Evidence map›Paper›PMID 40730609›Full record

ArticleScientific reports2025

Optimizing net-zero energy strategies in airports through a hybrid multi-method framework.

Filiz Mizrak, Kagan Cenk Mizrak, Turhan Karakaya

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Filiz MizrakManagement Information Systems (MIS), Atlas University, Istanbul, Turkey. flzmizrak@gmail.com.
Kagan Cenk MizrakAviation Management, Nisantasi University, Istanbul, Turkey.
Turhan KarakayaEnviromental Protection Technologies, Dogus University, Istanbul, Turkey.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Indexed as

Airport sustainabilityK-Means clusteringMulti-Criteria Decision-MakingNSGA-II optimizationPythagorean fuzzy AHPRenewable energy.

Identifiers

PMID40730609
PMCPMC12307590

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.