A Decadal Analysis of Research Trends in Sustainable Waste Management in India Using Power-BI

• Published in: Water, air, and soil pollution air, and soil pollution, 2024-09, Vol.235 (9), p.579-579, Article 579
• Main Authors: Sawant, Aryan, Plappally, Anand, Soboyejo, Winston, Nighojkar, Amrita
• Format: Article
• Language: English
• Subjects: air; Atmospheric Protection/Air Quality Control/Air Pollution; Biomass; Biomass energy production; Climate Change/Climate Change Impacts; computer software; Data analysis; data visualization; Decision making; Earth and Environmental Science; energy; Energy resources; Energy sources; Environment; hybrids; Hydrogeology; India; Initiatives; issues and policy; landscapes; Municipal solid waste; Municipal waste management; Renewable energy; renewable energy sources; Scientific visualization; soil; Soil Science & Conservation; Solid waste management; Solid wastes; stakeholders; Sustainability; Sustainability management; Sustainable development; Sustainable Development Goals; Sustainable energy; Sustainable practices; Sustainable waste management; Trends; Visual fields; Visualization; Waste analysis; Waste management; water; Water Quality/Water Pollution
• ISSN: 0049-6979; 1573-2932
• DOI: 10.1007/s11270-024-07396-8

Effective waste management is crucial for achieving sustainable development goals, which require a comprehensive understanding of environmentally sound practices. This study introduces a pioneering methodology by employing Microsoft's Power BI data visualization tool to analyze and predict trends in sustainable waste management in India. The investigation spans a decade of sustainable handling of diverse waste categories, identifying key research entities and influential journals. Notably, Elsevier and Springer are prominent publishers, with hybrid publishing accounting for 62% of articles. Research focuses predominantly on municipal solid waste management (57%), followed by biomass waste management (15%). Leveraging Power BI facilitates intricate temporal analysis of waste patterns, providing a nuanced view of the evolving landscape in sustainable waste management. The study innovatively integrates data visualization with predictive analytics to forecast trends through 2034, particularly in converting municipal solid and biomass waste into valuable energy resources. These predictive insights are indispensable for long-term strategic planning and informed policy decisions, empowering stakeholders with actionable intelligence for sustainable energy and waste management strategies. By harnessing Power BI's forecasting capabilities and analyzing historical Scopus data, this research underscores the strategic significance of visual analytics in guiding data-driven decision-making for sustainable practices. This comprehensive examination of waste management dynamics establishes a benchmark for future research and policy formulation in the field.