Building a mechanistic biogeochemical reaction network for upscaling Characterization of mass transport limitation between regions of hydrolysis and methanogenesis

Mechanistic models have been developed to understand longterm landfill emissions and settlement (White et al., 2004; McDougall, 2007) . By finding emission/settlement controlling processes with these models, mechanistic boundary conditions can be applied in modeling to enhance predictions. In our research, we focus on finding the mechanistic biogeochemical reaction network that best describes biodegradation within landfills which is considered an important (sub)process in these models. We hope to eventually enhance predictions of longterm emissions and settlement by obtaining a mechanistically complete and fully identifiable biogeochemical reaction network. Previously, we presented a mechanistic biogeochemical reaction network that optimally described a dataset from a lysimeter experiment in which shredded Municipal Solid Waste (MSW) was anaerobically degraded and leachate was recirculated (van Turnhout et al., 2015). Values from model parameters were taken from ’ideal experiments’ published in literature, and the most uncertain parameters were optimized. All optimized parameters were identifiable and were comparable with bandwidths published in literature except for the half saturation constant of methanogenesis. Therefore in order to find a mechanistically complete network, a mass transport limitation was added to the network between regions of hydrolysis and methanogenesis following previous studies (Veeken and Hamelers, 2000; Vavilin et al., 2002). This resulted in a fully identifiable and mechanistically complete reaction network for describing the measured dataset (van Turnhout et al., 2014). This strongly suggests that this biogeochemical reaction network includes all emission controlling reactions for lysimeter scale (with recirculation), and that all rate controlling parameters are identifiable from standard emissions measurements. In this study, we aim to validate the reaction network with an idealized experiment. We want to show that 1) rate controlling parameters are identifiable from the measured data by inverse modeling, and 2) that this network is able to predict the measured emissions in the experiment given the initial conditions. In the experiment, cabbage is used as substitute for waste, and partial pressures of CO2 and CH4, cumulative production of gas, Volatile Fatty Acid (VFA), NH 4 and pH are measured. Different mass transport limitation between regions of hydrolysis and methanogenesis are imposed on the system. Once validated, the network can be validated for less ideal systems and eventually be used for upscaling. In this conference proceeding, we present in short the biogeochemical reaction network, our experimental set up and discuss the expected experimental results by forward modeling.