the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Climate change metrics: IPCC AR6 updates, discussions and dynamic assessment applications
Abstract. Climate change metrics result from analytical simplification of complex and diverse climate models. Assessment communities do not always take the time to understand this complexity. We investigated the last IPCC report to properly gather updated metric equations, climate parameters and associated uncertainties. In each future Assessment Reports, IPCC is encouraged to recall climate equations and parameters values in a pedagogical way. Global Warming Potential (GWP) is an easy-to-use, but simplistic and criticised metric. Alternative Global Temperature change Potential (GTP) remains as GWP: relative to carbon dioxide and used at arbitrary fixed time horizons (H). This study focuses on two dynamic metrics – cumulative radiative forcing (AGWP or ΔF) and global temperature change (AGTP or ΔT) – and applies them to the three major anthropogenic greenhouse gases (GHGs) – carbon dioxide, methane and nitrous oxide. Dynamic climate metrics better assess impacts by differentiating GHGs contribution over time. For radiative forcing metrics, indicators at common H – 20, 100, 500 years – are sufficient, with no hierarchy between these timescales. As for global temperature change metrics, they have two advantages that offset their higher uncertainties. (1) They are more policy-relevant with an easily understandable unit. (2) Peak and long-term temperature change enable to get rid of H major issue, i.e. IPCC is encouraged to adopt AGTPpeak and AGTPlong-term characterisation factors. We also recommend plotting complementary cumulative radiative forcing and temperature change temporal profiles of a product system up to 600 years. This enables going towards climate neutral product systems with more clarity, transparency and understanding.
- Preprint
(1148 KB) - Metadata XML
-
Supplement
(294 KB) - BibTeX
- EndNote
Status: final response (author comments only)
-
RC1: 'Comment on egusphere-2024-3918', Anonymous Referee #1, 25 Feb 2025
Discussions of the benefits and drawbacks of different climate emission metrics is important and I believe this paper could make a useful contribution to the literature. In its present state, I found it a little confusing and in places repetitive of the earlier literature, and so I think it could be made much sharper.
It seems that the main intended usage of this work is in LCA, so it is cross-disciplinary in that sense but it will need to be an Editorial decision as to whether this paper fits the scope of the journal.
My background is more in the formulation of climate metrics and I am less familiar with applications in LCA, so I apologize in advance for any misunderstandings. As I understand it, a primary application of the work is from the illustration in Section 5.5 where a given activity is leading to compensating impacts on climate; the additional metrics here would then be important for understanding the nature of these compensations. If that is correct, I feel a restructuring of the paper is needed to make this much clearer much earlier in the paper.
Overarching comments
- I felt that the case for the AGTPpeak and AGTPlongterm was not made clearly, and simpler variants might serve almost the same purpose. Since the time of peak warming for all climate forcing mechanisms is really 10+/-10 years (see e.g. Figure 8.33 of Myhre et al. 2013) then AGTPlong is effectively AGTP500. I wonder what the policy relevance of this is, in terms of trying to achieve a peak warming during this century? An alternative analysis of AGTPpeak is in Allen et al. 2016 (https://doi.org/10.1038/nclimate2998) which asks a slightly different question which is “what is the contribution of an emission of a gas now to the timing of (when we hope) temperatures will peak from all gases?” I was slightly surprised that this paper was not cited; I think a clearer case needs to be made here for the utility of the AGTPpeak here. Given the comment above about the similarities of the timing of peak warming, I doubt there is much difference, between AGTPpeak and, say, AGTP10 or AGTP20.
- Related to this (and perhaps this is more an observation of possible policymaker response than a scientific comments) policymakers would rightly need to understand the utility of new metrics, compared to existing ones and what new perspective emerges from them. Convincing them that what is proposed is not “just another metric” is not straightforward. If my first point above is broadly correct, then it is more an argument about which time horizons should be used for the AGTP and this could lead to a more focused discussion.
Other comments – noted by line number. An M before indicates a more major comment
M9: The abstract and maybe the title needs to make it much clearer that the principal motivation for this work is in the application of metrics to LCA. I did not really understand this clearly until Section 5.5 and it seems particularly relevant to LCA in cases where there are contributions to climate change that have opposing signs
M14: The meaning of “dynamic” throughout this article is unclear to me. I have seen “dynamic” used in the context of combined target and metric approaches, where the time horizon changes as an assumed temperature target is approached (see Abernethy and Jackson (2013), Berntsen et al., 10.1007/s10584-010-9941-3 and Shine et al., 10.1098/rsta.2007.2050). But here, “dynamic” seems to just mean “absolute” and I don’t know why new terminology is introduced.
