Supporting dataset and code for the PhD dissertation "Characterizing the transport patterns and climate effects of aviation emissions using a novel Lagrangian tagging method"
DOI: 10.4121/79bcd360-04fc-4efc-a908-09874b9703c5
Datacite citation style
Dataset
This repository supports Chapter 6 of the PhD dissertation titled "Characterizing the transport patterns and climate effects of aviation emissions using a novel Lagrangian tagging method". It contains six simulations conducted with the newly developed AIRTRAC v2.0 submodel, integrated within the ECHAM/MESSy Atmospheric Chemistry (EMAC) model framework.
Two of these simulations comprise the Lagrangian dataset used to track the production and transport of sulfate aerosols (SO₄ in the soluble Aitken and accumulation modes) resulting from aviation emissions of SO₂ and H₂SO₄. These species are emitted at points following the SO₂ mass flux distributions from the 2015 CMIP6 aviation emissions inventory and injected at a pressure altitude of approximately 240 hPa. The magnitude of total emitted SO₂ corresponds to the global total from one day of aviation activity.
The remaining four simulations are part of a perturbation experiment designed to validate the AIRTRAC v2.0 submodel. For each period, a pair of simulations was conducted: one with aviation SO₂ and H₂SO₄ emissions and one without. The simulation without emissions serves as a reference case.
All simulations span two 90-day periods: January 1–March 31, 2015 and July 1–September 30, 2015.
The repository also includes the Python code for the EP_selector tool, which was developed to automatically define a set of pulse emission points that closely align with sustained emissions from any given emissions inventory used in simulations.
For further details, please consult the README file and the dissertation.
History
- 2025-06-03 first online, published, posted
Publisher
4TU.ResearchDataFormat
netCDFAssociated peer-reviewed publication
Characterizing the transport patterns and climate effects of aviation emissions using a novel Lagrangian tagging methodFunding
- Advancing the Science for Aviation and ClimAte (grant code 875036) [more info...] European Commission
Organizations
TU Delft, Faculty of Aerospace Engineering, Department of Control & Operations, Operations & Environment;Deutsches Zentrum für Luft- und Raumfahrt - DLR (German Aerospace Center)
DATA
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EP_selector_tool.py -
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