Supplementary Data of "Transport Patterns of Global Aviation NOx and their Short-term O3 Radiative Forcing – A Machine Learning Approach"

DOI:10.4121/16886977.v1
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DOI: 10.4121/16886977
Datacite citation style:
Maruhashi, Jin; Grewe, Volker; Frömming, Christine; Jöckel, Patrick; Irene C Dedoussi (2022): Supplementary Data of "Transport Patterns of Global Aviation NOx and their Short-term O3 Radiative Forcing – A Machine Learning Approach". Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/16886977.v1
Other citation styles (APA, Harvard, MLA, Vancouver, Chicago, IEEE) available at Datacite

Dataset

Delft University of Technology logo

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Time coverage

2014

Licence

CC BY 4.0

Supplementary data accompanying the article "Transport Patterns of Global Aviation NOx and their Short-term O3 Radiative Forcing – A Machine Learning Approach". 


This data tracks the global transport of emitted NOx throughout a 90-day period since its emission from a representative aircraft cruising altitude of 250 hPa (~10.4 km) in 5 regions (North America, South America, Eurasia, Africa and Australasia) during the first day of January and July of 2014.


The short-term NOx-induced net O3 production is also calculated as well as its associated instantaneous radiative forcing impact. The Lagrangian modelling approach adopted in this study allows for the amount of NOx emitted and consequent O3 produced to be accompanied along each point of every air parcel trajectory. Lastly, information regarding the background NOx conditions during the times of emission is also included. 

History

  • 2022-12-09 first online, published, posted

Publisher

4TU.ResearchData

Format

netCDF (.nc)

Funding

  • Advancing the Science for Aviation and ClimAte (grant code 875036) [more info...] European Commission

Organizations

TU Delft, Faculty of Aerospace Engineering, Section Aircraft Noise and Climate Effects

Deutsches Zentrum für Luft- und Raumfahrt, Institut für Physik der Atmosphäre

DATA

Files (449)