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Record W1989515990 · doi:10.1021/es2001503

Lead Speciation in House Dust from Canadian Urban Homes Using EXAFS, Micro-XRF, and Micro-XRD

2011· article· en· W1989515990 on OpenAlexaffabout
Lachlan C. W. MacLean, Suzanne Beauchemin, Pat E. Rasmussen

Bibliographic record

VenueEnvironmental Science & Technology · 2011
Typearticle
Languageen
FieldEnvironmental Science
TopicHeavy metals in environment
Canadian institutionsNatural Resources CanadaUniversity of OttawaHealth Canada
Fundersnot available
KeywordsExtended X-ray absorption fine structureLead (geology)Genetic algorithmEnvironmental scienceEnvironmental chemistryLead exposureMaterials scienceChemistryGeologyPhysicsEngineeringAbsorption spectroscopyOpticsEcology

Abstract

fetched live from OpenAlex

X-ray absorption fine-structure (XAFS) spectroscopy, micro-X-ray fluorescence (μXRF), and micro-X-ray diffraction (μXRD) were used to determine the speciation of Pb in house dust samples from four Canadian urban homes having elevated Pb concentrations (>1000 mg Pb kg(-1)). Linear combination fitting of the XAFS data, supported by μXRF and μXRD, shows that Pb is complexed in a variety of molecular environments, associated with both the inorganic and organic fractions of the dust samples. The inorganic species of lead identified were as follows: Pb metal, Pb carbonate, Pb hydroxyl carbonate, Pb oxide, and Pb adsorbed to iron oxyhydroxides. Pb carbonate and/or Pb hydroxyl carbonate occurred in all four dust samples and accounted for 28 to 75% of total Pb. Pb citrate and Pb bound to humate were the organic species identified. The results of this study demonstrate the ability of XAFS to identify Pb speciation in house dust and show the potential to identify Pb sources from new homes versus older homes. Understanding Pb speciation and how it influences bioaccessibility is important for human health risk assessment and risk management decisions which aim to improve indoor environmental 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.

How this classification was reachedexpand

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 categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.220
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.004
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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.

Opus teacher head0.014
GPT teacher head0.200
Teacher spread0.186 · 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

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations63
Published2011
Admission routes2
Has abstractyes

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