Driving toward sustainable algal fuels: A harmonization of techno-economic and life cycle assessments
Open accessAbstract
Research efforts have investigated a range of system designs for algae growth and conversion into biofuels. The economic feasibility and environmental impact of these systems are frequently evaluated through techno-economic analyses (TEA) and life-cycle assessment (LCA), which typically determine the levelized cost of fuel production in gallons of gasoline equivalent (MFSP, in $-gge−1), global warming potential (GWP, in g CO2-eq-MJfuel−1), and net energy ratio (NER, unitless). While the outputs from these models seem comparable, the results often conceal the impact of a large number of assumptions inherent to the modeling, limiting direct comparisons. As such, a direct comparison of the modeling results as published can be misleading due to differences in critical assumptions and/or foundational methodology. This work applies harmonization methodology to several sustainability assessment studies found in the literature with the goal of enhancing comparability through implementation of a standard set of assumptions. For the economic evaluation, two harmonization efforts were performed: the first focused on harmonizing productivity, economic assumptions, and cost year for the entire growth to product process; the second compared only downstream fuel conversion technologies by fixing the biomass cost, thereby removing the uncertainty of upstream-growth assumptions. For LCA, harmonization focused on productivity and system boundary. The results of these efforts show a decrease of 43% in the range of reported fuel prices and minimal redcution in the range of LCA results. Both TEA and LCA harmonization efforts then investigated the impact of productivity by simulating a range of biomass productivity values (12.5, 25, and 50 g-m−2 day−1). The work reveals limitations to both the economic and environmental benefits of productivity improvements past approximately 35 g-m−2 day−1. Results highlight the need to redirect research efforts not only to increase productivities, but also to other areas where investments can make a greater impact in terms of economic viability and environmental impact.
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Despite intensive research, multiple technical challenges must be addressed to produce low-cost algal biomass at the industrial scale.
“Despite intensive research, multiple technical challenges must be addressed to produce low-cost algal biomass at the industrial scale [2], [4], [7], [8].”
From Implications of Pond Reliability on the Techno-Economic and Life Cycle Environmental Impacts of Algal Biofuels (2024) · cites this paper as [2]
This critical aspect of outdoor biomass cultivation has been commonly overlooked by models informing techno-economic analyses and life cycle assessments of algal biofuels.
“This critical aspect of outdoor biomass cultivation has been commonly overlooked by models informing techno-economic analyses (TEAs) and life cycle assessments (LCAs) [1], [2], [8], [13]-[15] of algal biofuels.”
From Implications of Pond Reliability on the Techno-Economic and Life Cycle Environmental Impacts of Algal Biofuels (2024) · cites this paper as [2]
Existing process models in the literature have often used facility operational days as a proxy to model pond upsets.
“Existing process models in the literature have often used facility operational days as a proxy to model pond upsets.”
From Implications of Pond Reliability on the Techno-Economic and Life Cycle Environmental Impacts of Algal Biofuels (2024) · cites this paper as [2]
Several studies assume optimal facility performance and an optimistic annual pond downtime of 35 days to account for potential culture crashes, freezing events, or scheduled maintenance.
“For instance, several studies [2], [3], [8], [16], assume optimal facility performance and assume an optimistic annual pond downtime of 35 days to account for potential culture crashes, freezing events, or scheduled maintenance.”
