Volume Of Biogas Production Research Articles

Prediction of Biogas Production Volumes from Household Organic Waste Based on Machine Learning

The article proposes to use machine learning as one of the areas of artificial intelligence to forecast the volume of biogas production from household organic waste. The use of five regression algorithms (Linear Regression, Ridge Regression, Lasso Regression, Random Forest Regression, and Gradient Boosting Regression) to create an effective model for forecasting the volume of biogas production from household organic waste is considered. Based on the comparison of these algorithms by MSE and MAE indicators, the quality of training and their accuracy during forecasting are evaluated. The proposed algorithm for creating a model for forecasting biogas production volumes from household organic waste involves the implementation of 10 main and 3 auxiliary steps. Their advantage is that they aid in the performance of component data analysis, which is carried out based on the method of reducing the dimensionality of the data set, increasing interpretability, and minimizing the risk of data loss. An analysis of 2433 data is was carried out, which characterizes the formation of biogas from food (FW) and yard waste (YW) according to four features. Data preparation is performed using the Jupyter Notebook environment in Python. We select five machine learning algorithms to substantiate an effective model for forecasting volumes of biogas production from household organic waste. On the basis of the conducted research, the main advantages and disadvantages of the used algorithms for building forecasting models of biogas production volumes from household organic waste are determined. It is found that two models, “Random Forest Regressor” and “Gradient Boosting Regressor”, show the best accuracy indicators. The other three models (Linear Regression, Ridge Regression, Lasso Regression) are inferior in accuracy and were not considered further. To determine the accuracy of the “Random Forest Regressor” and “Gradient Boosting Regressor” models, we choose the MSE and MAE indicators. The Random Forest Regressor model is found to be a more accurate model compared to the Gradient Boosting Regressor. This is confirmed by the fact that the MSE of the “Random Forest Regressor” model on the training data set is 7.14 times smaller than that of the “Gradient Boosting Regressor” model. At the same time, MAE is 2.67 times smaller in the “Random Forest Regressor” model than in the “Gradient Boosting Regressor” model. The MSE and MAE of both models are worse on the test data set, which indicates overtraining tendencies. The Gradient Boosting Regressor model has worse MSE and MAE than the Random Forest Regressor model on both the training and test data sets. It is established that the model based on the “Random Forest Regressor” algorithm is the most effective for forecasting the volume of biogas production from household organic waste. It provides MAE = 0.088 on test data and the smallest absolute errors in predictions. Further systematic improvement of the “Random Forest Regressor” model for forecasting biogas production volumes from household organic waste based on new data will ensure its accuracy and maintain competitive advantages.

Study of parameters for the design of a continuous flow laboratory biogas reactor

This study aimed to determine the parameters needed to design a continuos flow bioreactor. Developing studies that expand the quantity and efficiency of biogas currently produced on an industrial anaerobic wastewater treatment in a food processing plant in the Brazilian State of Goiás. The procedures developed in this work we used nine sets of bioreactors in batch and followed the German Standard VDI 4630. A special workbench was developed for that purpose, alternative procedures for determining the volume of the produced biogas were tested. The biomass studied in this work is the resulting sludge of the wastewater treatment from an industrial plant. The daily production is about nine tons, currently, which is totally discarded. Through this batch tests, it was possible to calculate the volume of biogas production and the ideal biomass retention time of the biomass. Obtained data to project a laboratory continuous flow bioreactor. With this data was made a projection of the biogas production potential by the use of this feedstock in an industrial bioreactor constructed for this purpose.

