the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 05 Jun 2025
Banked CFC-11 contributes to an unforeseen emission rise and sets back progress towards carbon neutrality
Abstract. An unexpected rise of trichlorofluoromethane (CFC-11) emissions has undermined the efforts behind the Montreal Protocol. However, the sources of these increased emissions, from CFC-11 banks to unreported production, remain contentious. Here, we enhanced the bottom-up dynamic material flow analysis model to characterize the stocks and flows of CFC-11, retrospectively and prospectively from 1950 to 2100. We find that dynamic changes in bank-related emissions could have led to an increased CFC-11 emissions from 2014 to 2018, implying an overestimation of unreported production. Long-term emission of banked CFC-11 will accumulate to accumulate to 1000 (700–1300) kilitons (Kt), equivalent to 4.6 (3.2–6.3) gigatons (Gt) CO2e, between 2025 and 2100. Scenario analysis highlights the potential to reduce up to 50 % of emissions through optimized end-of-life management strategies. Our results call for further investigation into the lifespan and EoL processes of products containing ozone-depleting substances (ODSs) to reconcile emission estimates derived from bottom-up and top-down modeling approaches. The modeling approach could also be applied to estimate and project the bank-related emissions and impacts of other ODSs.
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The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
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RC1: 'Comment on egusphere-2025-2277', Anonymous Referee #1, 09 Jul 2025
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AC1: 'Reply on RC1', Heping Liu, 13 Aug 2025
Response to reviewers for preprint egusphere-2025-2277:
Banked CFC-11 contributes to an unforeseen emission rise and sets back progress towards carbon neutrality
RC1 Comment #1
General comments: This manuscript presents a bottom-up dynamic material flow analysis (D-MFA) to quantify the historical and projected emissions of banked CFC-11, aiming to reconcile these with observed atmospheric increases, highlighting the role of bank emissions and end-of-life (EoL) handling. This is a timely and important contribution given the unexpected rise in CFC-11 emissions after 2014 despite the Montreal Protocol controls. The study is well-structured and employs a robust methodological framework with extensive parameterization and uncertainty analysis. However, several aspects require clarification, additional quantitative support, or broader discussion before it can be recommended for publication.
Reply: We sincerely appreciate your thorough review of our manuscript and your insightful scientific and technical comments. These valuable insights have been instrumental in significantly improving the quality of our work. Our team has carefully and systematically addressed each of your recommendations, with each comment meaningfully integrated into the revised manuscript. We are confident that, guided by your expert input, the refined version more effectively conveys the significance of our findings on CFC-11 bank emissions and their broader implications. We deeply appreciate the time and expertise you dedicated to reviewing our manuscript and hope that the revised version aligns with the journal’s high standards.
Comment #2
Specific comments:
L112-113: Equation (6) models manufacturing, use, and end-of-life (EoL) stages emissions. However, whether the model explicitly accounts for CFC-11 servicing or maintenance activities is unclear. Could the authors clarify whether this servicing phase was considered and how it was incorporated? If not, please discuss whether the omission might underestimate the lifetime size of the in-use stock and how significant this could be relative to the total bank. A brief quantitative or qualitative assessment would strengthen the manuscript.
Reply: Thank you for highlighting this important issue. We have carefully considered the use of CFC-11 as a refrigerant in servicing and maintenance activities. Our analysis assumes that CFC-11 released during the use stage can be replenished through refilling. Based on Equation (6) and the parameters detailed in Supplementary Information (SI) Table S7, we estimated that approximately 190 kt of CFC-11 was used as the initial refrigerant charge in non-hermetic refrigeration systems, with an additional 600 kt used as refill quantities during servicing and maintenance over the study period. China’s National Plan for the Phase-out of Ozone-Depleting Substances (1993) reports a ratio of approximately 1:3 between initial fills for new products and refills (China MEE, 1993). These consistencies support the validity of our calculations.
CFC-11 usage in non-hermetic refrigeration systems accounts for a relatively small proportion (approximately 8%) of total CFC-11 consumption (AFEAS, 2003). Study conducted by the Technology and Economic Assessment Panel (TEAP) indicates that emissions from refrigeration systems do not make a significant contribute to overall CFC-11 emissions (TEAP, 2019). For these reasons, we did not assess its uncertainties to the same extent as those of foam sectors.
Following your suggestion to enhance the quantitative rigor of our findings, we have included the following text in SI, lines 506-510:
“It is assumed that the release of CFC-11 during the use stage can be refilled. Using this methodology, we estimated that approximately 190 kt of CFC-11 was used as the initial refrigerant charge in non-hermetic refrigeration systems, with an additional 600 kt applied as refill quantities during the usage stage for servicing and maintenance. These estimates align with previous records (AFEAS, 2003; China MEE, 1993).”
Comment #3
L145: The uniform 3% release rate may overlook differences between A5 and non-A5 parties, given historically higher fugitive emissions in developing countries. I would recommend either: (1) implementing region-specific r-values that reflect the technological disparities between A5 and non-A5 countries, or (2) providing robust justification for the uniform rate along with a comprehensive uncertainty analysis regarding this parameter.
Reply: Thank you for your attention to this detail. The 3% release rate applied to the production stage is based on two key considerations. First, CFC-11 production and consumption were predominantly concentrated in non-A5 countries. According to the TEAP, these regions accounted for 94% of global CFC-11 production (TEAP, 2021). Secondly, TEAP’s multi-scenario analyses demonstrate that the selection of this release rate has a negligible impact on total emissions (TEAP, 2019; 2021). Their model evaluated a wide range of production emission rates, from 0.5% to 5%, and even higher values, yet found that variations within this range do not significantly alter the overall emissions profile. For these reasons, we opted not to complicate the release rate setting and instead prioritized refining understudied aspects of previous bottom-up models, such as lifespan parameters and other critical variables.
As suggested, to further justify the use of a uniform rate, we have incorporated the following text in lines 154–155 of the revised main text:
“TEAP's multi-scenario assessments indicate that production-stage release rates have minimal overall impact on total emissions (TEAP, 2019; 2021). Therefore, in this study …”
Comment #4 and Comment #6
L188：Why does the study assume only two discrete EoL emission scenarios of 20% or 100%? What is the rationale or literature basis for these specific choices? It is recommended to consider a more nuanced range of fractions (e.g., 60%, 80%) or perform a more continuous sensitivity analysis to capture the spectrum of plausible emission pathways better.
L247: The authors mention that inadequate waste management systems may accelerate CFC-11 emissions (which is also mentioned in L328-329), yet the model does not appear to incorporate regionally differentiated EoL emission rates. Were regional differences (e.g., higher recovery/incineration rates in developed countries vs. more landfilling in developing countries) considered? If not, might the use of a globally uniform EoL emission fraction underestimate actual emissions in areas lacking effective collection and destruction systems, thereby affecting the regional attribution of emissions? If region-specific assumptions are not yet implemented, I would suggest discussing this as a limitation, along with the potential implications for the results and how future work could incorporate differentiated EoL management levels to improve realism and policy relevance.
Reply: Thank you for your constructive feedback. As these comments (#4 and #6) pertain to end-of-life (EoL) emission rates, we have consolidated our responses below to provide a comprehensive and coherent explanation.
The selection of 20% and 100% as the lower and upper bounds for EoL emission parameters in our uncertainty analysis is based on existing literature. The upper bound of 100% represents the maximum plausible emissions from retired foam products within unmanaged waste streams—a scenario that has been widely adopted in previous studies (McCulloch et al., 2001; Duan et al., 2018). Conversely, the lower bound of 20% reflects conservative estimates for controlled waste management systems, as assumed in the TEAP’s global assessment of CFC-11 emissions from foam products (TEAP, 2021). These bounds were deliberately chosen to encompass a broad range of potential outcomes while ensuring consistency with established scientific references.
While discrete intermediate values (e.g., 60%, 80%) were not explicitly modeled as standalone scenarios, our regional and global calculations implicitly incorporate intermediate emission levels by integrating diverse regional datasets (detailed in SI Tables S8–S13). Specifically, we applied region-specific emission factors. For example, in the United States, sector-specific factors range from 35% (appliance insulation foams) to 100% (spray insulation foams; Table S8), derived from the U.S. Environmental Protection Agency (EPA) 2024 Greenhouse Gas Inventory Annual Report (U.S.EPA, 2024). Similarly, in Japan, emission factors range from 10% (panel insulation foams) to 100% (appliance insulation foams; Table S10), based on the annual report from the Japan Ministry of Economy, Trade and Industry (Japan METI, 2024). Comparable regional variations in EoL emission rates were applied to other regions, based on a synthesis of literature review, field surveys, and assumptions (Duan et al., 2018; Gómez-Sanabria et al., 2022). Global estimates were derived from weighted averages of regional values, thereby naturally incorporating intermediate emission levels (Table S13). The variation of this factor is quite significant, making it challenging to define a specific value distribution.
Comment #5
L227-L231: When comparing the consistency of this study’s results with other published estimates, it would strengthen the discussion to quantify these comparisons (e.g., percentage differences or correlation metrics), rather than only describing them qualitatively. This would more clearly illustrate the degree of agreement or discrepancy.
Reply: Thank you for this valuable suggestion. In the revised manuscript, we have incorporated the following quantitative comparison in lines 268–274 of the main text:
“Using top-down approaches, Park et al. (2021) estimated a 7 ± 4 kt/yr increase in emissions from eastern China during 2014–2017 compared to 2008–2012. Our national-scale bottom-up modelling aligns the upward trend reported by Park et al. (2021), albeit with a slightly smaller magnitude. Yi et al. (2021) reported a national trend that climbed from 8.3 ± 1.6 kt/yr in 2009 to a peak of 13.9 ± 2.4 kt/yr in 2017, followed by a decline to 10.9 ± 1.7 kt/yr in 2019. Our independent estimates of 7 (4–14), 11 (5–14), and 10 (4–13) kt/yr for the corresponding years are broadly consistent with these findings when considering overlapping uncertainties.”
Comment #7
L320: As can be seen from Fig. S14a, the results for 2010 differ significantly from those of METI. The differences between the two results could be described quantitatively, with additional explanations. Furthermore, the results before 2010 vary considerably from those of METI. What is the reason for this?
Reply: Many thanks for highlighting this point. The discrepancies observed between our results and those reported by Japan METI prior to 2010 are primarily attributable to significant methodological changes in the calculation of foam sector emissions. From 2000 to 2012, METI estimated fluorocarbon emissions from closed-cell foam in construction based on a 30-year average lifespan and a 3.3% annual release rate. Before 2010, emissions were calculated by applying the 3.3% release rate to the remaining CFC-11 bank in installed foams, which was adjusted yearly by subtracting a 3.3% loss. Starting in 2010, METI instead applied the 3.3% rate to the total cumulative initial charge, not the adjusted bank. This change increased the calculation base and led to a notable rise in reported emissions.
Starting in 2013, METI updated its methodology to align with the 2006 Intergovernmental Panel on Climate Change (IPCC) Guidelines. These guidelines incorporate product-specific parameters, including distinct annual emission factors for various foam applications (e.g., spray foam, panels, and laminated boards). This methodological update explains the smoother emission trajectories observed from 2013 onwards compared to earlier periods.
As suggested, to further clarify the differences between our results and METI’s, we have added the following note in the revised SI (lines 596–602):
“Japan METI revised its emission calculation methodology over time. Prior to 2010, CFC-11 emissions from closed-cell foam in the construction industry were calculated by applying a 3.3% annual release factor to the bank of CFC-11 in installed foams, which was adjusted yearly by subtracting a 3.3% loss. Beginning in 2010, the calculation base shifted to the cumulative initial charge, resulting in a marked increase in reported emissions. Starting in 2013, METI adopted the 2006 IPCC Guidelines, which use product-specific emission factors, leading to smoother and more consistent emission trajectories after 2013.”
Comment #8
L350-351: In the results for Scenario S1 (with no unreported production), the cumulative emissions still reach approximately 4.2 Gt CO2e over 2025–2100. This suggests that legacy banks alone could substantially impact atmospheric CFC-11 levels even without ongoing illegal production. Could the authors comment on what this implies regarding the timing of ozone layer recovery? Although this study focuses on climate metrics (CO2e), it would be valuable to briefly discuss (at least qualitatively) how such sustained emissions from historical banks might delay the return of stratospheric ozone. This could help place the findings in the broader context of both climate and ozone protection goals.
Reply: Many thanks for pointing this out. Using the method described in Lickley et al. (2020), we estimated the potential delay in stratospheric ozone recovery caused by sustained emissions from historical banks. Our analysis projects that under Scenario 1 (S1), polar equivalent effective stratospheric chlorine (EESC) would returns to its 1980 level around the year 2086.
As suggested, we have added the following information in lines 399–403 of the main text:
“Using the method outlined in Lickley et al. (2020), polar equivalent effective stratospheric chlorine (EESC) under S1 is projected to return to pre-1980 levels around 2086. This projection is slightly earlier than WMO’s estimate of 2087 (WMO, 2022). This discrepancy primarily arises from higher CFC-11 concentrations in WMO assessment, attributed to their larger bank and emission estimates derived using the Lickley approach (Lickley et al., 2022; WMO, 2022).”
Comment #9
L451: The authors state that their findings “may also be applicable to other ODS and HFCs.” However, this generalization is not entirely accurate given the scope of the present study. This work emphasizes explicitly banked emissions from closed-cell foams, whereas most HFCs are used in direct refrigeration and air conditioning systems, which are very different. I would suggest that the authors explicitly qualify this statement in the conclusions to clarify the boundaries of applicability.
Reply: Thank you so much for your insightful comments. Given the discrepancies between atmospheric top-down modeling and bottom-up estimates derived from production and consumption data for some ozone-depleting substances (ODSs) and hydrofluorocarbons (HFCs), we propose that our bottom-up approach—which systematically incorporates uncertainties from underexplored factors—can be applied to the estimation of emissions of other ODSs and HFCs.
We have revised the relevant statement in the conclusion, lines 469-471 of the main text:
“While this study primarily focuses on CFC-11 emissions, the methodology developed here, which explicitly accounts for uncertainties from underexplored sources, may be broadly applicable to emission estimates of other ODS and hydrofluorocarbon.”
Comment #10
Technical corrections:
L111:In some formulas, there seems to be an extra space between symbols, such as Eq.6. Please check the whole text.
Reply: Thank you very much for your meticulous observation and valuable suggestion. We fully agree with your comment and sincerely appreciate your attention to technical details. We have thoroughly reviewed the entire text to correct any extraneous spaces between symbols and ensure consistency and accuracy in the presentation of all equations.
Comment #11
L172: The manuscript uses hyphens (-) extensively to indicate numeric ranges (e.g., “3-8 Kt/yr”), which should be replaced with standard en dashes (–) to conform to scientific publishing conventions. Please check the whole text.
Reply: We have replaced the hyphens (-) with standard en dashes (–). A thorough review of the entire manuscript has been conducted to implement the necessary revisions, ensuring consistency in this formatting aspect.
Comment #12
L173: S3 lacks the statement “Scenario 3.”
Reply: Scenario 3 has been added to the revised main text, line 215.
Comment #13
L357: The panel (b) label is missing in Fig. 3b.
Reply: Fig.3 has been revised, and the label for panel (b) has been added.
Comment #14
L480: O’doherty shoud be O’Doherty. Please check the references for additional details.
Reply: The name “O’doherty” has been consistently corrected to “O’Doherty” throughout the manuscript.
Reference
China Ministry of Ecology and Environment (China MEE). China’s National Plan for the Phase-601 out ozone-depleting substances, 1993. (In Chinese).
Alternative Fluorocarbons Environmental Acceptability Study (AFEAS). Production and atmospheric release data through 2003.
Technology and Economic Assessment Panel (TEAP), Report of the Technology and Economic Assessment Panel, September 2019, Volume 1: Decision XXX/3 TEAP Task Force Report on Unexpected Emissions of CFC-11, Final Report (2019).
Technology and Economic Assessment Panel (TEAP), volume 3: decision XXXI/3 TEAP Task Force Report on Unexpected Emissions of Trichlorofluoromethane (CFC-11, 2021).
McCulloch, A., P. Ashford, and P. M. Midgley. Historic emissions of fluorotrichloromethane (CFC-11) based on a market survey. Atmos. Environ. 35 (26): 4387-4397 (2001).
Duan, H., Miller, T.R., Liu, G., Zeng, X., Yu, K., Huang, Q., Zuo, J., Qin, Y., and Li, J.: Chilling prospect: climate change effects of mismanaged refrigerants in China, Environ. Sci. Technol., 52, 6350–6356, https://doi.org/10.1021/acs.est.7b05987, 2018.
United States Environmental Protection Agency (U.S.EPA). Inventory of Greenhouse Gas Emissions and Sinks: 1990-2022. https://www.epa.gov/ghgemissions/inventory-us-1376 greenhouse-gas-emissions-and-sinks-1990-2022 (accessed on August 11, 2024).
Japan Ministry of Economy, Trade and Industry (Japan METI). Documents pertaining to methods for estimating discharge, https://www.meti.go.jp/policy/chemical_management/law/prtr/6.html (in Japanese, accessed on August 30, 2024).
Gómez-Sanabria, A. et al. Potential for future reductions of global GHG and air pollutants from circular waste management systems. Nat. Commun. 13(1), 1-12 (2022).
Intergovernmental Panel on Climate Change (IPCC). IPCC Guidelines for National Greenhouse Gas Inventories, vol. 3. Industrial Process and Product Use (IPCC, 2006).
Lickley, M., Solomon, S. Fletcher, G.J.M. Velders, J. Daniel, M. Rigby, S.A. Montzka, L.J.M. Kuijpers, and K. Stone, Quantifying contributions of chlorofluorocarbon banks to emissions and impacts on the ozone layer and climate, Nat. Comm., 11(1), 1380, doi:10.1038/s41467-020-15162-7, 2020.
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AC1: 'Reply on RC1', Heping Liu, 13 Aug 2025
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RC2: 'Comment on egusphere-2025-2277', Anonymous Referee #2, 15 Jul 2025
General Comments
This study presents an updated bottom-up inventory of CFC-11 emissions globally, in an effort to better understand the cause of the well-documented, ‘unexpected’ rise in global emissions in the period 2014-2018. It employs a dynamic material flow analysis model to estimate aggregated emissions from the entire lifespan of CFC-11 containing products, such as closed-cell foams and refrigeration systems, as well as direct emissions from other uses. The authors estimate emissions that are broadly in line with previous work, although discrepancies are found in some places. This is attributed to a more thorough consideration of the different stages in the lifecycle of CFC-11 products. They also conclude that some of the unexpected increase between 2014 and 2018 could be attributed to increased emissions from existing banks, although unreported production also plays a role.
The model that the authors have developed is sound, and the application of Weibull survival functions to estimating global banks and emissions of CFC-11 is a sensible approach. However, I see a number of issues with this manuscript.
- Firstly, the method requires more rigorous analysis of uncertainties, and many of the parameters used to estimate emissions are not justified sufficiently.
- In addition, it is not clear to me, based on the evidence presented, how the authors justify their primary conclusion, that the global emissions rise seen between 2014 and 2018 can be attributed in part to emissions from banks.
- Finally, the results and discussion section is poorly structured and confusing. This makes it hard to determine the validity and significance of the authors’ conclusions.
Given these major concerns, I don’t think the current version warrants publication in ACP. However, if the authors can fully address the above issues, a revised version may be publishable, subject to further review.
Specific comments
L95: The description of the Weibull distribution does not make clear the significance of the shape and scale parameters. Details about what values are chosen are given in the supplementary information, but these are not cited or justified anywhere. In addition, it isn’t clear the role of ‘y’ in this function. Are the shape and scale parameters functions of the year? If they are, this should be explained clearly, and if not, then f isn’t a function of ‘y’ at all.
L145: No justification is given for the choice of values for the release rate from production, nor why the illegal and legal production are different.
L157: None of the data used to drive the model is presented in the main text. A summary of sources or perhaps a visualisation could be helpful.
L168: Claiming that unreported production is the ‘most likely’ scenario seems inappropriate, since the abstract claims that at least some of the increase is due to bank emissions. While there is a need for an intermediate scenario, there seems to be no justification for choosing 25 kt/yr as a value for the unreported production of CFC-11. Indeed, later on the authors go on to say that it is the highest emissions scenario (S3) that aligns with previous work.
L185: The ‘distributions’ referred to can only be found in the SI, and it is not clear how they are varied. What sort of sampling is done? A more sophisticated approach for sampling across parameter distributions, such as a Monte Carlo method, might be appropriate here.
L187: Why is 20% chosen? Could a range of values or a distribution be sampled instead? The same goes for 90% and 110% in L190
L191: I don’t follow what has been done here. Does it mean that the parameters are simply set to the values in Table S14? Are these global averages?
L213: This paragraph (L213-220) feels like it should be in the Methods section. The ‘temporal and spatial trajectories’ are clearly important to the results, as they lead to the divergence from other bottom-up inventories. It would be good to see these discussed or tabulated in the Methods section.
L231: Again, the discussion of the likely sources of unreported emissions feels out of place here. It might be better placed in the discussion, or in the section where the authors model potential scenarios of unreported production.
L242-L262: I find this section slightly confusing. The term ‘decommissioned’ CFC-11 has not been explained in the introduction or methods section, and is only mentioned in reference to figure 1c. Showing both banks and emissions on the same figures (1c and 1d) make them hard to interpret, and it is not clear which lines/shaded areas should be read off the left and right axes. The orange arrow is not explained, either.
L253: ‘If all decommissioned CFC-11 were released into the atmosphere, our global bottom-up CFC-11 emissions would align with top-down estimates (Montzka et al. 2018; 2021)’. It is unclear what time period this refers to, but if it refers to 2014-2018 then this appears to be the primary conclusion of this paper. However, it is not given any further development in this section nor in any of the figures.
L302: The text says that the new estimates are comparable with the McCulloch, Derwent and Manning estimates within the margin of uncertainty. However, figure 2 suggests that this is only true for a small number of years. The McCulloch estimates fall within the uncertainties of the present study for only one or two years between 1986 and 1996, the Derwent estimates for only two or three of those ten years, and the Manning estimates don’t appear to overlap at all with the present study. This is in contrast to the China estimates in figure 1b, where the authors describe the estimates as ‘significantly differing’ from the current work despite greater overlap with the plotted confidence intervals.
L333: ‘banked CFC-11 can probably result in an unexpected increase in emissions in 2014-18’. What does ‘probably’ mean in this case? As mentioned above, this has not been developed and I’m not convinced that it is a valid conclusion, especially given the trend shown in figure 1a. That figure shows emissions on a steady downward trend from 1995 onwards, with no suggestion of an increase after 2014 globally.
L342: It appears that limited assessment is done of how well each scenario would account for the unexpected emissions, in combination with varying the parameters of the main model. This seems to me to be a crucial element of the analysis that is missing.
L360: How are the mole fractions calculated? There is no mention of any atmospheric modelling in the manuscript.
L376: There are a lot of issues with this figure. The overlapping uncertainty intervals make subfigure (a) unreadable. Subfigures (b) and (c) are identical – the only difference being a simple rescaling of the y-axis, and the same goes for (e) and (f). There is no discussion of how the 99% confidence interval is calculated, either.
L398: It is not clear what is being varied in some cases. In the 20%/100% EoL case and 1.1/0.9x CCF cases, this is clear – but are the other parameters being simultaneously varied? If not, how are a mean, minimum and maximum calculated? For the shape/scale parameters, are all the different parameters (for different products and regions) varied simultaneously? As mentioned above, this seems like a case in which a Monte Carlo method would be suitable. The nine graphs in figure 4 are not a clear way of explaining the impact of each of the parameters, as they are all very similar in shape and the subtle differences are hard to spot. The right hand side of the figure is a more intuitive way of understanding the impact of varying these parameters. As with previous figures, the meaning of the 99% confidence interval is not clear, either.
L434: The final two paragraphs of the conclusion do not add much to the manuscript. They are a generic restatement of the introduction, with very little development.
Technical Corrections
L25: ‘accumulate to’ is repeated.
L25 and throughout: the abbreviation for ‘kilotonnes’ is kt, not Kt.
L28: ‘EoL’ is not yet defined
L44: over what period have emissions increased in other regions?
L59 : ‘this analysis’, not ‘these analysis’.
L181: Should read ‘sensitivity analysis’
L375: In addition to the issues with this figure mentioned above, there is no label for subfigure (b) and the y-axis label on subfigures (c) and (f) should be emissions. The GWP of CFC-11 does not vary with time, and does not have units of GtCO2eq.
Citation: https://doi.org/10.5194/egusphere-2025-2277-RC2 -
AC2: 'Reply on RC2', Heping Liu, 13 Aug 2025
We sincerely grateful your detailed and constructive feedback on our manuscript. Your time and effort in providing such valuable insights are greatly appreciated. Since our response includes formulas and revised figures, we would like to upload it as a *.pdf file.
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EC1: 'Reviewer comment on egusphere-2025-2277', Tanja Schuck, 28 Jul 2025
Posted on behalf of the 3rd reviewer by handling editor Tanja Schuck:
This is an analysis of CFC-11 emissions on global and regional scales through recent years when measured atmospheric changes suggested global emissions increased and subsequently decreased. These changes were described in previous papers as having been associated primarily with increased production (and emission) in part in and from China. With a dynamic material flow model to estimate emissions to the atmosphere from the relevant processes, the authors study the sensitivity of calculated emissions from a range of different parameters in an overall useful analysis. They suggest that some increase in emissions might be expected during recent years based on how materials containing CFC-11 were handled during decommissioning and “end-of-life”. This suggestion isn’t particularly novel, as it was explored to some extent in those initial 4 papers from 2018-2021, was mentioned in Chapter 7 of the 2005 IPCC/TEAP special report (led by P. Ashford et al., although the expected increases were anticipated to be slow and to occur in future years), and is worth repeating, as is the importance of management of these chemicals during decommissioning for minimizing future emissions and their adverse impacts. However, a number of other aspects of the work prevent me from suggesting that it is publishable in its current form, see below.
