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Article Dans Une Revue Remote Sensing of Environment Année : 2022

Reconciliation of asynchronous satellite-based NO2 and XCO2 enhancements with mesoscale modeling over two urban landscapes

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Fossil fuel carbon dioxide (CO 2ff), the main driver of global warming and climate change, is often co-emitted with nitrogen oxides (NO x) and precursors to ground-level ozone from anthropogenic sources like power plants or vehicles. In urban and suburban areas, satellite-based NO 2 can be used as a proxy to track the emissions of CO 2ff. Because of NO 2 's shorter lifetime, urban NO 2 plumes are more distinguishable from backgrounds and more sensitive to variations in emissions. However, the combination of these two gases is limited by the asynchrony among NO 2 and CO 2 monitoring satellites. We used CO 2ff simulated by the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) model to reconcile the tropospheric NO 2 vertical column density (VCD) from Tropospheric Monitoring Instrument (TROPOMI) and column-averaged dry-air mole fractions of carbon dioxide enhancements (ΔXCO 2) from Orbiting Carbon Observatory 3 (OCO-3) Snapshot Area Maps (SAMs) over a multicity area, Washington D.C.-Baltimore (DC-Balt), and a basin city, Mexico City. NO 2 /CO 2ff ratios over DC-Balt are smaller than Mexico City, indicative of stricter emission restrictions, a more combustionefficient vehicle fleet, and higher combustion efficiency due to lower altitude in DC-Balt. For single-track cases, the spatial correlations between NO 2 and ΔXCO 2 over Mexico City are stronger than DC-Balt because the NO 2 and CO 2 are mostly trapped in the valley of Mexico City, while DC-Balt is severely affected by distant sources (i. e., US East Coast cities). Using multi-track averaging, spatial correlation coefficients increase with the number of days used for averaging. The correlations reached a maximum when averaging >12 continuous images for DC-Balt and >10 continuous images for Mexico City. This finding indicates that multi-track averaging using modeled CO 2ff as a proxy is helpful to filter the noise in single-track images, to cancel the interference from distant sources, and to magnify correlations between NO 2 and CO 2ff. Mexico City showed stronger spatial correlations but weaker temporal correlations than DC-Balt due to biomass burning hot spots and large transport errors caused by the trapping effects of the surrounding mountains. Tracking the 20-day moving average of CO 2ff emissions using TROPOMI NO 2 seems technically feasible, considering the relationship between correlation coefficients and the number of available satellite images.
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hal-03790703 , version 1 (28-09-2022)

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Ruixue Lei, Sha Feng, Yang Xu, Sophie Tran, Michel Ramonet, et al.. Reconciliation of asynchronous satellite-based NO2 and XCO2 enhancements with mesoscale modeling over two urban landscapes. Remote Sensing of Environment, 2022, 281, pp.113241. ⟨10.1016/j.rse.2022.113241⟩. ⟨hal-03790703⟩
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