the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 24 Aug 2023
In-silico calculation of soil pH by SCEPTER v1.0
Abstract. One of the soil properties most commonly measured to describe agronomic and biogeochemical conditions of soils is “soil pH”. Soil pH measures the concentration of exchangeable H+ that resides in bulk soil samples taken from the field, through aqueous H+ measurements of extractants (e.g., deionized water or electrolyte solutions) added to dried bulk soil samples in the laboratory. Therefore, “soil pH” differs from “porewater pH”, the latter of which we define here as an in-situ measure of porewater H+ concentration in soil/weathering profiles. The difference between the two pH measurements is often not fully known for a given system but could lead to a misunderstanding of soil conditions if the two measurements are directly compared. Agricultural soils are one of the targeted loci for application of the “Enhanced Rock Weathering” (ERW), a technique aimed at counteracting increasing anthropogenic carbon dioxide from burning fossil fuels, and an increase in pH is thought to be one of key advantages of ERW as this can mitigating soil acidification and secure crop yields. As a result, fully evaluating the biogeochemical and agronomic consequences of ERW approaches requires accurate simulation of both soil pH (pHs) and porewater pH (pHpw). This paper presents an updated version of the reactive transport code SCEPTER (Soil Cycles of Elements simulator for Predicting TERrestrial regulation of greenhouse gases), which enables simulation of bulk soil pH measurement in the laboratory in addition to porewater pH as measured in the field along with a more comprehensive representation of cation exchange with solid-phase constituents of bulk soil. We first describe the implementation of cation exchange in the SCEPTER model, then introduce conceptual modelling frameworks enabling the calculation of bulk pHs. The validity of the model is examined through comparison of model results with soil pH measurements from mesocosm experiments of maize production with crushed basalt amendments. Finally, illustrative example simulations are shown demonstrating that a difference between pHs and pHpw can lead to significantly different estimates of carbon capture by ERW for a given targeted pH in cropland systems.
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RC1: 'Comment on gmd-2023-137', Anonymous Referee #1, 30 Dec 2023
Comments on In-silico calculation of soil pH by SCEPTER v1.0 by Kanzaki et al. In this paper, the author present the next version of their model SCEPTER, which has been developed to predict the CO2 exchange between soils and atmosphere, in particular as a response to the addition of silicates for enhancing alkalinity production via weathering. In version v1.0, they extended the set of processes by including ion exchange. The implementation of ion exchange is validated in various ways. The key test is the prediction of pH in a solution obtained by adding deionized water or CaCl2 solution in various solid/solution ratios to the soil. As an application, they demonstrate that the required amount of basalt addition depends on whether the target pH is based on pore water composition or on that of one or another soil extract. This is because the pH values of pore water and soil extracts differ, essentially due to the limited buffer intensity of the soil solution and the solid phase.
I find it difficult to evaluate this paper as it is not very clear to me, which conclusion the authors want to convey. In view of the journal, I presume that documenting the development of the model itself and not the application is of key relevance. In this case, a rigorous discussion of the results from the exemplary applications might not be expected. The applications would only serve the purpose to demonstrate that including ion exchange in the model can be of importance. Here, the authors show that the model is able to predict the pH of a solution, obtained by reacting deionized water or a (KCl)/CaCl2 solution with the soil at different solid/solution ratios. Essentially, cation exchange is used in the model to account for the pH buffer intensity in soils including reactions at the solid/water interface. However, the target application of SCEPTER is to predict weathering and CO2 sequestration in soils. I would then expect that the authors demonstrate that implementing ion exchange has consequences for calculating weathering rates or CO2 uptake. Wouldn’t it make it more sense to select one of the examples from the previous study (Kanzaki et al. 2022) and demonstrate that including ion exchange affects the predicted pH change (in the porewater) or the captured CO2 upon basalt amendment? Or to show, that cation exchange can exert influence on the saturation index and by this change mineralization rates. I find the story about the dependence of the required basalt dosage on how the pH is defined/determined a bit far-fetched. It is well established, that the pH in soil extracts depend on solid/solution ratio and initial composition of the solution (see papers cited by the authors). This inherently imply, that the pH of an extract does not reflect pore water pH. The consequences for basalt dosing as presented in Fig. 5 appear enormous as about eight times more basalt is required to increase porewater pH to 6.2 in comparison to the amount of basalt needed to increasing soil pH. However, this example is a bit misleading as the average pH for the top 15 cm after one year is used as a target. That is, the alkalinization front has only proceeded about 5 cm into the soil and the pore water pH in the deeper layers is already close to 6.2. In this case, the systematically lower pH in the soil pH has to be compensated by a higher pH in the upper 5 cm. I expect that the contrast is less when taking the average pH in the top 5 cm after 2 years as a target. Anyway, examples, which demonstrate that ion exchange is an important process when predicting the effect of enhanced weathering in terms of CO2 capture and resulting pH would be much more convincing. This would justify including this process in the model to achieve the model objectives. In conclusion the presented applications do not justify publication, and the justification should come from the model development itself.
