Abstract

Cities consume most of the global energy and account for approximately 75% of global CO2 emissions. Moreover, resource-based cities tend to consume higher amounts of fossil fuel and produce higher carbon emissions than other cities, whereas there are still insufficiencies about energy carbon reduction in resource-based cities in developed urban agglomerations. Therefore, it is necessary to explore the energy planning of such cities to achieve carbon peaking and carbon neutrality, and this is crucial for achieving carbon neutrality in urban agglomerations. This study aims to apply a scenario-based analysis approach to a resource-based heavy industrial city in China, Tangshan, based on the Long-range Energy Alternative Planning model, to explore Tangshan's future energy consumption, generation, and associated carbon emissions from 2010 to 2050. The impacts of different energy policies are analyzed for the Tangshan energy system by considering four scenarios. Under each scenario, energy consumption increased steadily by 2050, but the growth rate is different. The business as usual scenario is the fastest, and the low-carbon scenario is the slowest. In the comprehensive and integrated low-carbon transition scenarios, CO2 is expected to peak at 298.34 million tons (Mt) in 2028. The main industrial sectors of Tangshan with high output value, high energy consumption, and high carbon emissions include smelting and pressing of ferrous metals, petroleum processing and coking, raw chemical materials and chemical products, etc. Combining Tangshan's coal resource endowment, the development of renewable energy, and introducing advanced technology can effectively reduce carbon emissions and increase the diversity of energy supply. We analyzed the cost-benefit of the energy system and found that the implementation of carbon capture and storage technology could effectively reduce carbon emissions by 219.62 Mt and increased costs by 563.12 billion yuan. The research could provide a scientific basis for the medium and long-term energy sustainable transformation of resource-based cities, especially for resource-based cities in urban agglomerations.

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