Comprehensive Assessment of Technological Challenges In Photovoltaic Waste Recovery In India Using Principal Component Analysis and Analytic Hierarchy Process Models
{"title":"Comprehensive Assessment of Technological Challenges In Photovoltaic Waste Recovery In India Using Principal Component Analysis and Analytic Hierarchy Process Models","authors":"Dinesh Yadav, Sanjeev Kumar, Prabhu Paramasivam, Praveen Kumar Kanti, Rupesh Gupta, Mohamed Yusuf","doi":"10.1002/gch2.202400300","DOIUrl":null,"url":null,"abstract":"<p>The rapid expansion of photovoltaic (PV) technology has raised concerns about sustainable PV waste management, particularly in India, where inadequate infrastructure and technical limitations hinder effective recycling. Addressing these challenges is crucial for minimizing environmental risks and promoting a circular economy in the renewable energy sector. This study presents a smart multi-criteria decision-making (MCDM) approach that integrates Principal Component Analysis (PCA) and the Analytic Hierarchy Process (AHP) to assess technological challenges in PV waste management. PCA is applied to prioritize key challenges, while AHP evaluated their interrelationships through criteria weights. Despite the effectiveness of PCA and AHP, their combined application in PV waste recovery remains underexplored, particularly in the Indian context. Eight key challenges are identified, with hazardous recycling methods (83.2%) and low recycling potential (83.4%) ranking highest in PCA. AHP results highlighted the lack of advanced recycling technology (0.2298) and hazardous recycling methods (0.2084) as the most critical barriers. A multi-criteria utility function is developed to illustrate these interdependencies. This research bridges critical knowledge gaps by offering data-driven insights into PV waste recovery in India, contributing to sustainable waste management strategies and the development of an efficient recycling framework.</p>","PeriodicalId":12646,"journal":{"name":"Global Challenges","volume":"9 4","pages":""},"PeriodicalIF":4.4000,"publicationDate":"2025-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/gch2.202400300","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Global Challenges","FirstCategoryId":"103","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/gch2.202400300","RegionNum":4,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MULTIDISCIPLINARY SCIENCES","Score":null,"Total":0}
引用次数: 0
Abstract
The rapid expansion of photovoltaic (PV) technology has raised concerns about sustainable PV waste management, particularly in India, where inadequate infrastructure and technical limitations hinder effective recycling. Addressing these challenges is crucial for minimizing environmental risks and promoting a circular economy in the renewable energy sector. This study presents a smart multi-criteria decision-making (MCDM) approach that integrates Principal Component Analysis (PCA) and the Analytic Hierarchy Process (AHP) to assess technological challenges in PV waste management. PCA is applied to prioritize key challenges, while AHP evaluated their interrelationships through criteria weights. Despite the effectiveness of PCA and AHP, their combined application in PV waste recovery remains underexplored, particularly in the Indian context. Eight key challenges are identified, with hazardous recycling methods (83.2%) and low recycling potential (83.4%) ranking highest in PCA. AHP results highlighted the lack of advanced recycling technology (0.2298) and hazardous recycling methods (0.2084) as the most critical barriers. A multi-criteria utility function is developed to illustrate these interdependencies. This research bridges critical knowledge gaps by offering data-driven insights into PV waste recovery in India, contributing to sustainable waste management strategies and the development of an efficient recycling framework.