Is information and communications technology effective for industrial energy conservation and emission reduction? Evidence from three energy-intensive industries in China

Yihan Wang, Zongguo Wen, Xin Cao and Christian Doh Dinga

Renewable and Sustainable Energy Reviews, 2022, vol. 160, issue C

Abstract: Information and communications technology (ICT) can significantly contribute to industrial energy conservation and emission reduction by improving production and management efficiency. However, few studies have analyzed the technical mechanisms nor quantified the effects of ICT in the industrial sector, hence, existing studies cannot fully support the technology promotion strategy. To overcome this research gap, a nationwide industrial ICT system is built for the first time. Taking China's iron and steel, cement, and coal-fired power industry as case study, this paper has adopted bottom-up modeling approaches to simulate the material and energy metabolism of industrial production process, divided ICTs into six types based on their application units, and then quantified their energy conservation and emission reduction potential. In addition, Conservation Supply Curves, Latin Hypercube Sampling, and HSY algorithm methods are used to analyze their technical performance. Results show: (1) The application of ICT has considerable effects, as it can enlarge the industrial energy conservation and emission reduction potential by 10.7–21.7% in the next 15 years; (2) The differences between the technical costs of ICTs are significant, meanwhile more than 70% of this potential is cost-effective; (3) Uncertainty factors will affect technical potential and cost by 4–15%, amongst which technical popularity is the most sensitive factor. These findings reveal the significant effects of ICT and put forward policy suggestions on their promotion strategy in industrial energy conservation and emission reduction.

Keywords: Information and communications technology (ICT); Energy conservation; Emission reduction; Conservation supply curve; Uncertainty analysis; Sensitivity analysis (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (6)

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DOI: 10.1016/j.rser.2022.112344

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