the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Predicting the climate impact of aviation for en-route emissions: The algorithmic climate change function submodel ACCF 1.0 of EMAC 2.53
Volker Grewe
Federica Castino
Pratik Rao
Sigrun Matthes
Katrin Dahlmann
Simone Dietmüller
Christine Frömming
Hiroshi Yamashita
Patrick Peter
Emma Klingaman
Keith Shine
Benjamin Lührs
Florian Linke
Abstract. The Modular Earth Submodel System (MESSy) provides an interface to couple submodels to a base model via a modular flexible data management facility. This paper presents the newly developed MESSy submodel, ACCF version 1.0 (ACCF 1.0), based on algorithmic Climate Change Functions version 1.0 (aCCFs 1.0), which describes the climate impact of aviation emissions. The ACCF 1.0 is coupled via the second version of the standard MESSy infrastructure. ACCF 1.0 takes the simulated atmospheric conditions at the location of emission as input to calculate the climate impact (in terms of average temperature response over 20 years (ATR20)) of aviation emissions, including CO2 and non-CO2 impacts, such as from NOx emissions (via ozone production and methane destruction), water vapour emissions, and contrail-cirrus. The online calculated ATR20 value per emitted mass fuel burn or flown-kilometer using ACCF 1.0 in the ECHAM5/MESSy Atmospheric Chemistry (EMAC) model is presented. We perform quality checks of the ACCF 1.0 outputs in two aspects. Firstly, we compare climatological values calculated by the ACCF 1.0 to previous studies. Secondly, we evaluate the reduction of NOx-induced O3 effects through trajectory optimization, employing the tagging chemistry approach (contribution approach to tag species according to their emission categories and to inherit these tags to other species during the subsequent chemical reactions). Finally, we couple the ACCF 1.0 to the air traffic simulation submodel AirTraf version 2.0 and demonstrate the variability of the flight trajectories when the efficacy of individual effect is considered.
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Feijia Yin et al.
Status: closed
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RC1: 'Comment on gmd-2022-220', Anonymous Referee #1, 14 Oct 2022
This study presents the ACCF 1.0 to describe the climate impact of aviation emissions. ACCF 1.0 takes the atmospheric conditions as input to calculate the climate impact, mainly through the average temperature response over 20 years (ATR20). The emissions include , (via and ), vapour, and contrail-cirrus. The study is valuable as it provides an integrated model to assess the environmental impact of the non-CO2 emissions. I have a few comments below:
1.The ACCF 1.0 model is based on the aCCF, which is proposed by the earlier project REACT4C2 for researching the climate change caused by emissions. ACCF works as a sub-model of the global atmospheric-chemistry model EMAC. What new features/functions are developed should be discussed.
2.The application simulation of existing trajectory is conducted to show the climatology impact. They also used the calculation model to optimize the trajectory, from which they draw the conclusion that climate-optimized trajectories considering non-CO2 effects fly lower altitudes to reduce the impact of the total NOx, H2O, and contrails. The scalability of the tool for large-scale problems should be discussed.
3.However, in their scenarios, the CO2-related environmental impact is considered to be lower than the non-CO2 impact, which may limit the possible subsequent applications of the ACCF. Maybe discuss futural models which can provide a comprehensive assessment of climate impact caused by aviation emissions.
Citation: https://doi.org/10.5194/gmd-2022-220-RC1 -
AC1: 'Reply on RC1', Feijia Yin, 03 Mar 2023
We are grateful to referee #1 for the constructive and encouraging comments on the original version of our manuscript. We took all comments into account and revised the manuscript accordingly. Here are our replies:
- Comment: This study presents the ACCF 1.0 to describe the climate impact of aviation emissions. ACCF 1.0 takes the atmospheric conditions as input to calculate the climate impact, mainly through the average temperature response over 20 years (ATR20). The emissions include, (via and), vapour, and contrail-cirrus. The study is valuable as it provides an integrated model to assess the environmental impact of non-CO2 I have a few comments below:
Reply: We thank referee #1 for these positive comments. We have addressed all the comments as follows.
- Comment: The ACCF 1.0 model is based on the aCCF, which was proposed by the earlier project REACT4C2 for researching the climate change caused by emissions. ACCF works as a submodel of the global atmospheric-chemistry model EMAC. What new features/functions are developed should be discussed.
