Optimization of biohydrogen production from microalgae by response surface methodology (RSM)

被引:53
作者
Nazarpour, Mehrshad [1 ]
Taghizadeh-Alisaraei, Ahmad [1 ]
Asghari, Ali [1 ]
Abbaszadeh-Mayvan, Ahmad [1 ]
Tatari, Aliasghar [2 ]
机构
[1] Gorgan Univ Agr Sci & Nat Resources, Dept Biosyst Engn, Gorgan, Iran
[2] Gorgan Univ Agr Sci & Nat Resources, Fac Wood & Paper Engn, Dept Cellulose Ind Engn, Gorgan, Iran
关键词
Microalgae; Response surface methodology; Fuel; Photobioreactor; Biohydrogen; RHEOLOGICAL PROPERTIES; BIOETHANOL PRODUCTION; BIOFUELS PRODUCTION; LIFE-CYCLE; ALGAE; CHALLENGES; HYDROGEN; ENERGY; WASTE; HYDROLYSIS;
D O I
10.1016/j.energy.2022.124059
中图分类号
O414.1 [热力学];
学科分类号
摘要
In the present study, the design and fabrication of a micro-photobioreactor to produce the bio-hydrogen are aimed. Furthermore, the optimization of variables affecting hydrogen production was optimized using the response surface methodology (RSM). A quadratic model was used to predict the behavior of samples. The central composite design was applied using 20 treatments and 6 replications in the central points. Independent variables for evaluation included sulfur concentration (0.5-1%), run time (5-120 h) and algal biomass concentration (50-100 g/L). The results suggested that test length had a significant impact on hydrogen production and that sulfur content and biomass concentration had no significant effect on hydrogen production but did cause a little increase. The experimental values of response variable in these optimal conditions match the predicted values. Optimal conditions to produce biohydrogen were identified as the sulfur concentration of 0.75%, run time of 101.96 h, and biomass concentration of 53.31 g/L for maximum production of bio-hydrogen (66.32 mL g-VS-1). In conclusion, the response surface methodology can predict the production and extraction of bio-hydrogen in photobioreactors. (C) 2022 Elsevier Ltd. All rights reserved.
引用
收藏
页数:7
相关论文
共 50 条
[1]   Energy, exergy, economic and exergoenvironmental analyses of gas and air bottoming cycles for production of electricity and hydrogen with gas reformer [J].
Ahmadi, A. ;
Jamali, D. H. ;
Ehyaei, M. A. ;
Assad, M. El Haj .
JOURNAL OF CLEANER PRODUCTION, 2020, 259
[2]  
Alalayah WM, 2015, REV CHIM-BUCHAREST, V66, P788
[3]   Oil Price and Energy Depletion Nexus in GCC Countries: Asymmetry Analyses [J].
Alkhateeb, Tarek Tawfik Yousef ;
Mahmood, Haider .
ENERGIES, 2020, 13 (12)
[4]   Modeling and optimization of bioethanol production from breadfruit starch hydrolyzate vis-a-vis response surface methodology and artificial neural network [J].
Betiku, Eriola ;
Taiwo, Abiola Ezekiel .
RENEWABLE ENERGY, 2015, 74 :87-94
[5]  
Davis R., 2014, Process Design and Economics for the Conversion of Algal Biomass to Biofuels: Algal Biomass Fractionation to Lipid- Products Process Design and Economics for the Conversion of Algal Biomass to Biofuels: Algal Biomass Fractionation to Lipid- and Carbohyd, DOI DOI 10.2172/1159351
[6]   Potential of algal biofuel production in a hybrid photobioreactor [J].
de Jesus, Sergio S. ;
Maciel Filho, Rubens .
CHEMICAL ENGINEERING SCIENCE, 2017, 171 :282-292
[7]  
De Jong E, BIOREFINERIES INT ST
[8]   Sugarcane bagasse ex-situ catalytic fast pyrolysis for the production of Benzene, Toluene and Xylenes (BTX) [J].
Ghorbarmezhad, Payam ;
Firouzabadi, Mohammadreza Dehghani ;
Ghasemian, Ali ;
de Wild, Paul J. ;
Heeres, H. J. .
JOURNAL OF ANALYTICAL AND APPLIED PYROLYSIS, 2018, 131 :1-8
[9]   Biofuel types and membrane separation [J].
Hajilary, Nasibeh ;
Rezakazemi, Mashallah ;
Shirazian, Saeed .
ENVIRONMENTAL CHEMISTRY LETTERS, 2019, 17 (01) :1-18
[10]  
Hannon M, 2010, BIOFUELS-UK, V1, P763, DOI [10.4155/bfs.10.44, 10.4155/BFS.10.44]