Current State of Atmospheric Aerosol Thermodynamics and Mass Transfer Modeling: A Review
Bibliographic record
Abstract
A useful aerosol model must be able to adequately resolve the chemical complexity and phase state of the wide particle size range arising from the many different secondary aerosol growth processes to assess their environmental and health impacts. Over the past two decades, significant advances in understanding of gas-aerosol partitioning have occurred, particularly with respect to the role of organic compounds, yet aerosol representations have changed little in air quality and climate models since the late 1990s and early 2000s. The gas-aerosol partitioning models which are still commonly used in air quality models are separate inorganics-only thermodynamics and secondary organic aerosol (SOA) formation based on absorptive partitioning theory with an assumption of well-mixed liquid-like particles that continuously maintain equilibrium with the gas phase. These widely used approaches in air quality models for secondary aerosol composition and growth based on separated inorganic and organic processes are inadequate. This review summarizes some of the important developments during the past two decades in understanding of gas aerosol mass transfer processes. Substantial increases in computer performance in the last decade justify increasing the process detail in aerosol models. Organics play a central role during post-nucleation growth into the accumulation mode and change the hygroscopic properties of sulfate aerosol. At present, combined inorganic-organic aerosol thermodynamics models are too computationally expensive to be used online in 3-D simulations without high levels of aggregation of organics into a small number of functional surrogates. However, there has been progress in simplified modeling of liquid-liquid phase separation (LLPS) and distinct chemical regimes within organic-rich and inorganic-rich phases. Additional limitations of commonly used thermodynamics models are related to lack of surface tension data for various aerosol compositions in the small size limit, and lack of a comprehensive representation of surface interaction terms such as disjoining pressure in the Gibbs free energy which become significant in the small size limit and which affect both chemical composition and particle growth. As a result, there are significant errors in modeling of hygroscopic growth and phase transitions for particles in the nucleation and Aitken modes. There is also increasing evidence of reduced bulk diffusivity in viscous organic particles and, therefore, traditional secondary organic aerosol models, which are typically based on the assumption of instantaneous equilibrium gas-particle partitioning and neglect the kinetic effects, are no longer tenable.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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".