The Effect of Temperature, Pressure and PH on Volume of Biogas Production from Anaerobic Digestion of Plant & Animal Wastes

Many factors affect the volume of biogas production in the anaerobic digestion of plant and animal wastes. In this treatise the three major factors of temperature, pressure and PH are investigated. Here the biodegradable wastes used were Cassava peelings and cow dungs, Beans waste and cow dungs, Cassava peelings and beans wastes. For the purpose of this investigation, a 100 liters capacity steel biogas digester was constructed to investigate these factors. A batch operation method was used whereby a daily biogas generation was monitored for 24 consecutive days. It is pertinent to state here that other factors that could affect the volume of biogas production like alkalinity, acidity etc were ignored. Cassava peelings and cow dungs produced the highest biogas of 0.032m2 /kg/day at a pH value of 7.34, followed by beans waste and cow dungs mixture and lastly Cassava peelings and beans waste having the least volume. The respective effects of temperature, pressure and PH were monitored and plotted alongside these biogas productions to showcase their effects. From the plots, their respective effects on the respective volumes of biogas generated can easily be seen. It is important to note in the passing that biogas is a form of renewable energy.

Evaluation of Biogas Production Potential from Waste Coconut Water

Coconut oil production is the eminent agro based industries in Tamil Nadu. The matured coconut water was considered as a waste. Coconut oil industries discharge considerable amount of waste coconut water having very high values of Biochemical Oxygen Demand (BOD) to the extent of 29,000 mgl-1, the wash water about 3,000 mg. and Total Solids (TS) of 5.45 ± 0.35%. Coconut water contains most nutrients required for microbial growth. The pH of coconut water is 6.1. The Total Suspended Solids in coconut water is found out as 0.0028 g/ml. The Total Dissolved Solids is 0.8014 g/ml, Total Solids is 0.8042 g/ml and Volatile Soluble Solids is 99.5 %. A laboratory scale batch type anaerobic digester (Air tight 2 litre plastic bottles) was set up for the experimental purpose for a retention time of 35 days. Coconut water, water and cow dung were mixed in different proportions (5 treatments). Each treatment was replicated 3 times. Biogas volume and biogas composition were measured at 5:30 pm every day. Remarkable volume of biogas production was noticed between 12th and 16th days. Maximum biogas volume of 976. 67 ml was noticed for the combination of 1:1 (Cow dung: Coconut water) with methane content of 53 %. For the combination of 2:1:1 (Cow dung: Coconut water: Water) the maximum volume of biogas production is 833.3ml with methane content of 31 %. For the combination of 1:1 (water: Cow Dung) the maximum volume of biogas produced is 133.3 ml with methane content of 48 %. The biogas produced from different ratios was tested for its flammability. It was seen that blue flame is produced and the flame is last for few seconds for all ratios but the maximum amount of flame was produced from the sample which contains maximum amount of Coconut water than other samples.

Dynamics of gas distribution in batch-scale fermentation experiments: The unpredictive distribution of biogas between headspace and gas collection device

Biohydrogen potential of biodegradable samples is often evaluated with batch experiments, where gas collection devices (gasbags, syringes, water displacement units) are used for gas quantification and analysis. When calculating biohydrogen production rate and yield, the biogas distribution in headspace and gas collection devices is often assumed to be identical. For the first time, the effect of gas generation rate and headspace volume on gas distribution in these two locations was examined. Based on abiotic studies, a model for the biogas distribution was developed and experimentally validated. The results suggested a minimum 5% and a maximum 30% difference in biogas concentration between headspace and gas collection unit when the volume of biogas produced was between 0.1 and 20 times the headspace volume. The maximum difference (ca. 30%) was detected when volume of biogas production reached 1.6 times the volume of headspace. While a precise difference was evident with abiotic experiments, such a predictable difference was not observed with biotic experiments due to the dynamic nature of biological systems. Given this difference of biogas measurements between headspace and gas collection device was largely ignored in past research, the purity of produced biohydrogen reported in some literature remains notably inaccurate, specifically when concentrations reported were derived only with a measurement of biogas in either headspace or gas collection device. Further, this error in measurement in batch experiments carried out by industry to examine biogas potential, gas quality assurance and quality control has also likely negatively impacted industry operations, industry insights, strategic decision making, and regulatory compliance. This error in biogas measurement in batch experiments can be rectified by considering the biogas composition in both headspace and gas collection device.

