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Record W2505556244 · doi:10.5962/bhl.title.102010

Glyphosate residues in Alberta's atmospheric deposition, soils and surface waters

2005· book· en· W2505556244 on OpenAlexaboutno aff
D. T. Humphries, Gary Byrtus, Annemarie Anderson

Bibliographic record

Venuenot available
Typebook
Languageen
FieldEnvironmental Science
TopicPesticide and Herbicide Environmental Studies
Canadian institutionsnot available
Fundersnot available
KeywordsGlyphosateSoil waterEnvironmental scienceEnvironmental chemistryDeposition (geology)Surface waterAgronomyChemistrySoil scienceEnvironmental engineeringGeologyBiologyGeomorphologySediment

Abstract

fetched live from OpenAlex

Glyphosate is a non-selective herbicide used for the control of annual and perennial grasses and broadleaf weeds.Registered for use in Canada in 1974, it is currently registered and used in over 125 countries.With annual sales in Alberta (1998) exceeding 2.6 million kg of active ingredient, it is by far the most commonly used pesticide in the province.Long considered by scientists and farmers around the world as an effective and environmentally friendly herbicide, recent studies have shown some persistence and mobility in the environment.This study was designed to explore some of the pathways of glyphosate to surface waters such as atmospheric deposition, emissions during spraying, and persistence in soil; the study also included the monitoring of water from selected streams and wetlands.The sampling year 2002 proved to be a difficult year to undertake a glyphosate residue study due to environmental factors.The severe drought conditions in east central Alberta hampered canola growth and subsequently greatly reduced the amount of glyphosate used in this growing and sampling season.Despite the drought and reduced usage, glyphosate was found in many environmental samples.Atmospheric deposition was measured at three sites in east central Alberta.Rainfall and particulate matter were collected as total deposition at seven-day intervals throughout the growing season.The three precipitation sites had glyphosate detections throughout the sampling time period.Glyphosate deposition rates ranged from <0.001 to 1.51 ligW/day.Volatile and particulate emissions of glyphosate were measured before and after the spraying of a canola field with Roundup®.This study component was conducted in the Mannville area on a field with glyphosate tolerant canola.Pre-event air samples were taken two weeks prior to spraying.Post-event air sampling was conducted for 24-hour periods beginning at 1-hour post spray, 25-hour post spray and 49-hour post spray.Glyphosate was not detected in any of the air samples collected with polyurethane foam (PUF) samples but it was detected in some of the particulate samples.The detection of glyphosate in soil samples 10 months after spraying was indicative of some persistence.Glyphosate was detected in most of the wetlands and streams sampled for this project.Concentrations were generally close to the detection limit ( 0.2 |Lig/L).Higher levels were recorded at some sites: Wetland #5 sample (1.066 |ug/L), two Haynes Creek samples (1.105 and 0.425 |ig/L) and a sample from the St. Mary's River Irrigation District (6.079 fig/L).This study determined that glyphosate is transported in association with particulate matter (dust) and not as vapour.Detections in precipitation are more likely due to glyphosate associated with dust particles being washed down with rain than to glyphosate dissolved in rain.A follow up study is recommended to document residue levels in a year where glyphosate use and moisture patterns are closer to normal for that part of the province.As well, the persistence of glyphosate in soils warrants further studies under different climatic conditions.Glyphosate Residues in Alberta's Atmospheric Deposition, Soils and Surface Waters i ACKNOWLEDGEMENTS This project had complex technical and logistic demands that required teamwork from staff at the Alberta Research Council-Vegreville (ARC), Alberta Environment (AENV), and Alberta Agriculture Food and Rural Development (AAFRD).These three organizations were involved in the design of the study and in field-sampling aspects and contributed to the production of the technical report and interpretation of results.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.559
Threshold uncertainty score0.877

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.002

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 head0.005
GPT teacher head0.188
Teacher spread0.184 · 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations30
Published2005
Admission routes1
Has abstractyes

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