Characterization of trace gas emissions at an intermediate port
Notice bibliographique
Résumé
Abstract. Growing ship traffic in Atlantic Canada strengthens the local economy but also plays an important role in greenhouse gas and air pollutant emissions in this coastal environment. A mobile open-path Fourier transform infrared (OP-FTIR; acronyms defined in Appendix A) spectrometer was set up in Halifax Harbour (Nova Scotia, Canada), an intermediate harbour integrated into the downtown core, to measure trace gas concentrations in the vicinity of marine vessels, in some cases with direct or near-direct marine combustion plume intercepts. This is the first application of the OP-FTIR measurement technique to real-time, spectroscopic measurements of CO2, CO, O3, NO2, NH3, CH3OH, HCHO, CH4 and N2O in the vicinity of harbour emissions originating from a variety of marine vessels, and the first measurement of shipping emissions in the ambient environment along the eastern seaboard of North America outside of the Gulf Coast. The spectrometer, its active mid-IR source and its detector were located on shore while the passive retroreflector was on a nearby island, yielding a 455 m open path over the ocean (910 m two-way). Atmospheric absorption spectra were recorded during day, night, sunny, cloudy and substantially foggy or precipitating conditions, with a temporal resolution of 1 min or better. A weather station was co-located with the retroreflector to aid in the processing of absorption spectra and the interpretation of results, while a webcam recorded images of the harbour once per minute. Trace gas concentrations were retrieved from spectra by the MALT non-linear least squares iterative fitting routine. During field measurements (7 days in July–August 2016; 12 days in January 2017) AIS information on nearby ship activity was manually collected from a commercial website and used to calculate emission rates of shipping combustion products (CO2, CO, NOx, HC, SO2), which were then linked to measured concentration variations using ship position and wind information. During periods of low wind speed we observed extended (∼9 h) emission accumulations combined with near-complete O3 titration, both in winter and in summer. Our results compare well with a NAPS monitoring station ∼1 km away, pointing to the extended spatial scale of this effect, commonly found in much larger European shipping channels. We calculated total marine sector emissions in Halifax Harbour based on a complete AIS dataset of ship activity during the cruise ship season (May–October 2015) and the remainder of the year (November 2015–April 2016) and found trace gas emissions (tonnes) to be 2.8 % higher on average during the cruise ship season, when passenger ship emissions were found to contribute 18 % of emitted CO2, CO, NOx, SO2 and HC (0.5 % in the off season due to occasional cruise ships arriving, even in April). Similarly, calculated particulate emissions are 4.1 % higher during the cruise ship season, when passenger ship emissions contribute 18 % of the emitted particulate matter (PM) (0.5 % in the off season). Tugs were found to make the biggest contribution to harbour emissions of trace gases in both cruise ship season (23 % NOx, 24 % SO2) and the off season (26 % of both SO2 and NOx), followed by container ships (25 % NOx and SO2 in the off season, 21 % NOx and SO2 in cruise ship season). In the cruise ship season cruise ships were observed to be in third place regarding trace gas emissions, whilst tankers were in third place in the off season, with both being responsible for 18 % of the calculated emissions. While the concentrations of all regulated trace gases measured by OP-FTIR as well as the nearby in situ NAPS sensors were well below maximum hourly permissible levels at all times during the 19-day measurement period, we find that AIS-based shipping emissions of NOx over the course of 1 year are 4.2 times greater than those of a nearby 500 MW stationary source emitter and greater than or comparable to all vehicle NOx emissions in the city. Our findings highlight the need to accurately represent emissions from the shipping and marine sectors at intermediate ports integrated into urban environments. Emissions can be represented as pseudo-stationary and/or pseudo-line sources.
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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 | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| 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 ».