Optimizing biogas production using artificial neural network

The object of this study is the operating parameters of the anaerobic digestion unit. The study aims to increase the potential of biogas production. The task to select the optimal parameters of the working process of anaerobic digestion has been solved. A model of cumulative biogas and methane output in the process of anaerobic waste digestion has been constructed, which is conceptualized using the method of artificial neural network. The model is built on the basis of 11 process-related variables, such as hydraulic retention time, pH, operating temperature, etc. The plant parameters, leading to the highest volume of biogas production, were selected. It was determined that the optimal amount of biogas can be brought to 90 %, which exceeds the maximum value obtained from factory records by 12.6 % to 700 m3/t. Working conditions that led to optimal methane production were defined as the temperature of 39 °C, the total solids of 4.5 %, the organic percentage of 97.8 %, and pH 8.0. It was found that biogas production is the highest at temperature within the thermophilic range while the local maximum is achieved in the mesophilic temperature range. The model built serves to determine the optimal operating parameters for maximum biogas production and could be used to optimize biogas production productivity using limited experimental data. The model also makes it possible to predict the performance of anaerobic digestion under untested conditions. It is possible to practically use the developed biogas production model when monitoring the operation of the anaerobic digestion unit, to increase the efficiency of the process, and when adjusting the working conditions of the methane tank

Production and Kinetic Study of Biogas Formation from Cow Dung and Utilization of Biogas Effluent as Bio-Fertilizer

Biogas is an alternative and eco-friendly renewable power source and biogas effluent is used as a bio-fertilizer. In this research, the kinetic of biogas formation was studied and also the acceptance of biogas effluent as a bio-fertilizer was evaluated. 8000 g of cow dung and 600 ml of inoculum were fed to the digester. The volume of biogas production was observed for 50 days by using Orsat Apparatus and gas chromatography was used to analyze the gas. From the data, it was found that the formation of methane gas didn’t depend upon the concentration of cow-dung hydrocarbon and it followed the mechanism of the zero-order reaction. On the other hand, the elementary analysis of biogas effluent by AAS ensured the property of effluent as a bio-fertilizer. Utilization of Miscanthus fuscus with E. coli and S. aureus ensured a higher degree of biodegradation.

Production of Biogas from Distillation Residue as a Waste Material from the Distillery Industry in Poland

In this paper, the possibility to obtain an alternative source of energy from methane fermentation, catalysed by biomass, has been discussed in detail. As a main substrate, the distillation residue from the distillery industry was taken in the case of mono-fermentation and its co-fermentation with sewage sludge. The results showed that higher biogas and methane production can be obtained in a mono-fermentation process. Fermentation lasted for 23 days, and during this time, 333.14 and 249.64 L/kg VS of the total biogas for mono- and co-fermentation was subsequently obtained, which gives around 63% and 50% of methane in both types of the process, respectively. Additionally, to interpret the experimental data obtained and to predict the trend of the accumulation curves, a simple Gompertz model has been applied. The application of the Gompertz model has enabled us to estimate some important parameters with a strict physical meaning, namely, the maximum production value of the biogas and its components, the production rate of a given gas, as well as the incubation phase time. Finally, an approximate analysis of the potential volume of biogas production was also carried out, based on the mass of distillation residue produced annually in Poland.

Influence of Potash on Biogas Production from Cow Dung and Food Waste

This study investigated the production of biogas from food waste co-digested with potash and cow dung as inoculant. The aim of this study was to determine the amount of biogas generated from the waste substrate. Experimental research design was used and it was carried out at Uturu, Abia State, Nigeria. 4% to 12% concentrations of the substrate were mixed and fed into anaerobic digesters labeled B1 to B9 for 90days. Result of ultimate analysis showed oxygen (41.33%,14.06%), nitrogen (3.23%,1.48%), carbon (36.50%,29.67%) and PH value(6.25, 8.47) for food waste and cow dung respectively. The quantity of biogas generated in the different digesters (B1-B9) was 1341.2, 1668, 1784.5, 1945.2, 1941.7, 2159.2, 2328.1 and 2428.5m3/day respectively. Analysis of Covariance (ANCOVA) used to model the biogas production volume showed that there was significant contributions in predicting the volume of biogas produced with F (9,611) = 2684.28 and p-value <0.0001. The effect of potash on biogas production revealed that there was an increase in the quantity of gas generated by the substrates with increase in quantity of potash added. Digester B1 with the lowest quantity of potash, generated 1341.2m3/day of biogas while Digester B9 with the highest quantity of potash, generated 2428.5m3/day of biogas in 90days. The flame test showed that the biogas burned with a blue flame. The findings revealed that biogas can be generated from co-digestion of food waste, potash and cow dung. Thus, potash could have helped to boost the biogas production. More studies should be done on how local organic materials can be useful for the production of more biogas.

