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Author:

Cui, S. (Cui, S..) | Zhang, D. (Zhang, D..) | Sun, B. (Sun, B..) | Meng, L. (Meng, L..) | Yang, Z. (Yang, Z..) | Nie, Z. (Nie, Z..)

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Scopus

Abstract:

Nickel production is a typical multi-element symbiotic smelting process, and inventory allocation is an important technical factor that restricts the accuracy of its life cycle assessment. In this study, the flash furnace smelting process of nickel sulfide ore with the most intensive symbiotic reaction was taken as the research object, and various inventory allocation methods such as system boundary extension, physical relationship and mass allocation were adopted to allocate CO2 emissions among the three elements of Ni, Cu and S. The allocation calculation results by system boundary extension show that the allocation factor of non-metallic symbiotic elements is 29. 86%, and the allocation factor of metal symbiotic elements is 70. 14% . The results show that the system boundary extension method is not suitable for intermediate products. The factor of physical relationship allocation are accurate, but need to be supported by a large number of process parameters. The mass allocation is easy to calculate, however, its accuracy depends on the differences of physical and chemical properties between symbiotic products. © 2024 Beijing University of Technology. All rights reserved.

Keyword:

metal symbiosis nickel carbon emission inventory allocation life cycle assessment (LCA) metallurgy

Author Community:

  • [ 1 ] [Cui S.]College of Materials Science and Engineering, Beijing University of Technology, Beijing, 100124, China
  • [ 2 ] [Cui S.]National Engineering Laboratory for Industrial Big Data Application Technology, Beijing University of Technology, Beijing, 100124, China
  • [ 3 ] [Zhang D.]College of Materials Science and Engineering, Beijing University of Technology, Beijing, 100124, China
  • [ 4 ] [Zhang D.]National Engineering Laboratory for Industrial Big Data Application Technology, Beijing University of Technology, Beijing, 100124, China
  • [ 5 ] [Sun B.]College of Materials Science and Engineering, Beijing University of Technology, Beijing, 100124, China
  • [ 6 ] [Sun B.]National Engineering Laboratory for Industrial Big Data Application Technology, Beijing University of Technology, Beijing, 100124, China
  • [ 7 ] [Meng L.]College of Materials Science and Engineering, Beijing University of Technology, Beijing, 100124, China
  • [ 8 ] [Meng L.]National Engineering Laboratory for Industrial Big Data Application Technology, Beijing University of Technology, Beijing, 100124, China
  • [ 9 ] [Yang Z.]College of Materials Science and Engineering, Beijing University of Technology, Beijing, 100124, China
  • [ 10 ] [Yang Z.]National Engineering Laboratory for Industrial Big Data Application Technology, Beijing University of Technology, Beijing, 100124, China
  • [ 11 ] [Nie Z.]College of Materials Science and Engineering, Beijing University of Technology, Beijing, 100124, China
  • [ 12 ] [Nie Z.]National Engineering Laboratory for Industrial Big Data Application Technology, Beijing University of Technology, Beijing, 100124, China

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Source :

Journal of Beijing University of Technology

ISSN: 0254-0037

Year: 2024

Issue: 10

Volume: 50

Page: 1170-1178

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 6

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