In view of model development, the presented progress is, in my opinion, only marginal. The extension of processes by including cation exchange is small compared to the complexity of the the previous version of the model. The validation of the cation exchange module is, however, very original. Calculating the pH in soil extracts is not straightforward in SCEPTER and requires some tricks including the evaporation of the porewater in silico and redissolving the obtained salts in the respective solutions and equilibrating the solution with the exchange complex. In particular, the addition of carbonate is cumbersome and occurs in the form of easily degradable organic matter. I did not understand why DIC could not be transferred in the form of highly soluble carbonates. In any case, the correctness of this procedure should be tested and documented, too. The model reproduced the measured soil pH of one soil taken from a mesocosm experiment but this does not proof that the whole procedure does not create artefacts. The hassle of deforming the reactive transport model for aqueous equilibrium calculations implies, that it is unlikely that anybody will use the model for this purpose. That is because there a numerous alternatives for this purpose, or example PHREEQC, MINTEQ and other programs. Therefore, the authors should also verify the indirect model approach by comparing the predictions with those obtained from, for example, PHREEQC. The output of the model, including the composition of the exchange complex and the solution, could be directly used as an input in PHREEQC. The effect of diluting the porewater with CaCl2 solution can then be easily performed. In my opinion, comparing the predictions of SCEPTER and PHREEQC (or another chemical equilibrium model) as a benchmark should be included to demonstrate the correctness of the procedure to calculate soil pH.
The third aspect is the adequateness of the approach to account for the buffer intensity in soils. In a first instance, concepts for describing cation exchange have been developed to describe the exchange of major cations between solution and constant charge surfaces. Here, the authors apply the concepts to account for the pH buffering in soils. This can cause some inconsistencies, in particular, when the contribution of organic matter to the buffer intensity is restricted to cation exchange. This approach implies, for example, that the pKa value of functional groups of organic matter depend on whether the background electrolyte includes Na or Ca ions. Furthermore, it restricts the description of acid/base properties of soil organic matter to only one acidity constant. This might be sufficient in a limited pH range but, usually, multiple pKa models are used for an adequate description of the acid/base properties of soil organic matter. For the selected soil, the model preforms well but the versatility of the approach to account for the buffering intensity of other soils remains uncertain. However, I would not demand an extensive testing of the model to a large variety of soils but the possible limitations of the approach should be discussed.
In conclusion, the paper presents a marginal extension of the processes included in SCEPTER. The presented validation is creative but does not represent a relevant application. The possible limitations of the approach are not discussed and the performance is only tested for one soil. I propose to accept the manuscript with major revisions and I suggest following improvements: 1) The validation should include benchmarking with aqueous equilibrium models, 2) the possible limitations of using solely cation exchange to account for the pH buffering in soils should be rigorously discussed 3) the relevance of including cation exchange in the model should be demonstrated for the main application of the model, mineral weathering and CO2 sequestration. In general, the manuscript has a high quality, it is concisely written and the results are adequately presented figures and table. I have not tested the model and I hope other reviewers assessed the robustness and consistency of the model and investigated its usability and documentation.
