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Record W2991978208 · doi:10.1080/10962247.2019.1629360

Contribution of bioaerosols to airborne particulate matter

2019· review· en· W2991978208 on OpenAlex
Peter Hyde, Alex Mahalov

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

VenueJournal of the Air & Waste Management Association · 2019
Typereview
Languageen
FieldEnvironmental Science
TopicIndoor Air Quality and Microbial Exposure
Canadian institutionsnot available
Fundersnot available
KeywordsIndoor bioaerosolBioaerosolParticulatesEnvironmental scienceAir pollutionPhoenixAir quality indexAerobiologyEnvironmental engineeringAerosolMeteorologyEnvironmental chemistryEcologyGeographyPollenChemistryBiology

Abstract

fetched live from OpenAlex

Fine and coarse particulate matter (PM), as measured, for example, in regulatory air pollution monitoring networks, contains biological entities such as fungal spores, pollen, animal dander, leaf wax, and human skin cells, to mention but a few types. Although these bioaerosols come in a wide range of particle size, of 14 common types nine fall into the 0– 10 µm range and four are in the 0– 2.5 µm range. These bioaerosols contribute to the concentrations of particulates determined by both filter-based and continuous instruments. This paper reviews bioaerosol research conducted worldwide in the last twenty years. Such studies have been conducted in Toronto, Canada, central Germany, Phoenix, Arizona, Davis, California, Dallas, Texas, and at many other sites worldwide. Notwithstanding the wide variety of climates, ecological systems, and urban and rural environments in which these measurements have been made, a reasonable, first-order estimate of the overall bioaerosol contribution to particles 2.5 microns and smaller (PM2.5) is 16.5% and to particles 10 microns and smaller (PM10) is 16.3%. A percentage contribution of this magnitude from unregulated emissions means that achieving PM standards will require greater reductions in the better understood anthropogenic and natural emissions of geological and combustion particles. In one such case the emission reductions necessary to achieve the standard increase from 25% (with bioaerosols ignored) to 36% (with bioaerosols accounted for). Although to the uninitiated this difference may not appear to be substantial, it can only be considered vast and nearly regulatorily impossible to those policy makers and regulators responsible for enacting emission-reduction regulations. Emissions of airborne biological materials are unregulated. Ignoring this natural component in attempting to achieve national ambient air quality standards for particulates can lead to overly optimistic predictions of attainment.Implications: For those officials still striving to meet federal air quality standards for particulate matter, either PM10 or PM2.5, it would be prudent to acknowledge the presence of unregulated bioaerosols. Ignoring this portion of PM may lead to over-optimistic projections of attainment.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.595
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.015
GPT teacher head0.262
Teacher spread0.247 · 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