MyJournals Home  

RSS FeedsEnergies, Vol. 16, Pages 4498: Carbon-Neutral Steel Production and Its Impact on the Economies of China, Japan, and Korea: A Simulation with E3ME-FTT:Steel (Energies)

 
 

2 june 2023 12:13:15

 
Energies, Vol. 16, Pages 4498: Carbon-Neutral Steel Production and Its Impact on the Economies of China, Japan, and Korea: A Simulation with E3ME-FTT:Steel (Energies)
 


The iron and steel industry is a large emitter of CO2 globally. This is especially true for the iron and steel industries in China, Japan, and Korea due to their production volumes and the prevalence of carbon-based steel production. With few low-carbon and commercially available alternatives, the iron and steel industry is truly a hard-to-abate sector. Each of the countries of interest have committed to a net-zero future involving the mitigation of emissions from steel production. However, few studies have investigated the means by which to achieve decarbonization beyond the inclusion of price signalling policies (e.g., carbon tax or emission trading schemes). Here, we use E3ME-FTT:Steel to simulate technology diffusion in the ISI under several policy environments and we investigate the likely impacts on the wider economy. The results show that penalizing carbon intensive processes can incentivize a transition towards scrap recycling, but it is relatively unsuccessful in aiding the uptake of low carbon primary steelmaking. A combination of support and penalizing policies can achieve deep decarbonisation (>80% emission reduction compared with the baseline). Mitigating the emissions in the iron and steel industry can lead to economic benefits in terms of GDP (China: +0.8%; Japan: +1.3%; Korea: +0.1%), and employment (Japan: +0.7%; Korea: +0.3%) with China, where job losses in the coal sector would negate job gains elsewhere, as the exception.


 
86 viewsCategory: Biophysics, Biotechnology, Physics
 
Energies, Vol. 16, Pages 4497: Exploring the Impact of Economic Growth on the Environment: An Overview of Trends and Developments (Energies)
Energies, Vol. 16, Pages 4499: Forecasting Electricity Demand in Turkey Using Optimization and Machine Learning Algorithms (Energies)
 
 
blog comments powered by Disqus


MyJournals.org
The latest issues of all your favorite science journals on one page

Username:
Password:

Register | Retrieve

Search:

Physics


Copyright © 2008 - 2024 Indigonet Services B.V.. Contact: Tim Hulsen. Read here our privacy notice.
Other websites of Indigonet Services B.V.: Nieuws Vacatures News Tweets Nachrichten