Emissions and CO₂ Concentration—An Evidence Based Approach

Round 1

Reviewer 1 Report

This paper presents a simple approach to understanding the relationship between CO2 emissions and atmospheric CO2 concentration, based on the assumption that carbon sinks are linearly dependent on CO2 concentration on a decadal scale. The model uses only two parameters and accurately explains CO2 emission and historical CO2 concentration data, providing estimates of natural emissions, pre-industrial CO2 equilibrium concentration levels, the half-life time of an emission pulse, and future CO2 concentration levels. Validation through an ex-post forecast of the last 20 years shows that future CO2 concentrations will not rise above 475 ppm with the stated policy scenario of the IEA, and the model is compared with the Carbon module of the Bern model.

 

The article is well-written and has a clear research question, sound methodology, and logical analysis. I do not have major concerns. The paper can be accepted after minor revision. There are some typos. For instance, line 12: module, Line 177-186: 1-> (1) or 1), Line 376-383: The capitalization of the first letter should be consistent. In addition, the literature review could be improved; it is insufficient.

Author Response

Thank you for your review.

The typos are corrected, the introduction has been expanded and a paragraph with a method overview has been added. Furthermore, 8 additional literature references are included.

Due to the fact that there is such an overwhelming number of publications in the field, we had to select those publications that are either closest or most prominent to the specific question of CO₂ emissions/concentration, or those that are providing evidence to statements we made.   

We enclose the corrected PDF with markup at all places where we made changes.

Author Response File: Author Response.pdf

Reviewer 2 Report

Current paper discusses development of sustainable CO2 management approach motivated by the question of how much CO2 must necessarily be absorbed by sinks. Observations lead to the model assumption, that carbon sinks like oceans or biosphere are linearly dependent on CO2 concentration on a decadal scale. In particular this implies the falsifiable hypothesis that oceanic and biological CO2 buffers have not significantly changed in the past 50 years and are not saturated in the future. The simple model with parameters showed well the CO2 emission and historical CO2 concentration data and allows efficient predictions management.

Critical remarks can be made on MS quality:

1.      Figures 1,2,3, 4, 5 axis should contain subscription for CO2 as well as in legend and in the text.

2.      Language quality needs improvement

3.      Mentioning equations is not correctly done in text, use proper equation function for them.

4.      „approximately linear w.r.t“- meaning unclear

5.      Fig. 2,3, use Origin program to generate graphs, cite where necessary.

6.     Check ways to estimate CO2/bicarbonate equilibrium and possibilities to reduce CO2 by autotrophic processes as CO2 sink options: https://doi.org/10.1080/09593330.2012.665487

7.      The residual error of the model will need justification.

8.      Three-line table format is preferred over the one used by authors. P values of 0.000 seems to be unrealistic?

9.      Fig. 5 -trendlines seem wrongly drawn from very fluctuating data.

10.   Why period of study was chosen as 1950-2020 and used for predictions?

11.   Check that if Your calculations are correct and results reliable with available data, compare

12. Methods part of study is not described well and not given in abstract in precise manner.

13. Define abbreviations in first mentioning such as: "IEA"

Author Response

Thank your for your thorough review.

1. All figures have been remade with correct subscripting
2. Typos an language formulations have been corrected
3. One incorrect equation reference has been corrected and all others have been checked. I need to mention, that there are a few equation references pointing to referenced papers, these have now been marked with "his equation" or "their equation".
4. This sentence is redundant at this location and has been removed. 
5. Both figures have been remade (see point 1). I understand you are not trying to impose to use a specific tool, but rather ask for acceptable quality?
6. The point of the paper is that we have a complementary approach to the classical analysis of individual absorption processes. In order to clarify this we have added the sentence "While we do not know the contributing components, we can measure their total effect over time." (line 166). 
7. While in a statistical model the residual error is part of the model and does not need justification, we have clarified this by explicitly adding the statistical error R_i to equations 8 and 11.  Furthermore there is a discussion about the possible causes of non-random parts of the residual error (lines 289-293). 
8. All estimation results have been converted to the 3-line table format. The precision of the  p-values has been reduced to 2 decimal places.
9. The "trendlines" are not really trendlines, but model values. With constant absorption parameter the curve must be proportional to the CO₂ concentration curve and therefore is not "straight", nor following the wiggles. We noticed that our formulation in the text was a bit unclear, and therefore we replaced "constant relative absorption" by "constant absorption parameter" wherever needed. 
10. We have quite exensively discussed this question in section 2.5.2 . The decisive criterion is data quality, which has dramatically improved in the 1950s (we added a reference to make this point). 
11. In our understanding this is exactly what we have done with the ex-post prediction of measured CO₂ concentrations in Figure 6.   This result is absolutely remarkable, when you e.g. compare this to the incorrect ex-post predictions of the IPCC models or with the discussed and referenced 150% deviation of the Oeschger prediction.
12. We have expanded the introduction and added a method overview (lines 49-67), referencing the sections of the paper.  We added a statement describing the key method in the abstract precisely (line 7-9). We have also added 8 more literature references. 
13. All abreviations (IEA, IRF) are explained when they are mentioned for the first time. 

For your convenience I attach the adapted PDF with markups of all changes.

 

 

 

Author Response File: Author Response.pdf

Reviewer 3 Report

I enjoyed reading the manuscript “Emissions and CO2 concentration – an evidence based approach”. The Authors describe important issues regarding emissions and CO2 concentration. The presented model is validated by an ex-post forecast of the last 20 years. This model is also compared with the Carbon modul of the Bern model. The results of the study suggest that for the most likely IEA emission scenario of approximately constant, slightly decreasing global emissions we can expect a maximum CO2 concentration level of approximately 475 ppm in the second half of this century.

The material is presented appropriately and clearly, the data contained in Tables and Figures as well as in Appendix represent understandable documentation of the research problem. The manuscript has interesting results and will make a useful contribution to Atmosphere. I believe that the manuscript will certainly receive wide readership. I do not propose any comments. In my opinion, the manuscript can be accepted for publication.

Author Response

Thank you for your most encouraging review.