Estimating Methane Emissions in Canada Using Atmospheric Observations from Earth to Space
Bibliographic record
Abstract
Methane is a significant greenhouse gas with 25–32 times the global warming potential of carbon dioxide. Global sources and sinks of methane are understood to be 550 ± 60 Tg a-1. The possible causes of changing decadal trends in atmospheric methane concentrations since the 1990's is not well understood, since this requires a precision in global emissions quantification better than 20 Tg a-1. Atmospheric observations at the local, regional, or national scale can provide "top-down" constraints on emissions to verify "bottom-up" emissions that may not be well characterized. Cavity ring down spectroscopy (CRDS) instruments deliver highly precise in-situ measurements of methane, with 1 Hz precision better than 2 ppb. A comprehensive aircraft campaign in the Athabasca Oil Sands Region of Alberta (AOSR) in summer 2013, led by Environment and Climate Change Canada (ECCC), deployed a CRDS alongside a suite of instrumentation to measure atmospheric pollutants and meteorological parameters. These observations allowed for the comprehensive identification and quantification of methane emissions from unconventional oil extraction. Emissions estimates were 48% higher than those reported in the national greenhouse gas inventory. A series of lower cost follow up campaigns in 2014 and 2017 using a CRDS instrument mobilized with a vehicle allowed for cold season monitoring of emissions and select quantification where atmospheric parameters were favorable, showing continued discrepancies with inventory reporting. To estimate emissions across Canada at the national scale, methane measurements from ECCC long-term monitoring stations over 2010-2015 were utilized in conjunction with satellite remote sensing observations from the Greenhouse Gas Observing Satellite (GOSAT) operated by the Japanese Aerospace Agency (JAXA). These atmospheric observations were assimilated in the GEOS-Chem chemical transport model to constrain emissions using a Bayesian inverse modelling methodology. Results showed 42% higher emissions from anthropogenic sources and 21% lower emissions from natural sources, which are mostly wetlands, when compared to the prior estimate. Through the combinations of all studies presented herein, approximately 2–4 Tg a-1 of methane emissions in Canada were reallocated for the year of 2013, where 1–3 Tg a-1 was added to anthropogenic sources and 2–4 Tg a-1 was deducted from natural sources, which is substantial relative to the anthropogenic inventory in Canada which is 4–5 Tg a-1. This reallocation is 0.4–0.8% of the entire global budget of 550 Tg a-1, where only a ~3% change in the source-sink balance can cause the observed trends in atmospheric methane. These results show that atmospheric observations from surface, aircraft and satellites are critical for constraining the methane budget in Canada, and improvements are necessary to these types of atmospheric observations over the world to constrain the methane cycle within the precision needed to understand decadal trends.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.199 | 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 teacher head, 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".