Life cycle assessment of Brazilian sugarcane products: GHG emissions and energy use

被引:173
作者
Seabra, Joaquim E. A. [1 ,2 ]
Macedo, Isaias C. [1 ]
Chum, Helena L. [3 ]
Faroni, Carlos E. [4 ]
Sarto, Celso A. [4 ]
机构
[1] Univ Estadual Campinas, Sao Paulo, Brazil
[2] Brazilian Bioethanol Sci & Technol Lab CTBE, Sao Paulo, Brazil
[3] Natl Renewable Energy Lab NREL, US DOE, Golden, CO USA
[4] Ctr Tecnol Canavieira CTC, Sao Paulo, Brazil
来源
BIOFUELS BIOPRODUCTS & BIOREFINING-BIOFPR | 2011年 / 5卷 / 05期
关键词
Saccharum officinarum; GHG emissions mitigation; global warming; energy balance; uncertainty analysis; sugarcane refineries; ETHANOL-PRODUCTION; BALANCES; CORN;
D O I
10.1002/bbb.289
中图分类号
Q81 [生物工程学(生物技术)]; Q93 [微生物学];
学科分类号
071005 ; 0836 ; 090102 ; 100705 ;
摘要
Sugarcane is currently the main renewable energy source in Brazil. Due to the importance of the cane industry and its contribution to a wide range of biobased energy and other products, LCA studies regarding cane-derived products are needed to assess their environmental benefits. The main objective of this work was the assessment of life cycle energy use and greenhouse gas (GHG) emissions related to cane sugar and ethanol, considering bagasse and electricity surpluses as coproducts. We performed an overall balance for the Brazilian Center-South Region, adopting different methods to evaluate sugar and ethanol production separately. The GREET 1.8c.0 model was used for the 'well-to-wheels' calculations but adapted to the comprehensive set of Brazilian parameters that best represent the Center-South Region. For the reference case, fossil energy use and GHG emissions related to sugar production were evaluated as 721 kJ/kg and 234 g CO(2)eq/kg, respectively. For the ethanol life cycle, these values were 80 kJ/MJ and 21.3 g CO(2)eq/MJ. Special attention was paid to the variation of some parameters among producing units based on data collected by industry. The consequent uncertainties in ethanol life cycle emissions were assessed through a Monte Carlo analysis based on assigned distribution of probability curves for eleven selected parameters and informed by partial statistical data available from industry for distribution generation. Projections were also made for 2020 scenario parameters based on the best in current class technologies and technological improvements deemed commercially possible today. Published in 2011 by John Wiley & Sons, Ltd
引用
收藏
页码:519 / 532
页数:14
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