Calculator Tool for Determining Greenhouse Gas Emissions for Biosolids Processing and End Use
Bibliographic record
Abstract
A greenhouse gas (GHG) calculator tool (Biosolids Emissions Assessment Model, BEAM) was developed for the Canadian Council of Ministers of the Environment to allow municipalities to estimate GHG emissions from biosolids management. The tool was developed using data from peer reviewed literature and municipalities. GHG emissions from biosolids processing through final end use/disposal were modeled. Emissions from nine existing programs in Canada were estimated using the model. The program that involved dewatering followed by combustion resulted in the highest GHG emissions (Mg CO(2)e 100 Mg(-1) biosolids (dry wt.). The programs that had digestion followed by land application resulted in the lowest emissions (-26 and -23 Mg CO(2)e 100 Mg(-1) biosolids (dry wt.). Transportation had relatively minor effects on overall emissions. The greatest areas of uncertainty in the model include N(2)O emissions from land application and biosolids processing. The model suggests that targeted use of biosolids and optimizing processes to avoid CH(4) and N(2)O emissions can result in significant GHG savings.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.021 | 0.005 |
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".