Optimizing net-zero energy strategies in airports through a hybrid multi-method framework
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| הוצא לאור ב: | Scientific Reports (Nature Publisher Group) vol. 15, no. 1 (2025), p. 27732-27767 |
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| מחברים אחרים: | , |
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Nature Publishing Group
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| גישה מקוונת: | Citation/Abstract Full Text Full Text - PDF |
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| 022 | |a 2045-2322 | ||
| 024 | 7 | |a 10.1038/s41598-025-12438-0 |2 doi | |
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| 045 | 2 | |b d20250101 |b d20251231 | |
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| 100 | 1 | |a Mizrak, Filiz |u Management Information Systems (MIS), Atlas University, Istanbul, Turkey (ROR: https://ror.org/02jqzm779) (ISNI: 0000 0004 7863 4273) | |
| 245 | 1 | |a Optimizing net-zero energy strategies in airports through a hybrid multi-method framework | |
| 260 | |b Nature Publishing Group |c 2025 | ||
| 513 | |a Journal Article | ||
| 520 | 3 | |a This study introduces a hybrid decision-making framework to evaluate and prioritize energy retrofit strategies in airport infrastructure, addressing the dual goals of sustainability and operational feasibility. The proposed model integrates the Non-Dominated Sorting Genetic Algorithm II (NSGA-II) for generating Pareto-optimal solutions, K-Means clustering for classifying strategies, and the Pythagorean Fuzzy Analytic Hierarchy Process (PFAHP) for prioritizing alternatives under uncertainty. The framework was applied to a representative mid-sized international airport scenario, constrained by a maximum budget of $1 million, implementation timelines of up to 18 months, and an operational disruption threshold of 3 on a 5-point scale. Nine distinct retrofit strategies were identified, with costs ranging from $850,000 to $1,000,000 and energy savings between 20% (250,000 kWh) and 30% (360,000 kWh) annually. Carbon reductions ranged from 15% (approximately 102 metric tons per year) to 30% (around 144 metric tons per year), while implementation times varied from 6.16 to 11.92 months. Disruption levels ranged from minimal (1.23) to moderate (5.00). Among these, Solution 9 achieved the highest overall priority score (0.708), offering 30% energy and carbon savings at a cost of $1,000,000, with an 11.03-month timeline and moderate disruption level (4.09). Cluster analysis grouped solutions into three profiles: low-cost (average cost $859,375, energy savings 20.63%), balanced (average cost $906,250, energy savings 23.75%), and high-impact (average cost $973,750, energy savings up to 30%). Sensitivity analysis further confirmed the robustness of the prioritization, with only minor score fluctuations under adjusted scenarios. These findings provide concrete, actionable guidance for airport decision-makers to support strategic energy retrofit investments aligned with ICAO’s CORSIA framework and UN Sustainable Development Goals, enabling tangible progress toward net-zero operations. | |
| 610 | 4 | |a United Nations--UN | |
| 653 | |a SWOT analysis | ||
| 653 | |a Fuzzy sets | ||
| 653 | |a Emissions | ||
| 653 | |a Optimization techniques | ||
| 653 | |a Aviation | ||
| 653 | |a Environmental impact | ||
| 653 | |a Energy conservation | ||
| 653 | |a Pareto optimum | ||
| 653 | |a Airports | ||
| 653 | |a Wind power | ||
| 653 | |a Artificial intelligence | ||
| 653 | |a Infrastructure | ||
| 653 | |a Alternative energy | ||
| 653 | |a Sustainable development | ||
| 653 | |a Decision making | ||
| 653 | |a Planning | ||
| 653 | |a Renewable resources | ||
| 653 | |a Multiple criteria decision making | ||
| 653 | |a Energy management | ||
| 653 | |a Classification | ||
| 653 | |a Sensitivity analysis | ||
| 653 | |a Game theory | ||
| 653 | |a Geographic information systems | ||
| 653 | |a Energy efficiency | ||
| 653 | |a HVAC | ||
| 653 | |a Carbon | ||
| 653 | |a Stakeholders | ||
| 653 | |a Net zero | ||
| 653 | |a Sustainable Development Goals | ||
| 653 | |a Economic | ||
| 700 | 1 | |a Mizrak, Kagan Cenk |u Aviation Management, Nisantasi University, Istanbul, Turkey (ROR: https://ror.org/04tah3159) (GRID: grid.449484.1) (ISNI: 0000 0004 4648 9446) | |
| 700 | 1 | |a Karakaya, Turhan |u Enviromental Protection Technologies, Dogus University, Istanbul, Turkey (ROR: https://ror.org/0272rjm42) (GRID: grid.19680.36) (ISNI: 0000 0001 0842 3532) | |
| 773 | 0 | |t Scientific Reports (Nature Publisher Group) |g vol. 15, no. 1 (2025), p. 27732-27767 | |
| 786 | 0 | |d ProQuest |t Science Database | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/3234543463/abstract/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text |u https://www.proquest.com/docview/3234543463/fulltext/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/3234543463/fulltextPDF/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch |