the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 09 May 2025
The Chemical Mechanism Integrator Cminor v1.0: A Stand-Alone Fortran Environment for the Particle-Based Simulation of Chemical Multiphase Mechanisms
Abstract. We present version 1.0 of the Chemical Mechanism Integrator (Cminor), a fully modularized modern Fortran software package for the computational simulation of skeletal and detailed chemical kinetic systems derived from atmospheric and combustion chemistry. Cminor aims for the efficient simulation of complex chemical mechanisms by using various mathematical techniques. These are tailored to systems of ordinary differential equations (ODEs), having the specific structure arising from chemical reaction systems. Additionally, a high-speed mechanism parser allows the user to interchange reactions or their parameters in an ASCII format text file and immediately start a new simulation without recompiling, enabling fast and numerous simulations. Cminor's solver technique is based on Rosenbrock methods. Different measures of local errors and an analytical Jacobian matrix approach are implemented, where efficiency is obtained by exploiting the sparsity structure of the Jacobian.
Cminor can be run in one of three configurations:
- A box-model framework for either pure gas-phase mechanisms or a multi-modal aerosol distribution dissolved in mono-dispersed cloud droplets.
- A rising adiabatic parcel, in which the activation of multi-modal aerosols is represented by solving the droplet condensation equation.
- A constant volume environment, where thermodynamic properties are evaluated by polynomial functions of temperature according to the standards of the Chemkin thermodynamic data base.
The software package is evaluated by applying seven different chemical mechanisms. Three of them are from the field of air-quality modeling and three are from the area of combustion kinetics, ranging from 7 species and 10 reactions to 10,196 species and 23,098 reactions. The last mechanism describes sulfur accumulation in clouds, which is tested along with a rising parcel and condensating cloud droplets.
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RC1: 'Comment on egusphere-2025-380', Anonymous Referee #1, 15 Jun 2025
This paper presents Cminor a stand-alone solver environment to simulate chemical kinetic systems of different complexity to solve atmospheric and combustion chemistry problems. The novelty is the fact that it does not requite any separate solvers but applies linear-implicit Rosenbrock numerical schemes. Given that chemical mechanisms have grown over the last decades to several 1000s of reaction, new numerical tools are needed to solve such computational demanding equation sets. In the present paper, Cminor ahs been applied to several chemical mechanisms of widely varying complexity and thus the applicability of Cminor has been demonstrated. The model description is very detailed and clear; the model is easy to use with a logical file structure. I only have a few, mostly minor, comments that should be addressed prior to acceptance for publication.
Main comments
1) To prove the validity of the model, it would be more convincing if the authors showed a comparison to previous model studies. Particularly, I am surprised about the sentence “The comparatively high number concentration of cloud droplets is due to our low water accomodation (sic! – note that an ‘m’ is missing) coefficient.” (l. 505/6). In line 210, it is mentioned that alpha = 1 is used, which is the upper limit for this coefficient. What was the drop number concentration as predicted by Jaruga and Pawlowska (2018) and which accommodation coefficient did they use? Please clarify.
2) How does the new solver compare in terms of computing time to previous ones that have been used for the same chemical mechanisms used here? Is it comparable?
3) The chemical systems addressed are highly idealized. While I understand that the current paper is a model development paper, some more perspectives should be given how to apply Cminor to current atmospheric chemical problems that deviate from the rather simple cases. This could be briefly mentioned in the conclusions as a perspective for future extensions and applications. They include, for example,
- chemical processes in/on aerosol particles (doi: 10.5194/acp-10-3673-2010)
- ionic strength effects: aqueous phase rate constants have been shown to be a function of the salt content of the aqueous phase
- phase partitioning of semivolatile compounds. Even though it is mentioned that CAPRAM4.0a can be used to predict SOA formation in the aqueous phase, it is not clear how Cminor treats gas-aqueous partitioning of formed aqSOA species that may not follow Henry’s law since they form salts or partition according to their volatility which may not follow Henry’s law when water content becomes small
- could an externally mixed aerosol or drop population be considered, i.e. particles or droplets of the same size but different chemical composition?