Minor comments:
Figure 2: Exchangeable fraction is in units of ppm. Is this correct? Are the other 99.99 % occupied by protons?
Citation: https://doi.org/10.5194/gmd-2023-137-RC1 - AC1: 'Reply on RC1', Yoshiki Kanzaki, 11 Mar 2024
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RC2: 'Comment on gmd-2023-137', Anonymous Referee #2, 12 Feb 2024
Review GMD-2023-137, Kanzaki et al.
Kanzaki et al. propose a new model framework to predict soil pH and highlight the difference from porewater pH. The new scheme is an extension of the existing model SCEPTER, which now accounts for cation exchange reactions, thus enabling soil pH determination. Here, the authors test the new framework against a mesocosm soil experiment. Furthermore, they illustrate the applicability of the model to track pH amendments through enhance rock weathering via crushed basalt dispersal.
In general, the manuscript is nicely written and has a logical flow. The results suggest that the model performs well on the proposed tests, however these seem to not be extensive. Nevertheless, this work is a worthy contribution. Overall, it only requires some clarifications and perhaps expansion of a few points in the results and discussion (see comments below). Therefore, I recommend minor revisions before it is acceptable for publication.
Specific comments
Abstract: Generally fine, but there is an imbalance of overall description and results. The latter needs more emphasis or details. I suggest condensing the "general introduction" and expand the key findings and implications.
L.15-17: Split in two sentences for clarity.
L.44-47: Shouldn't it be highlighted here the potential/efficiency of adding crushed basalt is somewhat dependent on the basalt composition itself, gran size, soil temperature, moisture and drainage? Furthermore, what are the possible impacts (positive or negative) of ERW for soils themselves and downstream (if/when leachates escape to the surrounding environment)?
L.48-52: Is there comparative evidence to bridge gaps between pH(s) and pH(pw), as predicted by models?
L.81-82: What are the solid species involved in cation exchange?
L.130-138: It is probably easier to follow here as a table or as single-line items instead of a running text.
L.138-144: This would read best right after Eq.(11), then followed by the table/list of individual parameters (L.130-138).
L.160-161: Is the pH(s) modelling a two-step process (i.e., a "normal" field run is required to provide the needed boundary conditions for the "lab" experiment.)? Can it be run stand-alone with assumed boundary conditions? Can one obtain only set depths or averaged conditions, or is it possible to calculate the pH(s) continuously along the soil profile?
L.180-181: Why is DIC added as labile organic matter?
L.181-190: This would read better as an equation, followed by the list of components.
L.208-209: Is such difference between pH(s) and pH(pw) systematic or predictable in any way based on boundary conditions/assumptions?
L.219: A brief description here and/or an appendix/SI is needed.
L.245-248: Did you test the effect of not including NO3 and Cl to the lab runs?
L.250-251: The model seems to slightly underestimate Ca and Mg. Any particular reason?
L.254-256: Can such variability provide any predictability of pH(s) concerning the media used to exchange cations from the solid-phase?
L.260-262: 1) The results shown here are based and compared to one mesocosm experiment. Although it looks the model performs well, there is not much to compare in terms of distinct set up conditions. Do these comparisons hold for another mesocosm conditions and natural/agricultural soils?
2) How does the model closely reproduce pH(s) of previously publish data? This is not shown.
L.275: Are these target pH values for the average soil profile or at a specific depth?
L.288-289: 1) Would these basalt amendments/pH correction change in any meaningful way under different environmental conditions (e.g., temperature, soil moisture)?
2) Are these predicted basalt contents in line with any expected or suggested plans of soil amendment?