39: “characterisation factors”. Maybe in other areas this is used as terminology, but I haven’t seen this before. I thought it meant the input parameters to the metric calculations (and so I quite like the term) but this is not clearly explained and not clearly used in what follows. But when I get to line 280, I doubt my interpretation and it seems to refer to the absolute metrics (which is what I thought were called “dynamic metrics”). I apologise if I am missing the point here.
M47-48: I didn’t understand point 3. GWP does not sum emissions. Does it mean sums CO2eq emissions? This comment seemed to make a bit more sense when I reached Section 5.5. I think the introduction and the motivation for the paper could be made clearer by a much more detailed discussion on this kind of application of metrics, in the Introduction. For readers of this journal, it is a quite specialised application and so greater clarity here would benefit the whole paper.
M60-61: This seems a criticism of IPCC but if I understand that “dynamic” means “absolute” then I don’t agree with the statement. The Supplementary of AR6 Chapter 7 (Smith et al. ) does present absolute metric values.
72: The values presented here do not seem any more up-to-date than in AR6. Perhaps I misunderstand the point being made.
91-92: Isn’t this the definition of “characterisation factors”. If so, it could be made clear here. And it seems to be repeated at lines 160-161, again with no connection to CFs. And again at 241, where they seem to be called “climate parameters”?
96: I have no objection to it, but I wasn’t completely clear how useful this Figure is in this paper, as it is not really used in detail.
98, Table 1: I suggest adding the AGWP(100) for CO2 to this table, as this explains some part of the GWP changes for CH4 and N2O (see e.g. Fig 8.31of Myhre et al. (2013)). Note that tau, and its units, is undefined.
105: Instantaneous radiative forcings have not been used in metric calculations, not even in the first IPCC assessment. It has been either SARF or ERF. So this is confusing. Also confusing is the use of IRF for the impulse response function when IRF is commonly used for instantaneous radiative forcing.
116: this definition of RE is confusing. It is the RF (not the change in RF) per unit change in atmospheric abundance.
119: And the RE for, say, CH4 depends on N2O.
189: This equation differs from the incorrect IPCC AR7 Equation 7.SM.5.5. And as far as I can see, this has not been corrected properly in the AR6 errata at https://www.ipcc.ch/report/ar6/wg1/downloads/report/IPCC_AR6_WGI_Errata.pdf
where dt should be dt’. Worth pointing out?
(189: No need for the authors to respond to this, but my personal view is that the incorporation of this CCf term in the AGWP means that the AGWP formulation is no longer transparent and no longer easy to calculate)
204: “well” – a very minor comment, but it may already be well quantified, but we don’t know, as so few other groups have computed this term. Maybe “not been confidently quantified” would be better?
267: I don’t agree that the accumulated energy remains over centuries. The temperature of the Earth system responds quite quickly (Fig 2b). I think it is a fault of the GWP that it appears to accumulate, like an elephant that never forgets, but in reality Fig 2b shows that it does forget.
275: GTP100 – I don’t think there is any clear reason for using GTP100 (here or in AR6), and it seems just to follow the fact that GWP100 is used. I wasn’t clear what is being added here beyond my comment in M14 in the combined target and metric approaches, which show how the GTP value changes with adopted time horizon. Perhaps this could be made clearer.
293: What is FU in the y-axis labels in Figure 3a and 3b?
293: It took me a while to understand this Figure, and maybe it could be made clearer that it is comparing a 100 kg emission of CO2 with a 3.46 kg emission of CH4 (since 3.46xGWP100(CH4) = 100). Note that Figure 3b gives essentially the same information as Figure 2a of Allen et al. (2016).
297: This confused me a bit, as Figure 4 does not, as I understand it, use GWP100, but uses the AGTP of each gas. Figure 4b is essentially similar to Figure 8.33 in Myhre et al. (2013) but I think the stacked form of Fig. 4b is not very helpful. To see the N2O signal you have to subtract two curves and a straightforward line diagram would seem better for this purpose. But then it needs to be made clear what extra information comes from this figure.
M303: “predominantly due to CH4”. It seems 50:40 CO2 and CH4 in Figure 4b and I think (see previous comment) a straightforward line diagram would make this clear
309: “lack of clear equations … in AR6”. They seem very clear in Smith et al. (2021) Section 7.SM.5 (the errata above excepted), so I do not understand this statement.
336-340: This is an interesting discussion, but I am a bit short of being convinced by it. This relates to some of the discussion above as to whether the contribution of emissions now to the (likely) time of peak warming due to all gases might be more relevant for policymakers. As noted above, I think it is essentially an argument that AGTP20 has utility and such an argument needs to be made more clearly. I would argue that GTP50 has more utility than GTP100 for current climate policy timeframes.
