Enhancement of Biogas Production During Start-Up Operations of the Anaerobic Digestion of Wastewater Sludge
The global energy sector is seeing an ever-increasing demand for renewable alternatives to fossil fuels to meet current and future energy demands. One of the most versatile alternatives to fossil fuels, such as natural gas, is biogas, which is a by-product of the decomposition of organic matter known as anaerobic digestion (AD). Biogas is produced by specialized methane-producing microorganisms known as methanogens. It constitutes a carbon-neutral energy source with a similar composition to natural gas at about 60% methane and 40% carbon dioxide. One of the biggest challenges that biogas production faces are the start-up lag phase, as biogas output can take up to twelve weeks to achieve a steady yield. Understanding the effects that temperature, pH, bioaugmentation, microbial composition and the use of sensor and electrode technology have on biogas production under start-up operations could provide a better understanding of the underlying causes affecting start-up and how it could be improved to reach optimal biogas production. The results from this research showed that temperature has a significant role in biogas production by driving the biogas process. The effect of thermophilic temperatures caused a decrease in the methanogenic microbial diversity of sludge. pH control only offers a limited effect on overall biogas yield within a 6.5-7.5 range. Novel technological approaches such as sensors and electrode enhanced AD (MEC-AD) can provide a stabilizing effect during AD under start-up operation, MEC-AD provided a six-fold increase in biogas yield compared to conventional AD. Microbial activity tracking was attempted using bio-impedance with promising results and the effects of bioaugmentation and toxic shock in MEC-AD digesters showed that bioaugmentation potential benefits are only significant in the absence of inhibitory conditions. Overall, the characterization of the AD processes in a bench-scale system could provide valuable insight for large-scale systems aiming to optimize and update their operational procedures.
URI for this recordhttp://hdl.handle.net/1974/28981
Request an alternative formatIf you require this document in an alternate, accessible format, please contact the Queen's Adaptive Technology Centre
The following license files are associated with this item: