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  • 标题:Sensitivity analysis of parameters affecting carbon footprint of fossil fuel power plants based on life cycle assessment scenarios
  • 本地全文:下载
  • 作者:F. Dalir ; M. Shafiepour Motlagh ; K. Ashrafi
  • 期刊名称:Global Journal of Environmental Science and Management
  • 印刷版ISSN:2383-3572
  • 电子版ISSN:2383-3866
  • 出版年度:2017
  • 卷号:3
  • 期号:1
  • 页码:75-88
  • DOI:10.22034/gjesm.2017.03.01.008
  • 语种:English
  • 出版社:Iran Solid Waste Association
  • 其他摘要:In this study a pseudo comprehensive carbon footprint model for fossil fuel power plants is presented. Parameters which their effects are considered in this study include: plant type, fuel type, fuel transmission type, internal consumption of the plant, degradation, site ambient condition, transmission and distribution losses. Investigating internal consumption, degradation and site ambient condition effect on carbon footprint assessment of fossil fuel power plant is the specific feature of the proposed model. To evaluate the model, a sensitivity analysis is performed under different scenarios covering all possible choices for investigated parameters. The results show that carbon footprint of fossil fuel electrical energy that is produced, transmitted and distributed, varies from 321 g CO2 eq/kWh to 980 g CO2 equivalent /kWh. Carbon footprint of combined cycle with natural gas as main fuel is the minimum carbon footprint. Other factors can also cause indicative variation. Fuel type causes a variation of 28%. Ambient condition may change the result up to 13%. Transmission makes the carbon footprint larger by 4%. Internal consumption and degradation influence the result by 2 and 2.5%, respectively. Therefore, to minimize the carbon footprint of fossil fuel electricity, it is recommended to construct natural gas ignited combined cycles in low lands where the temperature is low and relative humidity is high. And the internal consumption is as least as possible and the maintenance and overhaul is as regular as possible.
  • 其他关键词:Carbon footprint ; Life cycle assessment (LCA) ; Modeling ; Power plant ; Sensitivity
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