ArticleGlobal challenges (Hoboken, NJ)2025
Comprehensive Assessment of Technological Challenges In Photovoltaic Waste Recovery In India Using Principal Component Analysis and Analytic Hierarchy Process Models.
Article in Global challenges (Hoboken, NJ), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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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.
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.
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Who cites it
1 citing paper in PubMed.
- Comprehensive Assessment of Technological Challenges In Photovoltaic Waste Recovery In India Using Principal Component Analysis and Analytic Hierarchy Process Models.Global challenges (Hoboken, NJ) · 2025Article
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
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.
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Registered trials
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.