Estimating methane emissions from the waste sector in Southern Ontario using atmospheric measurements
Bibliographic record
Abstract
We estimate methane emissions for urban waste treatment facilities from mobile in situ atmospheric concentration measurements using an inverse Gaussian plume methodology at facilities in Southern Ontario, Canada. We use these emission rates to assess and improve the existing high-resolution methane inventories for waste sources throughout Southwestern Ontario. Our measurements encompass tens of thousands of kilometres worth of mobile survey data collected over 7 years, including more than 650 downwind transects where we surveyed 14 active landfills, 11 closed landfills, 2 organic waste processing facilities, 3 open-air windrow compost facilities, and 11 water resource recovery facilities. These sources account for 77% of the active landfills within Southern Ontario, which is estimated in inventories to be the largest source of methane emissions in the region. Within the Greater Toronto Area (GTA) megacity, the measured facilities represent about 52% of the total inventoried non-wetland methane emissions. We find that emissions from closed landfills are lower than inventory estimates, with significant implications for the methane budget in the GTA. We update the Facility Level and Area Methane Emissions for the GTA inventory with our measured emissions rates, which results in a 54% decline in the solid waste emissions, effecting a 35% lower estimate for the total anthropogenic methane emissions in the region. We attribute the bulk of this difference to a single facility: the Keele Valley landfill. Our atmospheric measurements serve as a metric for evaluating the discrepancies between four facility level and two high resolution gridded methane emission inventories. We find that the facility level first-order decay model maintained by Environment and Climate Change Canada (ECCC) to be the most consistent with our measured emission rates at landfills, and the self-reported emissions to the Greenhouse Gas Reporting Program of ECCC to be the least consistent with our measurements. Implications: We present estimates of atmospheric measurement derived methane emissions for multiple waste processing facilities in Canada. We investigate six emission inventories and models. Based on our atmospheric observations of landfills, we show that the self-reported methane emissions are not well correlated with our measured emissions, and that the first order decay models used in official emissions reporting are much better correlated. One of the most critical findings in this work is that methane emissions from the Keele Valley Landfill, assumed in some inventories to be the second largest anthropogenic source of methane in the country, are significantly less than predicted.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".