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Impact of alkalinity sources on the life-cycle energy efficiency of mineral carbonation technologies

doi: 10.1039/c2ee22180b
handle: 11577/3526006
This study builds a holistic, transparent life cycle assessment model of a variety of aqueous mineral carbonation processes using a hybrid process model and economic input–output life cycle assessment approach (hybrid EIO-LCA). The model allows for the evaluation of the tradeoffs between different reaction enhancement processes while considering the larger lifecycle impacts on energy use and material consumption. A preliminary systematic investigation of the tradeoffs inherent in mineral carbonation processes is conducted to provide guidance for the optimization of the life-cycle energy efficiency of various proposed mineral carbonation processes. The life-cycle assessment of aqueous mineral carbonation suggests that a variety of alkalinity sources and process configurations are capable of net CO2 reductions. The total CO2 storage potential for the alkalinity sources considered in the U.S. ranges from 1.8% to 23.7% of U.S. CO2 emissions, depending on the assumed availability of natural alkalinity sources and efficiency of the mineral carbonation processes.
- The University of Texas at Austin United States
- Stanford University United States
- Imperial College London United Kingdom
- University of Padua Italy
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).67 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 1% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 10% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 10%