The abstract is overly general and vague on the main point emphasized there: “bank related emissions could have led to an increased CFC-11 emissions from 2014 to 2018”. Figures in the paper actually show global totals declining through this period, and regional emissions from multiple regions that are also decreasing or essentially unchanged if one considers the uncertainties associated with the analysis. Ignoring the range of uncertainties and focusing on only their mid-range estimates, the results can be used to suggest that bank-related emissions increased from only China during this period, but this raises important questions: 1) why is the potential emission increase in China quite different from the decreases derived for the other regions? 2) What are the specific region-based factors/assumptions that cause this uniqueness for China in the model, and what is the supporting information that backs up these choices? Is the uniqueness of China related to the timing and fraction of CFC-11 in different sub-sectors or perhaps of assumptions on lifespan of foam product applications (Table S3)? Many input parameters are provided in tables, but no clarity on the specific ones that make China unique with respect to the time evolution of CFC-11 bank emissions is discussed. 2) Should an increase in Chinese bank-related emissions actually have occurred, the global decreasing trend would imply that the increases in China were offset by unexpectedly rapid decreases in other areas. Is this reasonable?
The main message of the abstract is written so that it is easy for the reader to be misled into thinking that perhaps CFC-11 production didn’t increase. This is inconsistent with the main text of the paper, discussions of scenarios, and the mismatch on a global scale between expected and atmosphere-derived emission in Figure 1a that would seem to require post-2010 production as an explanation.
Some points are also difficult to reconcile: inventory-based model-derived emissions are argued to be consistent with atmosphere-based results in the US, Europe, and China, yet the authors argue that there was substantial unreported production. Are we to conclude that it must have occurred outside these regions despite the contrary evidence provided elsewhere?
On the regional analyses.
Any revision should be sure to reflect on the uncertainties associated with the assumptions required to perform the analysis in the main text and be more circumspect about the conclusions. For example, China’s emissions are said to have increased from 8 (4-13) kt/yr during 2008-12 to 11 (5-13) kt/yr during 2014-18, but given these large uncertainties justifying a conclusion that emissions actually increased is problematic. Discussion of the very small increases reported by Redington et al. are mentioned without consideration of their uncertainties and that they are very small. Did atmosphere-based emissions from these regions actually increase above detectability? The manuscript doesn’t indicate that Dunse et al and Manning et al. actually suggested emissions increases through this period, although a reading of lines 43-46 would suggest otherwise. This very slight change in the Redington et al. study is very different from the much larger increase that the inventory model derives for Europe, in apparent contradiction to the wording and assertion on lines 313-314.
These points are central with respect to the stated purposes of this study, which is related to assertions that previous analyses “did not adequately consider the variabilities in lifespans of foam products and their EoL management” and that “surveys reveal significant temporal and spatial variability in the actual lifespans of buildings”. Many of the more recent inventory-based studies did provide an analysis of a range of parameter values. Providing more clarity on how the new model adds clarity and understanding to the situation is needed but currently lacking.
Details:
Further, the juxtaposition in Figure 1b of top-down and bottom-up estimates for “China” may not be appropriate, given that I believe some (or all) of the top-down estimates represent emissions from only portions of China, whereas I’m guessing the bottom-up estimates are for all of China.
Following up on the comment related to the abstract: the authors don’t address in the main text why the relative increase suggested in decommission- or EOL-related emissions for China, the US and the EU are so different. Were different parameters used for these different regions based on the unsupported suggestion that they depend on “cultural, economic, and political factors”? Why is different language used to describe the processes for these different regions? More clarity is needed here as to the cause for these differences.
With respect to the scenarios, some values for emission and unreported production are provided, with uncertainties, but no indication of how those numbers were arrived at and what constraints were used to allow those values to be estimated. Again, further clarity is needed here.
Lines 240-241, what is the evidence for this assertion and what do “(b)” and “(a)” refer to?
Lines 253-255, “if all decommissioned…” that’s a striking assertion without any clear demonstration and the time dependence of resulting emissions (and how they might compare to atmosphere-based if this were true) is not mentioned.
Lines 277-279, why would errors related to emissions estimated in one application (CFC-12 in AC and refrig) apply to CFC-11 whose emissions are from different processes? Gallagher estimates for CFC-11 look reasonably accurate.
Consider projecting the results in panels a-h of Figure 4 out to 2030, as the differences between the bottom-up approaches and assumption should become even larger through this period, and could enable an assessment of their reliability with the atmosphere-based results as they are updated.
IPCC/TEAP study reference mentioned above: Ashford, P. et al. in Safeguarding the Ozone Layer and the Global Climate System: Issues Related to Hydrofluorocarbons and Perfluorocarbons (eds Metz, B. et al.) Ch. 7 (Cambridge Univ. Press, Cambridge, 2005).). How do you results compare to this (while this could be referred to in the abstract, it perhaps is more a topic of discussion for the main text)?Citation: https://doi.org/10.5194/egusphere-2025-2277-EC1 - AC3: 'Reply on EC1', Heping Liu, 13 Aug 2025
Interactive discussion
Status: closed
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RC1: 'Comment on egusphere-2025-2277', Anonymous Referee #1, 09 Jul 2025
General comments:
This manuscript presents a bottom-up dynamic material flow analysis (D-MFA) to quantify the historical and projected emissions of banked CFC-11, aiming to reconcile these with observed atmospheric increases, highlighting the role of bank emissions and end-of-life (EoL) handling. This is a timely and important contribution given the unexpected rise in CFC-11 emissions after 2014 despite the Montreal Protocol controls. The study is well-structured and employs a robust methodological framework with extensive parameterization and uncertainty analysis. However, several aspects require clarification, additional quantitative support, or broader discussion before it can be recommended for publication.
Specific comments:
L112-113: Equation (6) models manufacturing, use, and end-of-life (EoL) stages emissions. However, whether the model explicitly accounts for CFC-11 servicing or maintenance activities is unclear. Could the authors clarify whether this servicing phase was considered and how it was incorporated? If not, please discuss whether the omission might underestimate the lifetime size of the in-use stock and how significant this could be relative to the total bank. A brief quantitative or qualitative assessment would strengthen the manuscript.
L145: The uniform 3% release rate may overlook differences between A5 and non-A5 parties, given historically higher fugitive emissions in developing countries. I would recommend either: (1) implementing region-specific r-values that reflect the technological disparities between A5 and non-A5 countries, or (2) providing robust justification for the uniform rate along with a comprehensive uncertainty analysis regarding this parameter.
L188：Why does the study assume only two discrete EoL emission scenarios of 20% or 100%? What is the rationale or literature basis for these specific choices? It is recommended to consider a more nuanced range of fractions (e.g., 60%, 80%) or perform a more continuous sensitivity analysis to capture the spectrum of plausible emission pathways better.
L227-L231: When comparing the consistency of this study’s results with other published estimates, it would strengthen the discussion to quantify these comparisons (e.g., percentage differences or correlation metrics), rather than only describing them qualitatively. This would more clearly illustrate the degree of agreement or discrepancy.
L247: The authors mention that inadequate waste management systems may accelerate CFC-11 emissions (which is also mentioned in L328-329), yet the model does not appear to incorporate regionally differentiated EoL emission rates. Were regional differences (e.g., higher recovery/incineration rates in developed countries vs. more landfilling in developing countries) considered? If not, might the use of a globally uniform EoL emission fraction underestimate actual emissions in areas lacking effective collection and destruction systems, thereby affecting the regional attribution of emissions? If region-specific assumptions are not yet implemented, I would suggest discussing this as a limitation, along with the potential implications for the results and how future work could incorporate differentiated EoL management levels to improve realism and policy relevance.
L320: As can be seen from Fig. S14a, the results for 2010 differ significantly from those of METI. The differences between the two results could be described quantitatively, with additional explanations. Furthermore, the results before 2010 vary considerably from those of METI. What is the reason for this?
L350-351: In the results for Scenario S1 (with no unreported production), the cumulative emissions still reach approximately 4.2 Gt CO2e over 2025–2100. This suggests that legacy banks alone could substantially impact atmospheric CFC-11 levels even without ongoing illegal production. Could the authors comment on what this implies regarding the timing of ozone layer recovery? Although this study focuses on climate metrics (CO2e), it would be valuable to briefly discuss (at least qualitatively) how such sustained emissions from historical banks might delay the return of stratospheric ozone. This could help place the findings in the broader context of both climate and ozone protection goals.
L451: The authors state that their findings “may also be applicable to other ODS and HFCs.” However, this generalization is not entirely accurate given the scope of the present study. This work emphasizes explicitly banked emissions from closed-cell foams, whereas most HFCs are used in direct refrigeration and air conditioning systems, which are very different. I would suggest that the authors explicitly qualify this statement in the conclusions to clarify the boundaries of applicability.