From Implications of Pond Reliability on the Techno-Economic and Life Cycle Environmental Impacts of Algal Biofuels (2024) · cites this paper as [2]
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Cites
Net energy and greenhouse gas emission evaluation of biodiesel derived from microalgae
Batan, L., Quinn, J., Willson, B., & Bradley, T. (2010) · Environmental Science & Technology · doi:10.1021/es102052y · Cited by 360 · see citing works
Self-citationAn economic, sustainability, and energetic model of biodiesel production from microalgae
Delrue, F., Setier, P.-A., Sahut, C., Cournac, L., Roubaud, A., Peltier, G., & Froment, A.-K. (2012) · Bioresource Technology · doi:10.1016/j.biortech.2012.02.020 · Cited by 335 · see citing works
Resource demand implications for us algae biofuels production scale-up
Pate, R., Klise, G., & Wu, B. (2011) · Applied Energy · doi:10.1016/j.apenergy.2011.04.023 · Cited by 315 · see citing works
Lifecycle assessment of microalgae to biofuel: Comparison of thermochemical processing pathways
Bennion, E. P., Ginosar, D. M., Moses, J., Agblevor, F., & Quinn, J. C. (2015) · Applied Energy · doi:10.1016/j.apenergy.2014.12.009 · Cited by 286 · see citing works
Self-citationBeal, C. M., Gerber, L. N., Sills, D. L., Huntley, M. E., Machesky, S. C., Walsh, M. J., Tester, J. W., Archibald, I., Granados, J., & Greene, C. H. (2015) · Algal Research · doi:10.1016/j.algal.2015.04.017 · Cited by 285 · see citing works
Microalgae Based Biorefinery Promoting Circular Bioeconomy-Techno Economic and Life-Cycle Analysis
Rajesh Banu, J., Preethi, Kavitha, S., Gunasekaran, M., & Kumar, G. (2020) · Bioresource Technology · doi:10.1016/j.biortech.2020.122822 · Cited by 280 · see citing works
Life cycle assessment of bio-jet fuel from hydrothermal liquefaction of microalgae
Fortier, M.-O. P., Roberts, G. W., Stagg-Williams, S. M., & Sturm, B. S. M. (2014) · Applied Energy · doi:10.1016/j.apenergy.2014.01.077 · Cited by 264 · see citing works
Techno-economic analysis of microalgal biomass production in a 1-ha Green Wall Panel (GWP®) plant
Tredici, M. R., Rodolfi, L., Biondi, N., Bassi, N., & Sampietro, G. (2016) · Algal Research · doi:10.1016/j.algal.2016.09.005 · Cited by 256 · see citing works
Comparative cost analysis of algal oil production for biofuels
Sun, A., Davis, R., Starbuck, M., Ben-Amotz, A., Pate, R., & Pienkos, P. T. (2011) · Energy · doi:10.1016/j.energy.2011.06.020 · Cited by 250 · see citing works
Liu, X., Saydah, B., Eranki, P., Colosi, L. M., Greg Mitchell, B., Rhodes, J., & Clarens, A. F. (2013) · Bioresource Technology · doi:10.1016/j.biortech.2013.08.112 · Cited by 246 · see citing works
Quantitative uncertainty analysis of life cycle assessment for algal biofuel production
Sills, D. L., Paramita, V., Franke, M. J., Johnson, M. C., Akabas, T. M., Greene, C. H., & Tester, J. W. (2013) · Environmental Science & Technology · doi:10.1021/es3029236 · Cited by 241 · see citing works
Techno-economic assessment of open microalgae production systems
Hoffman, J., Pate, R. C., Drennen, T., & Quinn, J. C. (2017) · Algal Research · doi:10.1016/j.algal.2017.01.005 · Cited by 241 · see citing works
Self-citationAlgae biodiesel life cycle assessment using current commercial data
Passell, H., Dhaliwal, H., Reno, M., Wu, B., Ben Amotz, A., Ivry, E., Gay, M., Czartoski, T., Laurin, L., & Ayer, N. (2013) · Journal of Environmental Management · doi:10.1016/j.jenvman.2013.06.055 · Cited by 215 · see citing works
Life cycle assessment on microalgal biodiesel production using a hybrid cultivation system
Adesanya, V. O., Cadena, E., Scott, S. A., & Smith, A. G. (2014) · Bioresource Technology · doi:10.1016/j.biortech.2014.04.051 · Cited by 183 · see citing works