Reply: As the reviewer might have noticed in Figure 1 of this manuscript, there are three stages of work leading to the current version of algorithmic climate change functions (aCCFs by short), which is the core of the ACCF submodel presented in this manuscript.
Stage one: In REACT4C, the original Climate Change Functions (CCFs by short) were developed and implemented for climate optimized flight trajectories, including the effects from CO2, NOx, H2O, and contrail cirrus (Grewe et al., 2014a). The various case studies showed the effectiveness of using CCFs to achieve flight routings with minimum climate impact (Grewe et al. 2014b; Grewe et al. 2017b). The main challenge is that CCFs cannot be directly implemented in trajectory planning tools since generating CCFs requires a heavy computational load.
This brought the work to the second stage to develop algorithmic CCFs in a previous EU project ATM4E (van Manen and Grewe, 2019; Matthes et al., 2017). aCCFs are simplified response models for estimating the climate impact of various aviation emissions (e.g., CO2, H2O and NOx)/effect (day/night contrails). Though the inputs to aCCFs are the original CCFs, the step from CCFs to aCCFs is innovative and essential, as unlike CCFs, aCCFs can be directly implemented in flight planning tools to obtain climate optimized flight trajectories quickly. The aCCFs for NOx and H2O estimating has been well documented by van Manen and Grewe (2019). The approach of developing contrails aCCFs is only made available in the current ACCF v1.0 manuscript as a supplement.
While continuing to the third stage of implementing the aCCFs in the current ACCF V1.0 (FlyATM4E scope), we noticed inconsistencies between the NOx/H2O aCCFs and contrails aCCFs due to different approaches in calculating radiative forcing and the emission scenarios concerned to develop the response models (Pulse vs. future increasing emissions). For details, please see the discussion in section 2 of this manuscript. Therefore, one significant effort in the current manuscript is to diagnose and correct the previous aCCFs models to be consistent.
Long story short, the novelty of the current paper is that we, for the first time, publish: 1) the contrail aCCFs development; 2) a consistent set of aCCFs models in terms of fuel scenario, metric, and efficacy for all species.
- Comment: The application simulation of existing trajectory is conducted to show the climatology impact. They also used the calculation model to optimize the trajectory, from which they draw the conclusion that climate-optimized trajectories considering non-CO2 effects fly lower altitudes to reduce the impact of the total NOx, H2O, and contrails. The scalability of the tool for large-scale problems should be discussed.
Reply: The application study in section 5 is based on a daily simulation. Accordingly, climate-optimized flights tend to reduce their flight altitudes driven by NOx and contrail effects. Regarding the tool's scalability, the quality check in section 4 can be seen as a scalability check of aCCFs models themselves. For instance, in section 4.1, we compared the climatological aCCFs with the literature to confirm that the pattern of aCCFs matches the previous studies. Furthermore, in general, NOx’s climate impact decreases at low altitudes and high latitudes due to shorter residence time or inactive atmospheric chemistry process of NOx. The climate impact of H2O reduces with altitude as well. The effect of contrails is vital in a narrow altitude band following the tropopause height. Following such behavior, we expect the flights with lower climate impact will favor a lower flight altitude than cost-optimal flights. We are performing work based on a year simulation to quantify the mitigation gains regarding climate impact.
- Comment: However, in their scenarios, the CO2-related environmental impact is considered to be lower than the non-CO2 impact, which may limit the possible subsequent applications of the ACCF. Maybe discuss futural models, which can provide a comprehensive assessment of climate impact caused by aviation emissions.
Reply: We agree that the lower CO2 impact estimated from the aCCFs model requires further diagnosis and new developments if required. During our current work, we performed intensive studies to understand the mechanism, and we suspect the reasons could be in the following aspects:
1) Metrics: when we convert the metrics to 100 years’ time horizon instead of 20 years in this paper, we observed an increase in CO2 contribution for the same set of flights.
2) Radiation scheme for developing the original CCFs.
3) Geographical representative: the current research is mainly on European regions. Ongoing research is investigating whether CO2 and non-CO2 relative importance are globally consistent, and this will help us understand better the local representation of aCCFs as well.
We have added one paragraph on page 24 Line 505-508, for this discussion. Please see the track change in the resubmission.
