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Record W3038080642 · doi:10.1080/10962247.2020.1779148

A wind tunnel and field evaluation of various dust suppressants

2020· article· en· W3038080642 on OpenAlex
Colette Alexia Preston, Cheryl McKenna Neuman, J. Wayne Boulton

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueJournal of the Air & Waste Management Association · 2020
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicAeolian processes and effects
Canadian institutionsRowan Williams Davies & Irwin (Canada)Trent University
Fundersnot available
KeywordsWind tunnelAeolian processesEnvironmental scienceTailingsAbrasion (mechanical)Wind speedDust controlAtmospheric sciencesAirflowAdvectionMeteorologyWaste managementGeologyMaterials scienceEngineeringMetallurgyGeomorphology

Abstract

fetched live from OpenAlex

A series of experiments was designed to assess the relative efficacy of various dust suppressants to suppress PM10 emissions from nepheline syenite tailings. The experiments were conducted in the Trent University Environmental Wind Tunnel, Peterborough, Ontario, and on the tailings ponds at a mine near Havelock, Ontario. Treated surfaces were subjected to particle-free airflow, abrasion with blown sand particles, and particle-free airflow after physical disturbance. Emission rates in the wind tunnel tests were calculated from dust concentration measurements obtained in vertical profile with DustTrak™ II aerosol monitors (model 8530); rates in the field were measured using a Portable In-Situ Wind Erosion Laboratory (PI-SWERL). In the particle-free wind tunnel tests, three of the surface treatments performed well, and PM10 emission scaled inversely with crust strength. Light bombardment of each surface by saltating sand grains increased PM10 emission rates by two orders of magnitude. All treated surfaces emitted significantly more PM10 after physical disturbance. In the field study, plots treated with a commercial dust suppressant were found to release more PM10 than either the control or irrigated plots, although it should be noted that the emission rates were similar in magnitude. As in the wind tunnel experiments, all of the field plots became significantly more emissive after physical disturbance. The field results suggest that the site conditions, inclusive of the potential for dust advection and resuspension, must be taken into account when considering the use of a commercial dust suppressant.Implications: Fugitive dust (PM10) emissions from mining and industrial operations worldwide present significant environmental and human health risks, leaving mine operators challenged to find reliable, durable, and cost-effective mitigation options. Commercial dust suppressants boast unique chemical compositions and commensurate particle binding capabilities, although few side-by-side comparisons exist in the literature. The efficacy of four commercial products to suppress PM10 emissions from mine tailings, before and after physical disturbance, was assessed using robust field and wind tunnel experiments. All surfaces emitted significantly more PM10 after physical disturbance but with considerable variability amongst products. Possible reasons for the differences in relative performance are explored.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.063
Threshold uncertainty score0.151

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.015
GPT teacher head0.219
Teacher spread0.204 · 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