the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Remote Sensing Estimates of Time-Resolved HONO and NO2 Emission Rates and Lifetimes in Wildfires
Abstract. Quantification of wildfire emissions is essential for comprehending and simulating the effects of wildfires on atmospheric chemical composition. Sub-orbital measurements of vertical column nitrous acid (HONO) and nitrogen dioxide (NO2) were made during the Fire Influence on Regional to Global Environments and Air Quality (FIREX-AQ) field campaign using the GeoCAPE Airborne Simulator (GCAS) instrument aboard the NASA ER-2 aircraft. Emission rates and lifetimes of HONO and NO2 from the Sheridan Fire were estimated by fitting exponentially modified Gaussians (EMGs) to line densities, a technique previously used to estimate urban and point source NO2 emissions. As the EMG approach does not capture temporal changes in emissions and lifetimes due to time-varying fire behavior, we developed a Monte Carlo implementation of the Python Editable Chemical Atmospheric Numeric Solver (PECANS) model that includes diurnal fire radiative power (FRP) behavior. We assess the validity of a range of emission rate and lifetime combinations for both HONO and NO2 as the fire evolves by comparing the resulting line density predictions to the observations. We find that our method results in emissions that are lower than top-down biomass burning emissions inventories and higher than bottom-up inventories. Our approach is applicable to interpreting time-resolved remotely sensed measurements of atmospheric trace gases such as those now becoming available with instruments aboard geo-stationary satellites such as the Tropospheric Emissions: Monitoring of Pollution (TEMPO) and the Geostationary Environment Monitoring Spectrometer (GEMS) instruments.
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Status: open (until 30 Oct 2024)
Data sets
FIREX-AQ 2019 The FIREX-AQ Science Team https://www-air.larc.nasa.gov/cgi-bin/ArcView/firexaq
ERA5 hourly data on pressure levels from 1940 to present H. Hersbach, B. Bell, P. Berrisford, G. Biavati, A. Horányi, J. Muñoz Sabater, J. Nicolas, C. Peubey, R. Radu, I. Rozum, D. Schepers, A. Simmons, C. Soci, D. Dee, and J.-N. Thépaut https://cds.climate.copernicus.eu/cdsapp#!/dataset/reanalysis-era5-pressure-levels?tab=overview
Global Fire Emissions Database (GFED) 4s G. R. van der Werf, J. T. Randerson, L. Giglio, T. T. van Leeuwen, Y. Chen, B. M. Rogers, M. Mu, M. J. E. van Marle, D. C. Morton, G. J. Collatz, R. J. Yokelson, and P. S. Kasibhatla https://www.geo.vu.nl/~gwerf/GFED/GFED4/
Fire Inventory from NCAR version 2 Fire Emission C. Wiedinmyer and L. Emmons https://rda.ucar.edu/datasets/d312009/
Quick Fire Emissions Dataset v2.5 A. Darmenov and A. da Silva https://portal.nccs.nasa.gov/datashare/iesa/aerosol/emissions/QFED/v2.5r1/0.25/QFED/
CAMS global biomass burning emissions based on fire radiative power (GFAS) J. W. Kaiser, A. Heil, M. O. Andrae, A. Benedetti, N. Chubarova, L. Jones, J.-J. Morcrette, M. Razinger, M. G. Schultz, M. Suttie, and G. R. van der Werf https://ads.atmosphere.copernicus.eu/cdsapp#!/dataset/cams-global-fire-emissions-gfas?tab=overview
Model code and software
v0.1.1-custom: Fredrickson et al. 2024 J. Laughner, Q. Zhu, and C. Fredrickson https://doi.org/10.5281/zenodo.13621859
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