Ship emissions measurement in the Arctic by plume intercepts of the Canadian Coast Guard icebreaker Amundsen from the Polar 6 aircraft platform
Notice bibliographique
Résumé
Decreasing sea ice and increasing marine navigability in northern latitudes have changed Arctic ship traffic patterns in recent years and are predicted to increase annual ship traffic in the Arctic in the future. Development of effective regulations to manage environmental impacts of shipping requires an understanding of ship emissions and atmospheric processing in the Arctic environment. As part of the summer 2014 NETCARE (Network on Climate and Aerosols) campaign, the plume dispersion and gas and particle emission factors of effluents originating from the Canadian Coast Guard icebreaker Amundsen operating near Resolute Bay, NU, Canada, were investigated. The Amundsen burned distillate fuel with 1.5 wt% sulfur. Emissions were studied via plume intercepts using the Polar 6 aircraft measurements, an analytical plume dispersion model, and using the FLEXPART-WRF Lagrangian particle dispersion model. The first plume intercept by the research aircraft was carried out on 19 July 2014 during the operation of the Amundsen in the open water. The second and third plume intercepts were carried out on 20 and 21 July 2014 when the Amundsen had reached the ice edge and operated under ice-breaking conditions. Typical of Arctic marine navigation, the engine load was low compared to cruising conditions for all of the plume intercepts. The measured species included mixing ratios of CO2, NO x, CO, SO2, particle number concentration (CN), refractory black carbon (rBC), and cloud condensation nuclei (CCN). The results were compared to similar experimental studies in mid-latitudes. Plume expansion rates () were calculated using the analytical model and found to be D 0.75 0.81, 0.93 0.37, and 1.19 0.39 for plumes 1, 2, and 3, respectively. These rates were smaller than prior studies conducted at mid-latitudes, likely due to polar boundary layer dynamics, including reduced turbulent mixing compared to midlatitudes. All emission factors were in agreement with prior observations at low engine loads in mid-latitudes. Ice-breaking increased the NO x emission factor from EFNO x D 43.1 +/- 15.2 to 71.6 +/- 9.68 and 71.4 +/-+/- 4.14 g kgdiesel 1 for plumes 1, 2, and 3, likely due to changes in combustion temperatures. The CO emission factor was EFCO D 137 +/- 120, 12.5 +/- 3.70 and 8.13 +/- 1.34 g kgdiesel 1 for plumes 1, 2, and 3. The rBC emission factor was EFrBC D 0.202 +/- 0.052 and 0.202 +/-+/- 0.125 g kg-diesel 1 for plumes 1 and 2. The CN emission factor was reduced while ice-breaking from EFCN D 2.41 +/- 0.47 to 0.45 +/- 0.082 and 0.507 +/- 0.037 +/- 1016 kg-diesel 1 for plumes 1, 2, and 3. At 0.6% supersaturation, the CCN emission factor was comparable to observations in mid-latitudes at low engine loads with EFCCN D 3.03 +/- 0.933, 1.39 +/- 0.319, and 0.650 +/- 0.136 +/- 1014 kg-diesel 1 for plumes 1, 2, and 3.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 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 tête enseignante, 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 ».