M406: This section is potentially very interesting but from my perspective it comes “out of the blue”. The section has no references and seems rather abstract, based as it is on “four theoretical materials” with no elaboration on what this means. This framework may be familiar to those in the LCA community, but for this particular journal I think a better description is needed. There are cases in “pure” atmospheric sciences where emissions lead to both negative and positive effects, notably for NOx (see e.g. Figure 6 of Fuglestvedt et al. 2010). I did wonder whether the proposed framework here may be more suitable for characterising such complex cases and this should be stated much earlier in the paper as the principal motivation. For me, that might help motivate why AGTPpeak could be useful in some cases.
446 and 455: dTnegative is only applicable for a few cases.. It seems its utility here arises from LCA cases where there are competing processes from different emissions. Again, if this is more clearly explained earlier in the paper, it might help clarify the motivation and application of this research.
Typos
51: 2005 not 2015
68: Throughout Szopa should be Szopa et al.
97: Hodnebrog is mis-spelt
112: “of in”. Is a word missing?
207: “other things to OH”?
252: Throughout Smith should be Smith et al.
Citation: https://doi.org/10.5194/egusphere-2024-3918-RC1 -
AC1: 'Comment on egusphere-2024-3918', Vladimir Zieger, 10 Mar 2025
Dear referee,
Thanks for your meaningful response. As you mentioned, it is a cross-disciplinary article addressed to two communities: Climate science and LCA. It seems important to us to be published by an Editor that focus on climate science rather than on LCA. Indeed, climate science is the foundation of climate metrics, IPCC has such an influence for the LCA community on metrics and characterization factors, and it was a pleasure to condense AR6 data and propose a summary.
The global aim of the article is raising climate scientist’s awareness on their influence, as well as helping LCA scientists on CC metrics understanding. Your comments really help to propose a restructured version of the article which is more balanced and clearer.
Firstly, we agree have a more concise article. For instance, figures 1 and 4 are proposed to be deleted Fig. 4 is replaced by citing Allen et al., 2016 and Myhre et al. 2013 interesting work.
Secondly, we have noted the vocabulary issues. A little glossary is proposed in the appendix section to clarify our choices.
Thirdly, section 5.5 is proposed to appear much earlier in the text, in Section 4 ‘Result’. Hence, one can get before the ‘Discussion’ section that dynamic CC assessment can be applied to long-lasing products and systems, as well has to biogenic materials that store carbon. Setting a time horizon - AGTP10, AGTP20, AGTP50 retained by IPCC - is always subject to value judgement. AGTPpeak mathematically depict the maximum of the curve. Fig. 5 appearing much earlier illustrates that AGTP peak can be linked to a pulse that do not occur at t0, but for instance at t=50 years.
This clearly helps a constructive discussion on AGTP / ΔT and on the proposition of new characterization factors - peak and long-term. This helps to convince that this proposal is not “just another metric”, but enables current climate policy for 2050 to be better aligned with the Paris Agreement.
A proposed restructured version can be submitted once another reviewer will post comments.
_ _ _ _ _ _ _
Referee comments are in italic. Author answers are just below
M9: The abstract and maybe the title needs to make it much clearer that the principal motivation for this work is in the application of metrics to LCA. I did not really understand this clearly until Section 5.5 and it seems particularly relevant to LCA in cases where there are contributions to climate change that have opposing signs
[Authors]: We agree. Title, abstract and introduction have been adapted to link climate metrics to LCA (and more precisely dynamic climate change assessment) application.
Title: Climate change metrics: bridging IPCC AR6 updates and dynamic life cycle assessments
Intro: “Last but not least, CF are developed by climate scientist on a single emission pulse basis that might not be optimal for dLCA. Metrics and CF are here discussed with the perspective to properly assess objects with several emission pulses spread over time, e.g. long-lasting systems, or materials containing biogenic carbon.”
M14: The meaning of “dynamic” throughout this article is unclear to me. I have seen “dynamic” used in the context of combined target and metric approaches, where the time horizon changes as an assumed temperature target is approached (see Abernethy and Jackson (2013), Berntsen et al., 10.1007/s10584-010-9941-3 and Shine et al., 10.1098/rsta.2007.2050). But here, “dynamic” seems to just mean “absolute” and I don’t know why new terminology is introduced.
[Authors]: ‘Dynamic’ illustrates that time horizon is not fixed, in contrary to static GWP100 for instance. ‘Absolute’ describes that AGWP(t) or AGTP(t) are not relative metrics. GWP(t) is a relative and dynamic metric (see equation 11). Here is the proposed definition in the glossary:
Dynamic climate metrics: metrics used in a temporal dynamic approach that considers timing of uptakes and emissions. First attempts on dynamic climate change assessment calculated the benefits implied by a delayed emission, but still with a fixed time horizon (Fearnside et al., 2000). Levasseur and her co-workers (2011, 2012) extended the approach by calculating absolute and relative radiative forcing metrics on a yearly basis over several hundred years.
