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The impact of the 2016 Fort McMurray Horse River Wildfire on ambient air pollution levels in the Athabasca Oil Sands Region, Alberta, Canada

2018· article· en· W2765372730 on OpenAlexafffundabout
Matthew S. Landis, Eric S. Edgerton, Emily M. White, Gregory R. Wentworth, Amy P. Sullivan, Ann M. Dillner

Bibliographic record

VenueThe Science of The Total Environment · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicFire effects on ecosystems
Canadian institutionsAlberta Environment and Protected Areas
FundersWood Buffalo Environmental AssociationU.S. Department of Agriculture
KeywordsEnvironmental scienceOil sandsAir quality indexParticulatesAir pollutionPollutionEnvironmental chemistryHydrology (agriculture)Environmental engineeringMeteorologyGeographyChemistryGeologyEcologyArchaeology

Abstract

fetched live from OpenAlex

An unprecedented wildfire impacted the northern Alberta city of Fort McMurray in May 2016 causing a mandatory city wide evacuation and the loss of 2,400 homes and commercial structures. A two-hectare wildfire was discovered on May 1, grew to ~ 157,000 ha by May 5, and continued to burn an estimated ~ 590,000 ha by June 13. A comprehensive air monitoring network operated by the Wood Buffalo Environmental Association (WBEA) in and around Fort McMurray provided essential health-related real-time air quality data to firefighters during the emergency, and provided a rare opportunity to elucidate the impact of gaseous and particulate matter emissions on near-field communities and regional air pollution concentrations. The WBEA network recorded 188 fire-related exceedances of 1-hr and 24-hr Alberta Ambient Air Quality Objectives. Two air monitoring sites within Fort McMurray recorded mean/maximum 1-hr PM2.5 concentrations of 291/5229 μg m− 3 (AMS-6) and 293/3259 μg m− 3 (AMS-7) during fire impact periods. High correlations (r2 = 0.83–0.97) between biomass combustion related gases (carbon monoxide (CO), non-methane hydrocarbons (NMHC), total hydrocarbons (THC), total reduced sulfur (TRS), ammonia) and PM2.5 were observed at the sites. Filter-based 24-hr integrated PM2.5 samples collected every 6 days showed maximum concentrations of 267 μg m− 3 (AMS-6) and 394 μg m− 3 (AMS-7). Normalized excess emission ratios relative to CO were 149.87 ± 3.37 μg m− 3 ppm− 1 (PM2.5), 0.274 ± 0.002 ppm ppm− 1 (THC), 0.169 ± 0.001 ppm ppm− 1 (NMHC), 0.104 ± 0.001 ppm ppm− 1 (CH4), 0.694 ± 0.007 ppb ppm− 1 (TRS), 0.519 ± 0.040 ppb ppm− 1 (SO2), 0.412 ± 0.045 ppb ppm− 1 (NO), 1.968 ± 0.053 ppb ppm− 1 (NO2), and 2.337 ± 0.077 ppb ppm− 1 (NOX). A subset of PM2.5 filter samples was analyzed for trace elements, major ions, organic carbon, elemental carbon, and carbohydrates. Sample mass reconstruction and fire specific emission profiles are presented and discussed. Potential fire-related photometric ozone instrument positive interferences were observed and were positively correlated with NO and NMHC.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.901
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.005
Scholarly communication0.0000.000
Open science0.0030.001
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 head0.006
GPT teacher head0.201
Teacher spread0.195 · 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 teacher head, not a consensus.

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

Citations115
Published2018
Admission routes3
Has abstractyes

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