# Airline Network Planning Considering Climate Impact: Assessing New Operational Improvements
## 5 Conclusions and Outlook  
In this study, we developed a framework for multi-objective airline network planning. We assessed four scenarios using the framework to evaluate the synergy between climate-aware network design and OI integration. We adopted an integrated approach to simultaneously solve network planning and flight scheduling to address the involved interdependencies. For the first time, the ISO and LISO implementation was evaluated at the network level to capture the implications and network effects associated with them. We also performed a comprehensive comparison of the results for three representative airline types. The comparison showed how a climate-aware network design in combination with OIs can assist in climate impact mitigation. Such an advancement offers great potential to enhance the effectiveness of network planning and decision-making processes in the aviation industry, leading to more efficient and sustainable operations.  
To mimic the profit-maximising nature of airlines, a BAU scenario with a profit-only objective function was used as the reference case. This scenario is based on the actual demand distribution from the operations of the representative airlines in 2018. ATR20 was assumed as the climate impact representative, and incorporating it into the optimisation subroutine was aided by a transformation function. The evaluated case studies suggest that the ATR scenario can reduce the climate impact by 10-36% at the cost of 8-20% profit loss. LISO also outperforms the ATR scenario regarding the ATR20 reduction. The ATR20 reduction in LISO could be up to 31% more than the ATR scenario, while the profit is reduced by only 6%. The climate impact mitigation values show a lower total reduction than similar studies due to the network implications of implementing the OIs.  
We assumed that passenger demand and airfares are static, and are not affected by changing operational conditions. To improve the reliability of the results, it would be interesting to incorporate the relationship between air service, costs, and competition in future work in both demand and airfares. Furthermore, uncertainties in the flight's climate impact calculations need to be addressed in more detail. Incorporating the uncertainty modelling of climate impact is necessary to obtain more accurate results.  
**Author Contributions:** Conceptualisation, M.N., B.F.S., A.S., Z.L.Z., F.L. and V.G.; methodology, M.N., B.F.S. and A.S.; software, M.N., Z.L.Z., C.M.W. and F.L.; writing--original draft preparation, M.N. and Z.L.Z.; writing--review and editing, M.N., B.F.S., A.S., Z.L.Z., C.M.W., F.L. and V.G.; visualisation, M.N.; supervision, B.F.S., A.S. and V.G.; funding acquisition, V.G., B.F.S. and F.L. All authors have read and agreed to the published version of the manuscript.  
**Funding:** This research was funded by the project _ClimOP_, which is part of the European Union's Horizon 2020 Research and Innovation Programme under Grant Agreement No. 875503.  
**Institutional Review Board Statement:** Not applicable.  
**Data Availability Statement:** Restrictions apply to the availability of passenger demand and schedule data, which were obtained from _Sabre Market Intelligence_ as well as the _Base of Aircraft Data_ (_BADA_) for the aircraft performance data.  
**Acknowledgments:** We would like to thank the _ClimOP_ consortium for providing their feedback on the methodology and input data and [PERSON] from the _DLR Institute of Atmospheric Physics_ for supporting the climate impact assessment with AirClim. We also would like to express our sincere gratitude to [PERSON], whose comments and suggestions helped improve the manuscript's clarity and rigour.  
**Conflicts of Interest:** The authors declare no conflict of interest.