Production of Biogas from Food Waste Using the Anaerobic Digestion Process with Biofilm-Based Pretreatment

The production of biogas from food waste is a good approach to the minimization of food waste and increase in the production of renewable energy. However, the use of food waste as a feedstock for biogas production currently poses a difficulty due to an ineffective hydrolysis process, which is a pretreatment procedure and the initial step of the biogas conversion process. This restriction results from the food waste polymers’ solubilization and breakdown. This has an impact on the volume of biogas produced during the methanogenesis stage. It is essential to increase the biodegradation of organic compounds (OC) during the hydrolysis process to increase biogas generation. This study focuses on the enhancement of biogas production by the anaerobic digestion (AD) of food waste (FW). FW was hydrolyzed by the immobilized biofilm and digested anaerobically in a semi-continuous digester. Four different digesters including the control were prepared. The control digester composed of no hydrolyzed food waste had no immobilized biofilm while the other three digesters had immobilized biofilm-hydrolyzed food waste with inoculum concentrations of 10%, 30%, and 50%. The results showed that the 50% digester had the highest biogas yield of about 2000 mL/500 mL. The 10%, 30%, and control digesters had a biogas yield of 1523 mL, 753 mL, and 502 mL respectively. Thus, the analysis of total volatile solid (TVS) reduction in the digesters with 10%, 30%, and 50% inoculum and the control have increased to 43.4% for the digesters with 30% and 10%, 60% for the digester with 50% inoculum, and only 29% for the control. Total chemical demand (TCOD) removal increased to 29%, 33%, 43%, and 56% for the control, and 10%, 30%, and 50%, respectively for the inoculum-to-feed ratio. From these results, the 50% inoculum-to-feed ratio has shown the highest biogas production and highest degradation based on TVS reduction and TCOD reduction. Based on this study, the biofilm pretreatment method can be considered a promising method for the enhancement of biogas volume and biodegradation. Biogas production was high (2000 mL) for hydraulic retention time (HRT = 20) days but the HRT = 15 days was also able to produce a significant amount (1400 mL) of biogas and the 50% inoculum-to-feed ratio has shown the highest volume of biogas production.

Hydrolysis of Food Waste with Immobilized Biofilm as a Pretreatment Method for the Enhancement of Biogas Production

The present study shows the opportunity of using biofilm in the hydrolysis step of food waste (FW) to increase biogas production. Therefore, screened biofilm-producing microorganisms were adopted to facilitate the biodegradation of organic compounds (OCs) and enhance the volume of biogas production. The biofilm-producing microorganisms were first immobilized on a granular activated carbon (GAC) surface, and the optimum values of immobilization time, mass of the GAC surface, and size of the microbial inoculums were found using the statistical methods of one-factor-at-a-time (OFAT) and the response surface methodology (RSM) using a face-centered central composite design (FCCCD). Based on the results, 48 h of incubation, 8 g of GAC, and 1 mL of inoculum were the optimum conditions when shaken at 37 °C and 150 rpm. Different biofilm amounts (328 mg, 492 mg, 656 mg, 820 mg, and 984 mg) were used in hydrolysis flasks operated in batch mode to increase the degradation of the OCs. The optimal level of the hydrolysis degradation was on day 3 and at 328 mg of biofilm; the total solid (TS) content was decreased from 115 gL−1 to 79 gL−1 (31%), and the TCOD was decreased from 85.33 gL−1 to 54.50 gL−1 (36%).

