Biogas Plants Research Articles

The Identification and Quantification of 21 Antibacterial Substances by LC-MS/MS in Natural and Organic Liquid Fertilizer Samples.

Antibiotics in animal production are widely used around the world for therapeutic and preventive purposes, and in some countries, they still serve as antibiotic growth stimulants. Regardless of the purpose of using antibiotics in livestock, they may be present in animal tissues and organs as well as in body fluids and excretions (feces and urine). Farm animal excrement in unprocessed form (natural fertilizers) or processed form (organic fertilizers) is applied to agricultural fields because it improves soil fertility. Antibiotics present in fertilizers may therefore contaminate the soil, surface, groundwater, and plants, which may pose a threat to the environment, animals, and humans. Therefore, it is important to develop analytical methods that will allow for the control of the presence of antibacterial substances in natural and organic fertilizers. Therefore, in this study, an LC-MS/MS method was developed and validated for the determination of 21 antibacterial substances in natural and organic liquid fertilizers. The developed method was used to analyze 62 samples of natural and organic liquid fertilizers, showing that over 24% of the tested samples were contaminated with antibiotics, mainly from the group of tetracyclines and fluoroquinolones. Studies of post-fermentation sludge from biogas plants have shown that the processes of anaerobic methane fermentation, pH, and temperature changes taking place in bioreactors do not lead to the complete degradation of antibiotics present in the material used for biogas production. For this reason, monitoring studies of natural and organic fertilizers should be undertaken to limit the introduction of antibiotics into the natural environment.

Machine learning for high solid anaerobic digestion: Performance prediction and optimization

Biogas production through anaerobic digestion (AD) is one of the complex non-linear biological processes, wherein understanding its dynamics plays a crucial role towards process control and optimization. In this work, a machine learning based biogas predictive model was developed for high solid systems using algorithms, including SVM, ET, DT, GPR, and KNN and two different datasets (Dataset-1:10, Dataset-2:5 inputs). Support Vector Machine had the highest accuracy (R2) of all the algorithms at 91 % (Dataset-1) and 87 % (Dataset-2), respectively. The statistical analysis showed that there was no significant difference (p = 0.377) across the datasets, wherein with less inputs, accurate results could be predicted. In case of biogas yield, the critical factors which affect the model predictions include loading rate and retention time. The developed high solid machine learning model shows the possibility of integrating Artificial Intelligence to optimize and control AD process, thus contributing to a generic model for enhancing the overall performance of the biogas plant.

Modeling of the Process of Functioning of the Digester of a Biogas Plant during Methane Fermentation of Сow Manure

Ensuring high and stable biogas output during digester operation is ensured by regulating and monitoring values of control parameters. The purpose of article is to develop model of process of functioning of digester during methane mono-fermentation of cow manure with establishment of values of control parameters. A solution to model was found to obtain dynamics of biogas yield, while experimental and simulated dynamics of biogas yield were as close as possible. The developed model is system of differential equations that describe changes in concentrations of substrate nutrients , methanogen biomass and dynamics of biogas output in digester. The system of differential equations was solved in Simulink package , obtaining dependencies and . The dependence was compared with results of studies conducted on laboratory biogas plant with digester with useful volume of 30 liters at temperature of 37°C with periodic substrate loading system. By selecting parameters of model, resulting function was compared with similar one obtained experimentally. It has been established that in model of digester functioning process during methane mono-fermentation of cow manure, following coefficients have following meaning: bacterial growth rate m3/(kg day); substrate assimilation ; bacterial growth rate m3/(kg day); rate of conversion of nutrients into biogas m6/kg. The obtained values of coefficients make it possible to carry out modeling of process of methane mono-digestion of cow manure and predict biogas yield at different initial values of concentration of methanogen biomass, concentration of substrate nutrients, digester volume, which is used in industrial biogas plants.

