Mapping anthropogenic B(a)P releases in the Great Lakes Basin
Bibliographic record
Abstract
Benzo(a)pyrene (BaP) is one of the most toxic PAHs.It is listed as a priority toxic substance with a target for virtual elimination under the Great Lakes Bi-national Toxics Strategy (GLBTS).At the GLBTS's meeting in December 2005, BaP monitoring data of both Canada and U.S.A. shows that ambient BaP concentrations at urban sites are 10 times higher than those in rural sites, reflecting a significant local source contribution.This paper is prepared to (1) Map the local releases in nine province/states of the Great Lakes Basin (2) Analyze sources of BaP in high-releasing regions (3) Map ambient air monitoring data in the Basin.The BaP inventories used for the mapping originated from USEPA's 1999 National Emissions Inventory (NEI) and Environment Canada's Ontario inventory 2003.Approximately 27,000 kg of BaP releasing from the Basin's anthropogenic sources were mapped, with 30% from Ontario, Canada and 70% from the eight states in the U.S. The Basin is divided into 280 grid cells (each 100 km x 100 km) using a high-resolution GIS mapping tool.It is found that five grid cells with releases in 1,000-2,000 kg/year are the highest relative to the others in 10-1,000 kg/y.They are located in Ontario, Ohio, Illinois, and Indiana.This agrees well with the higher ambient BaP concentrations detected in the Chicago, Hamilton, and Toronto areas in these province/states in the past 15 years.The 2003 annual averages were 500, 300, 200 pg/m 3 for these three cities, respectively.The common source sectors of BaP in both countries are steel manufacturing, residential wood combustion, scrap tire burning, the use of creosote railway ties, primary metals production, household waste burning, and motor vehicles.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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 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".