Aviation contributes significantly to anthropogenic climate change, and one promising possibility for mitigation is eco-efficient flight planning by avoiding climate sensitive regions with only small changes in the aircraft trajectories. Climate sensitive regions result from strong spatial variation of the global climate impact of local non-CO2 emissions, which are expressed by so-called climate change functions. Previous research established high-fidelity climate change functions (CCFs) for aviation water vapour and NOx emissions, and contrail formation with a climate model as inputs for air traffic optimisation. The mitigation potential in this case study is promising but the climate change function simulations are too computationally intensive for real-time calculation and thus cannot be applied operationally. In this study we show for the first time that this problem can be overcome by formulating algorithmic approximations of the global climate impact. Here we approximate water vapour concentration changes from local aviation water vapour emissions, ozone changes from local NOx emissions and methane changes from local NOx emissions (i.e. algorithmic climate change functions; aCCFs) from instantaneous model weather data using regression analysis. Four candidate algorithms are formulated per chemical species and traded off. The final adjusted regression coefficients, indicating how well the aCCFs represent the CCFs, are 0.59, 0.42, and 0.17 for water vapour, ozone and methane. The results show that the meteorology at the time of emission largely controls the fate of the emitted species, where the quality of the aCCF degrades with increasing lifetime of the respective species.


    Access

    Download


    Export, share and cite



    Title :

    Algorithmic climate change functions for the use in eco-efficient flight planning


    Contributors:

    Publication date :

    2018


    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



    Classification :

    DDC:    380
    RVK:    ZO 0001




    Concept of robust climate-friendly flight planning under multiple climate impact estimates

    Simorgh, Abolfazl / Soler, Manuel / Castino, Federica et al. | Elsevier | 2024

    Free access

    EVOLUTIONARY ALGORITHMIC STATE MACHINE FOR AUTONOMOUS VEHICLE PLANNING

    WHITTAKER THOMAS / JENSEN JARED | European Patent Office | 2020

    Free access

    Incorporating Climate Change Considerations into Transportation Planning

    Schmidt, Nicholas / Meyer, Michael D. | Transportation Research Record | 2009