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Dataset results
26 results for “biogas”
Dataset _ Influence of the seasonal variation of environmental conditions on biogas upgrading in an outdoors pilot scale high rate algal pond
<p>This is the dataset used for the publication of the journal article title<em> “</em><strong>Influence of the seasonal variation of environmental conditions on biogas upgrading in an outdoors pilot scale high rate algal pond”. </strong>In this dataset there is all the information collected in the experimentation process.</p>
Dataset _ Seasonal variation of biogas upgrading coupled with digestate treatment in an outdoors pilot scale algal-bacterial photobioreactor
<p>This is the dataset used for the publication of the journal article title<em> “</em><strong>Seasonal variation of biogas upgrading coupled with digestate treatment in an outdoors pilot scale algal-bacterial photobioreactor</strong><strong>”. </strong>In this dataset there is all the information collected in the experimentation process.</p>
Methane losses from different biogas plant technologies
<p>This dataset and R code supplement the publication "Methane losses from different biogas plant technologies" by Wechselberger et al. (2023).</p> <p>The dataset contains primary and secondary data underlying the reported emission factors. By using the R code, emission factors are calculated as published.</p> <p>Available files:</p> <ul> <li>Glossary.csv (column/variable descriptions of dataset)</li> <li>Wechselberger_et_al_2023_data.csv (dataset)</li> <li>Wechselberger_et_al_2023_R_code.Rmd (code for calculating the emission factors reported in Table 2 of the publication)</li> <li>Wechselberger_et_al_2023_data_supplement.zip (containing all of the files above)</li> </ul> <p>Version v2 contains the final reference to the publication Wechselberger et al. (2023). The data are the same as in version v1.</p>
Data for :Nitrogen availability in digestates from full-scale biogas plants following soil application as affected by operation parameters and input feedstocks
<p>This archive contains data for the paper "Nitrogen availability in digestates from full-scale biogas plants following soil application as affected by operation parameters and input feedstocks". Obtained from a soil incubation experiment for 80 days.</p><p> </p>
Dataset _ Influence of liquid-to-biogas ratio and alkalinity on the biogas upgrading performance in a demo scale algal-bacterial photobioreactor
<p>This is the dataset used for the publication of the journal article title<em> “</em><strong>Influence of liquid-to-biogas ratio and alkalinity on the biogas upgrading performance in a demo scale algal-bacterial photobioreactor</strong><strong>”. </strong>In this dataset there is all the information collected in the experimentation process.</p>
Triggering Sustainable Biogas Energy Communities through Social Innovation- ISABEL ---- Social Innovation and Community energy best preactices, methods and tools across Europe ----Semi-structured interviews from communities
<p>Having identified through the literature review various success and failure factors for social innovation applied to community energy projects, ISABEL has further conducted 18 semi-structured interviews of a range of stakeholders. The interviewee sample was a convenience sample of participants in existing projects and thus, inevitably, they are able to speak more to successful than unsuccessful projects and they likely have had less exposure to obstacles to the success of their projects. T The interviews have focused on identifying answers to the questions: <em>What were the key success factors? What obstacles were overcome? How? Participants were also asked to specify the type of renewable energy and community energy model. </em></p>
Dataset of the article: "Technology validation of photosynthetic biogas upgrading in a semi-industrial scale algal-bacterial photobioreactor".