Reference
- Grewe, V., Frömming, C., Matthes, S., Brinkop, S., Ponater, M., Dietmüller, S., Jöckel, P., Garny, H., Tsati, E. and Dahlmann, K. (2014a). "Aircraft routing with minimal climate impact: the REACT4C climate cost function modelling approach (V1. 0)." Geoscientific Model Development, 7(1): 175-201. DOI: https://doi.org/10.5194/gmd-7-175-2014.
- Grewe, V., Champougny, T., Matthes, S., Frömming, C., Brinkop, S., Søvde, O. A., Irvine, E. A. and Halscheidt, L. (2014b). "Reduction of the air traffic's contribution to climate change: A REACT4C case study." Atmospheric Environment, 94: 616-625. DOI: https://doi.org/10.1016/j.atmosenv.2014.05.059.
- Grewe, V., Matthes, S., Frömming, C., Brinkop, S., Jöckel, P., Gierens, K., Champougny, T., Fuglestvedt, J., Haslerud, A., Irvine, E. and Shine, K. (2017b). "Feasibility of climate-optimized air traffic routing for trans-Atlantic flights." Environmental Research Letters, 12(3): 034003. DOI: 10.1088/1748-9326/aa5ba0.
- van Manen, J. and Grewe, V. (2019). "Algorithmic climate change functions for the use in eco-efficient flight planning." Transportation Research Part D: Transport and Environment, 67: 388-405. DOI: https://doi.org/10.1016/j.trd.2018.12.016.
- Matthes, S., Grewe, V., Dahlmann, K., Frömming, C., Irvine, E., Lim, L., Linke, F., Lührs, B., Owen, B., Shine, K., Stromatas, S., Yamashita, H. and Yin, F. (2017). "A Concept for Multi-Criteria Environmental Assessment of Aircraft Trajectories." Aerospace, 4(3): 42.
Citation: https://doi.org/10.5194/gmd-2022-220-AC1
-
AC1: 'Reply on RC1', Feijia Yin, 03 Mar 2023
-
RC2: 'Comment on gmd-2022-220', Anonymous Referee #2, 11 Nov 2022
The paper deals with an interesting approach to the determination of the climate impact on air traffic. The abstract lacks motivation, results and applicability. The first sentence of the abstract has no content. Already in the abstract, there are numerous unexplained abbreviations.
In the introduction, the motivation is based on a 4-year-old prediction. This should be made acute. The state of the art is completely missing. Instead, we find a paragraph with far too many self-citations, which summarises preliminary views of the authorship.
The work is based on Climate costs functions CCF, which is not comprehensibly derived in any of the sources mentioned. The errors of the CCF are not discussed. The transferability to other time periods is very questionable and is not discussed. The scientific amount of Figure 1 to the paper is not made clear. Equations 1 and 2 were copied from Manen and Grewe and should be properly cited. The constant factor 0.0151 K/W/m2 in line 244 should be critically questioned and its error should be critically discussed. The sole distinction between day and night is not sufficient in the context of the Contrail RF and ignores cooling effects during sunrise and sunset. The extreme heterogeneity of the contrail CCFs in Figure 6 supports the assumption that the developed CCFs are extremely weather-dependent and thus not applicable to other time periods. Please explain why the effectiveness in line 285 is not included in the CCF and derive the uncertainty of the effectiveness. In Figure 9, your definition of a cost-optimal and a climate-optimal trajectory is absolutely necessary to understand the procedure. The dents and ripples in the optimised trajectories in Figures 10 and 11 should definitely be explained and critically questioned. All results and assumptions should have been critically questioned and discussed in the conclusions at the latest. An error analysis of such a strongly empirically driven model is absolutely necessary.Citation: https://doi.org/10.5194/gmd-2022-220-RC2 - AC2: 'Reply on RC2', Feijia Yin, 03 Mar 2023
Status: closed
-
RC1: 'Comment on gmd-2022-220', Anonymous Referee #1, 14 Oct 2022
This study presents the ACCF 1.0 to describe the climate impact of aviation emissions. ACCF 1.0 takes the atmospheric conditions as input to calculate the climate impact, mainly through the average temperature response over 20 years (ATR20). The emissions include , (via and ), vapour, and contrail-cirrus. The study is valuable as it provides an integrated model to assess the environmental impact of the non-CO2 emissions. I have a few comments below:
1.The ACCF 1.0 model is based on the aCCF, which is proposed by the earlier project REACT4C2 for researching the climate change caused by emissions. ACCF works as a sub-model of the global atmospheric-chemistry model EMAC. What new features/functions are developed should be discussed.
