The current study investigated anaerobic biodigestion (AD) of livestock manure, including camel dung (CD) and sheep manure (SM) mixed with tomato and rumen at different mixed ratios under mesophilic (24–34°C) conditions. The study yielded successful results, as the process was able to produce sustainable bioenergy. Predicted biogas data was acquired through fundamental mathematical calculations using SPSS statistical analysis by nonlinear regression. Three kinetic models, namely the modified Gompertz, Logistic, and Transference models, were used for simulating the daily biogas produced from the examinations, and model parameters were determined simultaneously. The three models performed well in AD simulations, with high correlation coefficient values (R-squared) and low root mean square error (RMSE), showing a significant link between experimental data and model parameters. However, modified Gompertz demonstrated an improved fit in the simulation of the measurements, as it could accurately represent the curves in the plots, with the highest R-squared of 0.987 compared to Logistics 0.981 and Transference models 0.933, and the lowest RMSE was 0.356 compared to 0.432, and 0.812, respectively. This work suggested that a modified Gompertz model is suitable for estimating the biogas yield potential. The findings also show that rumen, tomato, and control biodigesters operating in mesophilic environments are dependable choices for producing biogas.
This paper investigates the influence of thermal pretreatment on kinetic parameters based on four kinetic models: Modified Gompertz, transference and logistic functions and first order equation. The kinetic modeling was applied on experimental results of previous study on producing methane from anaerobic digestion of Recycled Pulp and Paper Sludge (RPPS) under mesophilic conditions. We observed that the thermal pretreatment improve considerably improved the kinetic parameters mainly the methane production rate and the lag phase. Indeed, it can be noted that methane production rate μ increases significantly from a value of 4.72 to 16.27 ml/h using logistic function for 1 g VS/L added load. Then the lag phase parameter λ has dramatically decreased from 5.46 to 1.04 h using logistic function for 1.5 g VS/L added load. This means that the thermal pretreatment of RPPS accelerates the methane production process and saves time.
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