Source-specific light absorption by carbonaceous components in thecomplex aerosol matrix from yearly filter-based measurements
Bibliographic record
Abstract
Abstract. Understanding the sources of light-absorbing organic (brown) carbon (BrC) and its interaction with black carbon (BC) and other non-refractory particulate matter (NR-PM) fractions is important for reducing uncertainties in the aerosol direct radiative forcing. In this study, we combine multiple filter-based techniques to achieve long-term, spectrally-resolved, source- and species-specific atmospheric absorption closure. We determine the total aerosol absorption at seven wavelengths based on the Aethalometer attenuation measurements, calibrated with the multi-wavelength absorption analyzer. We measure the spectrally-resolved imaginary part of the refractive index, k, for methanol extracts and determine the source-specific k for organic aerosol (OA) fractions using positive matrix factorization. The average k at 370 nm is found to be 0.06 for fresh biomass smoke, 0.03 for winter-oxygenated OA, and 0.006 for other less absorbing OA, which translates to corresponding mass absorption efficiencies (MAE) in dilute bulk solutions of 1.4, 0.7 and 0.13 m2 g−1. We apply Mie calculations to estimate the contributions of these fractions to total aerosol absorption. While enhanced absorption in the near-UV has been traditionally attributed to primary biomass smoke, here we show that anthropogenic oxygenated OA may be as important for BrC absorption during winter, especially at an urban background site. We demonstrate the absence of tar-balls in residential biomass burning particles of this study, and attribute the totality of the NR-PM absorption at shorter wavelengths to methanol-extractable BrC. As for BC, we show that the mass absorption cross-section (MAC) of this fraction is independent of its source, while we observe evidence for a lensing effect associated with the presence of NR-PM components. We find that bare BC has a MAC of 6.3 m2 g−1 at 660 nm and an absorption Ångström exponent (AAE) of 0.93 ± 0.16, while in the presence of coatings its absorption is enhanced by a factor of ~1.4. This falls within the global average enhancement factor of 1.5 ± 0.3 from filter-based techniques. Based on Mie-calculations of closure between observed and predicted total light absorption, we provide the first experimental evidence for a suppression of the lensing effect by BrC. The total absorption suppression remains modest, ~10–20 % at 370 nm, and is restricted to shorter wavelengths where BrC absorption is significant. Our long-term observations at locations representative of European urban background and rural Alpine sites show that extractable particulate BrC accounts for ~30 % of the absorption in the near-UV range (370 nm) on a yearly basis. However, if lensing suppression occurred due to internal mixing of BC and BrC as apparently the case for many samples in our study, then the additional absorption by BrC (vs transparent OA) would be partially compensated by a concurrent BC lensing factor reduction, which manifests as lower than expected total aerosol AAE values. Overall, when integrated with the solar spectrum at 300–900 nm, bare BC is found to contribute around two thirds of the solar radiation absorption by total carbonaceous aerosols, amplified by the lensing effect (with an interquartile range, IQR, of 8–27 %), while the IQR of yearly average contributions by particulate BrC is 6–13 % (13–20 % at the rural site during winter).
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 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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".