A critical evaluation of proxy methods used to estimate the acidity of atmospheric particles
Bibliographic record
Abstract
Abstract. Given significant challenges with available measurements of aerosol acidity, proxy methods are frequently used to estimate the acidity of atmospheric particles. In this study, four of the most common aerosol acidity proxies are evaluated and compared: (1) the ion balance method, (2) the molar ratio method, (3) thermodynamic equilibrium models, and (4) the phase partitioning of ammonia. All methods are evaluated against predictions of thermodynamic models and against direct observations of aerosol–gas equilibrium partitioning acquired in Mexico City during the Megacity Initiative: Local and Global Research Objectives (MILAGRO) study. The ion balance and molar ratio methods assume that any deficit in inorganic cations relative to anions is due to the presence of H+ and that a higher H+ loading and lower cation / anion ratio both correspond to increasingly acidic particles (i.e., lower pH). Based on the MILAGRO measurements, no correlation is observed between H+ levels inferred with the ion balance and aerosol pH predicted by the thermodynamic models and NH3–NH4+ partitioning. Similarly, no relationship is observed between the cation / anion molar ratio and predicted aerosol pH. Using only measured aerosol chemical composition as inputs without any constraint for the gas phase, the E-AIM (Extended Aerosol Inorganics Model) and ISORROPIA-II thermodynamic equilibrium models tend to predict aerosol pH levels that are inconsistent with the observed NH3–NH4+ partitioning. The modeled pH values from both E-AIM and ISORROPIA-II run with gas + aerosol inputs agreed well with the aerosol pH predicted by the phase partitioning of ammonia. It appears that (1) thermodynamic models constrained by gas + aerosol measurements and (2) the phase partitioning of ammonia provide the best available predictions of aerosol pH. Furthermore, neither the ion balance nor the molar ratio can be used as surrogates for aerosol pH, and previously published studies with conclusions based on such acidity proxies may need to be reevaluated. Given the significance of acidity for chemical processes in the atmosphere, the implications of this study are important and far reaching.
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 | 0.024 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".