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作者:

Sun, Wanyi (Sun, Wanyi.) | Gong, Xianzheng (Gong, Xianzheng.) | Sun, Boxue (Sun, Boxue.) | Ding, Qing (Ding, Qing.)

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EI Scopus

摘要:

This study analyzed the environmental impacts due to lead production in China, which is the largest producer and consumer of lead in the world, by the method of life cycle assessment (LCA). Based on the Chinese refined lead smelting process, a process-based life cycle assessment model was established to assess the environmental load of lead production system which includes the processes of mining, beneficiation, smelting, electrorefining and transportation. The result shows that the cumulative consumption of electricity and the cumulative emission of greenhouse gases for the production of 1t of refined lead are 1111.93kWh and 2.06E+03kg CO2 eq, respectively. Smelting process is the largest contributor to the environmental impact load, accounting for 51.16% of the total environmental impact. The environmental category of human toxicity potential(HTP), accounting for 35.26% of the total environmental impact, is the largest contributor between different environmental categories to the total environmental impact, followed by metal depletion potential(MDP) and fossil depletion potential(FDP), accounting for 27.94% and 11.80% of the total environmental impact, respectively. Improving the resource efficiencies of the processes of smelting and beneficiation, and using cleaner energy to generate electricity are the key approaches to reduce the overall environmental impact of lead production in China. © 2019 Trans Tech Publications, Switzerland.

关键词:

Beneficiation Concentration (process) Environmental impact Greenhouse gases Lead smelting Life cycle

作者机构:

  • [ 1 ] [Sun, Wanyi]College of Materials Science and Engineering, Beijing University of Technology, 100 Ping Le Yuan, Chaoyang District, Beijing, China
  • [ 2 ] [Sun, Wanyi]National Engineering Laboratory for Industrial Big-data Application Technology, 100 Ping Le Yuan, Chaoyang District, Beijing, China
  • [ 3 ] [Gong, Xianzheng]College of Materials Science and Engineering, Beijing University of Technology, 100 Ping Le Yuan, Chaoyang District, Beijing, China
  • [ 4 ] [Gong, Xianzheng]National Engineering Laboratory for Industrial Big-data Application Technology, 100 Ping Le Yuan, Chaoyang District, Beijing, China
  • [ 5 ] [Sun, Boxue]College of Materials Science and Engineering, Beijing University of Technology, 100 Ping Le Yuan, Chaoyang District, Beijing, China
  • [ 6 ] [Sun, Boxue]National Engineering Laboratory for Industrial Big-data Application Technology, 100 Ping Le Yuan, Chaoyang District, Beijing, China
  • [ 7 ] [Ding, Qing]China National Institute of Standardization, 4 Zhi Chun Road, Haidian District, Beijing, China

通讯作者信息:

  • [gong, xianzheng]college of materials science and engineering, beijing university of technology, 100 ping le yuan, chaoyang district, beijing, china;;[gong, xianzheng]national engineering laboratory for industrial big-data application technology, 100 ping le yuan, chaoyang district, beijing, china

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来源 :

ISSN: 0255-5476

年份: 2018

卷: 944 MSF

页码: 1123-1129

语种: 英文

被引次数:

WoS核心集被引频次: 0

SCOPUS被引频次: 1

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