Considerations for hypothetical carbon dioxide removal via alkalinity addition in the Amazon River watershed

Mu, Linquan; Palter, Jaime B.; Wang, Hongjie

doi:https://doi.org/10.5194/egusphere-2022-1505

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https://doi.org/10.5194/egusphere-2022-1505

Preprints

05 Jan 2023

| 05 Jan 2023

Considerations for hypothetical carbon dioxide removal via alkalinity addition in the Amazon River watershed

Linquan Mu, Jaime B. Palter, and Hongjie Wang

Abstract. The Amazon River plume plays a critical role in shaping the carbonate chemistry over a vast area in the western tropical North Atlantic. We explore a thought experiment of ocean alkalinity enhancement (OAE) via hypothetical quicklime addition in the Amazon River watershed, examining the response of carbonate chemistry and air-sea carbon dioxide flux to the alkalinity addition. Through a series of sensitivity tests, we show that the detectability of the OAE-induced alkalinity increment depends on the perturbation strength (or size of the alkalinity addition, ΔTA) and the number of samples: there is a 90 % chance to meet a minimum detectability requirement with ΔTA > 15 μmol kg^-1 and sample size > 40, given background variability of 15–30 μmol kg^-1. OAE-induced pCO₂ reduction at the Amazon plume surface would range between 0–25 μatm when ΔTA = 20 μmol kg^-1, decreasing with increasing salinity. Adding 20 μmol kg^-1 of alkalinity at the river mouth could elevate the total carbon uptake in the Amazon River plume by 0.07–0.1 MtCO₂ month^-1. Such thought experiments are useful in designing minimalistic field trials and setting achievable goals for monitoring, reporting, and verification purposes.

Received: 25 Dec 2022 – Discussion started: 05 Jan 2023

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26 May 2023

Considerations for hypothetical carbon dioxide removal via alkalinity addition in the Amazon River watershed

Linquan Mu, Jaime B. Palter, and Hongjie Wang

Biogeosciences, 20, 1963–1977, https://doi.org/10.5194/bg-20-1963-2023,https://doi.org/10.5194/bg-20-1963-2023, 2023

Short summary

Linquan Mu, Jaime B. Palter, and Hongjie Wang

Interactive discussion

Status: closed

RC1:
'Comment on egusphere-2022-1505', Anonymous Referee #1, 27 Jan 2023
This study performs a thought experiment to explore the CO₂removal effect via ocean alkalinity enhancement (OAE) by the hypothetical quicklime addition in the Amazon River watershed. The calculation results suggest that the total carbon uptake in the Amazon River Plume is ~ 0.07-0.1 MtCO₂/month when . A Monte Carlo simulation is made to assess the detectability of alkalinity perturbation, which shows that the detectability depends on the perturbation strength, the sample sizes and background alkalinity variability. This paper also discusses other potential issues related with the OAE deployment, including secondary mineral precipitation, ecological consequence, and heat release during quicklime dissolution. In summary, the authors argue that the proposed thought experiment could serve as a great starting point for investigating further the feasibility of using OAE for CO₂removal.

I find this study interesting, and the argument is well organized and convincing. I do have however several concerns that need to be addressed first, which I summarize in the following.

Carbonate system calculation for excess CO₂uptake estimate. The author applies a subtle method to estimate the CO₂uptake via the quicklime addition. One fundamental assumption is the constant DIC before any significant air-sea equilibrium occurs (Line 123). It is supported by that the air-sea equilibration takes weeks in the study region while CaO dissolution happens on hour-scales. Correct me if I am wrong, but I think this assumption needs more justification. The CO₂uptake estimate is based on the whole Amazon River plume region. Although CaO dissolves fast, the timescale for spreading of alkalinity perturbation along the plume may be comparable to that required for the air-sea equilibration. It is reasonable to expect a DIC increase from the river gateway to the oceanic part. With an increase of DIC, the pCO₂in the distal plume seawater will increase, which will reduce the CO₂uptake in this region. According to Figure 5, the plume at near-oceanic salinity level contributes to the majority of CO₂uptake due to the large area. Thus, I suggest the authors discuss or test the sensitivity of CO₂uptake estimate to the CO₂exchange between ocean and atmosphere along the plume route.