<p>Excel document that contains the data of the article: ‘Technology validation of photosynthetic biogas upgrading in a semi-industrial scale algal-bacterial photobioreactor’. This dataset shows the values obtained during the experimental period and it complements the corresponding article.</p>
Techno Economic Analysis of Biogas Purification by Methane and Acetate Manufacturing CO2 to CH4 2024 SuppInfo
<p>Techno Economic Analysis calculations for manuscript of Biogas Purification by Methane and Acetate Manufacturing to convert CO2 to CH4: Wastewater treatment plants have two persistent financial and energetic drains, the carbon dioxide content of biogas, which limits its commercial sale, and the presence of trace organics in the wastewater effluent, which damages the aquatic ecosystem. Biogas is a renewable methane resource that is underutilized due to the variable CO2 content (~40%). Biogas is energy intensive to purify and limited by the economy of scale (>8.85 GJ/hour) to large-scale purification methods, thus small-scale processes require development. Electrocatalytic microbes native to wastewater have been shown to convert CO2 to CH4 and acetate, however complete conversion of the CO2 content to CH4 is energy intensive. Here we show a low power bioelectrochemical fuel cell design to purify biogas to pipeline quality methane (98%), manufacture methane and/or acetate, and remove trace organics, using HCO3- as the transport charge carrier from dissolved CO2 from the biogas through an anion exchange membrane. This decreased the power required to separate CO2 from methane in biogas on a molar basis, resulting in a net energy recovery similar to current industrial systems. Magnesium anode use resulted in an energy positive system. Tests evaluated the influence of cathode potential on the current density, HCO3- ion flux and the rates and efficiencies of methane production, resulting in optimization at -0.7V vs Standard Hydrogen Electrode (SHE). A techno-economic analysis modeled a positive return on investment for scaled-up production to purify small biogas streams that are otherwise financially unrecoverable. Carbon sequestration by production of methane, acetate and solid fertilizers demonstrated profitable and energy efficient waste-to-resource conversion.</p>
Dataset on PowerWorld Software Power Flow Calculations on an Underground Distribution Feeder for Inserting Renewable Distribution Generation from Biogas, Photovoltaic and Small Wind Sources
<p>This Dataset brings all the information, details and source files used for power flow studies of the USP-105 underground feeder of the distribution medium voltage network in the University of São Paulo campus, which has received several embedded DG sources, namely a biogas plant, photovoltaic units and a small wind turbine.</p> <p>The power flow simulations were realized using the PowerWorldTM Simulator, v.23</p> <p>The files types on the Dataset are: </p> <p>.pwb, .pwd and tsb: Powerworld software input files for the simulations</p> <p>.csv: where a semicolon symbol (;) is used as a column separator, while a dot symbol (.) represents the decimal separator. The first row of each CSV file corresponds to the header row to help identify data.</p>
Data from: Effect of yeast addition on the biogas production performance of a food waste anaerobic digestion system
<p>Food waste contains numerous easily degradable components, and anaerobic digestion is prone to acidification and instability. This work aimed to investigate the effect of adding yeast on biogas production performance, when substrate is added after biogas production is reduced. The results showed that the daily biogas production increased 520 ml and 550 ml by adding 2.0% (VS) of activated yeast on the 12th and 37th day of anaerobic digestion, respectively, and the gas production was relatively stable. In the control group without yeast, the increase of gas production was significantly reduced. After the second addition of substrate and yeast, biogas production only increased 60 ml compared with that before the addition. After fermentation, the biogas production of yeast group also increased by 33.2% compared with the control group. Results of the analysis of indicators, such as volatile organic acids, alkalinity, and propionic acid, showed that the stability of the anaerobic digestion system of the yeast group was higher. Thus, the yeast group is highly likely to recover normal gas production when the biogas production is reduced, and substrate is added. The results provide a reference for experiments on the industrialisation of continuous anaerobic digestion to take tolerable measures when the organic load of the feed fluctuates dramatically.</p>
Data for: Brown juice assisted ensiling of straw and press cake for enhanced biogas production and nutrient availability in digestates
<p>Data for: <span>Brown juice assisted ensiling of straw and press cake for enhanced biogas production and nutrient availability in digestates (https://doi.org/10.1016/j.eti.2023.103248)</span></p>
Dataset - Biogas composition from agricultural sources and organic fraction of municipal solid waste
<p>Data in this file compiled by H. Madi, A. Calbry-Muzyka, F. Rüsch-Pfund, M. Gandiglio, and S. Biollaz as Supplementary Information for "Biogas composition from agricultural sources and organic fraction of municipal solid waste", 2021. Table format in this file adapted from D. Papadias et al. at Argonne National Labs, www.cse.anl.gov/FCs_on_biogas/Impurities%20-%20LFG.xls and www.cse.anl.gov/FCs_on_biogas/Impurities%20-%20WWTP.xls (see also doi.org/10.1016/j.energy.2012.06.031).</p>
Dataset - Biogas production from concentrated yeast biomass by anaerobic (co)-digestion
