Fermentative Biohydrogen Modelling and Optimization Research in Light of Miniaturized Parallel Bioreactors

Thermophilic Biogas Upgrading via ex Situ Addition of H2 and CO2 Using Codigested Feedstocks of Cow Manure and the Organic Fraction of Solid Municipal Waste

Bioconversion of renewable H₂ and waste CO₂ using methanogenic archaea is a promising technology for obtaining high-purity CH₄, which can serve as an alternative for natural gas. This process is known as ex situ biogas upgrading. This work highlights the pathway toward the bioconversion of renewable H₂ and CO₂ into high-purity biomethane by exploiting highly accessible agro-municipal residues: cow manure (CM) and the organic fraction of solid municipal waste (OFSMW), which used to be called "waste materials". More specifically, an ex situ thermophilic (55 °C) biogas upgrading process was conducted by CM and OFSMW codigestion at different mass proportions: 100:0, 80:20, 70:30, 60:40, and 50:50. Maximum CH₄ concentrations of 92-97 vol % and biogas volumetric production rates of 4954-6605 NmL/L.d were obtained from a batch reactor of 3 L working volume. Feedstock characterization, pH monitoring, and the carbon-to-nitrogen ratio were critical parameters to evaluate during biogas upgrading experiments. In this work, the usefulness of agro-municipal substrates is highlighted by producing high-purity biomethane-an energetic chemical to facilitate renewable energy conversion, which supports various end-use applications. This process therefore provides a solution to renewable energy storage challenges and future sustainable and green energy supply.

Microbial cell immobilization in biohydrogen production: a short overview

The high dependence on fossil fuels has escalated the challenges of greenhouse gas emissions and energy security. Biohydrogen is projected as a future alternative energy as a result of its non-polluting characteristics, high energy content (122 kJ/g), and economic feasibility. However, its industrial production has been hampered by several constraints such as low process yields and the formation of biohydrogen-competing reactions. This necessitates the search for other novel strategies to overcome this problem. Cell immobilization technology has been in existence for many decades and is widely used in various processes such as wastewater treatment, food technology, and pharmaceutical industry. In recent years, this technology has caught the attention of many researchers within the biohydrogen production field owing to its merits such as enhanced process yields, reduced microbial contamination, and improved homogeneity. In addition, the use of immobilization in biohydrogen production prevents washout of microbes, stabilizes the pH of the medium, and extends microbial activity during continuous processes. In this short review, an insight into the potential of cell immobilization is presented. A few immobilization techniques such as entrapment, adsorption, encapsulation, and synthetic polymers are discussed. In addition, the effects of process conditions on the performance of immobilized microbial cells during biohydrogen production are discussed. Finally, the review concludes with suggestions on improvement of cell immobilization technologies in biohydrogen production.

Back propagation neural network modelling of biodegradation and fermentative biohydrogen production using distillery wastewater in a hybrid upflow anaerobic sludge blanket reactor

In a hybrid upflow anaerobic sludge blanket (HUASB) reactor, biodegradation in association with biohydrogen production was studied using distillery wastewater as substrate. The experiments were carried out at ambient temperature (34±1°C) and acidophilic pH of 6.5 with constant hydraulic retention time (HRT) of 24h at various organic loading rates (OLRs) (1-10.2kgCODm(-3)d(-1)) in continuous mode. A maximum hydrogen production rate of 1300mLd(-1) was achieved. A back propagation neural network (BPNN) model with network topology of 4-20-1 using Levenberg-Marquardt (LM) algorithm was developed and validated. A total of 231 data points were studied to examine the performance of the HUASB reactor in acclimatisation and operation phase. The statistical qualities of BPNN models were significant due to the high correlation coefficient, R(2), and lower mean absolute error (MAE) between experimental and simulated data. From the results, it was concluded that BPNN modelling could be applied in HUASB reactor for predicting the biodegradation and biohydrogen production using distillery wastewater.