Technical corrections:
L111:In some formulas, there seems to be an extra space between symbols, such as Eq.6. Please check the whole text.
L172: The manuscript uses hyphens (-) extensively to indicate numeric ranges (e.g., “3-8 Kt/yr”), which should be replaced with standard en dashes (–) to conform to scientific publishing conventions. Please check the whole text.
L173: S3 lacks the statement “Scenario 3.”
L357: The panel (b) label is missing in Fig. 3b.
L480: O’doherty shoud be O’Doherty. Please check the references for additional details.
Citation: https://doi.org/10.5194/egusphere-2025-2277-RC1 -
AC1: 'Reply on RC1', Heping Liu, 13 Aug 2025
Response to reviewers for preprint egusphere-2025-2277:
Banked CFC-11 contributes to an unforeseen emission rise and sets back progress towards carbon neutrality
RC1 Comment #1
General comments: This manuscript presents a bottom-up dynamic material flow analysis (D-MFA) to quantify the historical and projected emissions of banked CFC-11, aiming to reconcile these with observed atmospheric increases, highlighting the role of bank emissions and end-of-life (EoL) handling. This is a timely and important contribution given the unexpected rise in CFC-11 emissions after 2014 despite the Montreal Protocol controls. The study is well-structured and employs a robust methodological framework with extensive parameterization and uncertainty analysis. However, several aspects require clarification, additional quantitative support, or broader discussion before it can be recommended for publication.
Reply: We sincerely appreciate your thorough review of our manuscript and your insightful scientific and technical comments. These valuable insights have been instrumental in significantly improving the quality of our work. Our team has carefully and systematically addressed each of your recommendations, with each comment meaningfully integrated into the revised manuscript. We are confident that, guided by your expert input, the refined version more effectively conveys the significance of our findings on CFC-11 bank emissions and their broader implications. We deeply appreciate the time and expertise you dedicated to reviewing our manuscript and hope that the revised version aligns with the journal’s high standards.
Comment #2
Specific comments:
L112-113: Equation (6) models manufacturing, use, and end-of-life (EoL) stages emissions. However, whether the model explicitly accounts for CFC-11 servicing or maintenance activities is unclear. Could the authors clarify whether this servicing phase was considered and how it was incorporated? If not, please discuss whether the omission might underestimate the lifetime size of the in-use stock and how significant this could be relative to the total bank. A brief quantitative or qualitative assessment would strengthen the manuscript.
Reply: Thank you for highlighting this important issue. We have carefully considered the use of CFC-11 as a refrigerant in servicing and maintenance activities. Our analysis assumes that CFC-11 released during the use stage can be replenished through refilling. Based on Equation (6) and the parameters detailed in Supplementary Information (SI) Table S7, we estimated that approximately 190 kt of CFC-11 was used as the initial refrigerant charge in non-hermetic refrigeration systems, with an additional 600 kt used as refill quantities during servicing and maintenance over the study period. China’s National Plan for the Phase-out of Ozone-Depleting Substances (1993) reports a ratio of approximately 1:3 between initial fills for new products and refills (China MEE, 1993). These consistencies support the validity of our calculations.
CFC-11 usage in non-hermetic refrigeration systems accounts for a relatively small proportion (approximately 8%) of total CFC-11 consumption (AFEAS, 2003). Study conducted by the Technology and Economic Assessment Panel (TEAP) indicates that emissions from refrigeration systems do not make a significant contribute to overall CFC-11 emissions (TEAP, 2019). For these reasons, we did not assess its uncertainties to the same extent as those of foam sectors.
Following your suggestion to enhance the quantitative rigor of our findings, we have included the following text in SI, lines 506-510:
“It is assumed that the release of CFC-11 during the use stage can be refilled. Using this methodology, we estimated that approximately 190 kt of CFC-11 was used as the initial refrigerant charge in non-hermetic refrigeration systems, with an additional 600 kt applied as refill quantities during the usage stage for servicing and maintenance. These estimates align with previous records (AFEAS, 2003; China MEE, 1993).”
Comment #3
L145: The uniform 3% release rate may overlook differences between A5 and non-A5 parties, given historically higher fugitive emissions in developing countries. I would recommend either: (1) implementing region-specific r-values that reflect the technological disparities between A5 and non-A5 countries, or (2) providing robust justification for the uniform rate along with a comprehensive uncertainty analysis regarding this parameter.
Reply: Thank you for your attention to this detail. The 3% release rate applied to the production stage is based on two key considerations. First, CFC-11 production and consumption were predominantly concentrated in non-A5 countries. According to the TEAP, these regions accounted for 94% of global CFC-11 production (TEAP, 2021). Secondly, TEAP’s multi-scenario analyses demonstrate that the selection of this release rate has a negligible impact on total emissions (TEAP, 2019; 2021). Their model evaluated a wide range of production emission rates, from 0.5% to 5%, and even higher values, yet found that variations within this range do not significantly alter the overall emissions profile. For these reasons, we opted not to complicate the release rate setting and instead prioritized refining understudied aspects of previous bottom-up models, such as lifespan parameters and other critical variables.
As suggested, to further justify the use of a uniform rate, we have incorporated the following text in lines 154–155 of the revised main text:
“TEAP's multi-scenario assessments indicate that production-stage release rates have minimal overall impact on total emissions (TEAP, 2019; 2021). Therefore, in this study …”
Comment #4 and Comment #6
L188：Why does the study assume only two discrete EoL emission scenarios of 20% or 100%? What is the rationale or literature basis for these specific choices? It is recommended to consider a more nuanced range of fractions (e.g., 60%, 80%) or perform a more continuous sensitivity analysis to capture the spectrum of plausible emission pathways better.
L247: The authors mention that inadequate waste management systems may accelerate CFC-11 emissions (which is also mentioned in L328-329), yet the model does not appear to incorporate regionally differentiated EoL emission rates. Were regional differences (e.g., higher recovery/incineration rates in developed countries vs. more landfilling in developing countries) considered? If not, might the use of a globally uniform EoL emission fraction underestimate actual emissions in areas lacking effective collection and destruction systems, thereby affecting the regional attribution of emissions? If region-specific assumptions are not yet implemented, I would suggest discussing this as a limitation, along with the potential implications for the results and how future work could incorporate differentiated EoL management levels to improve realism and policy relevance.
Reply: Thank you for your constructive feedback. As these comments (#4 and #6) pertain to end-of-life (EoL) emission rates, we have consolidated our responses below to provide a comprehensive and coherent explanation.
The selection of 20% and 100% as the lower and upper bounds for EoL emission parameters in our uncertainty analysis is based on existing literature. The upper bound of 100% represents the maximum plausible emissions from retired foam products within unmanaged waste streams—a scenario that has been widely adopted in previous studies (McCulloch et al., 2001; Duan et al., 2018). Conversely, the lower bound of 20% reflects conservative estimates for controlled waste management systems, as assumed in the TEAP’s global assessment of CFC-11 emissions from foam products (TEAP, 2021). These bounds were deliberately chosen to encompass a broad range of potential outcomes while ensuring consistency with established scientific references.
While discrete intermediate values (e.g., 60%, 80%) were not explicitly modeled as standalone scenarios, our regional and global calculations implicitly incorporate intermediate emission levels by integrating diverse regional datasets (detailed in SI Tables S8–S13). Specifically, we applied region-specific emission factors. For example, in the United States, sector-specific factors range from 35% (appliance insulation foams) to 100% (spray insulation foams; Table S8), derived from the U.S. Environmental Protection Agency (EPA) 2024 Greenhouse Gas Inventory Annual Report (U.S.EPA, 2024). Similarly, in Japan, emission factors range from 10% (panel insulation foams) to 100% (appliance insulation foams; Table S10), based on the annual report from the Japan Ministry of Economy, Trade and Industry (Japan METI, 2024). Comparable regional variations in EoL emission rates were applied to other regions, based on a synthesis of literature review, field surveys, and assumptions (Duan et al., 2018; Gómez-Sanabria et al., 2022). Global estimates were derived from weighted averages of regional values, thereby naturally incorporating intermediate emission levels (Table S13). The variation of this factor is quite significant, making it challenging to define a specific value distribution.
Comment #5
L227-L231: When comparing the consistency of this study’s results with other published estimates, it would strengthen the discussion to quantify these comparisons (e.g., percentage differences or correlation metrics), rather than only describing them qualitatively. This would more clearly illustrate the degree of agreement or discrepancy.