A network design problem for upgrading decentrally produced biogas into biomethane

In this paper, we explore the possibility of connecting decentralized biogas plants via a pipeline network to terminals that upgrade biogas into biomethane. We present a mixed-integer linear program that forms subnetworks of such plants, decides on suitable terminal locations, and establishes pipeline connections to maximize profit. We apply this model to a real-world scenario in Northern Germany. The results show a much higher total profit for the optimized network compared to the benchmark solutions where each plant upgrades biogas into biomethane on its own. Therefore, plants can increase their profitability by collaborating with other (neighboring) plants. However, the collaboration requires a fair profit-sharing model as network participation is not individually profitable for all plants, especially small ones.

The Improved Method for Identifying Parameters of Interval Nonlinear Models of Static Systems

The article discusses the method of identifying parameters for interval nonlinear models of static systems. The method is based on solving an optimization problem with a smooth objective function. Additional coefficients are added to the objective function's variables to solve the optimization problem, complicating the computational procedures. The computational complexity of quasi-Newton methods used to solve the optimization problem is analyzed. Excessive computational complexity is caused by many iterations when transforming the value of the objective function to zero. To address this, the article proposes using the optimization stop criterion based on the determination of the model's adequacy at the current iteration of the computational optimization procedure. Numerical experiments were conducted to identify nonlinear models of depending the pH of the environment in the fermenter of the biogas plant on influencing factors. It was established that the proposed criterion reduced the number of iterations by 4.5 times, which is proportional to the same reduction in the number of calculations of the objective function. Gotten results are also important for reducing the computational complexity of algorithms of structural identification of these models.

A Study on Utilization of Co-Digested Citronella Oilmeal Cake, Cow Dung and Poultry Dropping for Enhancement of Biogas Yield

Abstract: Power plays a pivotal role in the industrial, economic and infrastructural development of the country’s growth. India is on the exponential growth paradigm and is playing a leadership role in the implementation of renewable energy projects for achieving the INDC’s committed in the Paris agreement and meeting the net carbon zero economy by 2070. The present research work attempts to utilize the co-digested agriwaste and livestock to enhance the biogas productivity. The experimental study considered a co-digested feedstock of cow dung (CD), poultry dropping (PD) and Citronella grass oilmeal cake (CG) using different ratios of each in five different digesters. Amongst all five digesters R1, R2, R3, R4 and R5; R4 having a co-digested feedstock of CD: PD: CG in the ratio of 20% : 55% : 25% respectively. The cumulative biogas yield for an experimental period was observed to 41.26 litres whereas the methane percentage in the biogas was 74%. The feedstock quantity required for 1 m3 biogas production was found to be 18.9 kg which was observed to be lower than the cowdung based monodigester which is 25 kg. Thus, co-digestion of the Citronella grass oilmeal cake along with poultry dropping using cow dung as substrate showed promising results which can be scaled up to commercial level biogas plants in villages where these feedstocks are easily available.

The Effects of Liquid Biogas Digestate on Yield and Mineral Nutrition of Cucumber Growing in Greenhouse

This study aimed to investigate the effects of a liquid fraction of digestate obtained from different biogas plants on the growth and mineral nutrition of cucumber plants under greenhouse conditions. For this purpose, Liquid Biogas Digestates (LBD) obtained from two different plants (A-B) with different properties were applied to pots with 10 kg of soil in 5 different doses (0, 20, 40, 60, and 80 t ha-1) and the effects of the treatments were observed. As a result of the research, the highest yields increased 24.6% for digestate A in A5 (80 t ha-1) and 29% for digestate B in B3 (40 t ha-1) compared to control. While LBD contributed to the increase of N, Ca, Zn, Cu, and Mn concentrations in the leaf samples, it was observed that the dose increase did not have a linear effect on N, Ca, Zn, Cu, and Mn concentrations in the leaf samples. It is thought that liquid biogas wastes produced in biogas plants have positive effects on fruit yield, agricultural practices can be taken as the basis for the disposal of these wastes and the use of liquid biogas residues in soils by eliminating potential risks can provide significant benefits.

