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Vertical Accumulation of Ozone and Aerosol during the 2016 Southeastern U.S. Wildfires
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  • Bo Wang,
  • Shi Kuang,
  • Gabriele G. Pfister,
  • Arastoo Pour Biazar,
  • Michael J. Newchurch,
  • Rebecca R Buchholz,
  • Andrew O'Neil Langford
Bo Wang
University of Alabama in Huntsville

Corresponding Author:[email protected]

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Shi Kuang
University of Alabama in Huntsville
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Gabriele G. Pfister
National Center for Atmospheric Research (UCAR)
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Arastoo Pour Biazar
University of Alabama in Huntsville
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Michael J. Newchurch
University of Alabama in Huntsville
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Rebecca R Buchholz
National Center for Atmospheric Research (UCAR)
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Andrew O'Neil Langford
NOAA Earth System Research Laboratory
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Abstract

The vertical accumulation of ozone and aerosol during an episode of the 2016 Southeastern United States Wildfires is analyzed by integrating a regional chemical transport model with ozonesonde, O$_3$ Differential Absorption Lidar (DIAL), ceilometer, surface monitors, and satellite products. The results indicate that measurements capture the vertical extent of the smoke plumes affecting the surface and upper air over Huntsville, AL, and also the enhanced ozone lamina in the plumes. Sensitivity simulations and tendency diagnostics characterize the chemical and physical processes affecting the vertical profiles downstream of the wildfires. The model results show that the net chemical ozone production (PO$_3$) dominates the daytime ozone accumulation by up to 19 ppb/10 hrs in the upper air over Huntsville. At the surface, the negative PO$_3$ is offset by positive O$_3$ contributions from vertical mixing and advection. Fire emissions increase the vertical ozone by affecting local chemical reactions, transportation, and vertical exchange. The dominant processes exhibit daily, diurnal, and vertical variability. Quantitatively, fire emissions increase the daytime positive PO$_3$ by up to 25\% in the upper air, and increase the daytime PM2.5 by up to 77\%. The capability of the regional model for reproducing the observations is explored. Increasing the fire aerosol emissions improves the model performance on domain-averaged PM2.5. The model captures the well-mixed aerosol in the boundary layer but fails to fully reproduce the densest plumes seen in the DIAL and satellite. The discrepancies are associated with poor satellite observing condition due to clouds and with uncertainties in emission inventories.