Journal
ENVIRONMENTAL SCIENCE & TECHNOLOGY
Volume 48, Issue 10, Pages 6035-6042Publisher
AMER CHEMICAL SOC
DOI: 10.1021/es4055719
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Funding
- U.S. Department of Energy (DOE)
- Argonne National Laboratory is a DOE laboratory [DE-AC02-06CH11357]
- NREL is a national laboratory of the U.S. Department of Energy, Office of Energy Efficiency & Renewable Energy [DE-AC36-08GO28308]
- Pacific Northwest National Laboratory [DE-AC05-76RL01830]
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Costs, emissions, and resource availability were modeled for the production of 5 billion gallons yr(-1) (5 BGY) of renewable diesel in the United States from Chlorella biomass by hydrothermal liquefaction (HTL). The HTL model utilized data from a continuous 1-L reactor including catalytic hydrothermal gasification of the aqueous phase, and catalytic hydrotreatment of the HTL oil. A biophysical algae growth model coupled with weather and pond simulations predicted biomass productivity from experimental growth parameters, allowing site-by-site and temporal prediction of biomass production. The 5 BGY scale required geographically and climatically distributed sites. Even though screening down to 5 BGY significantly reduced spatial and temporal variability, site-to-site, season-to-season, and interannual variations in productivity affected economic and environmental performance. Performance metrics based on annual average or peak productivity were inadequate; temporally and spatially explicit computations allowed more rigorous analysis of these dynamic systems. For example, 3-season operation with a winter shutdown was favored to avoid high greenhouse gas emissions, but economic performance was harmed by underutilized equipment during slow-growth periods. Thus, analysis of algal biofiiel pathways must combine spatiotemporal resource assessment, economic analysis, and environmental analysis integrated over many sites when assessing national scale performance.
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