Towards a sustainable energy future: Evaluating Arundo donax L. in continuous anaerobic digestion for biogas production

AbstractIn response to the EU's REPowerEU initiative (COM (2022) 108) which encourages an increase in biogas production by 20% in member states by 2030 to boost energy independence, it has become essential to identify sustainable alternatives to traditional feedstocks for biogas production, especially in the EU Member states where there is still high dependence on corn silage as the main raw material in biogas plants. While corn silage, predominantly used in the European biogas plants today, serves primarily for the livestock sector, alternative sources need to be explored. Therefore, this study aimed to evaluate the potential of Arundo donax, a perennial energy crop, as an alternative feedstock in a continuous anaerobic process. The biogas yield and its quality, characterized by CH4, CO2, H2S and O2 content, were determined during a continuous process with A. donax, compared with two mixed feedstocks of A. donax and corn silage over a 5‐month period in a continuous anaerobic digestion process. The results revealed that A. donax exhibits a biogas yield and methane content comparable to corn silage, indicating its potential as a viable and sustainable alternative feedstock for biogas production.

Laboratory Investigation of Biogas Production Using Cow Dungs and Kitchen Wastes Otta

Laboratory Investigation of Biogas Production Using Cow Dungs and Kitchen Wastes Otta

Assessment of Environmental and Economic-Financial Feasibility of Biogas Plants for Agricultural Waste Treatment

The use of individual biogas plants can be a means of solving many energy-environmental and financial-economic problems. The article aims to assess the prerequisites and consequences of using biogas plants at the macro and micro levels to search for opportunities to reduce the cost of their installation and make them more affordable for individual farms. The need for the use of biogas plants by farms is determined by the fact that these farms have a raw material base; the growing cost of energy resources pushes them to search for new sources of profit. At the micro level, the costs of biogas plants in the conditions of companies and individual farms in the Slovak Republic are evaluated. At the macro level, the aggravation of energy and agricultural problems and the need to transition to green technologies require a comprehensive approach to their solution. The article investigated the cost of purchasing and operating biogas plants based on a private company’s data. It assessed the cost of the construction of a biogas plant and more. The analysis of biogas plant operation results showed that its purchase and use by a farm can be financially unprofitable but bring significant benefits in the energy, environmental, and social dimensions.

Fuzzy-random robust flexible programming on sustainable closed-loop renewable energy supply chain

Photovoltaic (PV) systems have become a widely accepted method of harnessing solar energy in recent decades. In addition to the growing use of renewable energies are being used due to the depletion of fossil fuel supplies and the corresponding pollution generated by these non-renewable fuels. Since PV systems possess a limited lifespan, and are predicted to eventually become outdated, sustainability and recycling that should be incorporated into the structure of the solar system supply chain. The management of high and low moisture waste (H&LMW) is crucial due to its harmful environmental impacts, including sludge waste, carbon dioxide (CO2), and acid compounds. This study explores the integration of research on H&LMW and PV systems, focusing on energy generation from biogas, incineration power plants, and PV systems. In this respect, we propose a multi-objective mixed-integer programming model to construct a sustainable closed-loop renewable energy supply chain by considering forward and reverse flow through solar, biogas, and incineration power plants. Reducing CO2 with power-to-gas technology is thought to be an environmentally friendly approach. A novel fuzzy-random robust flexible programming approach based on Me measure is proposed, which overcomes the limitations of addressing the uncertainty of the parameters. Next, in order to solve the suggested multi-objective model, a novel strategy known as utility function based multi-choice conic goal programming is presented. A case study explores the sustainable challenges of a closed-loop renewable energy supply network in India’s renewable energy sector. The experimental results indicate that 9 candidate locations are selected for solar wafer production facilities, while 10, 9, and 15 locations are chosen for solar cell production, module manufacturing, and solar power plants, respectively. A sensitivity analysis reveals that the proportion of air pollution limitations possessively rises from 100% to 80% corresponding to the aggregate cost increases from INR 8021452 to INR 8056542.

