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Record W3083712998 · doi:10.5194/acp-20-13957-2020

The effects of morphology, mobility size, and secondary organic aerosol (SOA) material coating on the ice nucleation activity of black carbon in the cirrus regime

2020· article· en· W3083712998 on OpenAlexaff
Cuiqi Zhang, Yue Zhang, Martin J. Wolf, Leonid Nichman, Chuanyang Shen, T. B. Onasch, Longfei Chen, Daniel J. Cziczo

Bibliographic record

VenueAtmospheric chemistry and physics · 2020
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric chemistry and aerosols
Canadian institutionsNational Research Council Canada
FundersChinese Government ScholarshipDivision of Atmospheric and Geospace SciencesNational Institutes of HealthNational Science Foundation
KeywordsNucleationIce nucleusCirrusAerosolSupersaturationChemical engineeringParticle (ecology)Materials scienceHomogeneousParticle sizeCarbon blackTroposphereChemical physicsSupercoolingTotal organic carbonChemistryAtmospheric sciencesEnvironmental chemistryGeologyComposite materialThermodynamicsOrganic chemistry

Abstract

fetched live from OpenAlex

There is evidence that black carbon (BC) particles may affect cirrus formation and, hence, global climate by acting as potential ice nucleating particles (INPs) in the troposphere. Nevertheless, the ice nucleation (IN) ability of bare BC and BC coated with secondary organic aerosol (SOA) material remains uncertain. We have systematically examined the IN ability of 100–400 nm size-selected BC particles with different morphologies and different SOA coatings representative of anthropogenic (toluene and n -dodecane) and biogenic ( β -caryophyllene) sources in the cirrus regime (−46 to −38 ∘ C). Several BC proxies were selected to represent different particle morphologies and oxidation levels. Atmospheric aging was further replicated with the exposure of SOA-coated BC to OH. The results demonstrate that the 400 nm hydrophobic BC types nucleate ice only at or near the homogeneous freezing threshold. Ice formation at cirrus temperatures below homogeneous freezing thresholds, as opposed to purely homogeneous freezing, was observed to occur for some BC types between 100 and 200 nm within the investigated temperature range. More fractal BC particles did not consistently act as superior INPs over more spherical ones. SOA coating generated by oxidizing β -caryophyllene with O 3 did not seem to affect BC IN ability, probably due to an SOA-phase state transition. However, SOA coatings generated from OH oxidation of various organic species did exhibit higher IN-onset supersaturation ratio with respect to ice (SS i ), compared with bare BC particles, with the toluene-SOA coating showing an increase in SS i of 0.1–0.15 while still below the homogeneous freezing threshold. Slightly oxidized toluene SOA coating seemed to have a stronger deactivation effect on BC IN ability than highly oxidized toluene SOA, which might be caused by oligomer formation and the phase state transition of toluene SOA under different oxidation levels. n -dodecane and β -caryophyllene-derived SOA-coated BC only froze in the homogeneous regime. We attribute the inhibition of IN ability to the filling of the pores on the BC surface by the SOA material coating. OH exposure levels of n -dodecane and β -caryophyllene SOA coating experiments, from an equivalent atmospheric exposure time from 10 to 90 d, did not render significant differences in the IN potential. Our study of selected BC types and sizes suggests that increases in diameter, compactness, and/or surface oxidation of BC particles lead to more efficient IN via the pore condensation freezing (PCF) pathway, and that coatings of common SOA materials can inhibit the formation of ice.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.006
GPT teacher head0.186
Teacher spread0.180 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations53
Published2020
Admission routes1
Has abstractyes

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