39: “characterisation factors”. Maybe in other areas this is used as terminology, but I haven’t seen this before. I thought it meant the input parameters to the metric calculations (and so I quite like the term) but this is not clearly explained and not clearly used in what follows. But when I get to line 280, I doubt my interpretation and it seems to refer to the absolute metrics (which is what I thought were called “dynamic metrics”). I apologise if I am missing the point here.
[Authors] : a definition of ‘characterization factor’ is proposed in the Glossary.
Characterisation factor (CF): produced by modelling consequences of withdrawals and discharges on ecosystems, human health or on resources, a characterisation factor provides the contribution of an elementary flow to an impact category. For climate metric, a CF convert a GHG emission or uptake into a climate change impact.
M47-48: I didn’t understand point 3. GWP does not sum emissions. Does it mean sums CO2eq emissions? This comment seemed to make a bit more sense when I reached Section 5.5. I think the introduction and the motivation for the paper could be made clearer by a much more detailed discussion on this kind of application of metrics, in the Introduction. For readers of this journal, it is a quite specialised application and so greater clarity here would benefit the whole paper
[Authors]: we change “sums” into “aggregates”.
Indeed, in LCA, GWP aggregates all pulses within the time horizon to one CO2 pulse at t0.
We agree to focus more on such applications for readers of the journal. This joins above general comments.
M60-61: This seems a criticism of IPCC but if I understand that “dynamic” means “absolute” then I don’t agree with the statement. The Supplementary of AR6 Chapter 7 (Smith et al. ) does present absolute metric values.
[Authors]: an absolute metric can be static. A definition of dynamic LCA is proposed in the glossary.
72: The values presented here do not seem any more up-to-date than in AR6. Perhaps I misunderstand the point being made.
[Authors]: 72: We agree. “up-to-date” is deleted.
91-92: Isn’t this the definition of “characterisation factors”. If so, it could be made clear here. And it seems to be repeated at lines 160-161, again with no connection to CFs. And again at 241, where they seem to be called “climate parameters”?
[Authors]: no it isn’t in a LCA perspective, cf. comment response of line 39.
96: I have no objection to it, but I wasn’t completely clear how useful this Figure is in this paper, as it is not really used in detail.
[Authors]: We agree. Figure removed and “(Hodnebrog et al., 2013)” cited instead of “(see Fig. 1)”.
98, Table 1: I suggest adding the AGWP(100) for CO2 to this table, as this explains some part of the GWP changes for CH4 and N2O (see e.g. Fig 8.31of Myhre et al. (2013)). Note that tau, and its units, is undefined.
[Authors]: “(year)” added for tau in the table, as well as “kgCO2e” for GWP(100) and GTP(100) units.
About AGWP_CO2(100) suggestion : AGWP(CO2) is function of RE(CO2) and IRF(CO2). As IRF(CO2) do not changes every IPCC report (Joos et al, 1996, then Joos et al, 2013), we think that RE(CO2) variations are enough to indirectly explain some part of the GWP changes for CH4 and N2O. Also, we thick that the table as already enough information.
105: Instantaneous radiative forcings have not been used in metric calculations, not even in the first IPCC assessment. It has been either SARF or ERF. So this is confusing. Also confusing is the use of IRF for the impulse response function when IRF is commonly used for instantaneous radiative forcing.
[Authors]: We were also confused during the literature review and we tried to clarify terms.
We agree to change “instantaneous” by “effective”. ERF definition is proposed to be in the glossary. IRF stays for “impulse response function” based on (Joos et al. 2013) and is also defined in the glossary.
116: this definition of RE is confusing. It is the RF (not the change in RF) per unit change in atmospheric abundance.
[Authors]: We agree with your definition.
119: And the RE for, say, CH4 depends on N2O.
[Authors]: Yes, we agree.
189: This equation differs from the incorrect IPCC AR7 Equation 7.SM.5.5. And as far as I can see, this has not been corrected properly in the AR6 errata at https://www.ipcc.ch/report/ar6/wg1/downloads/report/IPCC_AR6_WGI_Errata.pdf where dt should be dt’. Worth pointing out? (189: No need for the authors to respond to this, but my personal view is that the incorporation of this CCf term in the AGWP means that the AGWP formulation is no longer transparent and no longer easy to calculate)
[Authors]: Yes, worth pointing it out. We agree that metrics without CCf still need to be proposed, in order to have accessible metrics.
204: “well” – a very minor comment, but it may already be well quantified, but we don’t know, as so few other groups have computed this term. Maybe “not been confidently quantified” would be better?
[Authors]: Proposition accepted
267: I don’t agree that the accumulated energy remains over centuries. The temperature of the Earth system responds quite quickly (Fig 2b). I think it is a fault of the GWP that it appears to accumulate, like an elephant that never forgets, but in reality Fig 2b shows that it does forget.
