Green Industries and Their Role in Sustainable Human Development a Secondary-Data Assessment of Ahmedabad

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Juhi Mundra
Anjali Trivedi
Dipali Desai
Dr. Heena H Gupta

Resumen

Green industrialisation is increasingly viewed as a pathway for reconciling economic activity with environmental protection, resource efficiency and human well-being. This study assesses the role of green industries in sustainable human development in Ahmedabad using secondary evidence and a structured quantitative diagnostic framework. The research adopts a descriptive and exploratory secondary-data design and synthesises official government statistics, Ahmedabad Municipal Corporation documents, urban environmental assessments, policy reports and institutional sources. Four analytical dimensions are examined: environmental performance, economic and industrial transition, social and human-development relevance, and institutional capacity. A Green Industry Sustainability Index (GISI) is developed as a transparent diagnostic score using five measurable Ahmedabad indicators for which comparable reference values are available. The resulting diagnostic score is 60.44/100, indicating a mixed transition profile: strong collection coverage and relatively high CETP capacity adequacy coexist with low historical waste processing and limited treated-wastewater reuse. To provide longitudinal context, Gujarat's renewable-energy installed capacity is analysed from 2017–18 to 2024–25. Over this period, renewable capacity increased from 9.34 GW to 33.39 GW, while its share of total installed electricity capacity increased from 28.45% to 57.36%. Because the city-level indicators come from different reporting years, the GISI is interpreted as an evidence snapshot rather than a time-series performance index. The study maps the findings to SDGs 7, 8, 11 and 13 and identifies financing, skills, environmental monitoring, circular-economy infrastructure and inter-institutional coordination as policy priorities. The paper does not claim causal effects and does not use artificial primary observations.

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