Additives in the form of micronutrients and pretreatments play an important role in improving the performance and stability of the anaerobic digestion process. Moreover, for predicting and optimizing the performance of the anaerobic digestion process as a complex one, especially while using stimulants or additives, the kinetics of the process should be evaluated with statistical methods such as nonlinear regression method. Therefore, in this study, the effect of iron-based additives as well as drinking water treatment sludge (DWTS) as a cost-effective and combined additive on the anaerobic digestion of dairy manure, one of the best feedstocks in Iran, is investigated via non-linear regression methods. For this, methane production during AD of dairy manure, incorporating varying concentrations of Fe and Fe3O4 (10, 20, and 30 mg/L) and DWTS (6, 12, and 18 mg/L) is tested for 45 days. in Ferdowsi University biogas laboratory. Then an extensive library of non-linear regression (NLR) models, 26 candidates were scrutinized to model the desired process. Regarding criteria such as RMSE, R2, minimum production (MP) as well as the simplicity of the model, the modified Michael Menton model (MMM) was selected as the best model for estimating the kinetics of produced gas from all 9 treatments over time. Actually, with 8 emerging as robust predictors for the entire methane production process, the Michaelis-Menten model stood out as the superior choice, unraveling the kinetics of dairy manure AD with the specified additives. The comparison of three Fe treatments showed that the higher levels of this additive could increase the cumulative methane production by about 35% compared to the level of 10 mg, the highest level (30 mg) also showed the highest rate of methane production among these treatments. While in comparison between comparing Fe3O4 treatments, the highest cumulative methane production and methane production rate were reported for the lowest level. The comparison of three treatments with the addition of DWTS also indicated that two levels of 6 and 12 mg of this additive had relatively similar results and caused an increase in the cumulative methane produced by about 50% compared to the level of 18 mg. Fascinatingly, the findings revealed that different levels of DWTS showcased the highest methane production, while Fe3O420 and Fe3O430 recorded the lowest levels. Notably, DWTS6 demonstrated approximately 34% and 42% higher methane production compared to Fe20 and Fe3O430, respectively, establishing it as the most effective treatment. Additionally, DWTS12 exhibited the highest maximum methane production rate, reaching an impressive 147.6 cc on the 6th day. Emphasizing the practical implications, this research underscores the applicability of the proposed model for analyzing other parameters and optimizing AD performance. By delving into the potential of iron-based additives and DWTS, this study opens doors to revolutionizing methane production from dairy manure and advancing sustainable waste management practices. |