The pCO₂baseline derived from the mixing model is essential for the reliability of CO₂uptake estimate. However, the robustness of pCO₂baseline lacks discussion in the paper. I suggest plotting a figure (may be put in the extended figures) to compare the pCO₂-baseline with the pCO₂-empirical, which will make the performance of a simple mixing model more accessible to the reader.

As the authors said, the detectability experiment results depend on the background variability. There are six available alkalinity measurements for each gateway near the Amazon River mouth, which could be potentially applied to constrain the natural alkalinity variation. However, only data from North Macapa is used in this paper, which is “for a concise demonstration” according to Line 97. I did not get the meaning of concise demonstration here. So please elaborate the data choice here. Also, more discussions on the background variability from other regions (in addition to North Macapa) might also be helpful.

The theoretical saturation state for aragonite after the alkalinity perturbation is quite important to assess the performance of OAE, since secondary mineral precipitation will increase the oceanic pCO₂and reduce the CO₂uptake. The authors need to explain more about the calculation method (for instance, the Ca and CO₃^2- concentration, aragonite dissolution equilibrium constant for the calculation) for results in Table 3, rather than simply give the reference (Line 249). This is particularly important when salinity is low, because a lot of omega calculation is focused on seawater (with a high salinity). At low salinity (close to river), the equation to calculate omega might not hold.

Below are my minor comments

Two time periods, Sep-2011 and Jul-2012, shows distinct TA background (Figure 4a), empirical pCO₂values (Figure 1), and responses to alkalinity perturbation (Figure 4 and 5). These are good and I suggest the author adds more description and explanation of the differences between these two time periods, which will offer more insights into the seasonal dynamics of the carbonate system and how this will affect the OAE effects.

Line 78 TA is tracked by the addition of extra Ca²⁺, instead of using the carbonate species in Equation 1. Thus, I suggest changing the TA equation to the one that relies on the charge imbalance between major cations and anions.

Line 81 & 85 Ocean endmembers are not given explicitly in this manuscript, including the oceanic alkalinity and salinity.

Line 94 The authors state “measurements were made in both the river and throughout the Amazon River plume”. What kinds of measurements are made? In the later part of same paragraph, the authors explain the TA and DIC measurement strategy for the Amazon River mouth. However, the measurements for the Amazon River plume are not explained clearly.

Line 115 The way to parameterize α (solubility of CO₂in seawater) is not clearly explained.
Citation: https://doi.org/10.5194/egusphere-2022-1505-RC1
- AC1: 'Reply on RC1', Linquan Mu, 18 Apr 2023
  
  Thank you for your constructive feedback!
  Please find our response to the reviewers in the attachment.
  Best regards,
  Linquan Mu et al.
  
  Citation: https://doi.org/10.5194/egusphere-2022-1505-AC1
RC2:
'Comment on egusphere-2022-1505', Adam Subhas, 28 Feb 2023

