Anaerobic digestion of food waste. Predicting of methane production by comparing kinetic models
Main Article Content
Anaerobic Digestion (AD) of food waste (FW) reduces risks to human health and environment, also increases the life of landfills, and mainly is an strategy to produce energy renewable as methane. Kinetic models can determine the influence of the factors that affect the process of AD and predicts more precisely methane production in order to prevent overestimation or underestimation, which may lead to the definition of real criteria to implement the technology. This study evaluated by means of Biochemical Methane Potential (BMP) assays, the AD of FW from a university restaurant using sludge from a UASB reactor in charge of treating municipal wastewater as inoculum.
The factor evaluated was the influence of Substrate-Inoculum (S/I: 0.5, 1, 2 and 4 gVS substrate ·gVS inoculum-1) ratio. For the prediction of methane were applied the kinetic models: Transfer Function, Logistics Function and Modified Gompertz models. It was found that the S/I ratio affect both, the efficiency of AD process and prediction of methane production, presenting the better results for S/I ratio below one. Within the kinetic models evaluated, the Logistic Function presented the best settings for predicting methane production and lag phase (R2> 0.9).
The factor evaluated was the influence of Substrate-Inoculum (S/I: 0.5, 1, 2 and 4 gVS substrate ·gVS inoculum-1) ratio. For the prediction of methane were applied the kinetic models: Transfer Function, Logistics Function and Modified Gompertz models. It was found that the S/I ratio affect both, the efficiency of AD process and prediction of methane production, presenting the better results for S/I ratio below one. Within the kinetic models evaluated, the Logistic Function presented the best settings for predicting methane production and lag phase (R2> 0.9).
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Parra-Orobio BA, Donoso-Bravo A, Torres-Lozada P. Anaerobic digestion of food waste. Predicting of methane production by comparing kinetic models. inycomp [Internet]. 2017 Jan. 30 [cited 2024 Nov. 21];19(1):210-8. Available from: https://revistaingenieria.univalle.edu.co/index.php/ingenieria_y_competitividad/article/view/2145
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