L.289-290: From Fig. 6-7, it is unclear to me when the target pH are met. Except for target pH(s) = 6.2 (Fig. 6a), after one year all pH values largely exceed the target at the surface. Is that true or am I miss-interpreting the figure? If pH values would reach > 7.0, what consequences would that bring? Either way, it's not clear. Can you indicate in each panel the target pH (vertical dotter line or so)?
L.297-298: If so, which approach would be more suitable to adopt when tracking pH, either for natural/agricultural conditions or ERW conditions? Is there a recommendation to be made here, particularly when pH(s) is a more common practice to determine pH of soil systems?
L.298-300: In these basalt amendment scenarios, are there estimates of other "by products" (e.g., SiOH4 enrichment, secondary precipitation processes) and their fate?
L.305-310: Can these findings provide any recommendation or guidance for pH measurements in soil and/or ERW practices?
Citation: https://doi.org/10.5194/gmd-2023-137-RC2 - AC2: 'Reply on RC2', Yoshiki Kanzaki, 11 Mar 2024
Status: closed
-
RC1: 'Comment on gmd-2023-137', Anonymous Referee #1, 30 Dec 2023
Comments on In-silico calculation of soil pH by SCEPTER v1.0 by Kanzaki et al. In this paper, the author present the next version of their model SCEPTER, which has been developed to predict the CO2 exchange between soils and atmosphere, in particular as a response to the addition of silicates for enhancing alkalinity production via weathering. In version v1.0, they extended the set of processes by including ion exchange. The implementation of ion exchange is validated in various ways. The key test is the prediction of pH in a solution obtained by adding deionized water or CaCl2 solution in various solid/solution ratios to the soil. As an application, they demonstrate that the required amount of basalt addition depends on whether the target pH is based on pore water composition or on that of one or another soil extract. This is because the pH values of pore water and soil extracts differ, essentially due to the limited buffer intensity of the soil solution and the solid phase.
I find it difficult to evaluate this paper as it is not very clear to me, which conclusion the authors want to convey. In view of the journal, I presume that documenting the development of the model itself and not the application is of key relevance. In this case, a rigorous discussion of the results from the exemplary applications might not be expected. The applications would only serve the purpose to demonstrate that including ion exchange in the model can be of importance. Here, the authors show that the model is able to predict the pH of a solution, obtained by reacting deionized water or a (KCl)/CaCl2 solution with the soil at different solid/solution ratios. Essentially, cation exchange is used in the model to account for the pH buffer intensity in soils including reactions at the solid/water interface. However, the target application of SCEPTER is to predict weathering and CO2 sequestration in soils. I would then expect that the authors demonstrate that implementing ion exchange has consequences for calculating weathering rates or CO2 uptake. Wouldn’t it make it more sense to select one of the examples from the previous study (Kanzaki et al. 2022) and demonstrate that including ion exchange affects the predicted pH change (in the porewater) or the captured CO2 upon basalt amendment? Or to show, that cation exchange can exert influence on the saturation index and by this change mineralization rates. I find the story about the dependence of the required basalt dosage on how the pH is defined/determined a bit far-fetched. It is well established, that the pH in soil extracts depend on solid/solution ratio and initial composition of the solution (see papers cited by the authors). This inherently imply, that the pH of an extract does not reflect pore water pH. The consequences for basalt dosing as presented in Fig. 5 appear enormous as about eight times more basalt is required to increase porewater pH to 6.2 in comparison to the amount of basalt needed to increasing soil pH. However, this example is a bit misleading as the average pH for the top 15 cm after one year is used as a target. That is, the alkalinization front has only proceeded about 5 cm into the soil and the pore water pH in the deeper layers is already close to 6.2. In this case, the systematically lower pH in the soil pH has to be compensated by a higher pH in the upper 5 cm. I expect that the contrast is less when taking the average pH in the top 5 cm after 2 years as a target. Anyway, examples, which demonstrate that ion exchange is an important process when predicting the effect of enhanced weathering in terms of CO2 capture and resulting pH would be much more convincing. This would justify including this process in the model to achieve the model objectives. In conclusion the presented applications do not justify publication, and the justification should come from the model development itself.