This review is for the preprint manuscript submitted to Biogeosciences entitled "Considerations for hypothetical carbon dioxide removal via alkalinity addition in the Amazon River watershed" by Mu, Palter, and Wang. The authors conduct a series of calculations to investigate the potential for alkalinity enhancement to enhance the CO2 flux in the Amazon River and its plume. Mixing relationships are recalculated using several values of an enhanced-alkalinity river end member, mixed conservatively into the open-ocean end member using salinity. The plume's potential for CO2 uptake is calculated using satellite-derived salinity retrievals for the months of interest. Considerations for real-world deployment and MRV are posed.
Overall, this was an interesting manuscript and provides the kind of scale analyses that the community will need to move forward on OAE deployments and their MRV. However, I do have some comments and questions about the calculations that could be addressed before full publication. In particular, I have concerns about the pCO2-Salinity relationships, their variability in space and time, and the applicability to the entire plume. Some considerations of additional carbonate system variables (e.g. pH, DIC) should also be considered for MRV and sensitivity. I hope my comments are helpful and constructive.
Specific comments line-by-line below:
7: I am curious why the authors choose to limit themselves so early to quicklime addition. Most (if not all) of the calculations are insensitive to the style of OAE; it could even be accomplished through electrochemical alkalinity production. The authors could keep the discussion of quicklime below, but reframe the article to be about general OAE rather than a specific method. Then, give the example of quicklime later on.
12: It might be useful to mention the interesting conclusion here that most of the CO2 uptake happens at high salinity, because of the tradeoff between alkalinity enhancement and plume area during mixing with the open ocean.
29: The Bach et al., 2019 reference seems out of place here. I suggest Renforth and Henderson, 2017 as it surveys a number of different OAE approaches including liminal ones (in rivers/along coasts). The Bach reference has to do with ecological impacts following OAE deployment in the ocean.
51: Throughout the article, please check for consistency when referring to calcification (often shorthand for biological calcification) and secondary chemical precipitation. Again, the Bach paper refers to biological calcification feedbacks, whereas the Hartmann (and Moras) references investigate abiotic precipitation.
56a: I am wondering about this "thin layer" of surface salinity and what it means for total CO2 uptake by the plume. Does the total inventory of CO2 flux (in either mmol m-2 d-1 or in total Mt mo-1) depend on the assumption that salinity is constant in the mixed layer, and that the entire mixed layer is taking up CO2? I have seen these "thin layers' in the field and they can be quite thin!
56b: I am not sure what you mean by "low-carbonate plume." can you clarify?
67: Don't sell yourselves short -- this is not just a "thought experiment" but maybe a "sensitivity analysis"?
85: Is the river end member actually zero? Or some small nonzero number? Also, is the calcium concentration in the river zero, or is it a small but nonzero number? This will matter for mixing saturation state values. If you are specifically targeting quicklime, may also be useful to be explicit about the dissolution of quicklime and its impact on [Ca] (maybe negligible but potentially important at low salinity).
92-93: I am not sure that these equilibrium constants are appropriate for low-salinity waters. As stated in the header material for CO2SYS, the Mehrbach Refit is valid for salinities between 20-40. I would try the Cai and Wang constants; try out a couple that are valid for low salinity and see how much that impacts your calculations. It might be quite a bit in the low-salinity range, given the large sensitivity of pKa2 to salinity.
98: The discussion of gateways confused me. What is a gateway? What does it mean to "use one single gateway" with the mean and standard deviations of the TA values?
102: You mention calcification here, but also abiotic CaCO3 precipitation could be important.
107-108: I assume that the ships have underway CTD systems as well as pCO2. How well does the satellite SSS correspond with the underway salinity in the ANACONDAS transects? Given that the Mu et al (2021) calibration is only valid for salinity 15-35 how valid is it to apply this calibration to lower salinities? See for example Fig. 6B in Mu et al., 2021...it appears that a lot of lower salinity data falls off the mixing trend, and does not even appear to match with the end member composition of the river. I am thus skeptical of extrapolating this mixing trend back to salinities below 15.
125: One other important assumption in these calculations is that the alkalinity is homogeneously added to the river. If the addition is patchy, that adds another layer of variability that must be accounted for. Worth mentioning either here, or below.
150: Thinking out loud here, but is there a "sweet spot" at intermediate salinities where the variance is reduced compared to the river end member, giving a better chance of seeing a smaller perturbation?
174: Still not sure I understand what the gateway is referring to.
181: State the variance of these measurements, as you do with the July measurements.
183: I thought the samples are each from their own "gateway"? So, wouldn't this variance actually be inter-gateway variance, not variance at each gateway?
193: It might be nice to see a plot of plume area as a function of salinity, maybe as part of Figure 5, for each month.
193 cont'd: Given the breakdown in the empirical relationship for SSS<15, I am wondering if you could somehow state how much this relationship matters at these low salinities, especially because most of the CO2 flux does indeed fall in the 15<S<35 range.
200: Obviously, TA detection is great because you're measuring the thing you added. But, TA sensors aren't really commercialized yet and their precision/accuracy will likely be lower than laboratory measurements. You could do similar sensitivity calculations for pH and pCO2, which have commercial sensor options...given the large pH change you mention below, it may actually be much more sensitive to the perturbation than alkalinity, and give you a chance to see a clearer OAE signal in the river.
213-215: Why not try to do the same calculation as Fig. 4 for pCO2?
221: You could also use limestone to make ikaite, which is soluble at ocean surface conditions: https://doi.org/10.1016/j.joule.2022.11.001

In general, this section is good, but it feels limiting to the paper to just focus on quicklime.
240: This is a very large pH signal! I'd be very interested to see a similar calculation as Fig. 4, for pH.
271-275: The longer TA is left unequilibrated, the more time it has to be removed from the system as CaCO3, as well.
282: Please consider also citing Subhas et al., 2022, that showed some minor but largely negligible effects of OAE in shipboard incubations over a large range of alkalinity perturbations. They also showed no measurable changes in biological CaCO3 precipitation over the incubation period.
Subhas, A. V., Marx, L., Reynolds, S., Flohr, A., Mawji, E. W., Brown, P. J., & Cael, B. B. (2022). Microbial ecosystem responses to alkalinity enhancement in the North Atlantic Subtropical Gyre. Frontiers in Climate, 4, 784997. doi: 10.3389/fclim.2022.784997
292: You haven't proposed anymore, you have done it! Consider rewording to " We conducted a sensitivity analysis of alkalinity enhancement..."

