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Enhancing Biogas Production Kinetic of Meat Industrialwastewater by Microwave Pretreatment
... In comparison to the linear model, the exponential model has been reported to be more realistic for the ascending regime; while the linear model is supposedly better for a descending regime [57,58]. Ejimofor et al. [58], Veszelovszki et al. [59] and Pogaku et al. [60] reported that biogas production rate simulated by the linear model showed better correlation than the exponential model. ...
Biogas is a well-established renewable energy source produced from anaerobic digestion (AD) of biomass/feedstock. It is probably the most versatile and efficient biofuel in terms of utilisable feedstocks and energy applications. To monitor, optimise, and control anaerobic digestion (AD), numerous mathematical models describing AD have been developed and reported. Although literature on the use of these models and their reviews have been published, their differences have not been collectively analysed and no generalised classification criteria for these models has been proposed based on such an analysis. This review covers most reported AD models, from the simplest linear equation capturing biogas production rate to complex Anaerobic Digestion Model No. 1. In addition to model classification and biochemical stages in AD, other processes like feedstock hydrolysis or mass and heat transfer essential to AD were discussed, analysed, and available models on them reviewed. This collective and comprehensive review approach has been undertaken to enable the evaluation of the interdependence of all processes, process factors, and process estimations and their individual, and interactive effects on AD.
Biogas promises bioenergy to be developed as a renewable fuel to reduce the fossil energy crisis. Biogas raw material can be derived from tofu liquid waste. Biogas is processed by anaerobic digestion. This study aimed to develop a simulation of the kinetic model variations of biogas production from tofu liquid waste. The results showed that the ascending limb of the exponential equation had a greater coefficient (R2 = 1) than the ascending limb of the linear equation (R2 = 0.9574). The descending limb of the linear equation had a better coefficient (R2 = 0.9574) than the descending limb of the exponential equation (R2 = 0.95). The Gaussian model had the greatest R2 of 0.9937. Logistic growth had the greatest coefficient (R2 = 0.9951) compared to modified Gompertz (R2 = 0.9817) and exponential rise to maximum (R2 = 0.9852) in the simulation of cumulative biogas production. The fit model for kinetic biogas production from tofu liquid waste is Gaussian Model.
Abstrak: Biogas merupakan salah satu bioenergi yang menjanjikan untuk dikembangkan dalam mengurangi krisis energi fosil. Bahan baku biogas dapat berasal dari limbah cair tahu yang diolah secara anaerobic digestion. Penelitian ini bertujuan untuk mengembangkan variasi model simulasi kinetika produksi biogas dari limbah cair tahu. Hasil penelitian menunjukkan bahwa persamaan eksponensial untuk grafik kenaikan memilki koefisien yang lebih besar (R2 = 1) dibandingkan grafik kenaikan dengan persamaan linier (R2 = 0,9574). Grafik penurunan pada persamaan linier memiliki nilai koefisien lebih besar (R2 = 0,9574) dibandingkan grafik penurunan pada persamaan eksponensial (R2 = 0,95). Model Gaussian menghasilkan nilai koefisien tertinggi R2 = 0,9937. Logistic growth menghasilkan nilai R2 terbesar (0,9951) dibandingkan modified Gompertz (R2 = 0,9817) dan exponential rise to maximum (R2 = 0,9852) pada simulasi produksi biogas kumulatif. Model yang paling cocok untuk kinetika produksi biogas dari limbah cair adalah model Gaussian.
IntroductionProcess DescriptionProcess MicrobiologyMethods for Detection of MethanogensFactors Controlling Anaerobic DigestionAnaerobic Treatment of WastewaterWeb ResourcesQuestions and ProblemsFurther Reading
A review of the kinetics of anaerobic treatment and the reported values of such kinetic parameters as the maximum specific substrate utilization rate (k), the half-saturation constant (K(s)), the microbial growth yield (Y), and the microorganism decay rate constant (b) are presented. The available kinetic information is presented for each subprocess: (a) hydrolysis of complex, particulate organic materials; (b) fermentation of amino acids and sugars; (c) anaerobic oxidation of long-chain fatty acids and alcohols; (d) anaerobic oxidation of intermediary products (such as short-chain fatty acids); (e) homoacetogenesis; and (f) methanogenesis. The intrinsic rates of each step as well as mass transfer limitations and their effect on the intrinsic kinetics are discussed and areas requiring further research are also identified. Substantial variation exists in the reported values of the kinetic coefficients. This variation is due in part to the variability in mode of operation, environmental and operational conditions in the various studies as well as to the lack of a widely accepted standard procedure for measuring and expressing the biokinetic coefficients. The hydrolysis step is usually assumed to follow first-order kinetics. Whenever the kinetics of the hydrolysis step were studied, they were generally found to be the limiting-step in the overall conversion of complex substrates to methane. With the exception of the hydrolysis step, all other subprocesses of anaerobic treatment have been successfully modeled by following Monod kinetics. The Contois and Chen and Hashimoto model has also been used quite extensively to account for the effect of influent substrate concentration on effluent quality. Based on a brief overview of the observed phenomena related to the kinetics of mass transfer in methanogenesis, it is concluded that with but few exceptions, the evidence for the significance of mass transfer effects in the different reactor configurations is circumstantial and, in some cases, contradictory. Our understanding of the kinetics of particulate substrate removal in biofilms is still incomplete for engineering applications, and more research is necessary.
