Introduction: This preliminary assessment of a grey-box model, was predicated on system dynamics principles and developed using Vensim® DSS software. The purpose is to predict biogas production under anaerobic conditions for energy utilization at the design stage. Objective: To describe the process of a developed system dynamics model to predict biogas production under anaerobic conditions. Methods: This method involves two-stage kinetics of the biogas production process in anaerobic conditions using the first-order and Gompertz functions. The model is depicted in two parts: causal loop diagram and stock–flow diagram. The causal loop diagram describes the anaerobic digestion process a substrate undergoes for the production of biogas, while stock–flow diagram depicts basic building blocks of the dynamic behavior of an anaerobic digestion process. Primary data is from a laboratory-scale experiment of biogas production using vegetal wastes, while the secondary one is from the literature on studies using similar substrates. Results: Primary and secondary data are used to validate and stimulate the developed model. The kinetic model shows the substrate being reduced exponentially with increasing time; consumption of substrate and production of methane and carbon dioxide follows exponential growth and decay pattern, with carbon dioxide production starting early compared to methane, and was produced at a rate faster due to the strong and resilient characteristics of fermentative microorganisms. Discussion: Comparing data from empirical and model simulation shows some close relationship, though not too perfectly. Both results reflect signs of inhibitions occurring within the substrates in the digester under anaerobic conditions explaining the low methane yield or instability.
Global climate change impact is predicted to affect various sectors including the energy demand and supply sectors respectively. Combating this impact will require adoption of both global strategy and localized actions. The use of low carbon strategy based on renewables is a global strategy, while waste management of biodegradable materials through the use anaerobic technology to meet energy demand is a local action. Nigeria is among the vulnerable countries to global climate change impact; this is even more aggravated by its dependence on fossil fuel usage as well as poor waste management, which two, contribute significantly to greenhouse gas emissions. This chapter presents analysis of purified compressed biogas production, a waste conversion option, as a local action to meet rural household energy demand and contribute to global strategy of reducing climate change impact. It discusses both technical and business model approaches to upscale a laboratory experimental procedure for biogas production through anaerobic digestion using vegetal wastes. It shows that using anaerobic technology can achieve efficient waste management and at the same time generate energy that can be used to achieve avoided emissions for climate change impact reduction. The study also concludes that upscaling the project will be sustainable for rural energy augmentation as it produces clean and renewable energy, reduces the use of fossil fuels, provides jobs for skilled and unskilled labor, and generates new return streams.
Global climate change impact is predicted to affect various sectors including the energy demand and supply sectors respectively. Combating this impact will require adoption of both global strategy and localized actions. The use of low carbon strategy based on renewables is a global strategy, while waste management of biodegradable materials through the use anaerobic technology to meet energy demand is a local action. Nigeria is among the vulnerable countries to global climate change impact; this is even more aggravated by its dependence on fossil fuel usage as well as poor waste management, which two, contribute significantly to greenhouse gas emissions. This chapter presents analysis of purified compressed biogas production, a waste conversion option, as a local action to meet rural household energy demand and contribute to global strategy of reducing climate change impact. It discusses both technical and business model approaches to upscale a laboratory experimental procedure for biogas production through anaerobic digestion using vegetal wastes. It shows that using anaerobic technology can achieve efficient waste management and at the same time generate energy that can be used to achieve avoided emissions for climate change impact reduction. The study also concludes that upscaling the project will be sustainable for rural energy augmentation as it produces clean and renewable energy, reduces the use of fossil fuels, provides jobs for skilled and unskilled labor, and generates new return streams.
This study quantifies the effluents generated during processing in three industry types, estimates the energy potential from the quantified effluents in the form of biogas generation, and determines the economic viability of the biogas recovered. Data were procured from the relevant scientific publications to quantify the effluents generated from the production processes in the industry types examined, using industrial process calculations. The effluent data generated are used in the 2-module biogas energy recovery model to estimate the bioenergy recovery potential within it. Economic and financial analysis is based on a cash-flow comparison of all costs and benefits resulting from its activities. The effluents generated an average daily biogas of 2559 Nm3/gVS, having a daily potential combined heat and power of 0.52 GWh and 0.11 GWh, respectively. The life cycle analysis and cost-benefit analysis show the quantity of emissions avoided when using the effluents to generate heat and power for processes, along with the profitability of the approach. Conclusively, the study shows that the use of biomass effluents to generate biogas for Combined Heat and Power (CHP) is a viable one, based on the technologies of a reciprocating engine, gas turbine, microturbine, and fuel cell. However, it is recommended that the theoretical estimation be validated using a field-scale project.
The use of renewable energy sources including biomass for energy generation, to achieve diversification in energy production, has been found to be sustainable economically, financially and environmentally. Various energy production technologies exist by which biomass can be converted for energy generation. Such technologies include anaerobic digestion, gasification, thermal depolymerization, pyrolysis, fermentation, anaerobic digestion, amongst others. The focus of this study is on the use of anaerobic digestion technology. Anaerobic digestion is recognized as one of the best options for treating biomass as it helps to avoid CO 2 emissions and run off of biomass. It is a natural process in which bacteria convert organic materials into biogas and fertilizer production in an environmentally friendly way. Anaerobic digestion is a series of sequential process including hydrolysis, acidogenesis, acetogenesis and methanogenesis. Different models have been applied to capture the characteristics of the anaerobic digestion process such as first-order model, Gompertz model and logistic model. However, Gompertz model is considered as the best model in describing the growth of animals and plants as well as the volume of bacteria. It is also used to describe the cumulative biogas production curve in batch digestion assuming that substrate levels limit growth in a logarithmic relationship. This study developed a System Dynamics model (SDM) for predicting biogas production (BP) in an anaerobic condition, based on Gompertz-Laird model. The objective is to describe the process of a System Dynamic (SD) model of two stage kinetics of BP. Primary data used were obtained from a laboratory experiment of BP using vegetal wastes, while secondary data were obtained from literature on studies using similar substrates. The Causal loop diagram generated, describes the anaerobic digestion (AD) process usually undergone by a substrate, while the Stock Flow diagram depicts the building blocks of the dynamic behavior of the same process. The developed SD model consists of two-level variables which depict the equations driving the AD process represented as hydrolysis-acidogenesis and acetogenesis-methanogenesis. The model results showed a significant lag phase between methanogenesis and fermentation stage, which was found to be linked to the inoculum-substrate ratio. The study conclusion includes: inoculum to substrate ratio affects BP; inconsistency of the experimental data caused by inhibition explains the variation observed between the empirical and simulated results.
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