Citation: https://doi.org/10.5194/egusphere-2022-1505-RC2
- AC2:
  'Reply on RC2', Linquan Mu, 18 Apr 2023
  
  Hi Adam,
  Thank you for your constructive feedback! Please see our response to the reviewers comments in the attached pdf.
  Best regards,
  Linquan Mu et al.
  
  Citation: https://doi.org/10.5194/egusphere-2022-1505-AC2
  - AC3: 'Reply on AC2', Linquan Mu, 18 Apr 2023
    
    Hi Adam,
    I realized that you may not be able to see the revised manuscript when you are reading this comment, so just wanted to copy & paste a part of the manuscript that was directly cited from one of our answers in the Response to Reviewer file. Below is the sub-section we referred to in addressing Reviewer Comment 2.19. Thank you.
    4.1 Unaccounted for plume region with great CDR potential
    While we explored the OAE-induced additionality of the carbon uptake (or net CDR) at different salinities in the Amazon River plume (Figure 5), it is important to note that the cumulative additional uptake in Figure 5b excludes the freshest part of the plume (SSS < 15). Due to high organic carbon remineralization in shallow waters (Mu et al., 2021), the quasi-linear SSS versus pCO₂ empirical relationship collapses at SSS < 15 and prevents the establishment of empirical pCO₂ in this region. Therefore, we excluded SSS < 15 in our analyses (e.g., in Figure 3, coastal areas < 50 m deep near the mouth are masked) while acknowledging that because of the strong CO₂ outgassing in this region, the baseline air-sea CO₂ flux in the entire plume (0 < SSS < 35) will be shifted towards more CO₂ release, should the SSS < 15 water be included. However, once TA is added, surface pCO₂ will decline in the entire plume regardless of salinity, causing greater net CO₂ drawdown across the plume. In other words, the OAE-induced CO₂ uptake increase calculated for 15 < S < 35 plume water could substantially underestimate the true additionality when SSS < 15 is not considered. The area of the S < 15 water is small compared to the 15 < SSS < 35 plume (i.e., < 15% of the SSS > 15 plume area), but its lower buffer capacity also means pCO₂ is much more sensitive to TA addition, and therefore could still contribute a considerable amount to CDR.
    A basic scaling would suggest that 10% of the plume area with an OAE-induced surface pCO₂ decrease of 30 μatm would have as large an impact on area-integrated ocean uptake as the 15 < SSS < 35 portion of the plume with a 3 μatm decrease. Additionally, according to Mu et al. (2021), the SSS < 15 part of the plume could contribute up to 0.6 TgC month^-1 of CO₂ outgassing, compared to 0.07 TgC month^-1 by the much larger 15 < SSS < 35 plume waters in July 2012. Therefore, including the freshest part of the plume and calculating its reduction in outgassing could easily double our estimate of additional CO₂ uptake for the entire plume. Lacking both knowledge of the spatial distribution of salinity and a robust estimate for pCO₂ in this low salinity region prevent us from quantifying its CDR potential in a rigorously manner.
    However, we can still conduct a back of the envelope calculation to estimate the distribution of CDR between SSS < 15 and 15 < SSS < 35 regions of the plume. With an addition of 20 μmol kg^-1 TA and an averaged Amazon freshwater discharge of 0.18 Sverdrup (Figure S1), we can calculate the total transport of this TA addition of 9.3 × 10⁹ mol month^-1, given sufficient time for air-sea re-equilibration and the subsequent DIC increase due to OAE. If we assume the maximum DIC increase is 0.8 times the ΔTA (Wang et al., 2022), the maximum CDR resulting from TA addition would be 0.8 × 9.3 × 10⁹ mol month^-1 = 7.5 × 10⁹ mol month^-1 , or 0.3 MtCO₂ month^-1. Given the estimated enhanced CO₂ flux in the S > 15 region is approximately 0.07~0.1 MtCO₂ month^-1 (Table 2), ~0.2 Mt of CO₂ uptake per month would be expected to take place in the low salinity region (SSS < 15), which is consistent with the estimation based on direct air-sea CO₂ flux change. This calculation highlights the disproportionately important role of the freshest part of the plume in the net CDR by the entire plume relative to its small size.
    
