Bibliographic record
Abstract
Mitigating methane (CH4 ) emissions is a necessary intervention to address the immediate impacts of anthropogenic climate change. Bottom-up inventories and models are used to predict the quantity of CH4 emissions, but these estimates are poorly constrained, especially on a source-by-source basis. Measuring CH4 atmospheric concentrations enables direct estimation of emissions rates, and allows for the direct monitoring of the efficacy of emissions mitigation interventions. Within the GreaterToronto Area (GTA), high resolution CH4 inventories predict that anthropogenic CH4 comprises the majority of emissions, primarily from landfills. Atmospheric measurements of CH4 were conducted to quantify emissions from sources in the GTA and throughout Southern Ontario. Within the GTA, a network of solar-viewing Fourier transform infrared (FTIR) spectrometers was used to quantify the total column dry air mole fractions of CH4 and other greenhouse gases (GHG). This network was expanded to five semi-permanent observatory sites and operated to measure emissions coming from the GTA. In order to confirm, quantify, and discover new sources of CH4 emissions in the GTA, a bicycle-based mobile in situ measurement laboratory was deployed to measure CH4 concentrations downwind of sources in the city. These measurements were used to quantify emissions from various urban CH4 sources. Over 650 downwind transects of solid waste and water resource recovery facilities (WRRFs) were used to quantify CH4 emissions from the waste sector in Southern Ontario. From these measurements, solid waste emissions in the GTA in bottom-up inventories were shown to be overestimated. These data were used to investigate correlations between emissions and predictive variables such as meteorological variability for landfills, and volume of treated water for WRRFs. At a large, active landfill facility in Southern Ontario, six different emissions quantification technologies were compared. This study demonstrates that each technology was capable of quantifying emissions from this facility, and that their average measured emission rates all agreed within uncertainty. Lower measured emissions rates were observed from the ground-based in situ methodologies, and possible explanations for these differences are explored. Implications for monitoring Canadian landfill emissions are discussed with respect to the demonstrated detection limits of these technologies.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".