Spatial Distribution, Air-Water Exchange, and Toxicity of Organic Pollutants Using Passive Samplers
Bibliographic record
Abstract
Thousands of hydrophobic organic contaminants (HOCs) are present in air and water worldwide, yet we know little about how these chemicals’ concentrations vary spatially and temporally, or what biological effects they have in concert. The first four studies described in this dissertation present data from a sampling campaign in which passive polyethylene samplers (PEs) deployed throughout the lower Great Lakes region (Lake Erie and Lake Ontario) from 2011 to 2014. Results were used to deduce air-water fluxes and analyze spatial trends of the truly gaseous and dissolved fraction of three distinct groups of HOCs: polycyclic aromatic hydrocarbons (PAHs), polycyclic musks (PCMs), and organic flame retardants (OFRs), with the goal of better understanding how sources and physico-chemical properties determine the environmental transport and spatial distribution of these HOCs. The specific objectives of these studies were to determine whether gaseous and dissolved HOCs exhibited positive correlation with regional population density within 25 km of each site in the lower Great Lakes region, investigate whether diffusive air-water exchange of HOCs was primarily leading to volatilization from, or absorption into, the lakes’ surface waters, and investigate health risks of ambient urban air by measuring aromatic hydrocarbon receptor (AhR)-mediated potency of the truly gaseous mixture of HOCs accumulated in PEs deployed in air on the Lake Erie shoreline near Cleveland (OH). Results showed that the radius at which strongest correlation between gaseous HOC concentration and human population was observed depended on vapor pressure, and a relationship between the maximum distance where significant correlation occurred and compound vapor pressure is presented for amassed PAH, PBDE, and PCM data. Air-water exchange calculations based on simultaneously deployed air and water PEs indicated that diffusive exchange of PAHs was variable based on compound and season. PCMs were found to be volatilizing from the lakes’ surface waters, suggesting that Lake Erie and Lake Ontario were acting as secondary sources of PCMs, while PBDEs were absorbed into surface waters. Bioassay experiments performed on PE extracts showed that <30% of AhR-mediated potency for gaseous air extracts was explained by target compounds measured via chemical analysis, suggesting that targeted analysis may underestimate health risks posed by gas-phase ambient air. The fifth and sixth studies described in this dissertation focused on measuring uptake of emerging and legacy HOCs into PEs to inform future calculation of ambient air and water concentrations from PE measurements. PE uptake profiles over 21-day deployments were used to determine whether
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".