Complete Data Inventory of a Geothermal Power Plant for Robust Cradle-to-Grave Life Cycle Assessment Results

被引:17
作者
Tosti, Lorenzo [1 ,2 ]
Ferrara, Nicola [1 ,2 ]
Basosi, Riccardo [1 ,2 ,3 ]
Parisi, Maria Laura [1 ,2 ,3 ]
机构
[1] Univ Siena, Dept Biotechnol Chem & Pharm, R2ES Lab, I-53100 Siena, Italy
[2] CSGI Consortium Colloid & Surface Sci, Via Lastruccia 3, I-50019 Sesto Fiorentino, Italy
[3] CNR, Inst Chem OrganoMetall Cpds, CNR, ICCOM, I-50019 Sesto Fiorentino, Italy
基金
欧盟地平线“2020”;
关键词
geothermal energy; flash technology; Bagnore power plant; life cycle assessment; pedigree matrix; ELECTRICITY; IMPACT; LCA;
D O I
10.3390/en13112839
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
Technologies to produce electric energy from renewable geothermal source are gaining increasing attention, due to their ability to provide a stable output suitable for baseload production. Performing life cycle assessment (LCA) of geothermal systems has become essential to evaluate their environmental performance. However, so far, no documented nor reliable information has been made available for developing robust LCA studies. This work provides a comprehensive inventory of the Italian Bagnore geothermal power plants system. The inventory is based exclusively on primary data, accounting for every life cycle stage of the system. Data quality was assessed by means of a pedigree matrix. The calculated LCA results showed, with an overall low level of uncertainty (2-3%), that the commissioning and operational phases accounted for more than 95% of the environmental profile. Direct emissions to atmosphere were shown to be the major environmental impact, particularly those released during the operational phase (84%). The environmental performances comparison with the average Italian electricity mix showed that the balance is always in favor of geothermal energy production, except in the climate change impact category. The overall outcome confirms the importance, for flash technology employing fluid with a high concentration of gas content, of using good quality primary data to obtain robust results.
引用
收藏
页数:19
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