    Citation: https://doi.org/10.5194/egusphere-2022-1505-AC3

Interactive discussion

Status: closed

RC1:
'Comment on egusphere-2022-1505', Anonymous Referee #1, 27 Jan 2023
This study performs a thought experiment to explore the CO₂removal effect via ocean alkalinity enhancement (OAE) by the hypothetical quicklime addition in the Amazon River watershed. The calculation results suggest that the total carbon uptake in the Amazon River Plume is ~ 0.07-0.1 MtCO₂/month when . A Monte Carlo simulation is made to assess the detectability of alkalinity perturbation, which shows that the detectability depends on the perturbation strength, the sample sizes and background alkalinity variability. This paper also discusses other potential issues related with the OAE deployment, including secondary mineral precipitation, ecological consequence, and heat release during quicklime dissolution. In summary, the authors argue that the proposed thought experiment could serve as a great starting point for investigating further the feasibility of using OAE for CO₂removal.

I find this study interesting, and the argument is well organized and convincing. I do have however several concerns that need to be addressed first, which I summarize in the following.

Carbonate system calculation for excess CO₂uptake estimate. The author applies a subtle method to estimate the CO₂uptake via the quicklime addition. One fundamental assumption is the constant DIC before any significant air-sea equilibrium occurs (Line 123). It is supported by that the air-sea equilibration takes weeks in the study region while CaO dissolution happens on hour-scales. Correct me if I am wrong, but I think this assumption needs more justification. The CO₂uptake estimate is based on the whole Amazon River plume region. Although CaO dissolves fast, the timescale for spreading of alkalinity perturbation along the plume may be comparable to that required for the air-sea equilibration. It is reasonable to expect a DIC increase from the river gateway to the oceanic part. With an increase of DIC, the pCO₂in the distal plume seawater will increase, which will reduce the CO₂uptake in this region. According to Figure 5, the plume at near-oceanic salinity level contributes to the majority of CO₂uptake due to the large area. Thus, I suggest the authors discuss or test the sensitivity of CO₂uptake estimate to the CO₂exchange between ocean and atmosphere along the plume route.

The pCO₂baseline derived from the mixing model is essential for the reliability of CO₂uptake estimate. However, the robustness of pCO₂baseline lacks discussion in the paper. I suggest plotting a figure (may be put in the extended figures) to compare the pCO₂-baseline with the pCO₂-empirical, which will make the performance of a simple mixing model more accessible to the reader.

As the authors said, the detectability experiment results depend on the background variability. There are six available alkalinity measurements for each gateway near the Amazon River mouth, which could be potentially applied to constrain the natural alkalinity variation. However, only data from North Macapa is used in this paper, which is “for a concise demonstration” according to Line 97. I did not get the meaning of concise demonstration here. So please elaborate the data choice here. Also, more discussions on the background variability from other regions (in addition to North Macapa) might also be helpful.

The theoretical saturation state for aragonite after the alkalinity perturbation is quite important to assess the performance of OAE, since secondary mineral precipitation will increase the oceanic pCO₂and reduce the CO₂uptake. The authors need to explain more about the calculation method (for instance, the Ca and CO₃^2- concentration, aragonite dissolution equilibrium constant for the calculation) for results in Table 3, rather than simply give the reference (Line 249). This is particularly important when salinity is low, because a lot of omega calculation is focused on seawater (with a high salinity). At low salinity (close to river), the equation to calculate omega might not hold.

Below are my minor comments

Two time periods, Sep-2011 and Jul-2012, shows distinct TA background (Figure 4a), empirical pCO₂values (Figure 1), and responses to alkalinity perturbation (Figure 4 and 5). These are good and I suggest the author adds more description and explanation of the differences between these two time periods, which will offer more insights into the seasonal dynamics of the carbonate system and how this will affect the OAE effects.

Line 78 TA is tracked by the addition of extra Ca²⁺, instead of using the carbonate species in Equation 1. Thus, I suggest changing the TA equation to the one that relies on the charge imbalance between major cations and anions.

