Enhancing Biomass Productivity by Forecast‐Informed Pond Operations

Microalgal cultivation for biofuels and proteins holds significant promise but faces challenges in achieving economically viable biomass productivity under variable environmental conditions. This study introduces a forecast-informed pond operation (FIPO) system that uses numerical weather prediction (NWP) ensemble forecasts and the biomass assessment tool (BAT) to optimize daily dilution rates for enhanced biomass production. In contrast to the current practice, where fixed dilution rates are based on operator experience, the FIPO system determines the optimal dilution rate based on future weather forecasts and biomass growth conditions. Our experiments validate the effectiveness of FIPO in both short- and long-term growth scenarios. In short-term experiments, FIPO increased biomass production by 21.3% compared to batch growth and 7.4% over fixed dilution (60% every 3 days) operations. The NWP forecast-informed operations achieved biomass production nearly identical to that using perfect weather forecasts, highlighting the accuracy of current NWP forecasts for guiding pond operations. In long-term experiments, FIPO resulted in biomass production increases of 13.3% and 17.8% compared to two fixed dilution rates (60% every 3 days and 20% daily). These findings underscore the viability of using NWP forecasts to optimize microalgal cultivation systems. By adjusting daily dilution rates in response to forecasted weather, operators can achieve higher biomass yields and mitigate risks associated with environmental variability. This study provides a foundation for future research and practical applications in commercial-scale microalgal production.

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Publication Details

Journal
Biotechnology and Bioengineering
Published
2025-02-07
DOI
https://doi.org/10.1002/bit.28952
Citations
1
Primary Topic
Algal biology and biofuel production
Type
article
Field-Weighted Citation Impact
0.36

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article

Enhancing Biomass Productivity by Forecast‐Informed Pond Operations

Song Gao, Michael H. Huesemann, Mark S. Wigmosta, Ning Sun et al.
1 citations
Biotechnology and Bioengineering
Algal biology and biofuel production
0.36
article

Enhancing Biomass Productivity by Forecast‐Informed Pond Operations

Song Gao, Michael H. Huesemann, Mark S. Wigmosta, Ning Sun, Hongxiang Yan
article en
1 citations

Abstract

Microalgal cultivation for biofuels and proteins holds significant promise but faces challenges in achieving economically viable biomass productivity under variable environmental conditions. This study introduces a forecast-informed pond operation (FIPO) system that uses numerical weather prediction (NWP) ensemble forecasts and the biomass assessment tool (BAT) to optimize daily dilution rates for enhanced biomass production. In contrast to the current practice, where fixed dilution rates are based on operator experience, the FIPO system determines the optimal dilution rate based on future weather forecasts and biomass growth conditions. Our experiments validate the effectiveness of FIPO in both short- and long-term growth scenarios. In short-term experiments, FIPO increased biomass production by 21.3% compared to batch growth and 7.4% over fixed dilution (60% every 3 days) operations. The NWP forecast-informed operations achieved biomass production nearly identical to that using perfect weather forecasts, highlighting the accuracy of current NWP forecasts for guiding pond operations. In long-term experiments, FIPO resulted in biomass production increases of 13.3% and 17.8% compared to two fixed dilution rates (60% every 3 days and 20% daily). These findings underscore the viability of using NWP forecasts to optimize microalgal cultivation systems. By adjusting daily dilution rates in response to forecasted weather, operators can achieve higher biomass yields and mitigate risks associated with environmental variability. This study provides a foundation for future research and practical applications in commercial-scale microalgal production.

Biotechnology and BioengineeringVol. 122(5)
Pacific Northwest National Laboratory (US), University of Washington (US)
U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy, Bioenergy Technologies Office, Office of Energy Efficiency, Pacific Northwest National Laboratory
Openalex Percentile: Top 46%
Algal biology and biofuel production
0.36
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