A Novel Ground Based Mass-Balance Method for Methane Emission Quantification
Bibliographic record
Abstract
Emission of CH4 from landfills in Canada are not well constrained and in Ontario constitute the largest point source emitters. The purpose of this study was to develop and test a ground based method for quantifying CH4 emissions from large sources. Emissions of CH4 were quantified from the Keele Valley Landfill (KVL) using ground based mobile mass balance approach where a mobile cavity ring down spectroscopy (CRDS) instrument captured the downwind field of CH4 mixing ratio enhancements relative to the background. The approach involves measuring the downwind field of enhancements at successively further distances from the source until the integrated CH4 enhancements converge. On multiple days in April and May 2016 multiple transects were driven upwind and at increasing distances downwind from the KVL with the CRDS in a vehicle in order to determine integral flux emission estimates. The KVL was found to be a major local source of CH4 even though CH4 collection used for electricity generation is now terminated. An average emission rate of 429 199 kg/hr of CH4 was measured in 2017 on several days, which is less than the ECCC emission inventory value of 2149 kg/hr [2015]. The source of the discrepancy is not fully understood, but may be related to the shutdown of the KVL facility. The largest source of uncertainty in our emission estimate calculation was the height of the PBL, which
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".