Formation and growth of nucleated particles: observational constraints on cloud condensation nuclei budgets
Notice bibliographique
Résumé
Abstract. Aerosol nucleation occurs frequently in the atmosphere and is an important source of particle number. Observations suggest that nucleated particles are capable of growing to sufficiently large sizes that they act as cloud condensation nuclei (CCN), but some global models have reported that CCN concentrations are only modestly sensitive to large changes in nucleation rates. Here we present a novel approach for using long-term size distribution observations to evaluate the contribution of nucleation and growth to the tropospheric CCN budget. We derive from observations at five locations nucleation-relevant metrics such as nucleation rate of particles at diameter of 3 nm (J3), diameter growth rate (GR), particle survival probability (SP), condensation and coagulation sinks, and CCN formation rate. These quantities are also derived for a global microphysical model and compared to the observations on a daily basis to evaluate the model's CCN budget. Using the GEOS-Chem-TOMAS global aerosol model we simulate nucleation events predicted by ternary (with a 10−5 tuning factor) or activation nucleation over one year and find that the model does not understate the contribution of boundary layer nucleation to CCN concentrations. Model-predicted annual-average formation rates of 50 nm and 100 nm particles due to nucleation are always within 50% and show a slight tendency to over-estimate the observations. Because it is rare for observations to track the growth of a nucleation mode across several days, it is difficult to assess CCN formation when growth requires multiple days. To address multi-day growth, we present three cases of survival of particles beyond one day: single-day growth, partial multi-day survival, and total multi-day survival. For the single-day growth case, only particles that reach a CCN size (50 or 100 nm) on the same day are counted as contributing to the CCN budget, which represents a low estimate of CCN attributable to nucleation. The partial survival case extrapolates the coagulation sink and growth rate allowing nucleated particles as much time as needed to become CCN and represents a realistic, but perhaps somewhat high, estimate for CCN formation from nucleation. The total survival case assumes that all particles that survive the first day, no matter their end-of-day size, will eventually become CCN and represents a high estimate of CCN formation from nucleation. On days that the growing nucleation mode reaches 100 nm, median single-day survival probabilities to 100 nm for the model and measurements range from less than 1% to 9% across the five locations we considered. At the upper end, total survival median survival probabilities to 100 nm are no greater than 36% and the partial survival case survival probabilities are 5 to 25%, depending on the site. Using growth rates, nucleation rates, coagulation rates, survival probabilities, and an assumed CCN lifetime, we calculate that annually averaged CN100 concentrations (a proxy for CCN) formed from single-day nucleation and growth events does not exceed 50 cm−3 in both the model and the measurements across the five locations, representing no more than 3% of total CN100. When we extrapolate growth and loss to include growth to CCN beyond the first day (partial survival case), we find that both the model and measurements show a higher but still modest contribution (up to 14%) to total CN100. This detailed exploration of new particle formation and growth dynamics adds support to the use of global models as tools for assessing the contribution of microphysical processes such as nucleation to the total number and CCN budget.
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 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 | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,001 | 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 ».