WoS İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/394
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Article Citation - WoS: 1Citation - Scopus: 1Enhanced Objectivity of AHP for More Reliable Solar Farm Site Selection(Wiley, 2025-04-17) Dincer, A. E.; Demir, A.; Yilmaz, K.The analytic hierarchy process (AHP) is a popular decision-making method for reliable decisions in different areas of study. Although the conventional AHP method mathematically ensures the consistency of results, the reliability of these results depends on the expert manifests. While AHP was originally proposed for subjectively relatable criteria, there may also be additional objectively relatable criteria or a consensus about the final relation of some couple of criteria. To address these objective relations and/or consensuses, this study proposes the analytic hierarchy process with optimized hierarchy (AHP-OH). This method enhances the reliability of results by satisfying objective relations and/or consensuses about relations between criteria. The AHP-OH methodology was applied to select optimal photovoltaic (PV) farm locations in Konya Province, Turkey, a region characterized by diverse terrain and solar radiation levels. The study incorporated geographic information systems to analyze criteria, such as solar radiation rate, land use, slope, proximity to roads and transmission lines, and restricted areas. Results demonstrated that 2.56% of Konya's terrain is highly (80%-100%) suitable and 19.34% of it has moderately high (60%-80%) suitability for PV farm development, with five highly suitable regions identified. Notably, the locations of existing PV farms aligned closely with the identified suitable zones, validating the efficacy of the AHP-OH approach. This research underscores the importance of objectivity of decision-making methods and proposes AHP-OH to enhance the objectivity of the conventional AHP method. By providing a systematic and objective framework for spatial decision support systems, AHP-OH offers significant advancements for policymakers and developers in the renewable energy sector. Future applications of this methodology can extend to other regions and renewable energy sources, contributing to global efforts in sustainable energy development.Article Citation - WoS: 18Citation - Scopus: 18Efficient Disaster Waste Management: Identifying Suitable Temporary Sites Using an Emission-Aware Approach After the Kahramanmaras Earthquakes(Springer, 2023-07-31) Demir, A.; Dincer, A. E.The clean and sustainable disposal of waste generated by natural disasters is crucial for effective disaster waste management. The initial stages of waste management involve determining the quantity of waste and identifying suitable temporary sites for its disposal. This study estimates that the Kahramanmaras province produced approximately 15 million tons of construction and demolition waste and 41,000 tons of household waste following the recent Kahramanmaras Earthquakes on February 6, 2023. Additionally, the study proposes eight temporary disaster waste sites considering various environmental and technical criteria. It should be noted that this is the first study to factor in emissions from waste transportation when selecting temporary disaster waste sites. An algorithm that considers the transportation network to calculate emissions for each map pixel is developed and integrated with geographic information system to identify the best temporary disaster sites. The results show that the most suitable location for temporary sites is southeast of the city center. The transportation time of the waste to the most suitable temporary site is found to be 98 days when 1000 trucks are in operation. The estimated emissions due to the transportation of the waste to the recycling facilities in this region are approximately 88,000 tons of carbon dioxide, 4.4 tons of sulphur oxide, 7.6 tons of nitrogen oxide, and 47.7 tons of particulate matter. The approach employed in this study can be utilized to identify suitable temporary sites for waste management after any natural disaster.