Analysis of the Physico-Chemical Properties of Bean Seeds after Three Years of Digestate Use

Taking into consideration its physico-chemical properties, digestate should be used primarily as a fertiliser. The possible ways of using digestate as a fertiliser in agriculture were identified, and digestate collected from an agricultural biogas plant was tested for its macroelement and heavy metal content. The research was conducted on Haplic LUVISOLS soil according FAO classification. The area of the land plots was 75 m2. All measurements were carried out in ten replicates. Seed yield was determined at 2.6 t ha−1. The thousand-seed weight was similar in the three growing seasons, and averaged 171.49 g to 184.44 g for the three years under analysis. For the control object, the average thousand-seed weight from the three years of the experiment was 168.56 g. This parameter was significantly influenced by the year of analysis. The highest protein content was obtained in 2022 (an average of 20.3%), which was significantly higher than in 2021 (20.13%) and 2020 (20.12%). The analysis showed an increase in the average value for the three harvest years regarding the fat content of the multiflora bean seeds depending on the post-harvest digestate dose, ranging from 0.47% to 0.61%. In the control object, the average fat content for the three harvest years under analysis was 0.41%. The year under analysis had no significant impact on fat content. A positive correlation was found between the digestate dose and protein, fat, and carbohydrate contents per 100 g of beans. Increasing the dose resulted in statistically significant differences from the lower dose. The obtained results show an increase in macroelement content depending on the digestate dose applied. The average carbohydrate content per 100 g of beans for the three years under analysis ranged from 49.78 g to 54.01 g, while the calcium content per 100 g of beans ranged from 109.23 mg to 124.00 mg. In contrast, the magnesium content in 100 g of bean ranged from 129.91 g to 137.01 mg, the phosphorus content in 100 g of bean from 366.99 mg to 387.00 mg, and the potassium content in 100 g of bean from 1341.20 mg to 1394.06 mg. Statistical analysis revealed statistically significant differences except for potassium, where no differences were found for the two highest doses. In addition, no differences were found in the average phosphorus and potassium content between the years under analysis. The study showed an increase in yield depending on the amount of digestate applied. The highest dose used in the experiment provided the most nitrogen and macronutrients, with a positive effect on yield velocity, protein and fat content, micronutrients, and macronutrients in beans.

The Use of Hydrodynamic Cavitation to Improve the Anaerobic Digestion of Waste from Dairy Cattle Farming—From Laboratory Tests to Large-Scale Agricultural Biogas Plants

There is a need to find methods to intensify the anaerobic digestion process. One possibility is the use of pretreatment techniques. Many laboratory tests confirm their effectiveness, but in most cases, there is no verification work carried out on industrial plants. A reliable and complete evaluation of new solutions can only be carried out in plants that reflect operating conditions at a higher readiness technological level. This has a direct impact on the scientific value and, above all, on the high application value of innovative technologies. The aim of our research carried out under laboratory conditions and on a large scale was to determine the technological and energy efficiency of the use of hydrodynamic cavitation in the pretreatment of a waste mixture from dairy farms. It has been shown that hydrodynamic cavitation significantly increases the concentration of organic compounds in the dissolved phase. In the most effective variants, the increase in the content of these indicators was over 90% for both COD and TOC. The degree of solubilisation achieved was 49 ± 2.6% for COD and almost 52 ± 4.4% for TOC. Under laboratory conditions, the highest effects of anaerobic digestion were achieved after 10 min of pretreatment. The amount of biogas was, on average, 367 ± 18 mL/gCOD, and the amount of methane was 233 ± 13 mL/gCOD. Further large-scale optimisation trials showed that after 8 min of hydrodynamic cavitation, the biogas yield was 327 ± 8 L/kgCOD with a CH4 content of 62.9 ± 1.9%. With this variant, the net energy yield was 66.4 ± 2.6 kWh/day, a value that was 13.9% higher than the original variant with 10 min of disintegration and 3.1% higher than the variant without pretreatment.