In developing countries like India, urban solid waste (SW) generation is increasing enormously and most of the SWs are disposed off by land filling in low-lying areas, resulting into generation of large quantities of biogas. Methane, the major constituent gas is known to cause global warming due to green house gas (GHG) effect. There is a need to study the ever-increasing contribution of SW to the global GHG effect. To assess the impacts, estimation of GHG emission is must and to avoid misguidance by these emission-data, qualitative assessment of the estimated GHG is a must. In this paper, methane emission is estimated for a particular landfill site, using default methodology and modified triangular methodology. Total methane generation is same for both theoretical methodologies, but the modified triangular method has an upper hand as it provides a time-dependent emission profile that reflects the true pattern of the degradation process. To check the quality of calculated emission-data, extensive sampling is carried out for different seasons in a year. Field results show a different trend as compared to theoretical results, this compels for logical thinking. Each methane emission-data is backed up by the uncertainty associated with it, this further strengthens the quality check of these data. Uncertainty calculation is done using Monte Carlo simulation technique, recommended in IPCC Guideline. In the due course of qualitative assessment of methane emission-data, many site-specific sensitive parameters are discovered and are briefly discussed in this paper.
The effects of different thermo-chemical pre-treatment methods were determined on the biodegradability and hydrolysis rate of lignocellulosic biomass. Three plant species, hay, straw and bracken were thermo-chemically pre-treated with calcium hydroxide, ammonium carbonate and maleic acid. After pre-treatment, the plant material was anaerobically digested in batch bottles under mesophilic conditions for 40 days. From the pre-treatment and subsequent anaerobic digestion experiments, it was concluded that when the lignin content of the plant material is high, thermo-chemical pre-treatments have a positive effect on the biodegradability of the substrate. Calcium hydroxide pre-treatment improves the biodegradability of lignocellulosic biomass, especially for high lignin content substrates, like bracken. Maleic acid generates the highest percentage of dissolved COD during pre-treatment. Ammonium pre-treatment only showed a clear effect on biodegradability for straw.
Lignocellulosic biomass can be utilized to produce ethanol, a promising alternative energy source for the limited crude oil. There are mainly two processes involved in the conversion: hydrolysis of cellulose in the lignocellulosic biomass to produce reducing sugars, and fermentation of the sugars to ethanol. The cost of ethanol production from lignocellulosic materials is relatively high based on current technologies, and the main challenges are the low yield and high cost of the hydrolysis process. Considerable research efforts have been made to improve the hydrolysis of lignocellulosic materials. Pretreatment of lignocellulosic materials to remove lignin and hemicellulose can significantly enhance the hydrolysis of cellulose. Optimization of the cellulase enzymes and the enzyme loading can also improve the hydrolysis. Simultaneous saccharification and fermentation effectively removes glucose, which is an inhibitor to cellulase activity, thus increasing the yield and rate of cellulose hydrolysis.
Cellulosic plant material represents an as-of-yet untapped source of fermentable sugars for significant industrial use. Many physio-chemical structural and compositional factors hinder the enzymatic digestibility of cellulose present in lignocellulosic biomass. The goal of any pretreatment technology is to alter or remove structural and compositional impediments to hydrolysis in order to improve the rate of enzyme hydrolysis and increase yields of fermentable sugars from cellulose or hemicellulose. These methods cause physical and/or chemical changes in the plant biomass in order to achieve this result. Experimental investigation of physical changes and chemical reactions that occur during pretreatment is required for the development of effective and mechanistic models that can be used for the rational design of pretreatment processes. Furthermore, pretreatment processing conditions must be tailored to the specific chemical and structural composition of the various, and variable, sources of lignocellulosic biomass. This paper reviews process parameters and their fundamental modes of action for promising pretreatment methods.
The United Nations World Water Development Report
WWAP (United Nations World Water Assessment
Programme).: 2017. The United Nations World Water
Development Report 2017. Wastewater: The Untapped Resource.
Paris, UNESCO