Meta-Analysis of Life Cycle Assessment Studies on Electricity Generation with Carbon Capture and Storage
Article first published online: 27 MAR 2012
© 2012 by Yale University
Journal of Industrial Ecology
Special Issue: Meta-Analysis of Life Cycle Assessments
Volume 16, Issue Supplement s1, pages S155–S168, April 2012
How to Cite
Schreiber, A., Zapp, P. and Marx, J. (2012), Meta-Analysis of Life Cycle Assessment Studies on Electricity Generation with Carbon Capture and Storage. Journal of Industrial Ecology, 16: S155–S168. doi: 10.1111/j.1530-9290.2011.00435.x
- Issue published online: 3 MAY 2012
- Article first published online: 27 MAR 2012
- carbon dioxide (CO2) emissions;
- environmental impact;
- industrial ecology;
- life cycle assessment (LCA);
In the last decade, numerous life cycle assessments (LCAs) on environmental impacts of electricity generation with carbon capture and storage (CCS) have been conducted. This meta-analysis comprises 15 LCAs of the three CCS technologies (postcombustion, oxyfuel, precombustion) with a focus on greenhouse gas reduction for different regions (Europe, United States, Japan, global), different fuels (hard coal, lignite, natural gas), and different time horizons (between the present and 2050). It presents a condensed overview of methodological variations, findings, and conclusions gathered from these LCAs.
All LCAs show the expected reduction in global warming potential but an increase in many other impact categories, regardless of capture technology, time horizon, or fuel considered. Three parameter sets have been identified that have a significant impact on the results: (1) power plant efficiency and energy penalty of the capture process, (2) carbon dioxide capture efficiency and purity, and (3) fuel origin and composition.
This meta-analysis proves that LCA is a helpful tool to investigate the variety of environmental consequences associated with CCS. However, there are differences in the underlying assumptions of the LCAs as well as methodological shortcomings that yield heterogeneity of results. Without a better understanding of the technology, it is not possible to give a comprehensive picture. There also remains a wide field of subjects and technologies that have not yet been covered.