DICP OpenIR
Dynamic modeling of green algae cultivation in a photobioreactor for sustainable biodiesel production
del Rio-Chanona, Ehecatl A.1,2; Liu, Jiao3,4; Wagner, Jonathan L.2; Zhang, Dongda1,2; Meng, Yingying3,4; Xue, Song3; Shah, Nilay1,2
KeywordBiodiesel Production Chlorophyll Fluorescence Dynamic Modeling Light Dark Cycle Model Predictive Capability Nitrogen Limiting
Source PublicationBIOTECHNOLOGY AND BIOENGINEERING
2018-02-01
ISSN0006-3592
DOI10.1002/bit.26483
Volume115Issue:2Pages:359-370
Indexed BySCI
SubtypeArticle
WOS HeadingsScience & Technology ; Life Sciences & Biomedicine
WOS SubjectBiotechnology & Applied Microbiology
WOS Research AreaBiotechnology & Applied Microbiology
WOS KeywordCHLAMYDOMONAS-REINHARDTII ; NANNOCHLOROPSIS-SALINA ; BIOHYDROGEN PRODUCTION ; HYDROGEN-PRODUCTION ; LIPID-ACCUMULATION ; SULFUR DEPRIVATION ; GROWTH ; MICROALGAE ; OPTIMIZATION ; TEMPERATURE
AbstractBiodiesel produced from microalgae has been extensively studied due to its potentially outstanding advantages over traditional transportation fuels. In order to facilitate its industrialization and improve the process profitability, it is vital to construct highly accurate models capable of predicting the complex behavior of the investigated biosystem for process optimization and control, which forms the current research goal. Three original contributions are described in this paper. Firstly, a dynamic model is constructed to simulate the complicated effect of light intensity, nutrient supply and light attenuation on both biomass growth and biolipid production. Secondly, chlorophyll fluorescence, an instantly measurable variable and indicator of photosynthetic activity, is embedded into the model to monitor and update model accuracy especially for the purpose of future process optimal control, and its correlation between intracellular nitrogen content is quantified, which to the best of our knowledge has never been addressed so far. Thirdly, a thorough experimental verification is conducted under different scenarios including both continuous illumination and light/dark cycle conditions to testify the model predictive capability particularly for long-term operation, and it is concluded that the current model is characterized by a high level of predictive capability. Based on the model, the optimal light intensity for algal biomass growth and lipid synthesis is estimated. This work, therefore, paves the way to forward future process design and real-time optimization.
Language英语
WOS IDWOS:000418919800009
PublisherWILEY
Citation statistics
Cited Times:4[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://cas-ir.dicp.ac.cn/handle/321008/169195
Collection中国科学院大连化学物理研究所
Corresponding AuthorZhang, Dongda; Xue, Song
Affiliation1.Chinese Acad Sci, Dalian Inst Chem Phys, Marine Bioengn Grp, Dalian 16023, Peoples R China
2.Univ Chinese Acad Sci, Beijing, Peoples R China
3.Imperial Coll London, Ctr Proc Syst Engn, South Kensington Campus, London SW7 2AZ, England
4.Imperial Coll London, Dept Chem Engn, South Kensington Campus, London, England
Recommended Citation
GB/T 7714
del Rio-Chanona, Ehecatl A.,Liu, Jiao,Wagner, Jonathan L.,et al. Dynamic modeling of green algae cultivation in a photobioreactor for sustainable biodiesel production[J]. BIOTECHNOLOGY AND BIOENGINEERING,2018,115(2):359-370.
APA del Rio-Chanona, Ehecatl A..,Liu, Jiao.,Wagner, Jonathan L..,Zhang, Dongda.,Meng, Yingying.,...&Shah, Nilay.(2018).Dynamic modeling of green algae cultivation in a photobioreactor for sustainable biodiesel production.BIOTECHNOLOGY AND BIOENGINEERING,115(2),359-370.
MLA del Rio-Chanona, Ehecatl A.,et al."Dynamic modeling of green algae cultivation in a photobioreactor for sustainable biodiesel production".BIOTECHNOLOGY AND BIOENGINEERING 115.2(2018):359-370.
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