Reply: Thank you for this valuable suggestion. In the revised manuscript, we have incorporated the following quantitative comparison in lines 268–274 of the main text:
“Using top-down approaches, Park et al. (2021) estimated a 7 ± 4 kt/yr increase in emissions from eastern China during 2014–2017 compared to 2008–2012. Our national-scale bottom-up modelling aligns the upward trend reported by Park et al. (2021), albeit with a slightly smaller magnitude. Yi et al. (2021) reported a national trend that climbed from 8.3 ± 1.6 kt/yr in 2009 to a peak of 13.9 ± 2.4 kt/yr in 2017, followed by a decline to 10.9 ± 1.7 kt/yr in 2019. Our independent estimates of 7 (4–14), 11 (5–14), and 10 (4–13) kt/yr for the corresponding years are broadly consistent with these findings when considering overlapping uncertainties.”
Comment #7
L320: As can be seen from Fig. S14a, the results for 2010 differ significantly from those of METI. The differences between the two results could be described quantitatively, with additional explanations. Furthermore, the results before 2010 vary considerably from those of METI. What is the reason for this?
Reply: Many thanks for highlighting this point. The discrepancies observed between our results and those reported by Japan METI prior to 2010 are primarily attributable to significant methodological changes in the calculation of foam sector emissions. From 2000 to 2012, METI estimated fluorocarbon emissions from closed-cell foam in construction based on a 30-year average lifespan and a 3.3% annual release rate. Before 2010, emissions were calculated by applying the 3.3% release rate to the remaining CFC-11 bank in installed foams, which was adjusted yearly by subtracting a 3.3% loss. Starting in 2010, METI instead applied the 3.3% rate to the total cumulative initial charge, not the adjusted bank. This change increased the calculation base and led to a notable rise in reported emissions.
Starting in 2013, METI updated its methodology to align with the 2006 Intergovernmental Panel on Climate Change (IPCC) Guidelines. These guidelines incorporate product-specific parameters, including distinct annual emission factors for various foam applications (e.g., spray foam, panels, and laminated boards). This methodological update explains the smoother emission trajectories observed from 2013 onwards compared to earlier periods.
As suggested, to further clarify the differences between our results and METI’s, we have added the following note in the revised SI (lines 596–602):
“Japan METI revised its emission calculation methodology over time. Prior to 2010, CFC-11 emissions from closed-cell foam in the construction industry were calculated by applying a 3.3% annual release factor to the bank of CFC-11 in installed foams, which was adjusted yearly by subtracting a 3.3% loss. Beginning in 2010, the calculation base shifted to the cumulative initial charge, resulting in a marked increase in reported emissions. Starting in 2013, METI adopted the 2006 IPCC Guidelines, which use product-specific emission factors, leading to smoother and more consistent emission trajectories after 2013.”
Comment #8
L350-351: In the results for Scenario S1 (with no unreported production), the cumulative emissions still reach approximately 4.2 Gt CO2e over 2025–2100. This suggests that legacy banks alone could substantially impact atmospheric CFC-11 levels even without ongoing illegal production. Could the authors comment on what this implies regarding the timing of ozone layer recovery? Although this study focuses on climate metrics (CO2e), it would be valuable to briefly discuss (at least qualitatively) how such sustained emissions from historical banks might delay the return of stratospheric ozone. This could help place the findings in the broader context of both climate and ozone protection goals.
Reply: Many thanks for pointing this out. Using the method described in Lickley et al. (2020), we estimated the potential delay in stratospheric ozone recovery caused by sustained emissions from historical banks. Our analysis projects that under Scenario 1 (S1), polar equivalent effective stratospheric chlorine (EESC) would returns to its 1980 level around the year 2086.
As suggested, we have added the following information in lines 399–403 of the main text:
“Using the method outlined in Lickley et al. (2020), polar equivalent effective stratospheric chlorine (EESC) under S1 is projected to return to pre-1980 levels around 2086. This projection is slightly earlier than WMO’s estimate of 2087 (WMO, 2022). This discrepancy primarily arises from higher CFC-11 concentrations in WMO assessment, attributed to their larger bank and emission estimates derived using the Lickley approach (Lickley et al., 2022; WMO, 2022).”
Comment #9
L451: The authors state that their findings “may also be applicable to other ODS and HFCs.” However, this generalization is not entirely accurate given the scope of the present study. This work emphasizes explicitly banked emissions from closed-cell foams, whereas most HFCs are used in direct refrigeration and air conditioning systems, which are very different. I would suggest that the authors explicitly qualify this statement in the conclusions to clarify the boundaries of applicability.
Reply: Thank you so much for your insightful comments. Given the discrepancies between atmospheric top-down modeling and bottom-up estimates derived from production and consumption data for some ozone-depleting substances (ODSs) and hydrofluorocarbons (HFCs), we propose that our bottom-up approach—which systematically incorporates uncertainties from underexplored factors—can be applied to the estimation of emissions of other ODSs and HFCs.
We have revised the relevant statement in the conclusion, lines 469-471 of the main text:
“While this study primarily focuses on CFC-11 emissions, the methodology developed here, which explicitly accounts for uncertainties from underexplored sources, may be broadly applicable to emission estimates of other ODS and hydrofluorocarbon.”
Comment #10
Technical corrections:
L111:In some formulas, there seems to be an extra space between symbols, such as Eq.6. Please check the whole text.
Reply: Thank you very much for your meticulous observation and valuable suggestion. We fully agree with your comment and sincerely appreciate your attention to technical details. We have thoroughly reviewed the entire text to correct any extraneous spaces between symbols and ensure consistency and accuracy in the presentation of all equations.
Comment #11
L172: The manuscript uses hyphens (-) extensively to indicate numeric ranges (e.g., “3-8 Kt/yr”), which should be replaced with standard en dashes (–) to conform to scientific publishing conventions. Please check the whole text.
Reply: We have replaced the hyphens (-) with standard en dashes (–). A thorough review of the entire manuscript has been conducted to implement the necessary revisions, ensuring consistency in this formatting aspect.
Comment #12
L173: S3 lacks the statement “Scenario 3.”
Reply: Scenario 3 has been added to the revised main text, line 215.
Comment #13
L357: The panel (b) label is missing in Fig. 3b.
Reply: Fig.3 has been revised, and the label for panel (b) has been added.
Comment #14
L480: O’doherty shoud be O’Doherty. Please check the references for additional details.
Reply: The name “O’doherty” has been consistently corrected to “O’Doherty” throughout the manuscript.
Reference
China Ministry of Ecology and Environment (China MEE). China’s National Plan for the Phase-601 out ozone-depleting substances, 1993. (In Chinese).
Alternative Fluorocarbons Environmental Acceptability Study (AFEAS). Production and atmospheric release data through 2003.
Technology and Economic Assessment Panel (TEAP), Report of the Technology and Economic Assessment Panel, September 2019, Volume 1: Decision XXX/3 TEAP Task Force Report on Unexpected Emissions of CFC-11, Final Report (2019).
Technology and Economic Assessment Panel (TEAP), volume 3: decision XXXI/3 TEAP Task Force Report on Unexpected Emissions of Trichlorofluoromethane (CFC-11, 2021).
McCulloch, A., P. Ashford, and P. M. Midgley. Historic emissions of fluorotrichloromethane (CFC-11) based on a market survey. Atmos. Environ. 35 (26): 4387-4397 (2001).
Duan, H., Miller, T.R., Liu, G., Zeng, X., Yu, K., Huang, Q., Zuo, J., Qin, Y., and Li, J.: Chilling prospect: climate change effects of mismanaged refrigerants in China, Environ. Sci. Technol., 52, 6350–6356, https://doi.org/10.1021/acs.est.7b05987, 2018.
United States Environmental Protection Agency (U.S.EPA). Inventory of Greenhouse Gas Emissions and Sinks: 1990-2022. https://www.epa.gov/ghgemissions/inventory-us-1376 greenhouse-gas-emissions-and-sinks-1990-2022 (accessed on August 11, 2024).
Japan Ministry of Economy, Trade and Industry (Japan METI). Documents pertaining to methods for estimating discharge, https://www.meti.go.jp/policy/chemical_management/law/prtr/6.html (in Japanese, accessed on August 30, 2024).
Gómez-Sanabria, A. et al. Potential for future reductions of global GHG and air pollutants from circular waste management systems. Nat. Commun. 13(1), 1-12 (2022).
Intergovernmental Panel on Climate Change (IPCC). IPCC Guidelines for National Greenhouse Gas Inventories, vol. 3. Industrial Process and Product Use (IPCC, 2006).
Lickley, M., Solomon, S. Fletcher, G.J.M. Velders, J. Daniel, M. Rigby, S.A. Montzka, L.J.M. Kuijpers, and K. Stone, Quantifying contributions of chlorofluorocarbon banks to emissions and impacts on the ozone layer and climate, Nat. Comm., 11(1), 1380, doi:10.1038/s41467-020-15162-7, 2020.