Life Cycle Assessment of Exopolysaccharides and Phycocyanin Production with Arthrospira platensis

In the pursuit of sustainable solutions for contemporary environmental challenges arising from the increasing global demand for energy, this study delves into the potential of cyanobacteria, specifically Arthrospira platensis (commonly known as “spirulina”), as a versatile resource. Employing a life cycle assessment (LCA) in accordance with the ISO 14044:2006 standard and employing both midpoint and endpoint indicators, the study comprehensively evaluates environmental impacts. The research explored a range of scenarios, specifically investigating variations in light intensity and harvesting volume. These investigations were carried out using a pilot-scale photobioreactor, specifically an airlift reactor system featuring a horizontal tubular downcomer. The primary focus is on extracting valuable compounds, namely exopolysaccharides and phycocyanin. It emphasized the extraction of value-added products and strategic integration with a biogas plant for process heat, contributing to developing a sustainable supply network and offering insights into environmentally conscious algae cultivation practices with implications for renewable energy and the production of valuable products. The results emphasize the project’s potential economic feasibility with minimal energy impact from by-product extraction. The environmental assessment identifies marine ecotoxicity and fossil resource depletion as principal impacts, predominantly influenced by upstreaming and harvesting stages. After conducting comparisons across various scenarios, it was found that cultivations under higher light intensities have a lower environmental impact than cultivations with low light supply. However, regardless of light intensity, processes with shorter harvesting cycles tend to have a smaller environmental impact compared to processes with longer harvesting cycles. Overall, this research contributes a nuanced and realistic perspective, fostering informed decision-making in sustainable algae cultivation practices, with implications for renewable energy and valuable compound production.

Improvement of Biogas Production Utilizing a Complex Anaerobic Digestion Model and Gradient-Based Optimization

Anaerobic digestion (AD) is a promising technology for renewable energy production from organic waste. In order to maximize the produced biogas quantity and quality, this paper deals with the optimization of the AD process in a CSTR bioreactor of a full-scale biogas plant. For this purpose, a novel approach was adopted coupling, a highly complex BioModel for AD simulation, and a gradient-based optimization method. In order to improve AD performance, the dosages of various types of biological additives, the dosages of inorganic additives, and the temperature in the bioreactor were optimized in three different scenarios. The best biogas quality was obtained using multi-objective optimization, where the objective function involves the following two conflicting objectives: the maximization of biogas production and minimization of the needed heating energy. The obtained results show that, potentially, the content of CH4 can be increased by 11%, while the contents of H2, H2S, and NH3 can be reduced by 30%, 20%, and 81% when comparing the simulation results with the experimental data. The obtained results confirm the usefulness of the proposed approach, which can easily be adapted or upgraded for other bioreactor types.

Briquetting as a source pretreatment strategy to improve energy recovery from the anaerobic digestion of agricultural straw: Experimental and economic evaluation

The sustainability of biogas production from straws is limited by the collection, transportation, storage, and pretreatment of feedstocks. To address these constraints, this study investigated briquetting as a pretreatment strategy for rice straw (RS) to increase bioenergy generation. The results indicated that briquetted RS yielded 205.4 mL/g VS of methane, which was 11.7% higher compared to that produced by the untreated RS. The economic analysis revealed that the briquetting process had positive effects with a payback time of 3.4 y and an internal rate of return of 23.4%. It also reduced feedstock transportation and storage costs by 42.6%. Adding a NaOH treatment to the briquetting process increased methane production by 26.4% compared to untreated RS. However, the integration of briquetting with NaOH treatment might be an unprofitable method for processing RS. This became apparent when examining the production cost, which stood at 1.13 $/kg biomethane with an internal rate of return of 16.2%, representing an 8.7% increase and a 7.2% decrease, respectively, compared to the mono briquetting method. These results revealed that briquetting as a source pretreatment strategy can improve the productivity of straw biogas plants, thereby advancing the industry towards cleaner production.

