This study presents a hybrid two-stage model for municipal solid waste biodegradation that integrates key features of both two-stage and multistage models. The proposed model incorporates a separate pH submodule and gas partitioning to more accurately represent underlying biochemical processes. Furthermore, structured modeling techniques were applied to provide detailed insights into the fate of individual components. A tailored iterative calibration procedure combining Latin hypercube sampling and rank-based optimization was implemented for the determination of model parameters. The advantage of the proposed model over existing approaches is that it reduces the number of required parameters compared with multistage models and provides higher accuracy than standard two-stage models. In contrast to conventional multistage models that explicitly model biomasses across multiple stages, the model applies separate pH functions for each stage to capture stage-specific biomass variation. Local sensitivity analysis of pH controlling parameters verified that the microbial population involved in the first stage required a broad pH tolerance, while that for second stage required a narrow, specialized tolerance and slightly alkaline pH. The model was validated against experimental data from the literature for diverse waste types for four key state variables: solid degradable fraction (SDF), methane, volatile fatty acids (VFA), and settlement. The improved accuracy of the proposed model was quantified by comparing its performance to that of a conventional two-stage biodegradation model, which yielded normalized root mean square error reductions of 29%, 6.1%, 52%, and 68% for SDF, methane, VFA, and settlement predictions, respectively.
Syed et al. (Tue,) studied this question.