Arctic marine ice nucleating aerosol: a laboratory study of microlayer samples and algal cultures
Notice bibliographique
Résumé
Abstract. In recent years, sea spray and the biological material it contains has received increased attention as a source of ice nucleating particles (INPs). Such INPs may play a role in remote marine regions, where other sources of INPs are scarce or absent. Marine aerosol is of diverse nature, so identifying sources of INPs is challenging. One fraction of marine bioaerosol, phytoplankton and their exudates, has been a particular focus of marine INP research. In our study we attempt to address three main questions. Firstly, we compare the ice nucleating ability of two common phytoplankton species with Arctic seawater microlayer samples using the same instrumentation to see if these phytoplankton species produce ice nucleating material with sufficient activity to account for the ice nucleation observed in Arctic microlayer samples. We present first measurements of the ice nucleating ability of two predominant phytoplankton species, Melosira arctica, a common Arctic diatom species and Skeletonema marinoi, a ubiquitous diatom species across oceans worldwide. To determine the potential effect of nutrient conditions and characteristics of the algal culture, such as the amount of organic carbon associated with algal cells, on the ice nucleation activity, the Skeletonema marinoi was grown under different nutrient regimes. From comparison of the ice nucleation data of the algal cultures to those obtained from a range of sea surface microlayer (SML) samples obtained during three different field expeditions to the Arctic (ACCACIA, NETCARE, ASCOS) we found that although these diatoms do produce ice nucleating material, they were not as ice active as the investigated microlayer samples. Secondly, to improve our understanding of local Arctic marine sources as atmospheric INP we applied several aerosolisation techniques to analyse the ice nucleating ability of aerosolised microlayer and algae samples. The aerosols were generated either by direct nebulisation of the undiluted bulk solutions, or by the addition of the samples to a sea spray simulation chamber filled with artificial seawater. The latter method generates aerosol particles using a plunging jet to mimic the process of oceanic wave-breaking. We observed that the aerosols produced using this approach can be ice active indicating that the ice nucleating material in seawater can indeed transfer to the aerosol phase. Thirdly, we attempted to measure ice nucleation activity across the entire temperature range relevant for mixed-phase clouds using a suite of ice nucleation measurement techniques- an expansion cloud chamber, a continuous flow diffusion chamber, and a cold stage. In order to compare the measurements made using the different instruments, we have normalised the data in relation to the mass of salt present in the nascent sea spray aerosol. At temperatures above 248 K some of the SML samples were very effective at nucleating ice, but there was substantial variability between the different samples. In contrast, there was much less variability between samples below 248 K.
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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 | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 ».