Evaluating the opportunity for utilising anaerobic digestion and pyrolysis of livestock manure and grass silage to decarbonise gas infrastructure: A Northern Ireland case study
Bibliographic record
Abstract
The need to mitigate climate change and improve energy security has led to an increasing interest in the utilisation of renewable gas to decarbonise natural gas use. Northern Ireland serves as an interesting case study to evaluate how biomethane from manure and silage material can displace natural gas. This is because of high agricultural intensity, the low penetration of gas relative to the wider UK and the modern pipeline infrastructure. This study included spatial mapping of biomethane yield and life cycle assessment for processing scenarios. The results demonstrated that current manure management i.e., storage and application of manure to grassland, results in 344 kg CO2 equivalent/person of greenhouse gases and 9.7 kg/person of ammonia being emitted. In a second scenario where collected manure and underutilised grass silage is routed to anaerobic digestion, the estimated net energy produced is 6124 GWh, with −464 kg CO2 equivalent/person. A third scenario, combining anaerobic digestion and pyrolysis, also produces 6124 GWh and 200 kilo tonnes of biochar (retaining 64% of manure phosphorus), −563 kg CO2 equivalent/person. This research evaluates the opportunity for biomethane while acknowledging that a comprehensive approach which balances energy potentials and nutrient management is required for sustainable biomethane based decarbonisation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".