Screening-level assessment of cancer risk associated with ambient air exposure in Aamjiwnaang First Nation
Bibliographic record
Abstract
BACKGROUND AND AIM: The manuscript reports findings from a screening-level assessment of cancer risk from outdoor air in and around Aamjiwnaang First Nation. Aamjiwnaang is situated in the Sarnia-Lambton area, which is known for its industrial and petrochemical industry. The area is also known for poor air quality, chemical spills and other environmental events. Residents are concerned about the health impacts of these exposures. Ambient air pollution can contribute to cardiovascular, respiratory diseases, and certain types of cancer. Some communities may be at higher risk to these negative health impacts due to their geographical proximity to pollution sources. METHODS: Outdoor air concentrations were collected from four monitoring stations in the Aamjiwnaang region for known carcinogens benzene and 1,3-butadiene. Air quality data from both current (2015-2016) and historical (1995-1996, 2005-2006) records were examined. Air concentrations were mapped with geographic information systems to assess spatial variations. Outdoor air concentrations were compiled and the Lifetime Excess Cancer Risks (LECR) associated with long-term exposure to known carcinogens were estimated. RESULTS:LECR results for both benzene and 1,3-butadiene were above one per million. The LECR for benzene was 6.4 per million when the Health Canada slope factor was applied and 12.0 when using the US EPA. For 1,3-butadiene the LECR estimate was 8.8 per million. While air quality has improved over time, in 2015-2016 benzene and 1,3 butadiene levels were higher in Aamjiwnaang than provincial averages. Furthermore, benzene levels were above the Ambient Air Quality Criteria target. CONCLUSIONS:We found that ambient air in and around Aamjiwnaang contains a higher annual average concentration of benzene than recommended and may be related to higher cancer risks. This work provides a better understanding of environmental exposures and potential associated cancer risks for residents in the Aamjiwnaang community. This study highlights the need for further air monitoring and a more detailed risk assessment. KEYWORDS: Cancer and cancer-precursors, Risk assessment, Air pollution
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".