Prospective on energy related carbon emissions peak integrating optimized intelligent algorithm with dry process technique application for China's cement industry. (15th December 2018)

• Record Type: Journal Article
• Authors: Li, Wei; Gao, Shubin
• Is Part Of: Energy. Volume 165(2018)Part B
• Page Start: 33
• Page End: 54
• Publication Date: 2018-12-15
• Subjects: Carbon emissions peak -- Cement industry -- Scenario analysis -- Back Propagation Neural Network -- Particle Swarm Optimization -- The second generation of new dry cement technology systems; Power resources -- Periodicals; Power (Mechanics) -- Periodicals; Energy consumption -- Periodicals; 333.7905
• DOI: 10.1016/j.energy.2018.09.152
• Languages: English
• ISSNs: 0360-5442

Abstract

Abstract: Global climate change is a significant environmental problem. A major trigger of climate change is the excess carbon emissions. Based on 44 scenarios in the second generation of new dry cement technology systems, this paper establishes IPSO-BP model to forecast the carbon emissions peak of China's cement industry for 2016–2050 years. The results indicate that China's cement industry only implements capacity reduction plans and the second generation of new dry cement technology systems, so that carbon emissions can reach the peak before 2030. It is up to 19 years ahead of the carbon emissions peak of the basic scenario and the carbon emissions peak is reduced by 38 Mt. Moreover, this paper analyzes the technical combination of the earliest carbon emissions and the lowest carbon emissions. As for the earliest carbon emissions technical combination, China's cement industry carbon emissions will peak at 789.95 Mt in 2021. According to the lowest carbon emissions technical combination, China's cement industry carbon emissions will peak at 742.37 Mt in 2025. Accordingly, the conclusions will be helpful for making carbon emissions reduction policies for China's cement industry. Highlights: Carbon emission levels were reviewed from industrial output and technologies. The prediction model of carbon emissions was built with improved PSO and BPNN model. The scenarios were set to analyze carbon emission peak in China's cement industry. Importance of technique and capacity reduction in China's cement industry is defined. The best carbon emission peak plan for China's cement industry is discussed.