Author
Listed:
- Liu, Chunrui
- Sun, Mei
- Li, Yibo
- Han, Dun
- Xu, Wei
Abstract
The low-carbon transformation of iron and steel industry (ISI) is crucial to China ‘s goal of carbon neutrality, but this process is affected by long-term changes in production structure and short-term market fluctuations. This study constructs an inter-temporal stochastic evolutionary game framework of a coupled optimization model, aiming to analyze how policy mix can effectively stimulate the low-carbon transformation of ISI in uncertain environments, and identify the key factors affecting the strategic interaction between iron and steel enterprises (ISEs) and local governments. We also analyze the impact of uncertainty on the economic and environmental benefits of the low-carbon production path of ISEs. The research shows that the strategy interaction presents three-stage characteristics of policy-driven, bottleneck-watching and market-driven, and the evolution trend is closely related to factors including the initial strategy selection probability, taxation, and low-carbon value recognition of steel products. Under the single carbon emission trading (CET) policy, the probability of ISEs choosing a low-carbon production path has declined significantly during the bottleneck wait-and-see period, while the policy combination of green hydrogen subsidy and CET alleviates this downward trend and makes it converge to a steady state faster. Green hydrogen price and CET price are the sources of uncertainty affecting carbon emissions and benefits, with the uncertainty in green hydrogen prices having a more pronounced impact. This study provides an analytical tool and decision-making reference for understanding the dynamic mechanism of low-carbon transformation in ISI under uncertain environments.
Suggested Citation
Liu, Chunrui & Sun, Mei & Li, Yibo & Han, Dun & Xu, Wei, 2026.
"Low-carbon transformation of iron and steel: Combined effects of green hydrogen subsidy and carbon emissions trading under uncertain environments,"
Energy Economics, Elsevier, vol. 160(C).
Handle:
RePEc:eee:eneeco:v:160:y:2026:i:c:s0140988326002975
DOI: 10.1016/j.eneco.2026.109418
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