Articles | Volume 20, issue 21
Atmos. Chem. Phys., 20, 13109–13130, 2020
https://doi.org/10.5194/acp-20-13109-2020
Atmos. Chem. Phys., 20, 13109–13130, 2020
https://doi.org/10.5194/acp-20-13109-2020

Research article 09 Nov 2020

Research article | 09 Nov 2020

Impacts of global NOx inversions on NO2 and ozone simulations

Zhen Qu et al.

Data sets

Global (2∘×2.5∘) top-down NOx emissions from OMI NASA product (2005–2016) Qu, Z., Henze, D. K., Cooper, O. R., and Neu, J. L https://doi.org/10.7910/DVN/HVT1FO

Global (2∘×2.5∘) top-down NOx emissions from OMI DOMINO product (2005–2016) Qu, Z., Henze, D. K., Cooper, O. R., and Neu, J. L https://doi.org/10.7910/DVN/QBAQZA

DOMINO and QA4ECV NO2 retrievals KNMI http://www.temis.nl/airpollution/no2.html

Ozonesonde profiles from Shasta, Big Sur, Point Reyes, Joshua Tree, and San Nicolas NOAA Global Monitoring Laboratory ftp://aftp.cmdl.noaa.gov/data/ozwv/ Ozonesonde/2_FieldProjects/CALNEX/

Ozonesondes from Trinidad Head NOAA Global Monitoring Laboratory ftp://aftp.cmdl.noaa.gov/data/ozwv/Ozonesonde/TrinidadHead, California/100MeterAverageFiles/

Tropospheric Ozone Assessment Report, links to Global surface ozone datasets M. G. Schultz et al. https://doi.org/10.1594/PANGAEA.876108

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Short summary
We use satellite observations and chemical transport modeling to quantify sources of NOx, a major air pollutant, over the past decade. We find improved simulations of the magnitude, seasonality, and trends of NO2 and ozone concentrations using these derived emissions. Changes in ozone pollution driven by human and natural sources are identified in different regions. This work shows the benefits of remote-sensing data and inverse modeling for more accurate ozone simulations.
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