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Multi-Scale Modeling of Intensive Macroalgae Cultivation and Marine Nitrogen Sequestration

AbstractMulti-scale macroalgae growth models are required for the efficient design of sustainable, economically viable and environmentally safe farms. Here, we develop a multi-scale model for Ulva sp. macroalgae growth and nitrogen sequestration in an intensive cultivation farm, regulated by temperature, light and nutrients. The model incorporates a range of scales by incorporating spatial effects in two steps: light extinction at the reactor scale (1 m) and nutrient absorption at the farm scale (1 km). The model was validated on real data from an experimental reactor installed in the sea. Biomass production rates, chemical compositions and nitrogen removal were simulated under different seasons, levels of dilution in the environment and water-exchange rate in the reactor. This multi-scale model provides an important tool for environmental authorities and seaweed farmers who desire to upscale to large bioremediation and/or macroalgae biomass production farms, thus promoting the marine sustainable development and the macroalgae-based bioeconomy.
- University of California System United States
- Department of Mechanical Engineering University of California, Santa Barbara United States
- Department of Mechanical Engineering University of California at Berkeley United States
- University of California, Berkeley United States
- Department of Mechanical Engineering University of California at Berkeley United States
570, Conservation of Natural Resources, Life on Land, QH301-705.5, Nitrogen, Models, Biological, Article, Ulva, Models, Biomass, Biology (General), Ecosystem, 660, Reproducibility of Results, Biological, Seaweed, Seasons, Algorithms
570, Conservation of Natural Resources, Life on Land, QH301-705.5, Nitrogen, Models, Biological, Article, Ulva, Models, Biomass, Biology (General), Ecosystem, 660, Reproducibility of Results, Biological, Seaweed, Seasons, Algorithms
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).21 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 10% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Average impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 10%