Line 81 & 85 Ocean endmembers are not given explicitly in this manuscript, including the oceanic alkalinity and salinity.

Line 94 The authors state “measurements were made in both the river and throughout the Amazon River plume”. What kinds of measurements are made? In the later part of same paragraph, the authors explain the TA and DIC measurement strategy for the Amazon River mouth. However, the measurements for the Amazon River plume are not explained clearly.

Line 115 The way to parameterize α (solubility of CO₂in seawater) is not clearly explained.
Citation: https://doi.org/10.5194/egusphere-2022-1505-RC1
- AC1: 'Reply on RC1', Linquan Mu, 18 Apr 2023
  
  Thank you for your constructive feedback!
  Please find our response to the reviewers in the attachment.
  Best regards,
  Linquan Mu et al.
  
  Citation: https://doi.org/10.5194/egusphere-2022-1505-AC1
RC2:
'Comment on egusphere-2022-1505', Adam Subhas, 28 Feb 2023

This review is for the preprint manuscript submitted to Biogeosciences entitled "Considerations for hypothetical carbon dioxide removal via alkalinity addition in the Amazon River watershed" by Mu, Palter, and Wang. The authors conduct a series of calculations to investigate the potential for alkalinity enhancement to enhance the CO2 flux in the Amazon River and its plume. Mixing relationships are recalculated using several values of an enhanced-alkalinity river end member, mixed conservatively into the open-ocean end member using salinity. The plume's potential for CO2 uptake is calculated using satellite-derived salinity retrievals for the months of interest. Considerations for real-world deployment and MRV are posed.
Overall, this was an interesting manuscript and provides the kind of scale analyses that the community will need to move forward on OAE deployments and their MRV. However, I do have some comments and questions about the calculations that could be addressed before full publication. In particular, I have concerns about the pCO2-Salinity relationships, their variability in space and time, and the applicability to the entire plume. Some considerations of additional carbonate system variables (e.g. pH, DIC) should also be considered for MRV and sensitivity. I hope my comments are helpful and constructive.
Specific comments line-by-line below:
7: I am curious why the authors choose to limit themselves so early to quicklime addition. Most (if not all) of the calculations are insensitive to the style of OAE; it could even be accomplished through electrochemical alkalinity production. The authors could keep the discussion of quicklime below, but reframe the article to be about general OAE rather than a specific method. Then, give the example of quicklime later on.
12: It might be useful to mention the interesting conclusion here that most of the CO2 uptake happens at high salinity, because of the tradeoff between alkalinity enhancement and plume area during mixing with the open ocean.
29: The Bach et al., 2019 reference seems out of place here. I suggest Renforth and Henderson, 2017 as it surveys a number of different OAE approaches including liminal ones (in rivers/along coasts). The Bach reference has to do with ecological impacts following OAE deployment in the ocean.
51: Throughout the article, please check for consistency when referring to calcification (often shorthand for biological calcification) and secondary chemical precipitation. Again, the Bach paper refers to biological calcification feedbacks, whereas the Hartmann (and Moras) references investigate abiotic precipitation.
56a: I am wondering about this "thin layer" of surface salinity and what it means for total CO2 uptake by the plume. Does the total inventory of CO2 flux (in either mmol m-2 d-1 or in total Mt mo-1) depend on the assumption that salinity is constant in the mixed layer, and that the entire mixed layer is taking up CO2? I have seen these "thin layers' in the field and they can be quite thin!
56b: I am not sure what you mean by "low-carbonate plume." can you clarify?
67: Don't sell yourselves short -- this is not just a "thought experiment" but maybe a "sensitivity analysis"?
85: Is the river end member actually zero? Or some small nonzero number? Also, is the calcium concentration in the river zero, or is it a small but nonzero number? This will matter for mixing saturation state values. If you are specifically targeting quicklime, may also be useful to be explicit about the dissolution of quicklime and its impact on [Ca] (maybe negligible but potentially important at low salinity).
92-93: I am not sure that these equilibrium constants are appropriate for low-salinity waters. As stated in the header material for CO2SYS, the Mehrbach Refit is valid for salinities between 20-40. I would try the Cai and Wang constants; try out a couple that are valid for low salinity and see how much that impacts your calculations. It might be quite a bit in the low-salinity range, given the large sensitivity of pKa2 to salinity.
98: The discussion of gateways confused me. What is a gateway? What does it mean to "use one single gateway" with the mean and standard deviations of the TA values?
102: You mention calcification here, but also abiotic CaCO3 precipitation could be important.
107-108: I assume that the ships have underway CTD systems as well as pCO2. How well does the satellite SSS correspond with the underway salinity in the ANACONDAS transects? Given that the Mu et al (2021) calibration is only valid for salinity 15-35 how valid is it to apply this calibration to lower salinities? See for example Fig. 6B in Mu et al., 2021...it appears that a lot of lower salinity data falls off the mixing trend, and does not even appear to match with the end member composition of the river. I am thus skeptical of extrapolating this mixing trend back to salinities below 15.
125: One other important assumption in these calculations is that the alkalinity is homogeneously added to the river. If the addition is patchy, that adds another layer of variability that must be accounted for. Worth mentioning either here, or below.
150: Thinking out loud here, but is there a "sweet spot" at intermediate salinities where the variance is reduced compared to the river end member, giving a better chance of seeing a smaller perturbation?
174: Still not sure I understand what the gateway is referring to.
181: State the variance of these measurements, as you do with the July measurements.
183: I thought the samples are each from their own "gateway"? So, wouldn't this variance actually be inter-gateway variance, not variance at each gateway?
193: It might be nice to see a plot of plume area as a function of salinity, maybe as part of Figure 5, for each month.
193 cont'd: Given the breakdown in the empirical relationship for SSS<15, I am wondering if you could somehow state how much this relationship matters at these low salinities, especially because most of the CO2 flux does indeed fall in the 15<S<35 range.
200: Obviously, TA detection is great because you're measuring the thing you added. But, TA sensors aren't really commercialized yet and their precision/accuracy will likely be lower than laboratory measurements. You could do similar sensitivity calculations for pH and pCO2, which have commercial sensor options...given the large pH change you mention below, it may actually be much more sensitive to the perturbation than alkalinity, and give you a chance to see a clearer OAE signal in the river.
213-215: Why not try to do the same calculation as Fig. 4 for pCO2?
221: You could also use limestone to make ikaite, which is soluble at ocean surface conditions: https://doi.org/10.1016/j.joule.2022.11.001