Bioaugmentation strategies based on bacterial and methanogenic cultures to relieve stress in anaerobic digestion of protein-rich substrates

Anaerobic co-digestion of protein-rich substrates is a prominent strategy for converting valuable feedstocks into methane, but it releases ammonia, which can inhibit the overall process. This study developed a cutting-edge combined culturomic and metagenomic approach to investigate the microbial composition of an ammonia-tolerant biogas plant. Newly-isolated microorganisms were used for bioaugmentation of stressed batch reactors fed with casein, maize silage and their combination. A co-culture enriched with proteolytic bacteria was isolated, selected and compared with the proteolytic collection strain Pseudomonas lundensis DSM6252. The co-culture and P. lundensis were combined with the ammonia-resistant archaeon Methanoculleus bourgensis MS2 to boost process stability. A microbial population pre-adapted to casein was also tested for evaluating the digestion of protein-rich feedstock. The promising results suggest combining proteolytic bacteria and M. bourgensis could exploit microbial co-cultures to improve anaerobic digestion stability and ensure stable productivity even under the harshest of ammonia conditions.

Biogas adoption and its impact on women and the community: evidence from Nepal

ABSTRACT The study examines the benefits of biogas adoption in Nepal using survey data, land satellite images and GIS mapping tools. The study shows from the women’s standpoint how biogas has brought many benefits to local women and the environment. The findings suggest that installing biogas plants saves time for women and improves their respiratory health. It is also concluded that the saved time has not been effectively used. Biogas is also found to be the reason for increased revenues for the community, and replacing 2.7 to 5.3 tonnes of fuel wood annually with an increase in a forest area of 135 hectares. Two major challenges to the sustainability of these benefits related to health, well-being, environment and community are discussed, along with some suggestions for addressing them.

Harnessing sustainable opportunities for nutrient removal and recovery from liquid digestate in a modern municipal food waste biogas power plant

This study aims to efficiently remove and recover Nitrogen (N) and Phosphorus (P) from the Liquid Fraction of the Digestate (LFD) of a municipal Food waste (FW) Anaerobic Digestion (AD) biogas power plants. An experimental design was set up to evaluate the influence of pH, temperature, stirring time, stirring speed, and magnesium to phosphorus molar ratio (Mg: P) on nutrient removal efficiency. It was found that the experimental removal efficiency was up to 89% for P and 79% for N at pH 9.5, stirring at 200 rpm, and temperature of 35 °C. The maximum P removal was reached at 40 minutes of stirring time and an Mg:P molar ratio of 2:1, while the highest N removal was at 120 stirring time and Mg:P molar ratio of 4:1. The Mg:P molar ratio and pH significantly influenced N removal, p-value 0.0429 and < 0.0001, respectively; while stirring time greatly affected P removal efficiency, p-value < 0.0111. The analysis of X-ray diffraction (XRD) and Scanning Electron Microscopy (SEM) revealed that 92.5% of the precipitate consisted of struvite crystals confirming nutrient recovery. The numerical optimization of the experimental design determined that setting up the experiments at pH 8.8, 27°C, 64 minutes of stirring time at 158 rpm, and an Mg:P molar ratio of 2.35 resulted in 67% N and 81% P removal. This approach led to a cost-effective operation that resulted in a significant 66% reduction in process costs. This research identified a solution to managing effluent's environmental challenges for a FW biogas plants.

Influence of climate-smart technologies on the success of livestock donation programs for smallholder farmers in Rwanda

Climate change threatens the livelihoods of Sub-Saharan African farmers through increased droughts. Livestock donation programs offer a potential solution, but their effectiveness under climate stress remains unclear. This study assesses the economic viability of integrating climate-smart technologies (cowsheds and biogas plants) into these programs in Rwanda. Using a stochastic benefit–cost analysis from the beneficiary perspective, we evaluate the net gains for households receiving heifers compared to the current program. Our findings reveal that integrating climate-smart technologies significantly enhances economic viability. Households with cows and climate-smart technologies can possibly realise net benefits 3.5 times higher than the current program, with benefit–cost ratios reaching 5:1. Beyond economic benefits, adopting biogas reduces deforestation, greenhouse gas emissions, and respiratory illness risks. This study demonstrates that integrating climate-smart technologies into livestock donation programs can generate positive economic, environmental, and health benefits, leading to more resilient and sustainable smallholder systems. However, overcoming implementation challenges requires tailored policy packages addressing local barriers.