EU ETS and contrail formation avoidance: A case study about modelling contrail formation with limited dataset

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School of Business | Bachelor's thesis
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Date

2024

Department

Tieto- ja palvelujohtamisen laitos

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Mcode

Degree programme

Tieto- ja palvelujohtaminen

Language

en

Pages

42

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Abstract

This thesis concentrates on the usage of the real aircraft flight data in aviation non-CO2 emissions modelling. I investigate how real flight data that has missing, and corrupted parameters can be used in emissions calculations. The methodology of the thesis is a proof-of-concept quantitative study. Aviation share of the climate warming is estimated to be around 5 %. This total effect consists of CO2 and non-CO2 effects. Current EU Emission Trading Scheme (EU ETS) covers aviation CO2-emissions within flights inside EU-region. European commission has plans to expand ETS scheme to non-CO2 emissions of the aviation in the future. Airlines have natural intensive to reduce CO2 emissions as these emissions are directly proportional to fuel usage. However, when non-CO2 effects are considered, the situation is different. In many times a tradeoff exists between fuel consumption and non-CO2 effects. One of the main components of the non-CO2 emissions is contrails that are caused by aircraft soot and water vapor emissions at high altitudes. Persistent contrails can trigger cirrus cloud formation. In general cirrus clouds have a warming effect. EU is planning for a new monitor, report and verify (MRV) regulation for accounting non-CO2 emissions at the start of 2025. Publicly available software has been developed for the calculation of non-CO2 emissions. However, taking non-CO2 emissions accurately into count poses high requirements for the quality of the input data. Therefore, it is important to study how non-CO2 emissions can be modelled when using real data and current non-CO2 emission models. Three different datasets are used in the research setting. Full dataset contained all needed parameters. Limited dataset is the full dataset from which fuel flow and weight data are removed. Planned dataset contains waypoint location, time, and altitude information of the flight plan. The main finding of the study is that the performance model is underestimating on average fuel burn by 7.5 %. This bias could be reduced by using performance factor to take higher fuel consumption into account. Full and limited datasets give the same estimated duration of persistent contrail formation. Limited data provides 28.8 % lower energy forcing values than the full dataset due to lower fuel burn figures. Planned data does not give useful estimates of the energy forcing caused by contrails. In addition, flight data contains quite often corrupted parameter values that should be treated during data preprocessing phase to get reliable results from the calculation model.

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Thesis advisor

Nummi, Patrik

Keywords

aviation, emission trading scheme, contrails, climate change

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https://urn.fi/URN:NBN:fi:aalto-202409156356

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[kand] Kauppakorkeakoulu / BIZ