Impact of co-digestion versus mono-digestion on biogas and CH4 yield for a set of five biomass materials (vegetable food waste, cow dung, pig manure, grass clippings, and chicken manure) was investigated considering 95 different biomass mixes of the five materials under thermophilic conditions in bench-scale batch experiments over a period of 65days. Average biogas and CH4 yields were significantly higher during co-digestion than during mono-digestion of the same materials. This improvement was most significant for co-digestion experiments involving three biomass types, although it was independent of the specific biomasses being co-digested. Improvement in CH4 production was further more prominent early in the digestion process during co-digestion compared to mono-digestion. Co-digestion also appeared to increase the ultimate CH4/CO2 ratio of the gas produced compared to mono-digestion although this tendency was relatively weak and not statistically significant.
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http://dx.doi.org/10.1016/j.wasman.2016.05.020 | DOI Listing |
Water Sci Technol
January 2025
Engineering & Energy, College of Science Health Engineering and Education, Murdoch University, 6150 Perth, Australia E-mail:
Biogas, consisting mainly of CO and CH, offers a sustainable source of energy. However, this gaseous stream has been undervalued in wastewater treatment plants owing to its high CO content. Biogas upgrading by capturing CO broadens its utilisation as a substitute for natural gas.
View Article and Find Full Text PDFRSC Adv
January 2025
a, Department of Chemical Engineering, Birla Institute of Technology & Science, Pilani Campus Pilani Rajasthan 333031 India +91-1596255839.
To address the limitations of polymeric membranes, mixed matrix membranes for CO separation from biogas mixtures (CO and CH) have been investigated utilizing various fillers. In this study, we investigated novel MMMs using 3D and 2D indium-based MOFs, MIL-68(In)-NH and In(aip), in a polysulfone polymer matrix. To confirm synthesis, both fillers were subjected to XRD and FTIR analysis, as well as FESEM characterization to assess their 2D and 3D structures.
View Article and Find Full Text PDFEnviron Res
January 2025
Department of Chemistry, Faculty of Mathematics and Natural Sciences, Universitas Padjadjaran, Jatinangor, West Java, 45363, Indonesia; Research Collaboration Center for Biomass and Biorefinery Between BRIN and Universitas Padjadjaran, Jatinangor, West Java, 45363, Indonesia.
Managing wastewater and using renewable energy sources are challenges in achieving sustainable development goals. This study provides an overview of the factors influencing the performance of algae-based membrane bioreactors (AMBRs) for contaminant removal from wastewater and biogas production. This review highlights that the performance of AMBRs in removing total phosphorus (TP) and nitrogen (N) from wastewater can reach up to 93% and 97%, respectively, depending on parameters such as pH, hydraulic retention time (HRT), and algae concentration.
View Article and Find Full Text PDFEnviron Res
January 2025
Research & Development Institute in Shenzhen, School of Chemistry and Chemical Engineering, Northwestern Polytechnical University, China. Electronic address:
Adding additives exogenously is an effective strategy to enhance methanogenic activity and improve AD stability. Corn straw-based biochar@MIL-88A(Fe) (BM) was synthesized herewith and used as an exogenous additive to boost methane (CH) production. After adding BM at 250 mg/g WAS VS, the accumulative CH production and maximum CH yield increased by 1.
View Article and Find Full Text PDFJ Chem Theory Comput
January 2025
Department of Chemical and Bimolecular Engineering, National University of Singapore, 117576 Singapore.
Biogas, primarily composed of methane (CH) and carbon dioxide (CO), is considered an alternative renewable energy resource. Efficient CO/CH separation is essential for biogas upgrading to increase energy density, and in this context, metal-organic frameworks (MOFs) have demonstrated significant potential. Here, we integrate multiscale modeling with cross-diversity machine learning (ML) to unveil MOFs with open copper sites (OCS-MOFs) that exhibit exceptional CO/CH separation performance.
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