U.S.–Canada Cooperation: The U.S.–Canada Air Quality Agreement
Bibliographic record
Abstract
The impetus for the Canada-U.S. Air Quality Agreement was transboundary acid rain in eastern North America. This problem drove the parties to develop a bilateral agreement that not only addressed this issue, but also set up a broad and flexible framework to address other air quality problems. In 2000, the Ozone Annex to reduce smog and its precursor pollutants was negotiated. A transboundary particulate matter (PM) science assessment in 2004 led to the commencement of negotiation of a PM annex in late 2007. Over the course of 15 yr, Canada and the United States also developed innovative cooperative arrangements. Two transboundary airshed dialogues became important sources of practical on-the-ground cooperation in the Georgia Basin-Puget Sound and the Great Lakes Basin. In addition to providing the basis for ongoing international dialogue, these transboundary airshed projects resulted in changes to administrative practices as the parties exchange information and learn from each other in ways that benefit the airshed community. The nature of the Air Quality Agreement also enabled both Canada and the United States to address concerns each has had about specific pollutant sources and to address them in ways that avoided confrontation and resulted in air quality improvements for people living in the airsheds. Case studies of three of the "informal consultations" that have occurred under the agreement are described: where discussions occurred around a power plant in Michigan, a power plant in Saskatchewan, and a steel mill in Ontario. More than an agreement, this relationship has built a capacity to deal with common problems. Fostering such a relationship with its implicit transfer of knowledge and experience has opened doors for discussions on a new Clean Air framework in Canada and joint analyses of cross-border sulfur dioxide (SO2) and nitrogen oxides (NOx) emissions caps and trading. U.S. experience with cap and trading is highlighted for background and context. The flexibility inherent in the agreement provides a platform for future air quality issues and continued communication without borders.
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 | 0.007 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.028 | 0.006 |
| Scholarly communication | 0.012 | 0.003 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.010 | 0.007 |
| Insufficient payload (model declined to judge) | 0.012 | 0.001 |
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".