In view of model development, the presented progress is, in my opinion, only marginal. The extension of processes by including cation exchange is small compared to the complexity of the the previous version of the model. The validation of the cation exchange module is, however, very original. Calculating the pH in soil extracts is not straightforward in SCEPTER and requires some tricks including the evaporation of the porewater in silico and redissolving the obtained salts in the respective solutions and equilibrating the solution with the exchange complex. In particular, the addition of carbonate is cumbersome and occurs in the form of easily degradable organic matter. I did not understand why DIC could not be transferred in the form of highly soluble carbonates. In any case, the correctness of this procedure should be tested and documented, too. The model reproduced the measured soil pH of one soil taken from a mesocosm experiment but this does not proof that the whole procedure does not create artefacts. The hassle of deforming the reactive transport model for aqueous equilibrium calculations implies, that it is unlikely that anybody will use the model for this purpose. That is because there a numerous alternatives for this purpose, or example PHREEQC, MINTEQ and other programs. Therefore, the authors should also verify the indirect model approach by comparing the predictions with those obtained from, for example, PHREEQC. The output of the model, including the composition of the exchange complex and the solution, could be directly used as an input in PHREEQC. The effect of diluting the porewater with CaCl2 solution can then be easily performed. In my opinion, comparing the predictions of SCEPTER and PHREEQC (or another chemical equilibrium model) as a benchmark should be included to demonstrate the correctness of the procedure to calculate soil pH.
The third aspect is the adequateness of the approach to account for the buffer intensity in soils. In a first instance, concepts for describing cation exchange have been developed to describe the exchange of major cations between solution and constant charge surfaces. Here, the authors apply the concepts to account for the pH buffering in soils. This can cause some inconsistencies, in particular, when the contribution of organic matter to the buffer intensity is restricted to cation exchange. This approach implies, for example, that the pKa value of functional groups of organic matter depend on whether the background electrolyte includes Na or Ca ions. Furthermore, it restricts the description of acid/base properties of soil organic matter to only one acidity constant. This might be sufficient in a limited pH range but, usually, multiple pKa models are used for an adequate description of the acid/base properties of soil organic matter. For the selected soil, the model preforms well but the versatility of the approach to account for the buffering intensity of other soils remains uncertain. However, I would not demand an extensive testing of the model to a large variety of soils but the possible limitations of the approach should be discussed.
In conclusion, the paper presents a marginal extension of the processes included in SCEPTER. The presented validation is creative but does not represent a relevant application. The possible limitations of the approach are not discussed and the performance is only tested for one soil. I propose to accept the manuscript with major revisions and I suggest following improvements: 1) The validation should include benchmarking with aqueous equilibrium models, 2) the possible limitations of using solely cation exchange to account for the pH buffering in soils should be rigorously discussed 3) the relevance of including cation exchange in the model should be demonstrated for the main application of the model, mineral weathering and CO2 sequestration. In general, the manuscript has a high quality, it is concisely written and the results are adequately presented figures and table. I have not tested the model and I hope other reviewers assessed the robustness and consistency of the model and investigated its usability and documentation.
Minor comments:
Figure 2: Exchangeable fraction is in units of ppm. Is this correct? Are the other 99.99 % occupied by protons?
Citation: https://doi.org/10.5194/gmd-2023-137-RC1 - AC1: 'Reply on RC1', Yoshiki Kanzaki, 11 Mar 2024
-
RC2: 'Comment on gmd-2023-137', Anonymous Referee #2, 12 Feb 2024
Review GMD-2023-137, Kanzaki et al.
Kanzaki et al. propose a new model framework to predict soil pH and highlight the difference from porewater pH. The new scheme is an extension of the existing model SCEPTER, which now accounts for cation exchange reactions, thus enabling soil pH determination. Here, the authors test the new framework against a mesocosm soil experiment. Furthermore, they illustrate the applicability of the model to track pH amendments through enhance rock weathering via crushed basalt dispersal.
