TY - DATA
T1 - Supplementary Data of "Transport Patterns of Global Aviation NOx and their Short-term O3 Radiative Forcing – A Machine Learning Approach"
PY - 2022/12/09
AU - Jin Maruhashi
AU - Volker Grewe
AU - Christine Frömming
AU - Patrick Jöckel
AU - Irene C Dedoussi
UR - https://data.4tu.nl/articles/dataset/Supplementary_Data_of_Transport_Patterns_of_Global_Aviation_NOx_and_their_Short-term_O3_Radiative_Forcing_A_Machine_Learning_Approach_/16886977/1
DO - 10.4121/16886977.v1
KW - EMAC Model
KW - Lagrangian Simulations
KW - Aviation NOx
KW - Aviation Climate Impact
KW - Radiative Forcing
N2 - <p>Supplementary data accompanying the article "Transport Patterns of Global Aviation NO<sub>x</sub> and their Short-term O<sub>3</sub> Radiative Forcing – A Machine Learning Approach". </p>
<p><br></p>
<p>This data tracks the global transport of emitted NO<sub>x </sub>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.</p>
<p><br></p>
<p>The short-term NO<sub>x</sub>-induced net O<sub>3</sub> 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 NO<sub>x</sub> emitted and consequent O<sub>3</sub> produced to be accompanied along each point of every air parcel trajectory. Lastly, information regarding the background NO<sub>x</sub> conditions during the times of emission is also included. </p>
ER -