Managing air pollution impacts to protect local air quality
Bibliographic record
Abstract
Local industrial/commercial sources of air pollution in Ontario, Canada have been regulated for almost four decades using air emission estimating, atmospheric dispersion models and point of impingement (POI) standards.Historically, the provincial Ontario Ministry of the Environment (MOE) set standards that considered technical, economic and scientific issues.Compliance assessment used air emission inventories and atmospheric dispersion models originally developed in the 1960s.The challenges of this type of approach included:• A cumbersome standard-setting process that produced few standards -often dictated by technical/economic considerations.• Inaccuracies in air emission inventories.• Dispersion models that tended to under-predict impacts.In August 2005, Ontario announced a significant overhaul of the local air pollution regulation that included:• Air standards that are now set to protect against health and environmental impacts.• Phase-out of current dispersion models and replacement with the more accurate dispersion models from the United States Environmental Protection Agency (US EPA).• Rigorous air emission estimating rules including the use of a combination of dispersion modelling and ambient monitoring as a more accurate emission estimating technique for a wide variety of sources (including fugitives).• Technical/economic considerations that are now addressed through a publicly transparent alternative air standards process that promotes continuous improvement.Site specific alternative standards represent the lowest technically and/or economically feasible levels that a specific facility could achieve.Decisions often hinge on the technology benchmarking report, which is similar to the US EPA "top-down" analysis.This paper outlines key challenges and policy decisions during the development of the regulation; experiences in introducing more stringent scientific-based standards, including standards for lead and vinyl chloride, which are among some of the most stringently regulated standards in the world; and lessons-learned in the use of the combined monitoring and modelling emission estimating tool in the new alternative standards process.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".