RESUMEN
The objective of this work was to evaluate the technical feasibility of using both oil-extracted microalgae (M) and glycerol (G) in co-digestion with chicken litter (CL), thereby improving biochemical methane potential (BMP). Different feedstock ratios of M (0-30%), G (0-3%) and CL (67-100%) were investigated to determine the best co-digestion condition under mesophilic conditions. According to the modified Gompertz model, the best BMP (131.1mLCH4gVSfed-1) was obtained with the triple co-digestion (M:G:CL) in a proportion of 30:3:67. This yielded a methane production rate (µm) of 3.3mLCH4gVSfed-1d-1 and a lag time (λ) of 17.4d. This treatment reduced chemical oxygen demand (COD) by 91.02% and increased the methane yield 15.8% with respect to the CL control.
Asunto(s)
Glicerol/metabolismo , Metano/biosíntesis , Microalgas/metabolismo , Aceites/aislamiento & purificación , Eliminación de Residuos/métodos , Residuos , Acetatos/metabolismo , Anaerobiosis , Animales , Biocombustibles/análisis , Ácido Butírico/metabolismo , Pollos , Ácidos Grasos Volátiles/análisis , Concentración de Iones de Hidrógeno , Modelos Teóricos , Análisis de Componente Principal , Propionatos/farmacologíaRESUMEN
A molecular analysis found that poultry litter anaerobic digestion was dominated by hydrogenotrophic methanogens which suggests that bacterial acetate oxidation is the primary pathway in the thermophilic digestion of poultry litter. IWA Anaerobic Digestion Model No. 1 (ADM1) was modified to include the bacterial acetate oxidation process in the thermophilic anaerobic digestion (TAD). Two methods for ADM1 parameter estimation were applied: manual calibration with non-linear least squares (MC-NLLS) and an automatic calibration using differential evolution algorithms (DEA). In terms of kinetic parameters for acetate oxidizing bacteria, estimation by MC-NLLS and DEA were, respectively, km 1.12 and 3.25 ± 0.56 kg COD kg COD(-1)d(-1), KS 0.20 and 0.29 ± 0.018 kg COD m(-3) and Yac-st 0.14 and 0.10 ± 0.016 kg COD kg COD(-1). Experimental and predicted volatile fatty acids and biogas composition were in good agreement. Values of BIAS, MSE or INDEX demonstrate that both methods (MC-NLLS and DEA) increased ADM1 accuracy.