Comprehensive analysis of environmental particulate matter: Chemical composition and microbial assessment
Bibliographic record
Abstract
Rapid industrialization and population growth have contributed to a decline in air quality, with particulate matter (PM) posing particular concern. PM originates from both natural and human sources and often contains toxic chemicals and microorganisms, including potential pathogens. Inhalation of PM is linked to respiratory and cardiovascular diseases, underscoring the need to characterize better its chemical and biological composition in understudied region - Waterloo, Ontario, Canada. The present thesis is a culmination of three main parts. Part 1 will describe the use of the dithiothreitol (DTT) assay to quantify the oxidative potential of PM through DTT consumption of redox-active field PM species. Part II will describe and report details on PM collection from indoor and outdoor sites followed by chemical composition analysis. Part III will examine the biological content of PM using the real-time polymerase chain reaction (qPCR) technique to identify general bacterial load, and will use environmental sequencing to identify bacterial, fungal and DNA-genome viral species in the samples. Results demonstrate that during wildfire events, the Particle Into-Liquid Sampler (PILS) captured higher concentrations of water-soluble organic compounds (WSOC) than the Micro-Orifice Uniform Deposit Impactor (MOUDI), highlighting a predominance of submicron particles. On cleaner days, MOUDI more effectively recovered coarse-mode acid leachable organic compounds (ALOC). DTT assays, ICP-OES, and particle dosimetry modeling revealed size- and iron/copper/ALOC- dependent differences in oxidative potential. Fine particles (0.56-1 μm) showed the greatest reactivity during wildfire smoke event, while particles in the 1-1.8 μm range dominated oxidative potential on cleaner days. Biological analyses showed that PILS samples were more suitable for DNA extraction, qPCR, and sequencing. In contrast, MOUDI was more effective at collecting transition metals and organic compounds. Pathogenic microbes, including bacteria and fungi, were identified in Page | iv Waterloo air, alongside traces of human DNA linked to local activity. These findings point to both exposure risks and opportunities for community engagement on air quality issues. Overall, MOUDI and PILS offered complementary advantages: MOUDI for detailed size-resolved chemical analysis and PILS for operational efficiency and better compatibility with biological assays. Together, they provide a more comprehensive understanding of PM composition, oxidative capacity, and biological relevance. This research delivers the first in depth assessment of PM chemistry and bioaerosols in Waterloo, contributing critical insights for air quality monitoring, health risk assessment, and environmental policy.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".