Modeling lightning-NOx chemistry at sub-grid scale in a global chemical transport model

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Alicia, Gressent ; Sauvage, Bastien ; Danielle, Cariolle ; Evans, Mathew John ; Leriche, Maude ; Mari, Celine ; Thouret, Valerie (2015)

For the first time, a plume-in-grid approach is implemented in a chemical transport model (CTM) to parameterize the effects of the non-linear reactions occurring within high concentrated NOx plumes from lightning NOx emissions (LNOx) in the upper troposphere. It is characterized by a set of parameters including the plume lifetime, the effective reaction rate constant related to NOx-O3 chemical interactions and the fractions of NOx conversion into HNO3 within the plume. Parameter estimates were made using the DSMACC chemical box model, simple plume dispersion simulations and the mesoscale 3-D Meso-NH model. In order to assess the impact of the LNOx plume approach on the NOx and O3 distributions at large scale, simulations for the year 2006 were performed using the GEOS-Chem global model with a horizontal resolution of 2° × 2.5°. The implementation of the LNOx parameterization implies NOx and O3 decrease at large scale over the region characterized by a strong lightning activity (up to 25 and 8 %, respectively, over Central Africa in July) and a relative increase downwind of LNOx emissions (up to 18 and 2 % for NOx and O3, respectively, in July) are derived. The calculated variability of NOx and O3 mixing ratios around the mean value according to the known uncertainties on the parameter estimates is maximum over continental tropical regions with ΔNOx [−33.1; +29.7] ppt and ΔO3 [−1.56; +2.16] ppb, in January, and ΔNOx [−14.3; +21] ppt and ΔO3 [−1.18; +1.93] ppb, in July, mainly depending on the determination of the diffusion properties of the atmosphere and the initial NO mixing ratio injected by lightning. This approach allows (i) to reproduce a more realistic lightning NOx chemistry leading to better NOx and O3 distributions at the large scale and (ii) focus on other improvements to reduce remaining uncertainties from processes related to NOx chemistry in CTM.
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