State Estimation for Anaerobic Digesters using the ADM1

The optimization of full-scale biogas plant operation is of great importance to make biomass a competitive source of renewable energy. The implementation of innovative control and optimization algorithms, such as Nonlinear Model Predictive Control, requires an online estimation of operating states of biogas plants. This state estimation allows for optimal control and operating decisions according to the actual state of a plant. In this paper such a state estimator is developed using a calibrated simulation model of a full-scale biogas plant, which is based on the Anaerobic Digestion Model No.1. The use of advanced pattern recognition methods shows that model states can be predicted from basic online measurements such as biogas production, CH4 and CO2 content in the biogas, pH value and substrate feed volume of known substrates. The machine learning methods used are trained and evaluated using synthetic data created with the biogas plant model simulating over a wide range of possible plant operating regions. Results show that the operating state vector of the modelled anaerobic digestion process can be predicted with an overall accuracy of about 90%. This facilitates the application of state-based optimization and control algorithms on full-scale biogas plants and therefore fosters the production of eco-friendly energy from biomass.

Self-cleaning perovskite type catalysts for the dry reforming of methane

Gas-to-liquid processes are generally used to convert natural gas or other gaseous hydrocarbons into liquid fuels via an intermediate syngas stream. This includes the production of liquid fuels from biomass-derived sources such as biogas. For example, the dry reforming of methane is done by reacting CH4 and CO2, the two main components of natural biogas, into more valuable products, i.e., CO and H2. Nickel containing perovskite type catalysts can promote this reaction, yielding good conversions and selectivities; however, they are prone to coke laydown under certain operating conditions. We investigated the addition of high oxygen mobility dopants such as CeO2, ZrO2, or YSZ to reduce carbon laydown, particularly using reaction conditions that normally result in rapid coking. While doping with YSZ, YDC, GDC, and SDC did not result in any improvement, we show that a Ni perovskite catalyst (Na0.5La0.5Ni0.3Al0.7O2.5) doped with 80.9 ZrO2 15.2 CeO2 gave the lowest amount of carbon formation at 800 °C and activity was maintained over the operating time.

Integrated Earth Resistivity Tomography (ERT) and Multilevel Gas Sampling: A Tool to Map Geogenic and Anthropogenic Methane Accumulation on Brownfield Sites

Soil gas emissions of methane and carbon dioxide on brownfield sites are usually attributed to anthropogenic activities; however geogenic sources of soil gas are often not considered during site investigation and risk management strategies. This paper presents a field study at a redeveloped brownfield site on a flood plain to identify accumulations of methane biogas trapped in underlying sediments. The investigation is based on a multidisciplinary approach using direct multi-level sampling measurements and Earth resistivity tomography . Resistivity imaging was applied to evaluate the feasibility of identifying the size and spatial continuity of soil gas accumulations in anthropogenic and naturally occurring deposits. As a result, biogas accumulations are described within both anthropogenic deposits and pristine organic sediments. This result is important to identify the correct approaches to identify and manage risks associated with soil gas emissions on brownfield and pristine sites. The organic-rich sediments in Quaternary fluvial environments of São Paulo Basin in particular the Tietê River, biogas reservoirs can be generated and trapped beneath geogenic and anthropogenic layers, potentially requiring the management of brownfield developments across this region.

Self‐cleaning perovskite type catalysts for the dry reforming of methane

Gas-to-liquid processes are generally used to convert natural gas or other gaseous hydrocarbons into liquid fuels via an intermediate syngas stream. This includes the production of liquid fuels from biomass-derived sources such as biogas. For example, the dry reforming of methane is done by reacting CH4 and CO2, the two main components of natural biogas, into more valuable products, i.e., CO and H2. Nickel containing perovskite type catalysts can promote this reaction, yielding good conversions and selectivities; however, they are prone to coke laydown under certain operating conditions. We investigated the addition of high oxygen mobility dopants such as CeO2, ZrO2, or YSZ to reduce carbon laydown, particularly using reaction conditions that normally result in rapid coking. While doping with YSZ, YDC, GDC, and SDC did not result in any improvement, we show that a Ni perovskite catalyst (Na0.5La0.5Ni0.3Al0.7O2.5) doped with 80.9 ZrO2 15.2 CeO2 gave the lowest amount of carbon formation at 800 °C and activity was maintained over the operating time.