Title: Reconciliation of asynchronous satellite-based $$\mathrm{NO_2}$$ and $$\mathrm{XCO_2}$$ enhancements with mesoscale modeling over two urban landscapes

Abstract

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 NO₂ can be used as a proxy to track the emissions of CO_2ff. Because of NO₂’s shorter lifetime, urban NO₂ 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 NO₂ and CO₂ monitoring satellites. We used CO_2ff simulated by the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) model to reconcile the tropospheric NO₂ vertical column density (VCD) from the Tropospheric Monitoring Instrument (TROPOMI) and column-averaged dry-air mole fractions of carbon dioxide enhancements (ΔXCO₂) 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. NO₂/CO_2ff ratios over DC-Balt are smaller than Mexico City, indicative of stricter emission restrictions, a more combustion-efficient vehicle fleet, and higher combustion efficiency due to lower altitude in DC-Balt. For single-track cases, the spatial correlations between NO₂ and ΔXCO₂ over Mexico City are stronger thanmore » DC-Balt because the NO₂ and CO₂ 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 NO₂ 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 NO₂ seems technically feasible, considering the relationship between correlation coefficients and the number of available satellite images.« less

Authors:

Lei, Ruixue ^[1]; Feng, Sha ^[2]; Xu, Yang ^[3]; Tran, Sophie ^[3]; Ramonet, Michel ^[3]; Grutter, Michel ^[4]; Garcia, Agustin ^[4]; Campos-Pineda, Mixtli ^[4]; Lauvaux, Thomas ^[5]

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+ Show Author Affiliations

1. Pennsylvania State University, University Park, PA (United States); Johns Hopkins University, Baltimore, MD (United States)
2. Pennsylvania State University, University Park, PA (United States); Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)
3. University Paris-Saclay, Gif-sur-Yvette (France)
4. University Nacional Autonoma de Mexico (UNAM), Mexico City (Mexico)
5. University Paris-Saclay, Gif-sur-Yvette (France); University of Reims-Champagne Ardenne, Reims (France)

Publication Date:

Tue Sep 13 00:00:00 EDT 2022

Research Org.:

Pacific Northwest National Lab. (PNNL), Richland, WA (United States)

Sponsoring Org.:

USDOE; National Aeronautics and Space Administration; National Council of Science and Technology (CONACYT); Mexico City's Regional Carbon Impacts (MERCI-CO2); Dirección General de Asuntos del Personal Académico, Universidad Nacional Autónoma de México (DGAPA-UNAM)

OSTI Identifier:

1893830

Report Number(s):

PNNL-SA-176357
Journal ID: ISSN 0034-4257

Grant/Contract Number:  

AC05-76RL01830; 80NSSC18K1313; 80NSSC19k0093; 80HQTR21T0070; 290589; ANR-17-CE04-0013-01

Resource Type:

Accepted Manuscript

Journal Name:

Remote Sensing of Environment

Additional Journal Information:

Journal Volume: 281; Journal ID: ISSN 0034-4257

Publisher:

Elsevier

Country of Publication:

United States

Language:

English

Subject:

54 ENVIRONMENTAL SCIENCES; OCO-3 SAMs; TROPOMI; WRF-Chem; Washington D.C.-Baltimore; Mexico City