PRODUCTION OF BIOGAS FROM CO-DIGESTION OF COW DUNG, CHICKEN DROPPING AND COW RUMEN WASTES

The increased use of fossil fuels for energy consumption has caused environmental problems both locally and globally. This study investigates the anaerobic digestion in the production of biogas, a renewable energy from the digestion and co-digestion of three different types of biodegradable wastes available in Katsina (cow dung, chicken droppings and cow rumen waste) as an alternative for fossil fuels for energy consumption. This was carried out using a 25 Litres capacity plastic keg, constructed to investigate the anaerobic digestion in generating biogas. The experiment was batch operated and the digester was charged with 10 kg of each waste was mixed with 10 kg (10L) of water and loaded into six different batch type biogas plants. Biogas production was measured for a period of 15 days and at an average temperature of 370C. The average biogas production from poultry droppings, cow dung, cow rumen wastes, mixture of cow dung/cow rumen wastes, cow dung/chicken droppings and cow rumen wastes/chicken droppings was found to be 210 cm3/kg, 160 cm3/kg, and 520 cm3/kg, 375cm3/kg, 470 cm3/kg, 390cm3/kg, respectively. During the digestion period, the volume of biogas production and the changes in pH indicate that the pH decreases as the retention period increases. The study recommends that biogas is not just a renewable energy source but also an appropriate way of managing waste, having potential to replace fossil fuel.
 
 

Biogas manufacture from co-digestion of untreated primary sludge with raw chicken manure under anaerobic mesophilic environmental conditions

This work aimed to co-digest various wastes to assess the best combination of all mixing ratio, also at choosing the best ratio between untreated primary sludge (UPS) singly from two sources, (South valley University (SUPS) and Abu tesht wastewater station (AUPS) and raw chicken manure (RCM) and comparing the results in either case. The co-digestions of untreated primary sludge from Abu tesht wastewater treatment stations with different levels of raw chicken manure (0:100, 10:90, 30:70, 50:50, 90:10, and 100:0) to obtain the best mixtures. Also, co-digestion of untreated primary sludge from south valley university with different levels of raw chicken manure at the same ratios, to obtain the best mixtures. Batch digestion tests were applied in 2.5 L digester with a working volume of 2.0 L. The samples in triplicates were separately loaded into the digesters locally fabricated and kept for 20 days as a retention period and diluted with the same amount of water. Mesophilic under 35 °C was adopted for untreated primary sludge as well as mixtures with raw chicken manure based on total solids (TS) and volatile solid (VS) proportions. The average biogas yields from AUPS/RCM mixture obtained ranged from 8570 to 5600 ml, by the following descending order, 10: 90 > 90:10 and so on >100:0, and the average biogas yields from SUPS/RCM obtained ranged from 6330 to 5635 ml, in the order of 90: 10 > 10:90 and so on >100:0. The results showed highest biogas yield from AUPS/RCM and SUPS/RCM mixtures with mixing ratio of 10:90 and 90:10, respectively, however, the lowest biogas production detected in separate digestion of AUPS and SUPS. The results indicated that co-digestion between the sludge and raw chicken manure could increase total biogas production volume, enhance sludge treatment process, and produce eco-friendly sludge because of co-digestion process than separate processing of each feedstock.

Optimization of slurry ratio and sonication time on biogas production from chicken droppings.

