Staggering reductions in atmospheric nitrogen dioxide across Canada in response to legislated transportation emissions reductions
Notice bibliographique
Résumé
It is well established that atmospheric nitrogen dioxide (NO 2 ), associated mainly with emissions from transportation and industry, can have adverse effects on both human and ecosystem health. Specifically, atmospheric NO 2 plays a role in the formation of ozone, and in acidic and nutrient deposition. As such, international agreements and national legislation, such as the On-Road Vehicle and Engine Emission Regulations (SOR/2003-2) , and the Federal Agenda on Cleaner Vehicles, Engines and Fuel have been put into place to regulate and limit oxidized nitrogen emissions. The objective of this study was to assess the response of ambient air concentrations of NO 2 across Canada to emissions regulations. Current NO 2 levels across Canada were examined at 137 monitoring sites, and long-term annual and quarterly trends were evaluated for 63 continuous monitoring stations that had at least 10 years of data during the period 1988–2013. A non-parametric Mann-Kendall test (Z values) and Sen's slope estimate were used to determine monotonic trends; further changepoint analysis was used to determine periods with significant changes in NO 2 air concentration and emissions time-series data. Current annual average NO 2 levels in Canada range between 1.16 and 14.96 ppb, with the national average being 8.43 ppb. Provincially, average NO 2 ranges between 3.77 and 9.25 ppb, with Ontario and British Columbia having the highest ambient levels of NO 2 . Long-term tend analysis indicated that the annual average NO 2 air concentration decreased significantly at 87% of the stations (55 of 63), and decreased non-significantly at 10% (5 of 63) during the period 1998–2013. Concentrations increased (non-significantly) at only 3% (2 of 63) of the sites. Quarterly long-term trends showed similar results; significant decreases occurred at 84% (January–March), 88% (April–June), 83% (July–September), and 81% (October–December) of the sites. Declines in transportation emissions had the most influence on NO 2 air concentrations, and changepoint analysis identified three significant changepoints for the air concentration of NO 2 and transportation emissions data. The air concentration changepoints occurred immediately following changepoints in transportation emissions. The introduction of emissions limiting legislation, primarily from transportation sources, has lead to dramatic decreases of 32% in NO × emissions (42% from transportation sources [road, rail, air, marine]) and 47% in ambient NO 2 concentrations across Canada. With respect to human health, legislated changes in transportation emissions have the greatest impact on ambient concentration in urban areas.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi 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.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,003 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».