[Authors]: we agree. “This asymptote comes from AGWP mathematical construct and might lead to bias in long-term interpretations” instead of “accumulated energy remains over centuries”
275: GTP100 – I don’t think there is any clear reason for using GTP100 (here or in AR6), and it seems just to follow the fact that GWP100 is used. I wasn’t clear what is being added here beyond my comment in M14 in the combined target and metric approaches, which show how the GTP value changes with adopted time horizon. Perhaps this could be made clearer.
[Authors]: agree, ‘than static GTP(100) values’ replaced by ‘than the use of static GTP values’
293: What is FU in the y-axis labels in Figure 3a and 3b?
[Authors]: “FU” removed. (FU = functional unit, but not necessary and confusing)
293: It took me a while to understand this Figure, and maybe it could be made clearer that it is comparing a 100 kg emission of CO2 with a 3.46 kg emission of CH4 (since 3.46xGWP100(CH4) = 100). Note that Figure 3b gives essentially the same information as Figure 2a of Allen et al. (2016).
[Authors]: We agree, this part has proposed to be clearer: “an emission of 100kg of CO2, a 3.36 kg emission of CH4 and a pulse with three climate pollutants, mixed_GHGs, reflecting 2022 global emission proportion of major GHGs – 99% CO2, 0,97% CH4, 0,03% N2O”.
Complementary to Allen et al. 2016, here a mixed contribution is plotted that tells that kgCO2e is a proper approximation/simplification regarding global emissions. M303 response is connected to this.
297: This confused me a bit, as Figure 4 does not, as I understand it, use GWP100, but uses the AGTP of each gas. Figure 4b is essentially similar to Figure 8.33 in Myhre et al. (2013) but I think the stacked form of Fig. 4b is not very helpful. To see the N2O signal you have to subtract two curves and a straightforward line diagram would seem better for this purpose. But then it needs to be made clear what extra information comes from this figure.
[Authors]: We agree, no real extra information comes from this figure. Figure and allocated paragraph are removed. Figures from Myhre et al 2013 and Allen 2016 (Fig 2.d) are cited in paragraph linked to Figure 3.
M303: “predominantly due to CH4”. It seems 50:40 CO2 and CH4 in Figure 4b and I think (see previous comment) a straightforward line diagram would make this clear
[Authors]: We agree, a straightforward line diagram is proposed in relation to Figure 3b.
309: “lack of clear equations … in AR6”. They seem very clear in Smith et al. (2021) Section 7.SM.5 (the errata above excepted), so I do not understand this statement.
[Authors]: We agree. Replaced by “Lack of clearly gathered climate parameter values and associated uncertainties used in climate metrics defined in Smith et al. (2021), section 7.SM.5”.
336-340: This is an interesting discussion, but I am a bit short of being convinced by it. This relates to some of the discussion above as to whether the contribution of emissions now to the (likely) time of peak warming due to all gases might be more relevant for policymakers. As noted above, I think it is essentially an argument that AGTP20 has utility and such an argument needs to be made more clearly. I would argue that GTP50 has more utility than GTP100 for current climate policy timeframes.
[Authors]: As noted above, AGTPpeak appears more robust and flexible. In LCA, a system modelling of can lead to a temperature peak that occur 150 years after t0. Setting a time horizon - AGTP10, AGTP20, AGTP50 retained by IPCC - is always subject to value judgement.
Article and argumentation are proposed to be restructured to better promote the relevance of AGTPpeak and AGTPlong-term.
M406: This section is potentially very interesting but from my perspective it comes “out of the blue”. The section has no references and seems rather abstract, based as it is on “four theoretical materials” with no elaboration on what this means. This framework may be familiar to those in the LCA community, but for this particular journal I think a better description is needed. There are cases in “pure” atmospheric sciences where emissions lead to both negative and positive effects, notably for NOx (see e.g. Figure 6 of Fuglestvedt et al. 2010). I did wonder whether the proposed framework here may be more suitable for characterising such complex cases and this should be stated much earlier in the paper as the principal motivation. For me, that might help motivate why AGTPpeak could be useful in some cases.
[Authors]: We completely got your point. It is clear now why AGTP10 or AGTP20 seemed sufficient for you in a “pure” atmospheric sciences perspective. Section 5.5 is now in the ‘Result’ section. The article has been restructured accordingly in order to help understanding on AGTPpeak motivation.
446 and 455: dTnegative is only applicable for a few cases.. It seems its utility here arises from LCA cases where there are competing processes from different emissions. Again, if this is more clearly explained earlier in the paper, it might help clarify the motivation and application of this research.
[Authors]: We agree, it is proposed to be earlier explained in the paper.
