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    China Baowu–Rio Tinto low‑carbon steel trials: process design notes for engineers

    June 15, 2026|

    Reviewed by Tom Sullivan

    First reported on International Mining – News

    30 Second Briefing

    China Baowu and Rio Tinto have completed industrial-scale pelletisation and hydrogen-based shaft furnace trials at Baoshan Iron & Steel’s Zhanjiang operations using Rio Tinto’s Pilbara Blend fines. The campaign tested direct reduction-grade pellets in a shaft furnace charged with hydrogen-rich gas, aiming to validate lower-carbon ironmaking routes compatible with existing Baowu infrastructure. Results will inform process design for future DR-grade pellet plants and potential retrofits of blast furnace–basic oxygen furnace lines in China’s coastal steel hubs.

    Technical Brief

    • Industrial-scale pelletisation used Pilbara Blend fines, validating their agglomeration behaviour for direct reduction applications.
    • Hydrogen-based shaft furnace operation assessed reduction kinetics and metallisation using hydrogen-rich process gas.
    • China Baowu and Rio Tinto jointly designed the test matrix, aligning ore preparation, pellet firing and furnace charging conditions.
    • Operational learning focuses on adapting Pilbara Blend chemistry and pellet quality control to hydrogen-enriched shaft furnaces.

    Our Take

    In our database, China Baowu appears across several iron ore decarbonisation items, from EACON’s battery-electric AHS fleet at the Taihe iron ore mine to Fortescue–TISCO green iron pilots, signalling that Baowu is spreading technology risk across multiple low‑carbon ironmaking routes rather than backing a single pathway.

    The related industrial-scale hydrogen direct reduction trials using Pilbara Blend suggest Rio Tinto is working to future‑proof its mid‑grade Pilbara iron ore against potential shifts in blast furnace demand, which could influence long‑term product specifications and blending strategies for Pilbara Blend supplied to mills like Baoshan Zhanjiang.

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    Prepared by collating external sources, AI-assisted tools, and Geomechanics.io’s proprietary mining database, then reviewed for technical accuracy & edited by our geotechnical team.

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