A fast linear predictive adaptive model of packed bed coupled with UASB reactor treating onion waste to produce biofuel

Microbial Cell Factories

Research

Luis Blanco-Cocom¹  Harvey Milquez-Sanabria²  Liliana Alzate-Gaviria² 

[1] Mathematics Research Center, A.C., Jalisco S/N, Colonia Valenciana, 36023, Guanajuato, Gto, Mexico;Renewable Energy Unit, Yucatan Center for Scientific Research (CICY), Calle 40 No. 130, Colonia Chuburná de Hidalgo, 97200, Mérida, Yucatán, Mexico;

关键词: Predictive adaptive model;    Onion waste;    Coupled system;    Methane;    Anaerobic digestion;   

DOI  :  10.1186/s12934-016-0563-y

 received in 2016-06-14, accepted in 2016-09-21,  发布年份 2016

来源: Springer

【 摘 要 】

BackgroundAgro-industrial wastes are an energy source for different industries. However, its application has not reached small industries. Previous and current research activities performed on the acidogenic phase of two-phase anaerobic digestion processes deal particularly with process optimization of the acid-phase reactors operating with a wide variety of substrates, both soluble and complex in nature. Mathematical models for anaerobic digestion have been developed to understand and improve the efficient operation of the process. At present, lineal models with the advantages of requiring less data, predicting future behavior and updating when a new set of data becomes available have been developed. The aim of this research was to contribute to the reduction of organic solid waste, generate biogas and develop a simple but accurate mathematical model to predict the behavior of the UASB reactor.ResultsThe system was maintained separate for 14 days during which hydrolytic and acetogenic bacteria broke down onion waste, produced and accumulated volatile fatty acids. On this day, two reactors were coupled and the system continued for 16 days more. The biogas and methane yields and volatile solid reduction were 0.6 ± 0.05 m3 (kg VSremoved)−1, 0.43 ± 0.06 m3 (kg VSremoved)−1 and 83.5 ± 9.8 %, respectively. The model application showed a good prediction of all process parameters defined; maximum error between experimental and predicted value was 1.84 % for alkalinity profile.ConclusionsA linear predictive adaptive model for anaerobic digestion of onion waste in a two-stage process was determined under batch-fed condition. Organic load rate (OLR) was maintained constant for the entire operation, modifying effluent hydrolysis reactor feed to UASB reactor. This condition avoids intoxication of UASB reactor and also limits external buffer addition.

【 授权许可】

CC BY   
© The Author(s) 2016

【 图 表 】

Fig. 4