Typos
[Authors] : All suugestions accepted. Clarification on 207 question mark: “Not all CH4 is oxidised by OH radical since other CH4 sinks exist.”
Citation: https://doi.org/10.5194/egusphere-2024-3918-AC1 -
RC2: 'Comment on egusphere-2024-3918', Anonymous Referee #2, 02 Apr 2025
Main comments
As a researcher who worked on many studies of emissions metrics before, I took on this review task with great interest. I am sorry, however, that I cannot be very positive here. Here are my three main concerns.First, the manuscript does not discuss at all the previous extensive efforts that have led to the use of multiple metrics in the Life Cycle Impact Assessment (Levasseur et al., 2016a,b; Cherubini et al., 2016a,b; Frischknecht et al., 2016; Reisinger et al., 2017; Iordan et al., 2018; Jolliet et al., 2018; Tanaka et al., 2019). Much of what is discussed in the current manuscript has already been considered through the above-mentioned community-wide efforts. These very relevant UNEP/SETAC activities should be fully integrated into the manuscript.
Second, a large part of the manuscript is a summary of previous studies and essentially a repetition of what has already been written elsewhere. This limits the novelty of this work and raises the question of whether this manuscript should be considered for a peer-reviewed journal. In general, it is unclear what contributions this manuscript makes to the existing literature.
Third, the text needs to be thoroughly revised. I found that the text generally lacks academic rigor (e.g., lack of accuracy in statements, unsubstantiated statements, many repetitions, unclear and unstructured arguments, irrelevant statements, factual errors, grammatical errors, etc.). Many of my detailed comments below are about the text, but I cannot fully comment on them because there are so many. All of these problems prevent me from understanding the authors’ recommendations are their rationale clearly. Overall, I think that more descriptive care is needed for this manuscript, and the text almost needs an overhaul to make it suitable for academic consideration.
Detailed comments
Lines 17-18: This sentence is unclear and needs revision.
Line 20: “H major issue” has not been explained in the abstract.
Lines 31-32: An unsubstantiated sentence like this should be best avoided in scientific paper.
Line 33: Somewhere in this paragraph, the author should specifically cite relevant recent IPCC chapters (AR6 WGI Chapter 6; AR6 WGIII Cross-Chapter Box 2; AR6 WGIII Chapter 2SM). As a recent comprehensive summary, I further suggest Part 4 of FAO (2023).
Line 39: Characterization factors (CFs) require an explanation, as the readership of this journal may not be very familiar with this term.
Line 45: Edit the text on this line.
Lines 46-47: It is not clear in what way this point is a criticism.
Lines 47-48: This is not a criticism of GWP as such. I think that this is a criticism on how to use GWP.
Line 54: Define what the dynamic climate metrics are.
Line 59: Somewhere here, the UNEP/SETAC activities (see my first major comment) should be reviewed.
Line 67: 82% seems low. Is tropospheric ozone generated by CH4 included in this estimate?
Line 77: The manuscript never mentions the metric that has been intensively discussed for the past several years: GWP* (Allen et al., 2018; Lynch et al., 2020; Cain et al., 2021). Even though the authors do not recommend this metric, I would think that the authors should at least comment on it. I think that this metric might appeal to the authors (I am not necessarily recommending), as GTP* actually solves the time horizon issue, although it brings a range of other issues (e.g. Reisinger et al., 2021).
Line 80: There have been many attempts to generalize emission metrics. A recent example that I am aware of is Edwards and Trancik (2022).
Line 81: The authors could consider note that not all emission metrics can fit into this formulation. A notable exception is cost-effective metrics (e.g., Tanaka et al., 2021).
Line 113: Typo for “specie”.
Line 114: It is true that IRF is a sum of exponential functions, but it is just one exponential function for all other gases.
Line 121: I find it difficult to understand the first sentence.
Line 159: The abbreviation of GHG has been already introduced.
Line 161: It should be Szopa et al., 2021, as there are many co-authors.
Line 163: Describe what the chemical adjustments are.
Line 172: I would think Joos et al. (2013) is an appropriate source reference here.
Line 175: Somewhere here, one could also comment on uncertainties. In such a long time scale, the temperature response should be very uncertain (e.g., Reisinger et al., 2010).
Line 186: AR5 provides an alternative version of metric values that include CCf for both CO2 and nonCO2 terms (Table 8.SM.16), although errors were found later. Those in AR6 should be more correct.
Line 267: CO2 will be present in the atmosphere even 1,000 years after emissions (Joos et al., 2013).
Line 268: It is unclear what AGWP temporal emission profiles. AGWP is by definition based on a pulse emission in year 0.
Line 272: Revise “Concerning CO2 temperature change decrease at long-term H is very slight”.
Lines 273-274: I do not understand the sentences around here.
