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Enregistrement W4241068730 · doi:10.5194/acp-2020-1134

Soot-PCF: Pore condensation and freezing framework for sootaggregates

2020· preprint· en· W4241068730 sur OpenAlexaff
Claudia Marcolli, Fabian Mahrt, B. Kärcher

Notice bibliographique

Revuenon disponible
Typepreprint
Langueen
DomaineEarth and Planetary Sciences
ThématiqueAtmospheric chemistry and aerosols
Établissements canadiensUniversity of British Columbia
Organismes subventionnairesH2020 Marie Skłodowska-Curie ActionsEuropean Commission
Mots-clésSootIce nucleusIce crystalsCirrusNucleationAerosolParticle (ecology)CondensationChemical physicsCloud condensation nucleiMaterials scienceRelative humidityTroposphereMineralogyChemical engineeringChemistryAtmospheric sciencesThermodynamicsGeologyMeteorologyCombustionPhysical chemistryPhysics

Résumé

récupéré en direct d'OpenAlex

Abstract. How ice crystals form in the troposphere strongly affects cirrus cloud properties. Atmospheric ice formation is often initiated by aerosol particles that act as ice nucleating particles. The aerosol-cloud interactions of soot and associated feedbacks remain uncertain, in part because a coherent understanding of the ice nucleation mechanism and activity of soot has not yet emerged. Here, we provide a new framework that predicts ice formation on soot particles via pore condensation and freezing (PCF) that, unlike previous approaches, considers soot particle properties capturing their vastly different pore properties compared to other aerosol species such as mineral dust. During PCF, water is taken up below water saturation into pores on soot aggregates by capillary condensation. At cirrus temperatures, pore water can freeze homogeneously and subsequently grow into a macroscopic ice crystal. In the soot-PCF framework presented here, the relative humidity conditions required for these steps are derived for different pore types as a function of temperature. The pore types considered here evolve from idealized stacking of equally sized primary particles, either in tetrahedral or cubic packing arrangements. Specifically, we encompass n-membered ring pores that form between n individual spheres within the same layer of primary particles as well as pores in the form of inner cavities that form between two layers of primary particles. We treat soot primary particles as perfect spheres and use the contact angle between soot and water (θsw), the primary particle diameter (Dpp) and the degree of primary particle overlap (overlap coefficient, Cov) to characterize soot pore properties. We find that n-membered ring pores are the dominant pore structures for soot-PCF, as they are common features of soot aggregates and have a suitable geometry for both, filling with water and growing ice below water saturation. We focus our analysis on three-membered and four-membered ring pores as they are of the right size for PCF assuming primary particle sizes typical for atmospheric soot particles. For these pore types, we derive equations that describe the conditions for all three steps of soot-PCF, namely capillary condensation, ice nucleation, and ice growth. Since at typical cirrus conditions homogeneous ice nucleation can be considered immediate as soon as the water volume within the pore is large enough to host a critical ice embryo, soot-PCF becomes either limited by capillary condensation or ice crystal growth. For instance, our results show that at typical cirrus temperatures of T = 220 K, three-membered ring pores formed between primary particles with θsw = 60°, Dpp = 20 nm, and Cov = 0.05 are ice growth limited, as the ice requires a relative humidity with respect to ice of RHi = 137 % to grow out of the pore, while a sufficient volume of pore water for ice nucleation has condensed already at RHi = 86 %. Conversely, four-membered ring pores with the same primary particle size and an overlap coefficient of Cov = 0.1 are capillary condensation limited as they require RHi = 129 % to gather enough water for ice nucleation, compared with only 124 % RHi, required for ice growth. We use the soot-PCF framework to derive a new equation to parameterize of ice formation on soot particles via PCF. This equation is based on soot properties that are routinely measured, including the primary particle size and overlap, and the fractal dimension. These properties, along with the number of primary particles making up an aggregate and the contact angle between water and soot, constrain the parameterization. Applying the new parameterization to previously reported laboratory data of ice formation on soot particles provides direct evidence that ice nucleation on soot aggregates takes place via PCF. We conclude that this new framework clarifies the ice formation mechanism on soot particles at cirrus conditions and provides a new perspective to represent ice formation on soot in climate models.

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)0,001
score de la tête « metaresearch » (Gemma)0,001
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Simulation ou modélisation · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: aucune
Score de désaccord entre enseignants0,009
Score d'incertitude au seuil0,020

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0010,001
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0010,002
Bibliométrie0,0010,001
Études des sciences et des technologies0,0010,001
Communication savante0,0010,001
Science ouverte0,0020,001
Intégrité de la recherche0,0010,001
Charge utile insuffisante (le modèle a refusé de juger)0,0060,001

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 Opus0,036
Tête enseignante GPT0,251
Écart entre enseignants0,216 · 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'étudeSimulation ou modélisation
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

Citations12
Publié2020
Routes d'admission1
Résumé présentoui

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