Arctic marine secondary organic aerosol contributessignificantly to summertime particle size distributions in theCanadian Arctic Archipelago
Bibliographic record
Abstract
Abstract. Summertime Arctic aerosol size distributions are strongly controlled by natural regional emissions. Within this context, we use a chemical transport model with size-resolved aerosol microphysics (GEOS-Chem-TOMAS) to interpret measurements of aerosol size distributions from the Canadian Arctic Archipelago during the summer of 2016, as part of the NETwork on Climate and Aerosols: addressing key uncertainties in Remote Canadian Environments (NETCARE). Our simulations suggest that condensation of secondary organic aerosol (SOA) from precursor vapors emitted in the Arctic and near Arctic marine (open ocean and coastal) regions plays a key role in particle growth events that shape the aerosol size distributions observed at Alert (82.5° N, 62.3° W), Eureka (80.1° N, 86.4° W), and along a NETCARE ship track within the Archipelago. We refer to this SOA as Arctic marine SOA (Arctic MSOA) to reflect the Arctic marine-based and likely biogenic sources for the precursors of the condensing organic vapors. Arctic MSOA from a simulated flux (500 μg m−2 d−1, north of 50° N) of precursor vapors (assumed yield of unity) reduces the summertime particle size distribution model-observation mean fractional error by 2- to 4-fold, relative to a simulation without this Arctic MSOA. Particle growth due to the condensable organic vapor flux contributes strongly (30–50 %) to the simulated summertime-mean number of particles with diameters larger than 20 nm in the study region, and couples with ternary particle nucleation (sulfuric acid, ammonia, and water vapor) and biogenic sulfate condensation to account for more than 90 % of this simulated particle number, a strong biogenic influence. The simulated fit to summertime size-distribution observations is further improved at Eureka and for the ship track by scaling up the nucleation rate by a factor of 100 to account for other particle precursors such as gas-phase iodine and/or amines and/or fragmenting primary particles that could be missing from our simulations. Additionally, the fits to observed size distributions and total aerosol number concentrations for particles larger than 4 nm improve with the assumption that the Arctic MSOA contains semi-volatile species; reducing model-observation mean fractional error by 2- to 3-fold for the Alert and ship track size distributions. Arctic MSOA accounts for more than half of the simulated total particulate organic matter mass concentrations in the summertime Canadian Arctic Archipelago, and this Arctic MSOA has strong simulated summertime pan-Arctic-mean top-of-the-atmosphere aerosol direct (−0.04 W m−2) and cloud-albedo indirect (−0.4 W m−2) radiative effects. Future work should focus on further understanding summertime Arctic sources of Arctic MSOA.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".