Line 284: The equation “GWP100 =100 kgCO2e” does not make sense according to the definition of GWP100 in climate science, which should have a unit of 1. However, in the LCA, GWP100 is sometimes treated as being equal to (or being representative of) CO2-equivalent emissions (e.g., kgCO2e). This is an example of potential sources of confusion between the climate science and the LCA, which could be pointed out in this study.
Lines 284-285: Difficult to follow. Please revise.
Line 288: I suggest citing Allen et al. (2022), a consensus paper of this topic.
Line 291: AGTPlong-term is essentially AGTP500, as the time to peak temperature is very short relative to 500 years. Then, why is AGTPpeak needed as a point of reference? I still see that AGTPlong-term has a subjective choice of 500 years, as all other metrics have certain subjective judgment in them. Note also that metrics with very long-term time horizons were explored by Sterner et al. (2014).
Lines 308-309: There is one page summary with many equations in the Supplementary Material of AR6 WG1 Chapter 7 (Section 7.SM.5). I do not know if the authors have checked this AR6 section, but this looks sufficient to me. Please state specifically what exactly were not reported or missing in IPCC AR6.
Lines 312-313: Unclear sentence. The Aamaas 2013 paper was probably already considered for AR6. The Myhre 2013 reference is a chapter in AR5.
Line 322: What does “well” mean in this context?
Line 323: Unclear sentence “AGWP gives similar impact ranges than common GWP values.”
Line 334: GTP has been discussed in many papers and previous IPCC Assessment Reports (extensively since AR5).
Lines 336-337: I disagree with this point. I don’t see how AGTPpeak solves time-horizon problems. Fundamentally, I think that picking the peak temperature is also a form of value judgment, as is any choice of time horizon.
Lines 342-343: I am afraid that I do not see a valid and convincing argument to recommend AGTPpeak and GTPpeak. One should be free to propose new metrics or a new way of using metrics, but the manuscript does not make it clear why these choices are particularly appropriate for LCA broadly.
Line 353-354: Why do only the peak temperature matter for the impact assessment? The authors should clarify how to deal with the “off-peak” temperature, which should still cause environmental impacts.
Line 357: I do not understand “deltaTpeak can be interpreted as flow pollutants”. Peak temperature appears with an emission of any greenhouse gas.
Line 366: Earlier it was stated that the temperature is clearer to climate non-experts than the radiative forcing, although this is not an exact expression. But here it says the opposite.
Line 406: I think this section is completely out of the scope of this study, as the discussion is only about CO2, without any non-CO2 involved.
Line 462: The purpose of this appendix seems to be mainly to prevent potential confusion between “endpoint” in climate metric literature and that in LCIA. This point can be made only in a few lines in the main text. Hence, I don’t see a need for this Appendix.
Line 463: There is a typo: “As presented in 0”.References
Allen, M. R., Shine, K. P., Fuglestvedt, J. S., Millar, R. J., Cain, M., Frame, D. J., & Macey, A. H. (2018). A solution to the misrepresentations of CO2-equivalent emissions of short-lived climate pollutants under ambitious mitigation. npj Climate and Atmospheric Science, 1(1), 16. doi:10.1038/s41612-018-0026-8
Allen, M. R., Peters, G. P., Shine, K. P., Azar, C., Balcombe, P., Boucher, O., . . . Tanaka, K. (2022). Indicate separate contributions of long-lived and short-lived greenhouse gases in emission targets. npj Climate and Atmospheric Science, 5(1), 5. doi:10.1038/s41612-021-00226-2
Cain, M., Lynch, J., Allen, M. R., Fuglestvedt, J. S., Frame, D. J., & Macey, A. H. (2019). Improved calculation of warming-equivalent emissions for short-lived climate pollutants. npj Climate and Atmospheric Science, 2(1), 29. doi:10.1038/s41612-019-0086-4
Cherubini, F., Fuglestvedt, J., Gasser, T., Reisinger, A., Cavalett, O., Huijbregts, M. A. J., . . . Levasseur, A. (2016a). Bridging the gap between impact assessment methods and climate science. Environmental Science & Policy, 64, 129-140. doi:10.1016/j.envsci.2016.06.019
Cherubini, F., & Tanaka, K. (2016b). Amending the Inadequacy of a Single Indicator for Climate Impact Analyses. Environmental Science & Technology, 50(23), 12530-12531. doi:10.1021/acs.est.6b05343
Edwards, M. R., & Trancik, J. E. (2022). Consequences of equivalency metric design for energy transitions and climate change. Climatic Change, 175(1), 4. doi:10.1007/s10584-022-03442-8
FAO. (2023). Methane emissions in livestock and rice systems – Sources, quantification, mitigation and metrics. doi:10.4060/cc7607en
Frischknecht, R., Fantke, P., Tschümperlin, L., Niero, M., Antón, A., Bare, J., . . . Jolliet, O. (2016). Global guidance on environmental life cycle impact assessment indicators: progress and case study. International Journal of Life Cycle Assessment, 21(3), 429-442.
