A Critical Overview of the State-of-the-Art Methods for Biogas Purification and Utilization Processes
Bibliographic record
Abstract
Biogas is one of the most attractive renewable resources due to its ability to convert waste into energy. Biogas is produced during an anaerobic digestion process from different organic waste resources with a combination of mainly CH4 (~50 mol/mol), CO2 (~15 mol/mol), and some trace gasses. The percentage of these trace gases is related to operating conditions and feedstocks. Due to the impurities of the trace gases, raw biogas has to be cleaned before use for many applications. Therefore, the cleaning, upgrading, and utilization of biogas has become an important topic that has been widely studied in recent years. In this review, raw biogas components are investigated in relation to feedstock resources. Then, using recent developments, it describes the cleaning methods that have been used to eliminate unwanted components in biogas. Additionally, the upgrading processes are systematically reviewed according to their technology, recovery range, and state of the art methods in this area, regarding obtaining biomethane from biogas. Furthermore, these upgrading methods have been comprehensively reviewed and compared with each other in terms of electricity consumption and methane losses. This comparison revealed that amine scrubbing is one the most promising methods in terms of methane losses and the energy demand of the system. In the section on biogas utilization, raw biogas and biomethane have been assessed with recently available data from the literature according to their usage areas and methods. It seems that biogas can be used as a biofuel to produce energy via CHP and fuel cells with high efficiency. Moreover, it is able to be utilized in an internal combustion engine which reduces exhaust emissions by using biofuels. Lastly, chemical production such as biomethanol, bioethanol, and higher alcohols are in the development stage for utilization of biogas and are discussed in depth. This review reveals that most biogas utilization approaches are in their early stages. The gaps that require further investigations in the field have been identified and highlighted for future research.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.003 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".