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.
%I 4TU.ResearchData