Iordan, C. M., Verones, F., & Cherubini, F. (2018). Integrating impacts on climate change and biodiversity from forest harvest in Norway. Ecological Indicators, 89, 411-421. doi:10.1016/j.ecolind.2018.02.034
Jolliet, O., Antón, A., Boulay, A.-M., Cherubini, F., Fantke, P., Levasseur, A., . . . Frischknecht, R. (2018). Global guidance on environmental life cycle impact assessment indicators: impacts of climate change, fine particulate matter formation, water consumption and land use. The International Journal of Life Cycle Assessment, 23(11), 2189-2207. doi:10.1007/s11367-018-1443-y
Joos, F., Roth, R., Fuglestvedt, J. S., Peters, G. P., Enting, I. G., von Bloh, W., . . . Weaver, A. J. (2013). Carbon dioxide and climate impulse response functions for the computation of greenhouse gas metrics: a multi-model analysis. Atmospheric Chemistry and Physics, 13(5), 2793-2825. doi:10.5194/acp-13-2793-2013
Levasseur, A., Cavalett, O., Fuglestvedt, J. S., Gasser, T., Johansson, D. J. A., Jørgensen, S. V., . . . Cherubini, F. (2016a). Enhancing life cycle impact assessment from climate science: Review of recent findings and recommendations for application to LCA. Ecological Indicators, 71, 163-174. doi:10.1016/j.ecolind.2016.06.049
Levasseur, A., de Schryver, A., Hauschild, M., Kabe, Y., Sahnoune, A., Tanaka, K., & Cherubini, F. (2016b). Greenhouse gas emissions and climate change impacts. In R. Frischknecht & O. Jolliet (Eds.), Global Guidance for Life Cycle Impact Assessment Indicators (Vol. 1, pp. 59-75). Paris, France: UNEP.
Lynch, J., Cain, M., Pierrehumbert, R., & Allen, M. (2020). Demonstrating GWP*: a means of reporting warming-equivalent emissions that captures the contrasting impacts of short- and long-lived climate pollutants. Environmental Research Letters, 15(4), 044023. doi:10.1088/1748-9326/ab6d7e
Reisinger, A., Meinshausen, M., Manning, M., & Bodeker, G. (2010). Uncertainties of global warming metrics: CO2 and CH4. Geophysical Research Letters, 37(14), L14707. doi:10.1029/2010gl043803
Reisinger, A., Ledgard, S. F., & Falconer, S. J. (2017). Sensitivity of the carbon footprint of New Zealand milk to greenhouse gas metrics. Ecological Indicators, 81(Supplement C), 74-82. doi:10.1016/j.ecolind.2017.04.026
Reisinger, A., Clark, H., Cowie, A. L., Emmet-Booth, J., Gonzalez Fischer, C., Herrero, M., . . . Leahy, S. (2021). How necessary and feasible are reductions of methane emissions from livestock to support stringent temperature goals? Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 379(2210), 20200452. doi:10.1098/rsta.2020.0452
Sterner, E., Johansson, D. J. A., & Azar, C. (2014). Emission metrics and sea level rise. Climatic Change, 127(2), 335-351. doi:10.1007/s10584-014-1258-1
Tanaka, K., Boucher, O., Ciais, P., Johansson, D. J. A., & Morfeldt, J. (2021). Cost-effective implementation of the Paris Agreement using flexible greenhouse gas metrics. Science Advances, 7(22), eabf9020. doi:10.1126/sciadv.abf9020
Tanaka, K., Cavalett, O., Collins, W. J., & Cherubini, F. (2019). Asserting the climate benefits of the coal-to-gas shift across temporal and spatial scales. Nature Climate Change, 9(5), 389-396. doi:10.1038/s41558-019-0457-1Citation: https://doi.org/10.5194/egusphere-2024-3918-RC2
Viewed
HTML | XML | Total | Supplement | BibTeX | EndNote | |
---|---|---|---|---|---|---|
309 | 93 | 8 | 410 | 22 | 7 | 6 |
- HTML: 309
- PDF: 93
- XML: 8
- Total: 410
- Supplement: 22
- BibTeX: 7
- EndNote: 6
Viewed (geographical distribution)
Country | # | Views | % |
---|---|---|---|
United States of America | 1 | 138 | 32 |
France | 2 | 56 | 13 |
China | 3 | 55 | 13 |
Germany | 4 | 26 | 6 |
South Korea | 5 | 20 | 4 |
Total: | 0 |
HTML: | 0 |
PDF: | 0 |
XML: | 0 |
- 1
- 138