2.The application simulation of existing trajectory is conducted to show the climatology impact. They also used the calculation model to optimize the trajectory, from which they draw the conclusion that climate-optimized trajectories considering non-CO2 effects fly lower altitudes to reduce the impact of the total NOx, H2O, and contrails. The scalability of the tool for large-scale problems should be discussed.
3.However, in their scenarios, the CO2-related environmental impact is considered to be lower than the non-CO2 impact, which may limit the possible subsequent applications of the ACCF. Maybe discuss futural models which can provide a comprehensive assessment of climate impact caused by aviation emissions.
Citation: https://doi.org/10.5194/gmd-2022-220-RC1 -
AC1: 'Reply on RC1', Feijia Yin, 03 Mar 2023
We are grateful to referee #1 for the constructive and encouraging comments on the original version of our manuscript. We took all comments into account and revised the manuscript accordingly. Here are our replies:
- Comment: This study presents the ACCF 1.0 to describe the climate impact of aviation emissions. ACCF 1.0 takes the atmospheric conditions as input to calculate the climate impact, mainly through the average temperature response over 20 years (ATR20). The emissions include, (via and), vapour, and contrail-cirrus. The study is valuable as it provides an integrated model to assess the environmental impact of non-CO2 I have a few comments below:
Reply: We thank referee #1 for these positive comments. We have addressed all the comments as follows.
- Comment: The ACCF 1.0 model is based on the aCCF, which was proposed by the earlier project REACT4C2 for researching the climate change caused by emissions. ACCF works as a submodel of the global atmospheric-chemistry model EMAC. What new features/functions are developed should be discussed.
Reply: As the reviewer might have noticed in Figure 1 of this manuscript, there are three stages of work leading to the current version of algorithmic climate change functions (aCCFs by short), which is the core of the ACCF submodel presented in this manuscript.
Stage one: In REACT4C, the original Climate Change Functions (CCFs by short) were developed and implemented for climate optimized flight trajectories, including the effects from CO2, NOx, H2O, and contrail cirrus (Grewe et al., 2014a). The various case studies showed the effectiveness of using CCFs to achieve flight routings with minimum climate impact (Grewe et al. 2014b; Grewe et al. 2017b). The main challenge is that CCFs cannot be directly implemented in trajectory planning tools since generating CCFs requires a heavy computational load.
This brought the work to the second stage to develop algorithmic CCFs in a previous EU project ATM4E (van Manen and Grewe, 2019; Matthes et al., 2017). aCCFs are simplified response models for estimating the climate impact of various aviation emissions (e.g., CO2, H2O and NOx)/effect (day/night contrails). Though the inputs to aCCFs are the original CCFs, the step from CCFs to aCCFs is innovative and essential, as unlike CCFs, aCCFs can be directly implemented in flight planning tools to obtain climate optimized flight trajectories quickly. The aCCFs for NOx and H2O estimating has been well documented by van Manen and Grewe (2019). The approach of developing contrails aCCFs is only made available in the current ACCF v1.0 manuscript as a supplement.
While continuing to the third stage of implementing the aCCFs in the current ACCF V1.0 (FlyATM4E scope), we noticed inconsistencies between the NOx/H2O aCCFs and contrails aCCFs due to different approaches in calculating radiative forcing and the emission scenarios concerned to develop the response models (Pulse vs. future increasing emissions). For details, please see the discussion in section 2 of this manuscript. Therefore, one significant effort in the current manuscript is to diagnose and correct the previous aCCFs models to be consistent.
Long story short, the novelty of the current paper is that we, for the first time, publish: 1) the contrail aCCFs development; 2) a consistent set of aCCFs models in terms of fuel scenario, metric, and efficacy for all species.
- Comment: The application simulation of existing trajectory is conducted to show the climatology impact. They also used the calculation model to optimize the trajectory, from which they draw the conclusion that climate-optimized trajectories considering non-CO2 effects fly lower altitudes to reduce the impact of the total NOx, H2O, and contrails. The scalability of the tool for large-scale problems should be discussed.