In general, this section is good, but it feels limiting to the paper to just focus on quicklime.
240: This is a very large pH signal! I'd be very interested to see a similar calculation as Fig. 4, for pH.
271-275: The longer TA is left unequilibrated, the more time it has to be removed from the system as CaCO3, as well.
282: Please consider also citing Subhas et al., 2022, that showed some minor but largely negligible effects of OAE in shipboard incubations over a large range of alkalinity perturbations. They also showed no measurable changes in biological CaCO3 precipitation over the incubation period.
Subhas, A. V., Marx, L., Reynolds, S., Flohr, A., Mawji, E. W., Brown, P. J., & Cael, B. B. (2022). Microbial ecosystem responses to alkalinity enhancement in the North Atlantic Subtropical Gyre. Frontiers in Climate, 4, 784997. doi: 10.3389/fclim.2022.784997
292: You haven't proposed anymore, you have done it! Consider rewording to " We conducted a sensitivity analysis of alkalinity enhancement..."

Citation: https://doi.org/10.5194/egusphere-2022-1505-RC2
- AC2:
  'Reply on RC2', Linquan Mu, 18 Apr 2023
  
  Hi Adam,
  Thank you for your constructive feedback! Please see our response to the reviewers comments in the attached pdf.
  Best regards,
  Linquan Mu et al.
  
  Citation: https://doi.org/10.5194/egusphere-2022-1505-AC2
  - AC3: 'Reply on AC2', Linquan Mu, 18 Apr 2023
    
