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Technologies-based potential analysis on saving energy and water of China's iron and steel industry

pmid: 31677463
Water and energy conservation are indispensable commitments to achieve the sustainable development of the iron and steel industry. Hereby, this study established an evaluation framework to model the water and energy consumption in the iron and steel industry. This framework quantitatively assessed the energy and water saving with adoption of conventional and emerging technologies. Thirty mainstream technologies, among which 21 focused on energy saving and the remaining 9 focused on water saving, were selected for analysis. Five scenarios were developed to examine systematic water- and energy-saving potentials, including benchmark (BM) scenario, constrained product (CP) scenario, business as usual (BAU) scenario, and benefit/cost-driven (BD) scenario and strengthened policy (SP) scenario. The results show that the energy-saving potentials of BAU, BD and SP scenarios are 1.75 PJ, 1.21 PJ and 1.65 PJ, respectively. The water-saving potentials of BAU, BD and SP scenarios are 4.83 billion m3, 5.71 billion m3 and 9.15 billion m3, respectively. The specific energy consumption and water consumption decreased to 15.01-15.59 GJ/t and 54.13-58.77 m3/t, respectively. This study suggested to implement encouraging policies in prompt popularity rate of technologies, and promote energy-saving and water-saving technologies to achieve sustainable development of iron and steel industry.
- University of Maryland, College Park United States
- Northeastern University China (People's Republic of)
- University of Silesia Poland
- University of Silesia Poland
- University of Silesia in Katowice Poland
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).40 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 10% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 10% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 1%
