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Record W7080625003 · doi:10.25949/27885312

Measuring and evaluating contamination in homes using geochemical analysis: sources, pathways, and health risks

2024· dissertation· en· W7080625003 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueMacquarie University · 2024
Typedissertation
Languageen
FieldComputer Science
TopicGeochemistry and Geologic Mapping
Canadian institutionsnot available
Fundersnot available
KeywordsContaminationParticulatesTrace metalSmeltingHealth riskTRACE (psycholinguistics)Human health

Abstract

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Residents spend significant time at home, aggravating concerns about their exposure to contaminants and the associated health risks, highlighting the critical importance of addressing home contamination. This thesis delves into the intricate relationship between outdoor and indoor environments and their contamination pathways. This study enhances our understanding of home environment contamination and human exposure by employing a multi-approach that includes analytical methods, comprehensive probabilistic health risk assessment, analysis of trace metal sources, quantification of particle infiltration, and identification of indoor particulate matter sizes. Unravelling these connections and pathways is essential for taking informed actions and implementing effective measures to minimize exposure risks.The utility of pXRF as a practical and cost-effective method for analysing dust wipes in the mining and smelting areas of Noumea, and Thio, New Caledonia and Tsumeb, Namibia was carried out in Chapter 2. A comparison of pXRF and ICP-MS dust wipes analysis (n = 87) revealed strong agreement, with Spearman Rho correlations (0.489 - 0.956, p < 0.01) and coefficients of variation (r²: 0.432 - 0.989). Additionally, equations derived from ICP-MS results corrected pXRF data, improving mean recovery from 75-303% to 92-110%.Chapter 3 focused on studying polycyclic aromatic hydrocarbons and trace metal levels, including chromium (Cr), nickel (Ni), copper (Cu), lead (Pb), and zinc (Zn), their sources, and health risks in homes across the industrialised Illawarra region and Australia. Elevated concentrations of these trace metals were found in home garden soils and indoor dust near industrial areas, showing how outdoor industrial contamination affects indoor trace metal levels. Associations between arsenic (As), lead (Pb), and zinc (Zn) concentrations in indoor dust and home age were noted in Illawarra homes, highlighting the combined effects of aging homes and outdoor industrial activities on trace metal levels, often surpassing outdoor levels. Low polycyclic aromatic hydrocarbons (PAHs) were found in 7 of 23 homes, remaining below carcinogenic thresholds. Using Monte Carlo probabilistic human health risk assessment, higher non-carcinogenic and carcinogenic risks among children than adults were revealed when exposed to indoor dust and garden soils in the Illawarra region and Australian homes (p<0.01).Chapter 4 explored the pathways of trace metals from road dust and garden soils into indoor dust within homes. Higher Cu concentrations in road dust than in garden soils indicated an interaction between these environmental mediums. Similarly, correlations between garden soils and indoor dust for As and Zn showed their migration and interaction, with indoor dust having significantly higher concentrations of these trace metals. Conversely, Pb showed persistence and correlation between road dust, garden soils, and indoor dust, confirming its presence and resuspension across outdoor and indoor environments in Greater Sydney. Furthermore, a detailed analysis of individual dust particles using Scanning Electron Microscope (SEM) was used to estimate the proportion of indoor dust particles originating from outdoor sources. The study revealed that tracked-in outdoor particles represented an average of 57% of the total particle number in indoor dust samples.Chapter 5 measured and evaluated particle size distribution, morphometry, and morphology in indoor dust, drawing from observations on migration patterns, heightened levels of trace metals indoors than outdoors (p < 0.05), and the fine texture of indoor dust (Chapter 3 and 4).Analysis revealed that particles <250 μm comprised 45% of the bulk, with particles smaller than 20 μm making up 9% of the sample. PM2.5 (particles < 2.5 μm) constituted a substantial portion (76%) of suspended indoor 'settled dust' smaller than 20 μm from homes in Australia, Canada, China, Ghana, and Mexico, characterised by notably high circularity. These fine particles pose inhalation risks due to their size and shape, potentially penetrating deeply into the respiratory system.Particles < 20 μm showed higher concentrations of arsenic (As), chromium (Cr), and nickel (Ni) compared to < 250 μm particles, raising concerns about potential health effects from inhalation or ingestion. On the other hand, consistent concentrations of lead (Pb) across particle sizes indicate potential health risks regardless of size or exposure route, particularly in Australian homes where mean Pb concentrations exceeded those in other homes studied. Furthermore, particles smaller than or equal to 2.5 μm corresponding to cerussite, a 'white' lead paint manufacturing component, were identified as capable of reaching deep into the alveolar region of the lungs. Cerussite's solubility under acidic conditions found in the alveolar region suggests potential health risks upon inhalation or ingestion.By uncovering the link between outdoor and indoor contamination and potential health risks across its chapters, the findings in this thesis contributes invaluable insights to the existing literature on home environments and holds significant implications for policy development highlighting the urgency of addressing home contamination as a crucial step in safeguarding human health.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.790
Threshold uncertainty score0.869

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.089
GPT teacher head0.294
Teacher spread0.205 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it