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AC1: 'Reply on RC1', Heping Liu, 13 Aug 2025
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RC2: 'Comment on egusphere-2025-2277', Anonymous Referee #2, 15 Jul 2025
General Comments
This study presents an updated bottom-up inventory of CFC-11 emissions globally, in an effort to better understand the cause of the well-documented, ‘unexpected’ rise in global emissions in the period 2014-2018. It employs a dynamic material flow analysis model to estimate aggregated emissions from the entire lifespan of CFC-11 containing products, such as closed-cell foams and refrigeration systems, as well as direct emissions from other uses. The authors estimate emissions that are broadly in line with previous work, although discrepancies are found in some places. This is attributed to a more thorough consideration of the different stages in the lifecycle of CFC-11 products. They also conclude that some of the unexpected increase between 2014 and 2018 could be attributed to increased emissions from existing banks, although unreported production also plays a role.
The model that the authors have developed is sound, and the application of Weibull survival functions to estimating global banks and emissions of CFC-11 is a sensible approach. However, I see a number of issues with this manuscript.
- Firstly, the method requires more rigorous analysis of uncertainties, and many of the parameters used to estimate emissions are not justified sufficiently.
- In addition, it is not clear to me, based on the evidence presented, how the authors justify their primary conclusion, that the global emissions rise seen between 2014 and 2018 can be attributed in part to emissions from banks.
- Finally, the results and discussion section is poorly structured and confusing. This makes it hard to determine the validity and significance of the authors’ conclusions.
Given these major concerns, I don’t think the current version warrants publication in ACP. However, if the authors can fully address the above issues, a revised version may be publishable, subject to further review.
Specific comments
L95: The description of the Weibull distribution does not make clear the significance of the shape and scale parameters. Details about what values are chosen are given in the supplementary information, but these are not cited or justified anywhere. In addition, it isn’t clear the role of ‘y’ in this function. Are the shape and scale parameters functions of the year? If they are, this should be explained clearly, and if not, then f isn’t a function of ‘y’ at all.
L145: No justification is given for the choice of values for the release rate from production, nor why the illegal and legal production are different.
L157: None of the data used to drive the model is presented in the main text. A summary of sources or perhaps a visualisation could be helpful.
L168: Claiming that unreported production is the ‘most likely’ scenario seems inappropriate, since the abstract claims that at least some of the increase is due to bank emissions. While there is a need for an intermediate scenario, there seems to be no justification for choosing 25 kt/yr as a value for the unreported production of CFC-11. Indeed, later on the authors go on to say that it is the highest emissions scenario (S3) that aligns with previous work.
L185: The ‘distributions’ referred to can only be found in the SI, and it is not clear how they are varied. What sort of sampling is done? A more sophisticated approach for sampling across parameter distributions, such as a Monte Carlo method, might be appropriate here.
L187: Why is 20% chosen? Could a range of values or a distribution be sampled instead? The same goes for 90% and 110% in L190
L191: I don’t follow what has been done here. Does it mean that the parameters are simply set to the values in Table S14? Are these global averages?
L213: This paragraph (L213-220) feels like it should be in the Methods section. The ‘temporal and spatial trajectories’ are clearly important to the results, as they lead to the divergence from other bottom-up inventories. It would be good to see these discussed or tabulated in the Methods section.
L231: Again, the discussion of the likely sources of unreported emissions feels out of place here. It might be better placed in the discussion, or in the section where the authors model potential scenarios of unreported production.
L242-L262: I find this section slightly confusing. The term ‘decommissioned’ CFC-11 has not been explained in the introduction or methods section, and is only mentioned in reference to figure 1c. Showing both banks and emissions on the same figures (1c and 1d) make them hard to interpret, and it is not clear which lines/shaded areas should be read off the left and right axes. The orange arrow is not explained, either.
L253: ‘If all decommissioned CFC-11 were released into the atmosphere, our global bottom-up CFC-11 emissions would align with top-down estimates (Montzka et al. 2018; 2021)’. It is unclear what time period this refers to, but if it refers to 2014-2018 then this appears to be the primary conclusion of this paper. However, it is not given any further development in this section nor in any of the figures.
L302: The text says that the new estimates are comparable with the McCulloch, Derwent and Manning estimates within the margin of uncertainty. However, figure 2 suggests that this is only true for a small number of years. The McCulloch estimates fall within the uncertainties of the present study for only one or two years between 1986 and 1996, the Derwent estimates for only two or three of those ten years, and the Manning estimates don’t appear to overlap at all with the present study. This is in contrast to the China estimates in figure 1b, where the authors describe the estimates as ‘significantly differing’ from the current work despite greater overlap with the plotted confidence intervals.
L333: ‘banked CFC-11 can probably result in an unexpected increase in emissions in 2014-18’. What does ‘probably’ mean in this case? As mentioned above, this has not been developed and I’m not convinced that it is a valid conclusion, especially given the trend shown in figure 1a. That figure shows emissions on a steady downward trend from 1995 onwards, with no suggestion of an increase after 2014 globally.
L342: It appears that limited assessment is done of how well each scenario would account for the unexpected emissions, in combination with varying the parameters of the main model. This seems to me to be a crucial element of the analysis that is missing.
L360: How are the mole fractions calculated? There is no mention of any atmospheric modelling in the manuscript.
L376: There are a lot of issues with this figure. The overlapping uncertainty intervals make subfigure (a) unreadable. Subfigures (b) and (c) are identical – the only difference being a simple rescaling of the y-axis, and the same goes for (e) and (f). There is no discussion of how the 99% confidence interval is calculated, either.
L398: It is not clear what is being varied in some cases. In the 20%/100% EoL case and 1.1/0.9x CCF cases, this is clear – but are the other parameters being simultaneously varied? If not, how are a mean, minimum and maximum calculated? For the shape/scale parameters, are all the different parameters (for different products and regions) varied simultaneously? As mentioned above, this seems like a case in which a Monte Carlo method would be suitable. The nine graphs in figure 4 are not a clear way of explaining the impact of each of the parameters, as they are all very similar in shape and the subtle differences are hard to spot. The right hand side of the figure is a more intuitive way of understanding the impact of varying these parameters. As with previous figures, the meaning of the 99% confidence interval is not clear, either.
L434: The final two paragraphs of the conclusion do not add much to the manuscript. They are a generic restatement of the introduction, with very little development.
Technical Corrections
L25: ‘accumulate to’ is repeated.
L25 and throughout: the abbreviation for ‘kilotonnes’ is kt, not Kt.
L28: ‘EoL’ is not yet defined
L44: over what period have emissions increased in other regions?
L59 : ‘this analysis’, not ‘these analysis’.
L181: Should read ‘sensitivity analysis’
L375: In addition to the issues with this figure mentioned above, there is no label for subfigure (b) and the y-axis label on subfigures (c) and (f) should be emissions. The GWP of CFC-11 does not vary with time, and does not have units of GtCO2eq.
Citation: https://doi.org/10.5194/egusphere-2025-2277-RC2 -
AC2: 'Reply on RC2', Heping Liu, 13 Aug 2025
We sincerely grateful your detailed and constructive feedback on our manuscript. Your time and effort in providing such valuable insights are greatly appreciated. Since our response includes formulas and revised figures, we would like to upload it as a *.pdf file.
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EC1: 'Reviewer comment on egusphere-2025-2277', Tanja Schuck, 28 Jul 2025
Posted on behalf of the 3rd reviewer by handling editor Tanja Schuck:
This is an analysis of CFC-11 emissions on global and regional scales through recent years when measured atmospheric changes suggested global emissions increased and subsequently decreased. These changes were described in previous papers as having been associated primarily with increased production (and emission) in part in and from China. With a dynamic material flow model to estimate emissions to the atmosphere from the relevant processes, the authors study the sensitivity of calculated emissions from a range of different parameters in an overall useful analysis. They suggest that some increase in emissions might be expected during recent years based on how materials containing CFC-11 were handled during decommissioning and “end-of-life”. This suggestion isn’t particularly novel, as it was explored to some extent in those initial 4 papers from 2018-2021, was mentioned in Chapter 7 of the 2005 IPCC/TEAP special report (led by P. Ashford et al., although the expected increases were anticipated to be slow and to occur in future years), and is worth repeating, as is the importance of management of these chemicals during decommissioning for minimizing future emissions and their adverse impacts. However, a number of other aspects of the work prevent me from suggesting that it is publishable in its current form, see below.
