10.4121/79bcd360-04fc-4efc-a908-09874b9703c5.v1

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Supporting dataset and code for the PhD dissertation "Characterizing the transport patterns and climate effects of aviation emissions using a novel Lagrangian tagging method" Dataset

Jin Maruhashi, Volker Grewe, Irene C Dedoussi,
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

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