Treatment of non-ideality in the SPACCIM multiphase model – Part 1: Model development
Bibliographic record
Abstract
Abstract. Ambient tropospheric deliquesced particles generally comprise a complex mixture of electrolytes, organic compounds, and water. Dynamic modeling of physical and chemical processes in this complex matrix is challenging. Thus, up-to-date multiphase chemistry models generally do not consider non-ideal solution effects. Therefore, the present study was aimed at presenting further development of the SPACCIM (Spectral Aerosol Cloud Chemistry Interaction Model) through treatment of solution non-ideality, which has not been considered before. The present paper firstly describes the model developments including (i) the implementation of solution non-ideality in aqueous-phase reaction kinetics in the SPACCIM framework, (ii) the advancements in the coupling scheme of microphysics and multiphase chemistry and (iii) the required adjustments of the numerical schemes, especially in the sparse linear solver and the calculation of the Jacobian. Secondly, results of sensitivity investigations are outlined, aiming at the evaluation of different activity coefficient modules and the examination of the contributions of different intermolecular forces to the overall activity coefficients. Finally, first results obtained with the new model framework are presented. The SPACCIM parcel model was developed and, so far, applied for the description of aerosol–cloud interactions. To advance SPACCIM also for modeling physical and chemical processes in deliquesced particles, the solution non-ideality has to be taken into account by utilizing activities in reaction terms instead of aqueous concentrations. The main goal of the extended approach was to provide appropriate activity coefficients for solved species. Therefore, an activity coefficient module was incorporated into the kinetic model framework of SPACCIM. Based on an intercomparison of different activity coefficient models and the comparison with experimental data, the AIOMFAC approach was implemented and extended by additional interaction parameters from the literature for mixed organic–inorganic systems. Moreover, the performance and the capability of the applied activity coefficient module were evaluated by means of water activity measurements, literature data and results of other activity coefficient models. Comprehensive comparison studies showed that the SpactMod (SPACCIM activity coefficient module) is valuable for predicting the thermodynamic behavior of complex mixtures of multicomponent atmospheric aerosol particles. First simulations with a detailed chemical mechanism have demonstrated the applicability of SPACCIM-SpactMod. The simulations indicate that the treatment of solution non-ideality might be needed for modeling multiphase chemistry processes in deliquesced particles. The modeled activity coefficients imply that chemical reaction fluxes of chemical processes in deliquesced particles can be both decreased and increased depending on the particular species involved in the reactions. For key ions, activity coefficients on the order of 0.1–0.8 and a strong dependency on the charge state as well as the RH conditions are modeled, implying a lowered chemical processing of ions in concentrated solutions. In contrast, modeled activity coefficients of organic compounds are in some cases larger than 1 under deliquesced particle conditions and suggest the possibility of an increased chemical processing of organic compounds. Moreover, the model runs have shown noticeable differences in the pH values calculated with and without consideration of solution non-ideality. On average, the predicted pH values of the simulations considering solution non-ideality are −0.27 and −0.44 pH units lower under 90 and 70 % RH conditions, respectively. More comprehensive results of detailed SPACCIM-SpactMod studies on the multiphase processing in organic–inorganic mixtures of deliquesced particles are described in a companion paper.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".