Life-cycle assessment of hydrogen utilization in power generation: A systematic review of technological and methodological choices

被引:6
|
作者
Rinawati, Dyah Ika [1 ,2 ]
Keeley, Alexander Ryota [1 ,3 ]
Takeda, Shutaro [1 ]
Managi, Shunsuke [1 ,3 ]
机构
[1] Kyushu Univ, Dept Civil Engn, Fukuoka, Japan
[2] Diponegoro Univ, Dept Ind Engn, Semarang, Indonesia
[3] Kyushu Univ, Urban Inst, Fukuoka, Japan
来源
关键词
life-cycle assessment; hydrogen; power generation; environmental impact; electricity; FUEL-CELL; ENVIRONMENTAL IMPACTS; ENERGY-SYSTEMS; GAS; PERFORMANCE; STORAGE; EMISSIONS; DESIGN;
D O I
10.3389/frsus.2022.920876
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Interest in reducing the greenhouse gas emissions from conventional power generation has increased the focus on the potential use of hydrogen to produce electricity. Numerous life-cycle assessment (LCA) studies of hydrogen-based power generation have been published. This study reviews the technological and methodological choices made in hydrogen-based power generation LCAs. A systematic review was chosen as the research method to achieve a comprehensive and minimally biased overview of hydrogen-based power generation LCAs. Relevant articles published between 2004 and 2021 were identified by searching the Scopus and Web of Science databases. Electrolysis from renewable energy resources was the most widely considered type of hydrogen production in the LCAs analyzed. Fuel cell technology was the most common conversion equipment used in hydrogen-based electricity LCAs. A significant number of scenarios examine the use of hydrogen for energy storage and co-generation purposes. Based on qualitative analysis, the methodological choices of LCAs vary between studies in terms of the functional units, allocations, system boundaries, and life-cycle impact assessment methods chosen. These discrepancies were likely to influence the value of the environmental impact results. The findings of the reviewed LCAs could provide an environmental profile of hydrogen-based electricity systems, identify hotspots, drive future research, define performance goals, and establish a baseline for their large-scale deployment.
引用
收藏
页数:19
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