In general, the manuscript is nicely written and has a logical flow. The results suggest that the model performs well on the proposed tests, however these seem to not be extensive. Nevertheless, this work is a worthy contribution. Overall, it only requires some clarifications and perhaps expansion of a few points in the results and discussion (see comments below). Therefore, I recommend minor revisions before it is acceptable for publication.
Specific comments
Abstract: Generally fine, but there is an imbalance of overall description and results. The latter needs more emphasis or details. I suggest condensing the "general introduction" and expand the key findings and implications.
L.15-17: Split in two sentences for clarity.
L.44-47: Shouldn't it be highlighted here the potential/efficiency of adding crushed basalt is somewhat dependent on the basalt composition itself, gran size, soil temperature, moisture and drainage? Furthermore, what are the possible impacts (positive or negative) of ERW for soils themselves and downstream (if/when leachates escape to the surrounding environment)?
L.48-52: Is there comparative evidence to bridge gaps between pH(s) and pH(pw), as predicted by models?
L.81-82: What are the solid species involved in cation exchange?
L.130-138: It is probably easier to follow here as a table or as single-line items instead of a running text.
L.138-144: This would read best right after Eq.(11), then followed by the table/list of individual parameters (L.130-138).
L.160-161: Is the pH(s) modelling a two-step process (i.e., a "normal" field run is required to provide the needed boundary conditions for the "lab" experiment.)? Can it be run stand-alone with assumed boundary conditions? Can one obtain only set depths or averaged conditions, or is it possible to calculate the pH(s) continuously along the soil profile?
L.180-181: Why is DIC added as labile organic matter?
L.181-190: This would read better as an equation, followed by the list of components.
L.208-209: Is such difference between pH(s) and pH(pw) systematic or predictable in any way based on boundary conditions/assumptions?
L.219: A brief description here and/or an appendix/SI is needed.
L.245-248: Did you test the effect of not including NO3 and Cl to the lab runs?
L.250-251: The model seems to slightly underestimate Ca and Mg. Any particular reason?
L.254-256: Can such variability provide any predictability of pH(s) concerning the media used to exchange cations from the solid-phase?
L.260-262: 1) The results shown here are based and compared to one mesocosm experiment. Although it looks the model performs well, there is not much to compare in terms of distinct set up conditions. Do these comparisons hold for another mesocosm conditions and natural/agricultural soils?
2) How does the model closely reproduce pH(s) of previously publish data? This is not shown.
L.275: Are these target pH values for the average soil profile or at a specific depth?
L.288-289: 1) Would these basalt amendments/pH correction change in any meaningful way under different environmental conditions (e.g., temperature, soil moisture)?
2) Are these predicted basalt contents in line with any expected or suggested plans of soil amendment?
L.289-290: From Fig. 6-7, it is unclear to me when the target pH are met. Except for target pH(s) = 6.2 (Fig. 6a), after one year all pH values largely exceed the target at the surface. Is that true or am I miss-interpreting the figure? If pH values would reach > 7.0, what consequences would that bring? Either way, it's not clear. Can you indicate in each panel the target pH (vertical dotter line or so)?
L.297-298: If so, which approach would be more suitable to adopt when tracking pH, either for natural/agricultural conditions or ERW conditions? Is there a recommendation to be made here, particularly when pH(s) is a more common practice to determine pH of soil systems?
L.298-300: In these basalt amendment scenarios, are there estimates of other "by products" (e.g., SiOH4 enrichment, secondary precipitation processes) and their fate?
L.305-310: Can these findings provide any recommendation or guidance for pH measurements in soil and/or ERW practices?
Citation: https://doi.org/10.5194/gmd-2023-137-RC2 - AC2: 'Reply on RC2', Yoshiki Kanzaki, 11 Mar 2024
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