Mobile Greenhouse Gas Emission Surveys from Canadian Landfills (2022)
Bibliographic record
Abstract
Description This metadata contains the Greenhouse Gas (GHG) emission mixing ratios collected during mobile surveys by FluxLab between June 26th and November 20th, 2022, from 125 Canadian landfills through offsite transects measurement from public roads. The data is organized into two folders: 1. Time series for downwind offsite transects, including Methane (CH4) and Carbon Dioxide (CO2) concentration, wind speed and direction, and anonymized UTM location 2. Anonymized UTM location for landfill polygon. This project was funded by Environment and Climate Change Canada (ECCC) and aimed to provide insight into different types of landfills, including active and inactive a well as those with or without landfill gas collection systems. During our campaign, we equipped a research vehicle with a Picarro G2210i cavity ring-down spectrometer to measure CH₄ and CO₂ at 1-2 Hz. The inlet was mounted on a mast on the roof of the vehicle at a height of 80 cm, resulting in a total elevation of approximately 2.5-2.7 m above ground level. The mast supported other essential instruments, including a Gill Ultrasonic Anemometer for measuring wind speed and direction data with precision of 3% route mean square error (RMSE) for wind speed and ±3° for wind direction, a digital compass for precise orientation, and a high-accuracy GPS unit to track the vehicle's location throughout our surveys. Every day, we performed GPS calibration by driving the vehicle in all four cardinal directions—north, south, east, and west. This allowed us to assess the accuracy of the GPS readings and make necessary adjustments to ensure reliable positioning data. All of our sensor data were logged using a CR1000X Campbell Scientific data logger, allowing us to synchronize the data collection from each instrument. To ensure the accuracy of our gas measurements, we utilized benchmarking gases to evaluate the analyzer’s performance before and after the campaign in the lab using traceable gases, and daily during the campaign using compressed air cylinders of known concentration. Additionally, we conducted breath tests at the gas inlet prior to each survey to assess and correct for the time lag between the inlet and the analyzer introduced by the pump, tubing, and analyzer delay. We sampled by driving slowly (~15-20 km hr-1) from the ambient toward the elevated CH4 concentration and then back to the ambient to sample the entire crosswind section of the plume. In most cases, public road access was the limiting factor for the number and location of the offsite transects.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.011 | 0.003 |
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".