Benchmarking greenhouse gas management in the Canadian natural gas industry
Bibliographic record
Abstract
GHG management presents a challenge to the natural gas industry worldwide due to associated processing and transportation emissions and the product which they sell being a potent GHG as well as a fuel commodity. The Canadian natural gas industry is particularly challenged as an expanding primary export market for natural gas in the United States indicates large increases in natural gas production and exports in the short to medium term. Increases in production coupled with new gas supplies that are located geographically more distant from the USA and / or in deeper geological strata will be accompanied by increases in the GHG emissions from the wellhead to burner tip supply chain. The confluence of pressure to inventory and manage GHG emissions arising from governmental international commitments and higher emissions in an expanding and more distant market creates the need for robust and consistent GHG management systems that are able to clearly monitor and report emissions in a verifiable manner and offer mitigation solutions through identification of techniques to reduce absolute emission levels and to offset emissions through the potential for market based mechanisms. The thesis objective was to answer the general management question of: "How do natural gas companies in Canada and other annex I and annex b countries manage the liability posed by potential climate change related policy constraints on companies operations and are these systems comparable?" This was accomplished by addressing three underlying research questions. Research question one outlined GHG calculation, monitoring and verification practices. Research question two outlined GHG management practices. The third research question drew a qualitative comparison between Canadian and non-Canadian companies systems. The thesis outlines present practice and a qualitative comparison that points to the systems as described by respondents being broadly comparable with Canadian companies occupying middle to high position on a ranked response basis. No statistical valid comparison was undertaken due to a poor response from non-Canadian companies surveyed giving a non-representative statistical sample. The thesis concludes with a call for a broader statistically valid study to confirm the qualitative findings set out in this thesis.
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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 | 0.000 |
| 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) | 0.000 | 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".