4) l. 100: It is not clear why you single out peroxy radicals as being potentially constant and why they are summed up to a single entity (supplement l. 168), given that they may have very different reactivities. Please add a justification and appropriate reference
5) According to listing 1 of the supplement, it seems that only one salt can be used per CCN, e.g. NaCL or NH4(SO4)2. Could the model be used for realistic initial aerosol composition such as 50% amm sulf and 50% organics?
6) Some equations are numbered. Others are not. Please use consistent numbering throughout the paper.
Minor/technical comments:
l. 35: Phase transition depends also on chemical composition itself
l. 182: Call it ‘aqueous phase’ here because the following text only refers to water (not to liquid organic phases)
l. 187: It should be upper case K
Supplement:
l. 62 multiplied with…
l. 413: Avogadro number is 6.022 10^23 not ^22
Table 3: What is ‘accommodation coefficient’ here? Before you describe that the accommodation coefficient for each species can be set separately.
Citation: https://doi.org/10.5194/egusphere-2025-380-RC1 -
RC2: 'Comment on egusphere-2025-380', Anonymous Referee #2, 26 Jul 2025
The paper describes a new Fortran package named Cminor that provides an ordinary differential equations solver of chemical kinetics systems. The solver is based on Rosenbrock methods and relies on custom sparse Jacobian to ensure high performance. Cminor allows users to specify the included chemical reactions and their coefficients without the need to recompile the code. The paper describes in detail the numerics of the solver and showcases the different modeling setups applicable to combustion kinetics and atmospheric chemistry modeling that are supported by Cminor.
The description of the numerics of the solve is indeed very detailed, and I lack the experience to provide feedback on it. The shown simulation results are convincing and highlight the applicability of Cminor to different atmospheric chemistry and combustion problems, but maybe lack broader discussion. I have a couple of questions that I hope will clarify the presentation of the package to its potential future users.
1. I was a bit confused by the description of the initial aerosol condition and how it connects with the adiabatic parcel vs prescribed LWC modeling setups. The paper states that aerosol (assumed to be completely dissolved in droplets) is assigned to a user specified number of droplet classes. If I understand correctly, in the prescribed LWC scenario the model assumes a mono-disperse distribution of droplets. That would imply that no different droplet classes are needed, as each droplet is of the same size? On the other hand, in the adiabatic parcel scenario the model directly solves the aerosol activation. As a result the liquid droplet sizes should be solved for by the model, rather than prescribed by the user? Could I ask to clarify that?
2. Is it also possible to change the default values of equation parameters (like for example water accommodation coefficient in the adiabatic parcel model) through the text files, without recompiling the code? (In the same way as one would change the chemical reaction rate coefficients?) Also, the paper later states that a low value of the accommodation coefficient is used, but I think it is what is typically used. If anything, I saw studies that use lower values.
3. In the equation above equation (6) it should be moist air gas constant?4. It would be great to provide some more discussion and interpretation of what the different patterns in Figures 7 and 8 mean? I admit that I am not very familiar with Rosenbrok methods and I'm wondering what those figures are supposed to convey? Also, why do Figures 7 and 8 appear before Figure 3 in the text?
5. For the readers not familiar with the details of the numerics of Rosenbrok solvers, would it be possible to highlight which parts of the discussion in chapter 4 represent novel approaches, and which parts are standard in the community?
6. In the last column of Table 3 what do 26 (907) and 36 (1800) stand for? Aqueous phase sulfur oxidation should not need this many species and reactions?
7. What does the green shading represent in figure 4? - I'm guessing it's the effect of plotting blue over yellow with some opacity. But it would be nice to try to keep all three LWC shading regions appear in the same color.
8. Could I ask for a little more discussion of the results presented in Figures 7 and 8? For example: How well do they match the benchmark results from the literature? What was the computation time needed to generate those results and on what hardware? Would it be possible (and would it make sense) to include an example plot showing how the model performance scales with the number of included reactions? How does the performance scale with the number of CPU cores? How the performance of Cminor compare with other models?
9. Is the github link missing?
Citation: https://doi.org/10.5194/egusphere-2025-380-RC2
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