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Record W3016259896 · doi:10.1016/j.envint.2020.105680

Long-range transported North American wildfire aerosols observed in marine boundary layer of eastern North Atlantic

2020· article· en· W3016259896 on OpenAlexaboutno aff
Guangjie Zheng, Arthur J. Sedlacek, A. C. Aiken, Yan Feng, Thomas Watson, Shira Raveh‐Rubin, Janek Uin, Ernie R. Lewis, Jian Wang

Bibliographic record

VenueEnvironment International · 2020
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric chemistry and aerosols
Canadian institutionsnot available
FundersU.S. Department of Energy
KeywordsAtmospheric sciencesEnvironmental scienceAerosolRadiative forcingCloud condensation nucleiClimatologyRange (aeronautics)Angstrom exponentLatitudeBorealClimate changeClimate modelMeteorologyOceanographyGeologyGeographyMaterials science

Abstract

fetched live from OpenAlex

Wildfire is a major source of biomass burning aerosols, which greatly impact Earth climate. Tree species in North America (NA) boreal forests can support high-intensity crown fires, resulting in elevated injection height and longer lifetime (on the order of months) of the wildfire aerosols. Given the long lifetime, the properties of aged NA wildfire aerosols are required to understand and quantify their effects on radiation and climate. Here we present comprehensive characterization of climatically relevant properties, including optical properties and cloud condensation nuclei (CCN) activities of aged NA wildfire aerosols, emitted from the record-breaking Canadian wildfires in August 2017. Despite the extreme injection height of ~12 km, some of the wildfire plumes descended into the marine boundary layer in the eastern North Atlantic over a period of ~2 weeks, owing to the dry intrusions behind mid-latitude cyclones. The aged wildfire aerosols have high single scattering albedos at 529 nm (ω529; 0.92–0.95) while low absorption Ångström exponents (Åabs) at 464 nm/648 nm (0.7–0.9). In comparison, Åabs of fresh/slightly aged ones are typically 1.4–3.5. This low Åabs indicates a nearly complete loss of brown carbon, likely due to bleaching and/or evaporation, during the long-range transport. The nearly complete loss suggests that on global average, direct radiative forcing of BrC may be minor. Combining Mie calculations and the measured aerosol hygroscopicity, volatility and size distributions, we show that the high ω529 and low Åabs values are best explained by an external mixture of non-absorbing organic particles and absorbing particles of large BC cores (>~110 nm diameter) with thick non-absorbing coatings. The accelerated descent of the wildfire plume also led to strong increase of CCN concentration at the supersaturation levels representative of marine low clouds. The hygroscopicity parameter, κCCN, of the aged wildfire aerosols varies from 0.2 to 0.4, substantially lower than that of background marine boundary layer aerosols. However, the high fraction of particles with large diameter (i.e., within accumulation size ranges, ~100–250 nm) compensates for the low values of κ, and as a result, the aged NA wildfire aerosols contribute more efficiently to CCN population. These results provide direct evidence that the long-range transported NA wildfires can strongly influence CCN concentration in remote marine boundary layer, therefore the radiative properties of marine low clouds. Given the expected increases of NA wildfire intensity and frequency and regular occurrence of dry intrusion following mid-latitude cyclones, the influence of NA wildfire aerosols on CCN and clouds in remote marine environment need to be further examined.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

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)0.0040.000

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 head0.021
GPT teacher head0.193
Teacher spread0.172 · 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 teacher head, not a consensus.

Study designObservational
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

Citations127
Published2020
Admission routes1
Has abstractyes

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