A research was conducted on the ultrasonic pretreatment of chicken droppings for biogas production. The hydrolysis step in anaerobic digestion is rate-limiting and time-consuming due to the presence of complex molecules in the organic wastes. Pretreatment encourages faster digestion and yields improvement by making the organic waste ready for microbial attack. To achieve the optimum sonication time and slurry ratio for maximum biogas production, Response Surface Methodology (RSM) was used in this study. 13 experimental runs were developed according to Central Composite Design with different setup conditions and five replicates at center points to observe the Response, i.e., volumes of biogas produced. This was achieved with the aid of a software package (Design Expert 12.0.1.0). A quadratic model was developed for the responses and a 3D response surface plot was obtained to analyze the effect of the variables and their interactions to determine their optimum levels. The numerical optimization and point prediction result gave a sonication time of 18.6 minutes and a slurry ratio of 2.0 (i.e., 2.0 : 1.0). Under this condition, the predicted maximum volume of biogas production is 24.514 ml in 12 days. This prediction was tested and validated, and the volume of biogas produced under the same conditions was 22.282 ml. This confirmed the adequacy of the predicted model as only a 10.02% error was recorded. Henceforth, the optimum sonication time and slurry ratio were achieved for maximum biogas production from chicken droppings.

Strategic Potential of Agricultural Waste as a Feedstock for Biofuels Production in Ukraine

Abstract Ukraine’s agriculture is a leading sector of the national economy. Ukraine has a significant area (603628 km2), 70.9% of which are agricultural lands. Quality soil and good climatic conditions create favorable conditions for the development of crop and livestock production. The generation of a large amount of organic waste from agriculture opens wide opportunities for the development of the biogas technologies. The aim of the paper is to identify the main waste management trends in Ukraine based on data on waste generation and waste management and to calculate the strategic potential of agricultural waste as a feedstock for biofuels production. The resource potential of crop, livestock and processing waste has been considered and the necessity of its use for energy purposes has been substantiated. It has been determined that the greatest potential of agricultural waste that can be used for biogas production in Ukraine is concentrated in crop production. The livestock industry and processing enterprises also have a powerful feedstock base for biogas production. It has been determined that the agroindustrial sector of Ukraine produces significant amount of waste. As a result of the study, it has been found that the potential volume of biogas production from agricultural waste can replace 36.1% of natural gas consumption in Ukraine.

Solving the problem of logistics planning in the application of biotechnology in the energy sector of the region

The article provides a solution to the problem of logistics planning to implement the possibility of using biotechnology in the energy sector. The technology used is the production of biogas from animal wastes. Objects participating in the biogas production process are animal husbandry enterprises that are a source of raw materials, biogas complexes that produce biogas, as well as heat sources where biogas is converted into heat energy. The structure of the optimal location of objects participating in the biogas production process on the territory is built on the example of the Udmurt Republic. An economic criterion for minimizing the cost of biogas production and its delivery to consumers was chosen as an optimization criterion. For the numerical solution of the optimization problem, a genetic algorithm with real coding was implemented, and parallel computations were carried out. The maximum volume of biogas production has been calculated, at which it is economically feasible to replace natural gas with biogas for a given territory. For this volume, the optimal number was determined and the optimal territorial distribution of biogas complexes was constructed, which supply heat sources with fuel, the number of which was also found as a result of solving the optimization problem.

Обґрунтування економічної доцільності переробки зернових культур у біогаз

The article presents a study on the justification of the economic feasibility of processing cereals into biogas. Аt the first stage the sown areas and productivity of separate agricultural crops in the investigated enterprises of Brovarsky district, Kyiv region were analyzed. The tendency to increase the yield of agricultural crops in the studied enterprises was revealed. This was seen as evidence that they could potentially be fully self-sufficient in raw materials for the production of gaseous biofuels. At the second stage of the study, the potential volume of the raw material base for biogas production in the studied enterprises was calculated, potential volume of biogas production and economically feasible volume of biogas production for each enterprise. It is proposed to use part of the grown grain for bioenergy production, and this part should be 10-15% of the gross harvest of grain enterprises in order to prevent the food crisis in the country. At the third stage of the study to determine the economic efficiency of biogas production from wheat and corn, investment costs were calculated, necessary for the implementation of the project to install a biogas plant in the studied enterprises. The authors calculated the investment costs required to implement the project of installing a biogas plant at the studied enterprises. The authors also analyzed the costs of each company for future projects. Finally, the economic efficiency of the proposed project for biogas production in the studied enterprises of Brovary district, Kyiv region is calculated, the economic efficiency of the project in the long run is analyzed with the use of discounted indicators of economic efficiency with a life cycle of 5 years. It was found that the implementation of projects for biogas production may be accompanied by high efficiency, all enterprises will receive profits from the implementation of investment projects for the production of biogas and biofertilizers with the subsequent sale of biogas and the use of biofertilizers for their own needs.