    Hi Adam,
    I realized that you may not be able to see the revised manuscript when you are reading this comment, so just wanted to copy & paste a part of the manuscript that was directly cited from one of our answers in the Response to Reviewer file. Below is the sub-section we referred to in addressing Reviewer Comment 2.19. Thank you.
    4.1 Unaccounted for plume region with great CDR potential
    While we explored the OAE-induced additionality of the carbon uptake (or net CDR) at different salinities in the Amazon River plume (Figure 5), it is important to note that the cumulative additional uptake in Figure 5b excludes the freshest part of the plume (SSS < 15). Due to high organic carbon remineralization in shallow waters (Mu et al., 2021), the quasi-linear SSS versus pCO₂ empirical relationship collapses at SSS < 15 and prevents the establishment of empirical pCO₂ in this region. Therefore, we excluded SSS < 15 in our analyses (e.g., in Figure 3, coastal areas < 50 m deep near the mouth are masked) while acknowledging that because of the strong CO₂ outgassing in this region, the baseline air-sea CO₂ flux in the entire plume (0 < SSS < 35) will be shifted towards more CO₂ release, should the SSS < 15 water be included. However, once TA is added, surface pCO₂ will decline in the entire plume regardless of salinity, causing greater net CO₂ drawdown across the plume. In other words, the OAE-induced CO₂ uptake increase calculated for 15 < S < 35 plume water could substantially underestimate the true additionality when SSS < 15 is not considered. The area of the S < 15 water is small compared to the 15 < SSS < 35 plume (i.e., < 15% of the SSS > 15 plume area), but its lower buffer capacity also means pCO₂ is much more sensitive to TA addition, and therefore could still contribute a considerable amount to CDR.
    A basic scaling would suggest that 10% of the plume area with an OAE-induced surface pCO₂ decrease of 30 μatm would have as large an impact on area-integrated ocean uptake as the 15 < SSS < 35 portion of the plume with a 3 μatm decrease. Additionally, according to Mu et al. (2021), the SSS < 15 part of the plume could contribute up to 0.6 TgC month^-1 of CO₂ outgassing, compared to 0.07 TgC month^-1 by the much larger 15 < SSS < 35 plume waters in July 2012. Therefore, including the freshest part of the plume and calculating its reduction in outgassing could easily double our estimate of additional CO₂ uptake for the entire plume. Lacking both knowledge of the spatial distribution of salinity and a robust estimate for pCO₂ in this low salinity region prevent us from quantifying its CDR potential in a rigorously manner.
    However, we can still conduct a back of the envelope calculation to estimate the distribution of CDR between SSS < 15 and 15 < SSS < 35 regions of the plume. With an addition of 20 μmol kg^-1 TA and an averaged Amazon freshwater discharge of 0.18 Sverdrup (Figure S1), we can calculate the total transport of this TA addition of 9.3 × 10⁹ mol month^-1, given sufficient time for air-sea re-equilibration and the subsequent DIC increase due to OAE. If we assume the maximum DIC increase is 0.8 times the ΔTA (Wang et al., 2022), the maximum CDR resulting from TA addition would be 0.8 × 9.3 × 10⁹ mol month^-1 = 7.5 × 10⁹ mol month^-1 , or 0.3 MtCO₂ month^-1. Given the estimated enhanced CO₂ flux in the S > 15 region is approximately 0.07~0.1 MtCO₂ month^-1 (Table 2), ~0.2 Mt of CO₂ uptake per month would be expected to take place in the low salinity region (SSS < 15), which is consistent with the estimation based on direct air-sea CO₂ flux change. This calculation highlights the disproportionately important role of the freshest part of the plume in the net CDR by the entire plume relative to its small size.
    
    Citation: https://doi.org/10.5194/egusphere-2022-1505-AC3

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision | EF: Editorial file upload

ED: Publish subject to minor revisions (review by editor) (20 Apr 2023) by Jack Middelburg

AR by Linquan Mu on behalf of the Authors (21 Apr 2023) Author's response Manuscript

EF by Una Miškovic (24 Apr 2023)

EF by Una Miškovic (24 Apr 2023) Author's tracked changes

ED: Publish subject to technical corrections (25 Apr 2023) by Jack Middelburg

AR by Linquan Mu on behalf of the Authors (25 Apr 2023) Manuscript

Journal article(s) based on this preprint

26 May 2023

Considerations for hypothetical carbon dioxide removal via alkalinity addition in the Amazon River watershed

Linquan Mu, Jaime B. Palter, and Hongjie Wang

Biogeosciences, 20, 1963–1977, https://doi.org/10.5194/bg-20-1963-2023,https://doi.org/10.5194/bg-20-1963-2023, 2023

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Linquan Mu, Jaime B. Palter, and Hongjie Wang

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Linquan Mu, Jaime B. Palter, and Hongjie Wang

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Enhancing ocean alkalinity accelerates carbon dioxide removal from the atmosphere. We hypothetically added alkalinity to the Amazon River and examined the increment of the carbon uptake by the Amazon plume. We also investigated the minimum alkalinity addition in which this perturbation at the river mouth could be detected above the natural variability.


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