<p>Excel document that contains the data of the anaerobic digestion of concentrated yeast biomass as mono-substrate under mesophilic and thermophilic conditions. The dataset includes all values obtained during the experimental period from 11/2018 – 08/2019. The data were obtained as measurement data of the experimental work on biogas production. These data form the basis for the calculation of yields and productivities and for evaluating the process stability.</p>
biogasoutcomesmalawi: Data for 61 semi-structured interviews with biogas owners in Malawi
<p>This dataset consists of 61 semi-structured interviews with biogas owners in the Southern Region of Malawi. Interviews were conducted over multiple visits to sites over the course of a two-year period between June 2021 and October 2022.</p>
Data from: Effect of yeast addition on the biogas production performance of a food waste anaerobic digestion system
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Flexibilization or biomethane upgrading? Investment preference of German biogas plant operators for the follow-up of guaranteed feed-in tariffs
<p><span>This dataset reports the results of a discrete choice experiment with 183 German biogas plant operators designed to elicit the respondents' plans for biogas utilization pathways after the end of guaranteed feed-in tariffs. Participants could choose between 'flexibilization' for demand-based electricity generation and conversion to biomethane upgrading for direct feed-in into the natural gas grid. A binomial logit model revealed a 37% probability of switching to biomethane upgrading. These plants are characterized by higher capacities, several involved shareholders, secured succession, costly digestate disposal and belonging to the upper performance quartile. Mixed logit estimations conducted separately for the two investment concepts revealed a very high overall willingness to invest: 71% for flexibilization and 82% for biomethane upgrading. The respondents demand a return on investment of 19% for flexibilization and 26% for biomethane upgrading. Within the flexibilization, twofold overbuilding (installed capacity equals 2 times the rated power) is clearly preferred to fivefold overbuilding. For the biomethane upgrading, private ownership of the upgrading plant is preferred to a joint investment in a central upgrading facility. Limiting the use of energy crops reduces the propensity to invest in both models, while a longer utilization period enhances it. The respondents consider lack of planning reliability as the biggest obstacle to invest, followed by long approval procedures and high investment costs due to restrictive legal requirements.</span></p>
Socio-Economic Factors Influencing Biogas Technology Uptake among Rural Households in Kuresoi South Sub-County, Nakuru County
<p>Biogas technology presents an alternative sustainable energy source that offers an opportunity to transform energy security, environmental sustainability, and reduction in greenhouse gas emissions. The research study explores the socioeconomic factors affecting biogas technology uptake among rural households in Kuresoi South Sub-County, Nakuru County. This is a descriptive study design based on the use of both primary and secondary data sources. The data collection covered 155 respondents through the use of questionnaires, focus group discussions, key informant interviews and observations. Selection of the respondents was done by using systematic random sampling, while data analysis was done using descriptive statistics, chi-square tests, and cross-tabulation supported by SPSS version 26. Results indicated that despite high levels of awareness, the adoption of biogas technology was low, with firewood remaining the primary source of energy in 68% of the households. Fixed dome and tubular were the biogas digester types in use, since they are relatively cheaper and more durable; however, economic factors, mainly household income, were the main determinant of uptake. The chi-square results indicated that there was a significant relationship between household income and uptake of biogas, χ² = 9.531, p = 0.048, implying that the poorer a household is, the greater the financial barrier to the technology. Level of education, too had a say in energy adoption; education and energy choice had a strong association-since χ² = 12.814, p = 0.002-which depicted that more educated households were more likely to adopt the technology. The gender factor is insignificant in influencing energy choices, underlining a proof from the fact that χ² = 2.119, p = 0.346, where broader socio-economic factors played a much greater role in decisions. This study also revealed out that radio was the effective channel for knowledge sharing and information dissemination related to biogas technology. On the other hand, partial understanding of the technical aspects has acted as a big barrier to the better diffusion of this technology. In conclusion, income levels and education are two main factors affecting the uptake of biogas technology. Enhanced education, targeted financial support and better outreach strategies go toward increasing adoption rates and supporting transitions to sustainable energy in rural areas.</p>
Flexibilization or biomethane upgrading? Investment preference of German biogas plant operators for the follow-up of guaranteed feed-in tariffs
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INVESTIGATION OF BIOGAS PRODUCTION AT THE METANTENK INSTALLATION
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TECHNOLOGY OF BIOGAS PRODUCTION FROM LIVESTOCK WASTE IN A TRADITIONAL WAY
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