Seasonal Variations in Biogas Production from Excreta of Monogastric Farm Animals under Tropical Climate

The present study analysed the changes in the quantity and composition of biogas produced from the excreta of swine, rabbit and poultry during monsoon and summer seasons. The highest volume of biogas production was observed in rabbit excreta (0.0813 ± 0.0007m3), followed by poultry excreta (0.0778 ± 0.0005 m3) and swine excreta (0.0738 ± 0.0004 m3). Methane concentration was higher in biogas produced from rabbit excreta (70.96 ± 0.19) followed by that from poultry excreta (66.87 ± 0.21) and swine excreta (62.41 ± 0.20), whereas carbon dioxide concentration was highest in swine excreta (28.07 ± 0 .32) followed by rabbit excreta (24.54 ± 0.15) and poultry excreta (22.14 ± 0.14). The biogas production was significantly higher (P less than 0.01) in the summer season compared to monsoon in all three substrates. It was observed that daily mean temperature had a significant positive relationship and relative humidity had a negative relationship with the quantity of biogas produced (P less than 0.01). The gas production also had a significant positive correlation with the temperature and pH of the digesta.

Enhancing the biogas production and the treated effluent quality via an alternative Palm Oil Mill Effluent (POME) treatment process: Integration of thermal pretreatment and dewatering

To address the limitations associated with the disposal management and the treatment process of POME, an alternative process that consists of eliminating the cooling ponds and integrating a pretreatment technology combined with a dewatering device was proposed. Since the proposed treatment process has not been tested previously, the objective of this study is to investigate the effect of thermal pretreatment and solid loading alteration via dewatering on a thermophilic continuous set up consisting of an upflow anaerobic sludge blanket – hollow centered packed bed (UASB-HCPB) bioreactor. It was established that the best performing solid loading was the 40S:60L, which is made up of 40% by volume of POME settled solids and 60% of clarified liquid. Thermally pretreated 40S:60L solid loading had a significantly enhanced biogas production, methane purity, chemical oxygen demand (COD), biological oxygen demand (BOD), and total suspended solids (TSS) removal efficiencies. The reactor exhibited stability owing to the low volatile fatty acid/alkalinity ratio obtained throughout the run. With a reactor capacity of 5L, thermally pretreated 40S:60L achieved a daily biogas production volume of 48L and a methane purity of 77.2%. The COD, BOD, and TSS removal efficiencies of the thermally pretreated 40S:60L solid loading were evaluated to be 97.5, 95.1, and 94.5%. The enhanced process performance is due to the consistent solids concentration, which allowed a more effective mass transfer and transport in the medium. Meanwhile, thermal pretreatment promoted cell lysis, making the intercellular organic matter readily available for the bacteria consortium.

Analysis of Biogas Production From Fermentation Results of Pineapple Bark Waste as Main Raw Material

The need for energy is currently increasing. But, dependence on fossil energy is very high. So, there needs a real effort to develop new and renewable energy sources. One of the sources that can be developed for energy is biogas. Many natural resources can be used as raw material for biogas production, such as pineapple skin waste which is widely available in Kediri. This study aims to analyze the results of biogas production from a combination of pineapple skin, cow dung, EM4, and water. This research uses a qualitative approach. The research method is experimental research. The composition ratio used was 50 kg of pineapple skin, 50 liters of water, 2 kg of cow dung, and 2 liters of EM4. The study time was 30 days. the overall biogas production yield was 0.204 kg. The biggest increase in biogas production occurred on day 17 to day 25. From the results of data processing using numerical methods, the graphical equation of biogas production is described by the equation . y represents the volume of biogas production in grams. x represents the counted days to determine the production process.