Potential contribution of biogas to net zero energy systems – A comparative study of Canada and Germany
Bibliographic record
Abstract
Urgent action is needed to stay within the Paris Agreement's temperature goal of limiting global average temperature rise to 1.5 Celsius above the pre-industrial levels. Very stringent emissions reduction and accelerated transition from fossil fuel-based to low- or zero-carbon systems is key, together with additional atmospheric carbon removal to control remaining anthropogenic CO 2 levels. Biogas, derived from organic residues and waste, can not only provide a valuable sustainable substitute for natural gas, but also serve as a tool for carbon dioxide removal, e.g. when combined with CO2-separation during upgrading to biomethane, or through usage of digestate (including biochar). Moreover, as a mature technology, it provides a significant near-term opportunity for bioenergy with carbon capture and storage. This study assesses the potential contribution of biogas made from biogenic residues and waste to net-zero energy systems. Our comparative analysis includes a biomass potential assessment, a review of current biogas production practices, and an examination of CO 2 flows along the biogas value chain. We present a consolidated and harmonized dataset for Germany and Canada, identifying a significant potential to contribute to CO 2 emission reductions, with an estimated 30 million tons per year in each country. The contrast between the two countries is informative. In Germany, the provision of biogas and biomethane is already widely established, whereas Canadian biogas usage is still at an early stage in certain provinces. Canada, however, has a stronger focus on CO 2 separation, and more coherent options for carbon capture and storage. To unlock their full potential, each of the two countries' distinct strategies could draw on the other country's complementary experience in deriving an optimal solution. • Biogas provision can contribute to carbon dioxide removal in different ways. • Germany and Canada have reasonable biogenic residue streams for biogas production. • Both countries could capture up to 30 million tons CO2 per year with biogas. • Between the countries, different implementation strategies are necessary.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.005 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".