Impacts of global NOx inversions on NO2 and ozone simulations

Qu, Zhen; Henze, Daven K.; Cooper, Owen R.; Neu, Jessica L.

doi:https://doi.org/10.5194/acp-20-13109-2020

Articles | Volume 20, issue 21

https://doi.org/10.5194/acp-20-13109-2020

© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/acp-20-13109-2020

© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 20, issue 21

Research article

|

09 Nov 2020

Research article |

| 09 Nov 2020

Impacts of global NO_x inversions on NO₂ and ozone simulations

Zhen Qu, Daven K. Henze, Owen R. Cooper, and Jessica L. Neu

Supplement

https://doi.org/10.5194/acp-20-13109-2020-supplement

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 NO_x, 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.