Davis, R., Kinchin, C., Markham, J., Tan, E., Laurens, L., Sexton, D., Knorr, D., Schoen, P., & Lukas, J. (2014) · doi:10.2172/1159351 · Cited by 131 · see citing works
Mu, D., Ruan, R., Addy, M., Mack, S., Chen, P., & Zhou, Y. (2017) · Bioresource Technology · doi:10.1016/j.biortech.2016.12.108 · Cited by 78 · see citing works
Self-citationZhu, Y., Jones, S. B., Schmidt, A. J., Albrecht, K. O., Edmundson, S. J., & Anderson, D. B. (2019) · Algal Research · doi:10.1016/j.algal.2019.101467 · Cited by 77 · see citing works
Geographical assessment of microalgae biofuels potential incorporating resource availability
Quinn, J. C., Catton, K. B., Johnson, S., & Bradley, T. H. (2013) · BioEnergy Research · doi:10.1007/s12155-012-9277-0 · Cited by 67 · see citing works
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Chen, P. H., & Quinn, J. C. (2021) · Applied Energy · doi:10.1016/j.apenergy.2021.116613 · Cited by 120 · see citing works
Self-citationSomers, M. D., Chen, P., Clippinger, J., Cruce, J. R., Davis, R., Lammers, P. J., & Quinn, J. C. (2021) · Algal Research · doi:10.1016/j.algal.2021.102419 · Cited by 49 · see citing works
Greene, J. M., Quiroz, D., Limb, B. J., & Quinn, J. C. (2025) · Environmental Science & Technology · doi:10.1021/acs.est.4c06742 · Cited by 39 · see citing works
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Quiroz, D., Greene, J. M., Limb, B. J., & Quinn, J. C. (2025) · Environmental Science & Technology · doi:10.1021/acs.est.5c09113 · Cited by 21 · see citing works
Self-citationSingh, U., Naaz, F., Hawkins, T. R., Weinberg, E., Banerjee, S., Mroz, R., Ohri, N., Zhang, J., Lee, Y.-Y., Chen, F., et al. (2025) · Sustainable Energy & Fuels · doi:10.1039/d5se00329f · Cited by 12 · see citing works
Quiroz, D., McGowen, J., & Quinn, J. C. (2024) · Journal of Cleaner Production · doi:10.1016/j.jclepro.2024.143178 · Cited by 7 · see citing works
Self-citationBanks, A. B., Chen, P. H., Quiroz-Arita, C., Davis, R. W., & Quinn, J. C. (2023) · Algal Research · doi:10.1016/j.algal.2023.103100 · Cited by 3 · see citing works
Self-citation
- Authors
- Cruce, J. R., Beattie, A., Chen, P., Quiroz, D., Somers, M., Compton, S., DeRose, K., Beckstrom, B., & Quinn, J. C.
- Affiliations
- Colorado State University (US)
- Corresponding author
- Quinn, Jason C.
- Venue
- Algal Research
- Publisher
- Elsevier BV
- Published
- 2021-04
- Volume
- 54
- Pages
- 102169
- ISSN
- 2211-9264 (ISSN-L)
- OpenAlex
- W3123275429
- Cited by
- 53
- References
- 18
- Citations by year
- 2026: 10 · 2025: 13 · 2024: 5 · 2023: 8 · 2022: 9 · 2021: 8
- FWCI
- 1.41
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Algal Research (publishedVersion, cc-by-nc-nd)
- OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information) (submittedVersion)
- Funders
- U.S. Department of Energy
- Office of Energy Efficiency and Renewable Energy (DE-EE0007562, DE-FE0029623, 26336, DE-EE0008515)
- Bioenergy Technologies Office (DE-EE0008245)
- Topics
- Physical Sciences › Energy › Renewable Energy, Sustainability and the Environment › Algal biology and biofuel production
- Life Sciences › Agricultural and Biological Sciences › Agronomy and Crop Science › Bioenergy crop production and management
- Physical Sciences › Environmental Science › Environmental Engineering › Environmental Impact and Sustainability
- Keywords
- algal biofuels, techno-economic analysis, life cycle assessment, global warming potential, net energy ratio, algal productivity, biomass conversion technologies, system boundaries, economic feasibility, environmental impact
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