Impacts Of Nox And Sox Emissions And Regulations Form Alberta's Power Generation Industry
Bibliographic record
Abstract
The electricity sector is one of the largest emitters of Nitrogen Oxides (NOX) and Sulphur Dioxide (SO2) generated mainly from fossil fuel based sources. Alberta’s electricity industry is powered mainly by coal and gas making the sector one of the largest contributors of air emissions. Regulatory bodies across the country have implemented policies to set higher standards as initiatives to combat air emissions. The impacts associated with NOX and SO2 include human health issues and environmental impacts including acidification and eutrophication. Studies have shown the economic implications associated with exposure to these pollutants have cost the nation millions in health and environmental costs. This research study found Alberta emits the highest amounts of NOX and SO2, largely due to the availability of fossil fuel based natural resources and the economic development from the energy sector. In the past ten years, Alberta’s progressive initiatives have seen implementation of higher efficiency technologies, greater use of natural gas for power generation, and implementation of renewables. Alberta implemented initiatives including the climate change and emissions management act and the specified gas emitters regulation to encourage use of new technologies such as the integrated gasification combined cycle to replace existing high NOX and SO2 emitting coal facilities while sustaining the provinces energy needs. However, Alberta has yet to set a target to reduce their total overall emissions like Ontario recently implemented.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".