In silico optimization for production of biomass and biofuel feedstocks from microalgae.
In silico optimization for production of biomass and biofuel feedstocks from microalgae.
复制标题
利用微藻生产生物质和生物燃料原料的计算机优化。
DOI:
10.1007/s10811-014-0342-2
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发表时间:
2015
影响因子:
3.3
通讯作者:
Kenny P
中科院分区:
文献类型:
--
作者:
Kenny P
Optimization of the production rate of biomass rich in N (e.g. for protein) or C (e.g. for biofuels) is key to making algae-based technology commercially viable. Creating the appropriate conditions to achieve this is a challenge; operational permutations are extensive, while geographical variations localise effective methods of cultivation when utilising natural illumination. As an aid to identifying suitable operational envelopes, a mechanistic acclimative model of microalgae growth is used for the first time to simulate production in virtual systems over a broad latitudinal range. Optimization of production is achieved through selection of strain characteristics, system optical depth, nutrient supply, and dilution regimes for different geographic and seasonal illumination profiles. Results reveal contrasting requirements for optimising biomass vs biofuels production. Trade-offs between maximising areal and volumetric production while conserving resources, plus hydrodynamic limits on reactor design, lead to quantifiable constraints for optimal operational permutations. Simulations show how selection of strains with a high maximum growth rate,Um, remains the prime factor enabling high productivity. Use of an f/2 growth medium with a culture dilution rate set at ~25 % ofUmdelivers sufficient nutrition for optimal biomass production. Further, sensitivity to the balance between areal and volumetric productivity leads to a well-defined critical depth at ~0.1 m at which areal biofuel production peaks with use of a low concentration f/4 growth medium combined with a dilution rate ~15 % ofUm. Such analyses, and developments thereof, will aid in developing a decision support tool to enable more productive methods of cultivation.