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Enregistrement W6902440202 · doi:10.6084/m9.figshare.8120756

Advances in science and applications of air pollution monitoring: A case study on oil sands monitoring targeting ecosystem protection

2019· article· en· W6902440202 sur OpenAlexaboutno aff

Notice bibliographique

RevueFigshare · 2019
Typearticle
Langueen
DomaineChemistry
ThématiquePetroleum Processing and Analysis
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésOil sandsParticulatesPollutantAir pollutionAir pollutantsPollutionAir quality indexCriteria air contaminantsFossil fuelSulfur dioxide

Résumé

récupéré en direct d'OpenAlex

The potential environmental impact of air pollutants emitted from the oil sands industry in Alberta, Canada, has received considerable attention. The mining and processing of bitumen to produce synthetic crude oil, and the waste products associated with this activity, lead to significant emissions of gaseous and particle air pollutants. Deposition of pollutants occurs locally (i.e., near the sources) and also potentially at distances downwind, depending upon each pollutant’s chemical and physical properties and meteorological conditions. The Joint Oil Sands Monitoring Program (JOSM) was initiated in 2012 by the Government of Canada and the Province of Alberta to enhance or improve monitoring of pollutants and their potential impacts. In support of JOSM, Environment and Climate Change Canada (ECCC) undertook a significant research effort via three components: the Air, Water, and Wildlife components, which were implemented to better estimate baseline conditions related to levels of pollutants in the air and water, amounts of deposition, and exposures experienced by the biota. The criteria air contaminants (e.g., nitrogen oxides [NOx], sulfur dioxide [SO2], volatile organic compounds [VOCs], particulate matter with an aerodynamic diameter <2.5 μm [PM2.5]) and their secondary atmospheric products were of interest, as well as toxic compounds, particularly polycyclic aromatic compounds (PACs), trace metals, and mercury (Hg). This critical review discusses the challenges of assessing ecosystem impacts and summarizes the major results of these efforts through approximately 2018. Focus is on the emissions to the air and the findings from the Air Component of the ECCC research and linkages to observations of contaminant levels in the surface waters in the region, in aquatic species, as well as in terrestrial and avian species. The existing evidence of impact on these species is briefly discussed, as is the potential for some of them to serve as sentinel species for the ongoing monitoring needed to better understand potential effects, their potential causes, and to detect future changes. Quantification of the atmospheric emissions of multiple pollutants needs to be improved, as does an understanding of the processes influencing fugitive emissions and local and regional deposition patterns. The influence of multiple stressors on biota exposure and response, from natural bitumen and forest fires to climate change, complicates the current ability to attribute effects to air emissions from the industry. However, there is growing evidence of the impact of current levels of PACs on some species, pointing to the need to improve the ability to predict PAC exposures and the key emission source involved. Although this critical review attempts to integrate some of the findings across the components, in terms of ECCC activities, increased coordination or integration of air, water, and wildlife research would enhance deeper scientific understanding. Improved understanding is needed in order to guide the development of long-term monitoring strategies that could most efficiently inform a future adaptive management approach to oil sands environmental monitoring and prevention of impacts. Implications: Quantification of atmospheric emissions for multiple pollutants needs to be improved, and reporting mechanisms and standards could be adapted to facilitate such improvements, including periodic validation, particularly where uncertainties are the largest. Understanding of baseline conditions in the air, water and biota has improved significantly; ongoing enhanced monitoring, building on this progress, will help improve ecosystem protection measures in the oil sands region. Sentinel species have been identified that could be used to identify and characterize potential impacts of wildlife exposure, both locally and regionally. Polycyclic aromatic compounds are identified as having an impact on aquatic and terrestrial wildlife at current concentration levels although the significance of these impacts and attribution to emissions from oil sands development requires further assessment. Given the improvement in high resolution air quality prediction models, these should be a valuable tool to future environmental assessments and cumulative environment impact assessments.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,005
score de la tête « metaresearch » (Gemma)0,005
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,357
Score d'incertitude au seuil0,710

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0050,005
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0020,004
Études des sciences et des technologies0,0020,003
Communication savante0,0040,002
Science ouverte0,0010,002
Intégrité de la recherche0,0020,002
Charge utile insuffisante (le modèle a refusé de juger)0,0010,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,021
Tête enseignante GPT0,284
Écart entre enseignants0,263 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2019
Routes d'admission1
Résumé présentoui

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