Assessment of cancer and noncancer health risks from exposure to PAHs in street dust in the Tamale Metropolis, Ghana
Bibliographic record
Abstract
This study is part of a broader initiative to characterize, quantify and assess the human health risk associated with exposure to polycyclic aromatic hydrocarbons (PAHs) in street dust along the Trans-ECOWAS highway in West Africa. In the first part, PAHs were characterized and quantified in low- and high-traffic zones. In this study, cancer and noncancer human health risks from exposure to (PAHs) in street dust in the Tamale metropolis, Ghana were assessed in accordance with the USEPA risk assessment guidelines. The results of the study as obtained from inhalation of benzo [a] anthracene (BaA), benzo [a] pyrene (BaP), benzo [k] fluoranthene (BkF) and chrysene via central tendency exposure parameters (CTE) by trespassers (street hawkers including children and adults) in street dust within low traffic zones in the Tamale metropolis are 1.6E-02, 4.7E-02, 1.8E-03, and 1.6E-04 respectively. For reasonable maximum exposure parameters (RME), risk values of 1.2E-01, 3.5E-01, 1.3E-02 and 1.2E-03 respectively were obtained for benzo [a] anthracene, benzo [a] pyrene, benzo [k] fluoranthene and chrysene. Hazard index for acenaphthene, anthracene, fluoranthene, fluorine, naphthalene and pyrene in the CTE and RME scenarios were 2.2, 3.E-01, 2.6, 2.6, 100, 38 and 12, 1.7,15, 14, 550, 210 respectively. Generally, the cancer health risk associated with inhalation of benzo [a] anthracene, benzo [a] pyrene, benzo [k] fluoranthene and chrysene revealed that resident adults and children in the Tamale metropolis are at risk from exposure to these chemicals. The results of this preliminary assessment that quantified PAH related health risks along this part of the Trans-ECOWAS highway revealed that, there is the need for regulatory agencies to put in comprehensive measures to mitigate the risks posed to these categories of human receptors.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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 teacher head, 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".