The abstract is overly general and vague on the main point emphasized there: “bank related emissions could have led to an increased CFC-11 emissions from 2014 to 2018”. Figures in the paper actually show global totals declining through this period, and regional emissions from multiple regions that are also decreasing or essentially unchanged if one considers the uncertainties associated with the analysis. Ignoring the range of uncertainties and focusing on only their mid-range estimates, the results can be used to suggest that bank-related emissions increased from only China during this period, but this raises important questions: 1) why is the potential emission increase in China quite different from the decreases derived for the other regions? 2) What are the specific region-based factors/assumptions that cause this uniqueness for China in the model, and what is the supporting information that backs up these choices? Is the uniqueness of China related to the timing and fraction of CFC-11 in different sub-sectors or perhaps of assumptions on lifespan of foam product applications (Table S3)? Many input parameters are provided in tables, but no clarity on the specific ones that make China unique with respect to the time evolution of CFC-11 bank emissions is discussed. 2) Should an increase in Chinese bank-related emissions actually have occurred, the global decreasing trend would imply that the increases in China were offset by unexpectedly rapid decreases in other areas. Is this reasonable?
The main message of the abstract is written so that it is easy for the reader to be misled into thinking that perhaps CFC-11 production didn’t increase. This is inconsistent with the main text of the paper, discussions of scenarios, and the mismatch on a global scale between expected and atmosphere-derived emission in Figure 1a that would seem to require post-2010 production as an explanation.
Some points are also difficult to reconcile: inventory-based model-derived emissions are argued to be consistent with atmosphere-based results in the US, Europe, and China, yet the authors argue that there was substantial unreported production. Are we to conclude that it must have occurred outside these regions despite the contrary evidence provided elsewhere?
On the regional analyses.
Any revision should be sure to reflect on the uncertainties associated with the assumptions required to perform the analysis in the main text and be more circumspect about the conclusions. For example, China’s emissions are said to have increased from 8 (4-13) kt/yr during 2008-12 to 11 (5-13) kt/yr during 2014-18, but given these large uncertainties justifying a conclusion that emissions actually increased is problematic. Discussion of the very small increases reported by Redington et al. are mentioned without consideration of their uncertainties and that they are very small. Did atmosphere-based emissions from these regions actually increase above detectability? The manuscript doesn’t indicate that Dunse et al and Manning et al. actually suggested emissions increases through this period, although a reading of lines 43-46 would suggest otherwise. This very slight change in the Redington et al. study is very different from the much larger increase that the inventory model derives for Europe, in apparent contradiction to the wording and assertion on lines 313-314.
These points are central with respect to the stated purposes of this study, which is related to assertions that previous analyses “did not adequately consider the variabilities in lifespans of foam products and their EoL management” and that “surveys reveal significant temporal and spatial variability in the actual lifespans of buildings”. Many of the more recent inventory-based studies did provide an analysis of a range of parameter values. Providing more clarity on how the new model adds clarity and understanding to the situation is needed but currently lacking.
Details:
Further, the juxtaposition in Figure 1b of top-down and bottom-up estimates for “China” may not be appropriate, given that I believe some (or all) of the top-down estimates represent emissions from only portions of China, whereas I’m guessing the bottom-up estimates are for all of China.
Following up on the comment related to the abstract: the authors don’t address in the main text why the relative increase suggested in decommission- or EOL-related emissions for China, the US and the EU are so different. Were different parameters used for these different regions based on the unsupported suggestion that they depend on “cultural, economic, and political factors”? Why is different language used to describe the processes for these different regions? More clarity is needed here as to the cause for these differences.
With respect to the scenarios, some values for emission and unreported production are provided, with uncertainties, but no indication of how those numbers were arrived at and what constraints were used to allow those values to be estimated. Again, further clarity is needed here.
Lines 240-241, what is the evidence for this assertion and what do “(b)” and “(a)” refer to?
Lines 253-255, “if all decommissioned…” that’s a striking assertion without any clear demonstration and the time dependence of resulting emissions (and how they might compare to atmosphere-based if this were true) is not mentioned.
Lines 277-279, why would errors related to emissions estimated in one application (CFC-12 in AC and refrig) apply to CFC-11 whose emissions are from different processes? Gallagher estimates for CFC-11 look reasonably accurate.
Consider projecting the results in panels a-h of Figure 4 out to 2030, as the differences between the bottom-up approaches and assumption should become even larger through this period, and could enable an assessment of their reliability with the atmosphere-based results as they are updated.
IPCC/TEAP study reference mentioned above: Ashford, P. et al. in Safeguarding the Ozone Layer and the Global Climate System: Issues Related to Hydrofluorocarbons and Perfluorocarbons (eds Metz, B. et al.) Ch. 7 (Cambridge Univ. Press, Cambridge, 2005).). How do you results compare to this (while this could be referred to in the abstract, it perhaps is more a topic of discussion for the main text)?Citation: https://doi.org/10.5194/egusphere-2025-2277-EC1 - AC3: 'Reply on EC1', Heping Liu, 13 Aug 2025
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Heping Liu
Huabo Duan
Ning Zhang
Ruichang Mao
Travis Reed Miller
Ming Xu
Jiakuan Yang
Yin Ma
The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
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General comments:
This manuscript presents a bottom-up dynamic material flow analysis (D-MFA) to quantify the historical and projected emissions of banked CFC-11, aiming to reconcile these with observed atmospheric increases, highlighting the role of bank emissions and end-of-life (EoL) handling. This is a timely and important contribution given the unexpected rise in CFC-11 emissions after 2014 despite the Montreal Protocol controls. The study is well-structured and employs a robust methodological framework with extensive parameterization and uncertainty analysis. However, several aspects require clarification, additional quantitative support, or broader discussion before it can be recommended for publication.
Specific comments:
L112-113: Equation (6) models manufacturing, use, and end-of-life (EoL) stages emissions. However, whether the model explicitly accounts for CFC-11 servicing or maintenance activities is unclear. Could the authors clarify whether this servicing phase was considered and how it was incorporated? If not, please discuss whether the omission might underestimate the lifetime size of the in-use stock and how significant this could be relative to the total bank. A brief quantitative or qualitative assessment would strengthen the manuscript.
L145: The uniform 3% release rate may overlook differences between A5 and non-A5 parties, given historically higher fugitive emissions in developing countries. I would recommend either: (1) implementing region-specific r-values that reflect the technological disparities between A5 and non-A5 countries, or (2) providing robust justification for the uniform rate along with a comprehensive uncertainty analysis regarding this parameter.
L188：Why does the study assume only two discrete EoL emission scenarios of 20% or 100%? What is the rationale or literature basis for these specific choices? It is recommended to consider a more nuanced range of fractions (e.g., 60%, 80%) or perform a more continuous sensitivity analysis to capture the spectrum of plausible emission pathways better.
L227-L231: When comparing the consistency of this study’s results with other published estimates, it would strengthen the discussion to quantify these comparisons (e.g., percentage differences or correlation metrics), rather than only describing them qualitatively. This would more clearly illustrate the degree of agreement or discrepancy.
L247: The authors mention that inadequate waste management systems may accelerate CFC-11 emissions (which is also mentioned in L328-329), yet the model does not appear to incorporate regionally differentiated EoL emission rates. Were regional differences (e.g., higher recovery/incineration rates in developed countries vs. more landfilling in developing countries) considered? If not, might the use of a globally uniform EoL emission fraction underestimate actual emissions in areas lacking effective collection and destruction systems, thereby affecting the regional attribution of emissions? If region-specific assumptions are not yet implemented, I would suggest discussing this as a limitation, along with the potential implications for the results and how future work could incorporate differentiated EoL management levels to improve realism and policy relevance.
L320: As can be seen from Fig. S14a, the results for 2010 differ significantly from those of METI. The differences between the two results could be described quantitatively, with additional explanations. Furthermore, the results before 2010 vary considerably from those of METI. What is the reason for this?
L350-351: In the results for Scenario S1 (with no unreported production), the cumulative emissions still reach approximately 4.2 Gt CO2e over 2025–2100. This suggests that legacy banks alone could substantially impact atmospheric CFC-11 levels even without ongoing illegal production. Could the authors comment on what this implies regarding the timing of ozone layer recovery? Although this study focuses on climate metrics (CO2e), it would be valuable to briefly discuss (at least qualitatively) how such sustained emissions from historical banks might delay the return of stratospheric ozone. This could help place the findings in the broader context of both climate and ozone protection goals.
L451: The authors state that their findings “may also be applicable to other ODS and HFCs.” However, this generalization is not entirely accurate given the scope of the present study. This work emphasizes explicitly banked emissions from closed-cell foams, whereas most HFCs are used in direct refrigeration and air conditioning systems, which are very different. I would suggest that the authors explicitly qualify this statement in the conclusions to clarify the boundaries of applicability.
Technical corrections:
L111:In some formulas, there seems to be an extra space between symbols, such as Eq.6. Please check the whole text.
L172: The manuscript uses hyphens (-) extensively to indicate numeric ranges (e.g., “3-8 Kt/yr”), which should be replaced with standard en dashes (–) to conform to scientific publishing conventions. Please check the whole text.
L173: S3 lacks the statement “Scenario 3.”
L357: The panel (b) label is missing in Fig. 3b.
L480: O’doherty shoud be O’Doherty. Please check the references for additional details.