Characterising Mass-resolved Mixing State of Black Carbon in Beijing Using a Morphology-Independent Measurement Method
Bibliographic record
Abstract
Abstract. Refractory Black Carbon (rBC) in the atmosphere is known for its significant impact on the climate system in the atmosphere. The relationship between the microphysical and optical properties of rBC remain uncertain and are largely influenced by the size, coating thickness and mixing state of particles. This study presents a coupling of a centrifugal particle mass analyser (CPMA) and a single particle soot photometer (SP2) for the morphology-independent quantification of the mixing state of rBC-containing particles, used in the urban site of Beijing as part of the Air Pollution and Human Health-Beijing (APHH-Beijing) project during winter (10th Nov–10th Dec) and summer (18th May–25th June). An inversion method is applied to the measurements to present a two-variable distribution of both rBC core mass and total mass of rBC-containing particles and present the mass-resolved mixing state of rBC-containing particles. The mass ratio between non-rBC coating and rBC core (MR) is calculated to determine the coating thickness of the rBC-containing particles. The bulk MR was found to vary between 2–12 in winter and between 2–3 in summer. This mass-resolved mixing state is used to derive the mixing state index (χ) for the rBC-containing particles. χ quantifies whether the coating is evenly distributed across the rBC-containing particle population and is used to determine the degree of internal and external mixture of rBC-containing particles. The rBC-containing particles in Beijing were found to be 55%–70 % internally mixed in winter depending on the dominant air masses. χ of rBC-containing particles was highly positively associated with increased bulk MR, rBC mass loading or pollution level in winter, whereas χ of rBC-containing particles in summer varied significantly (ranging 60 %–75 %) within the narrowly-distributed bulk MR and was found to be independent of air mass sources. This concludes that the bulk MR may only act as a predictor of mixing state in winter, and χ is better to quantify the mixing state of rBC-containing particles. The same level of bulk MR corresponded with a higher χ in summer than in winter and this tended to suggest a limited formation of coatings on rBC largely depended on primary sources. However, with the higher Non-refractory PM1 (NR-PM1) concentration in winter, the coagulation process may still lead relative thick coatings. In summer the higher secondary compounds made the rBC-containing particles more homogeneous. But due to the higher temperatures and limited pollution level, the coating thickness in summer is limited. The mixing state of rBC-containing particles should also depend on the coating formation mechanism, both primary source influence and secondary coating formation mechanism should be considered in interpreting the rBC-containing particles mixing state in the atmosphere. This particle morphology-independent and mass-based data format as introduced in this study could be conviently applied in particle-resolved or other process models to investigate atmospheric rBC aging and mixing state properties.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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".