Microalgae Biomass Potential in Europe

Skarka, Johannes

doi:10.14512/tatup.21.1.72

Cited by 9 publications

(5 citation statements)

References 4 publications

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“…Based on measurements from different PBRs and strains, Williams and Laurens showed that only 30% of this theoretical energetic yield is usually obtained. Unlike the use of an overall “photosynthetic efficiency,” , which mixes inevitable biological losses and cultivation performance, this percentage can be argued to depend exclusively on the optimization level of the cultivation. In other words, it depends on how well the PBR geometry and operation parameters match the strain-specific “photobiological formula” .…”

Section: Methodsmentioning

confidence: 99%

Stochastic LCA Model of Upscaling the Production of Microalgal Compounds

Jouannais

Hindersin²,

Löhn

et al. 2022

Environ. Sci. Technol.

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Microalgae are currently being investigated for their promising metabolites but assessing the environmental impact of producing these compounds remains a challenge. Microalgae cultivation performance results from the complex interaction of biological, technological, geographical, and physical factors, which bioengineers try to optimize during the upscaling process. The path from the discovery of a microalgal compound to its industrial production is therefore highly uncertain. Nonetheless, it is key to anticipate the potential environmental impacts associated with the future production of a microalgal target compound. This is achieved in this study by developing an ex-ante, parameterized, and consequential LCA model that performs dynamic simulations of microalgae cultivation. The model is applied to calculate the environmental impacts of 9000 stochastically generated combinations of photobioreactor geometries and operational setups. The demonstration of the model is done for a fictive microalgal strain, parameterized to resemble Chlorella vulgaris, and a fictive target compound assumed to be a carbohydrate. The simulations are performed in Aalborg, Denmark, and Granada, Spain to appreciate geographical variability, which highly affects the requirements for thermoregulation. Open-source documentation allows full reproducibility and further use of the model for the ex-ante assessment of microalgal products.

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Section: Methodsmentioning

confidence: 99%

Stochastic LCA Model of Upscaling the Production of Microalgal Compounds

Jouannais

Hindersin²,

Löhn

et al. 2022

Environ. Sci. Technol.

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“…Similarly to any agricultural crop for which an increase in demand in Europe will be answered by different producers in distinct locations (a mix), an increase in demand for the bioprospected compound will be met by distinct microalgae plants in Europe belonging to a “compound production mix”. To anticipate the development of this compound production mix in Europe, we first assumed that the production would take place in the 10 countries which have the highest potential for microalgal biomass production as identified by Skarka: Spain (ES), Sweden (SE), Italy (IT), Portugal (PT), United Kingdom (UK), France (FR), Greece (EL), Cyprus (CY), Ireland (IE), and Germany (DE). The author identified these countries as the best combinations of temperature, solar irradiance, and available land after exclusion of urban, mountainous, and protected areas.…”

Section: Methodsmentioning

confidence: 99%

Stochastic Ex-Ante LCA under Multidimensional Uncertainty: Anticipating the Production of Undiscovered Microalgal Compounds in Europe

Jouannais

Pizzol

2022

Environ. Sci. Technol.

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Due to their biodiversity, microalgae represent a promising source of high-value compounds that bioprospecting is aiming to reveal. Performing an ex-ante Life Cycle Assessment (LCA) to anticipate and potentially minimize the environmental burden associated with the European production of a bioprospected microalgal compound is subject to substantial and multi-factorial uncertainty as the compound remains undiscovered. Given that any microalgal strain could potentially host the compound of interest, the ex-ante LCA should consider this bioprospecting uncertainty together with the uncertainty on the technology and the production mix. Using a parameterized cultivation simulation and consequential LCA model and an extensive stochastic pseudo Monte Carlo approach, we define and propagate techno-operational, bioprospecting, and production mix uncertainties for a microalgal compound being currently bioprospected in Europe. We perform global sensitivity analysis using different sampling strategies to identify the main contributors to the total output variance. Overall, the uncertainty propagation allowed us to define and analyze the probabilistic scope for the potential environmental impacts in the emerging production of high-value microalgal compounds in Europe based on current knowledge. These findings can support policy-making as well as actors in the microalgal sector toward technological paths with lower environmental impact.

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“…Another detailed study [31] based on a GIS model showed that algal biomass potential is limited by the limited availability of marginal land in densely populated Europe and by the slope of many of these areas or their status as protected areas. A general result was that about 50 Mt.…”

Section: Algal Biomass Availability In Europementioning

confidence: 99%

“…Maximum microalgae biomass resource potential per country in EU (Mt dry biomass per year) (Adapted from[31]). …”

mentioning

confidence: 99%

Feedstocks for Advanced Biofuels

Espí¹,

Ribas²,

Dı́az³

et al. 2020

Sustainable Mobility

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Advanced (also known as second-generation and third-generation) biofuels must comply with sustainability criteria related to the feedstock used (not competing directly or indirectly with food or feed crops) and to their greenhouse gases emission reduction. These fuels must reach at least 0.2% of transport energy used in Europe in 2022, 1% in 2025, and 3.5% by 2030. In this chapter, sustainable feedstocks that could be used for producing advanced biofuels are reviewed: energy crops grown on marginal land; wastes and residues-agricultural, forestry, food, municipal solid waste, and other organic wastes and residues; and novel feedstocks-such as aquatic biomass (macroalgae and microalgae).

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Microalgae Biomass Potential in Europe

Cited by 9 publications

References 4 publications

Stochastic LCA Model of Upscaling the Production of Microalgal Compounds

Stochastic LCA Model of Upscaling the Production of Microalgal Compounds

Stochastic Ex-Ante LCA under Multidimensional Uncertainty: Anticipating the Production of Undiscovered Microalgal Compounds in Europe

Feedstocks for Advanced Biofuels

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