Work Package 5
Policy Driven Flight Planning
Participant : DLR, Envisa, Thales, TUD
WP leader : DLR
Start month : 01 – End month : 46
Main contact: malte.Niklass@dlr.de
Evolve algorithmic 4-D cost functions for climate change for integrating price-based non-CO2 policies into flight planning and trajectory optimization .
Assess the effectiveness of the policy driven flight planning approach about its climate impact potential and feasibility
Description of work:
T5.1 Review of policy instruments for implementing climate-cost-efficient routing
- Review of different CO2 equivalent (CO2e) approaches incorporating non-CO2 effects into existing policy instruments like EU ETS or CORSIA (constant CO2e factor, distance-dependent CO2e factor, location-dependent CO2e factor, etc.)
- Review of flanking policy instruments for non-CO2 effects, like climate-restricted flight altitudes, climate-charged airspaces, no-fly areas, etc.
- Key policy indicators for review:
- incentive generated for mitigating non-CO2 effects
- effectiveness of overall climate impact reduction
- ease of implementation in terms of monitoring, reporting, and verification
- high transparency and easy comprehensibility
- easy adaptability to the level of scientific understanding (consideration of the existing uncertainties)
- Deduction of specifications for integrating price-based non-CO2 policies into flight planning and trajectory optimization
T5.2 Evolving a methodology for integrating non-CO2 policies into flight planning and trajectory optimization
- Develop an algorithmic concept characterizing weather-dependent climate charges of aircraft emissions at a given location and time (4-D cost functions for climate change).
- Elaborate a monetarization logic quantifying the amount of emission certificates to be surrendered or respectively the level of emission charge/tax to be paid per climate impact of CO2, H2O, NOx and contrail-cirrus.
- Elaboratie a methodology for integration existing non-CO2 uncertainties into the calculation of algorithmic cost functions for climate change (e.g., consideration of stochastic characteristics of weather forecasts; input from WP3)
- Calculate robust algorithmic cost functions for climate change for H2O, NOx, and contrail cirrus
T5.3 Assessing the effectiveness of the policy driven flight planning approach
- Expand a direct operating cost model with climate charges (input from T5.2)
- Implement robust algorithmic cost functions for climate change and the extended DOC model into the trajectory optimization (input for trajectory optimization in WP4).
- Parametric analysis of algorithmic cost functions for climate change to generate a robust climate-sensitive flight planning
- Applly optimization results (Input from WP4) for the evaluation of the developed climate policy concept