo | Labuschagne, Casper | Kozlova, Elena | Seitz, Thomas | Steinbacher, Martin | Mahdi, Reza | Murata, Isao | Ilmatieteen laitos | Finnish Meteorological Institute | 0000-0001-8828-2759
We perform a global inverse modelling analysis to quantify biomass burning emissions of carbon monoxide (CO) from the extreme wildfires in Canada between May and September 2023. Using the GEOS-Chem model, we assimilated observations at 3 d temporal and 2° × 2.5° horizontal resolution from the Tropospheric Monitoring Instrument (TROPOMI) separately and then jointly with Total Carbon Column Observing Network (TCCON) measurements. We also evaluated prior emissions from the Quick Fire Emissions Dataset (QFED), Blended Global Biomass Burning Emissions Product eXtended (GBBEPx), Global Fire Assimilation System (GFAS), and Canadian Forest Fire Emissions Prediction System (CFFEPS). The assimilation of TROPOMI-only measurements estimated posterior North America emissions for QFED, GBBEPx, GFAS, and CFFEPS of 110.4 ± 20, 112.8 ± 20, 127.2 ± 17, and 125.6 ± 18 Tg CO compared to prior estimates of 37.1, 42.7, 91.0, and 90.2 Tg CO, respectively. The joint assimilation of TROPOMI+TCCON reduced the posterior 1σ uncertainty on the North American emission estimates by up to about 30 %, while showing only a modest impact (<5 %) on the mean estimate of the inferred emissions. An evaluation against independent measurements reveals that adding TCCON data increases the correlations and slightly lowers the biases and standard deviations. Additionally, including an experimental TCCON product at East Trout Lake with higher surface sensitivity, we find better agreement of the assimilation results with nearby in situ tall tower and aircraft measurements. This highlights the potential importance of vertical sensitivity in these experimental data for constraining local surface emissions. Our results demonstrate the complementarity of the greater temporal coverage provided by TCCON with the spatial coverage of TROPOMI when these data are jointly assimilated.
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