<![CDATA[Scope 3 emissions constitute the largest and most difficult-to-manage component of the carbon footprint of the steel industry; however, they remain underexplored owing to fragmented data systems and the absence of holistic analytical approaches. This study presents an integrated, real-data-driven framework for quantifying and reducing Scope 3 emissions in a medium-scale steel supply chain in West Bengal, India. Primary operational data were collected from upstream suppliers, midstream manufacturing operations, and downstream distributors using transport logs, meter-based energy records, scrap inspection sheets, on-site walk-throughs, and structured stakeholder interviews. Environmental Value Stream Mapping (EVSM) coupled with life-cycle emission accounting was applied to six process stages (UP1, UP2, MS1, MS2, DS1, and DS2), revealing the Electric Arc Furnace (MS1) as the dominant hotspot, contributing more than 90% of the total Scope 3 emissions. Circularity metrics, namely the Scrap Quality Index (SQI) and Material Circularity Index (MCI), demonstrated that higher scrap quality and increased recycled content can significantly decrease upstream embodied emissions. A cooperative game-theoretic model quantified abatement opportunities for suppliers, the manufacturer, and distributors, showing that full coalition formation {U, M, D} generated the highest net payoff (₹1.89 million). Shapley value allocation confirmed the manufacturer as the major beneficiary (97.6%), with proportionate gains assigned to suppliers and distributors. The results highlight that collaborative governance, enhanced circularity, optimized logistics, and renewable energy integration, particularly solar-based electricity substitution, collectively offer a high-impact pathway for Scope 3 decarbonization. The proposed multi-method framework provides a transparent, equitable, and industry-ready decision support system for accelerating low-carbon transitions in the Indian steel sector. ]]>
