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 biofuel pathways must combine spatiotemporal resource assessment, economic analysis, and environmental analysis integrated over many sites when assessing national scale performance.