Reply: The application study in section 5 is based on a daily simulation. Accordingly, climate-optimized flights tend to reduce their flight altitudes driven by NOx and contrail effects. Regarding the tool's scalability, the quality check in section 4 can be seen as a scalability check of aCCFs models themselves. For instance, in section 4.1, we compared the climatological aCCFs with the literature to confirm that the pattern of aCCFs matches the previous studies. Furthermore, in general, NOx’s climate impact decreases at low altitudes and high latitudes due to shorter residence time or inactive atmospheric chemistry process of NOx. The climate impact of H2O reduces with altitude as well. The effect of contrails is vital in a narrow altitude band following the tropopause height. Following such behavior, we expect the flights with lower climate impact will favor a lower flight altitude than cost-optimal flights. We are performing work based on a year simulation to quantify the mitigation gains regarding climate impact.
- Comment: However, in their scenarios, the CO2-related environmental impact is considered to be lower than the non-CO2 impact, which may limit the possible subsequent applications of the ACCF. Maybe discuss futural models, which can provide a comprehensive assessment of climate impact caused by aviation emissions.
Reply: We agree that the lower CO2 impact estimated from the aCCFs model requires further diagnosis and new developments if required. During our current work, we performed intensive studies to understand the mechanism, and we suspect the reasons could be in the following aspects:
1) Metrics: when we convert the metrics to 100 years’ time horizon instead of 20 years in this paper, we observed an increase in CO2 contribution for the same set of flights.
2) Radiation scheme for developing the original CCFs.
3) Geographical representative: the current research is mainly on European regions. Ongoing research is investigating whether CO2 and non-CO2 relative importance are globally consistent, and this will help us understand better the local representation of aCCFs as well.
We have added one paragraph on page 24 Line 505-508, for this discussion. Please see the track change in the resubmission.
Reference
- Grewe, V., Frömming, C., Matthes, S., Brinkop, S., Ponater, M., Dietmüller, S., Jöckel, P., Garny, H., Tsati, E. and Dahlmann, K. (2014a). "Aircraft routing with minimal climate impact: the REACT4C climate cost function modelling approach (V1. 0)." Geoscientific Model Development, 7(1): 175-201. DOI: https://doi.org/10.5194/gmd-7-175-2014.
- Grewe, V., Champougny, T., Matthes, S., Frömming, C., Brinkop, S., Søvde, O. A., Irvine, E. A. and Halscheidt, L. (2014b). "Reduction of the air traffic's contribution to climate change: A REACT4C case study." Atmospheric Environment, 94: 616-625. DOI: https://doi.org/10.1016/j.atmosenv.2014.05.059.
- Grewe, V., Matthes, S., Frömming, C., Brinkop, S., Jöckel, P., Gierens, K., Champougny, T., Fuglestvedt, J., Haslerud, A., Irvine, E. and Shine, K. (2017b). "Feasibility of climate-optimized air traffic routing for trans-Atlantic flights." Environmental Research Letters, 12(3): 034003. DOI: 10.1088/1748-9326/aa5ba0.
- van Manen, J. and Grewe, V. (2019). "Algorithmic climate change functions for the use in eco-efficient flight planning." Transportation Research Part D: Transport and Environment, 67: 388-405. DOI: https://doi.org/10.1016/j.trd.2018.12.016.
- Matthes, S., Grewe, V., Dahlmann, K., Frömming, C., Irvine, E., Lim, L., Linke, F., Lührs, B., Owen, B., Shine, K., Stromatas, S., Yamashita, H. and Yin, F. (2017). "A Concept for Multi-Criteria Environmental Assessment of Aircraft Trajectories." Aerospace, 4(3): 42.
Citation: https://doi.org/10.5194/gmd-2022-220-AC1
-
AC1: 'Reply on RC1', Feijia Yin, 03 Mar 2023
-
RC2: 'Comment on gmd-2022-220', Anonymous Referee #2, 11 Nov 2022
The paper deals with an interesting approach to the determination of the climate impact on air traffic. The abstract lacks motivation, results and applicability. The first sentence of the abstract has no content. Already in the abstract, there are numerous unexplained abbreviations.
In the introduction, the motivation is based on a 4-year-old prediction. This should be made acute. The state of the art is completely missing. Instead, we find a paragraph with far too many self-citations, which summarises preliminary views of the authorship.
The work is based on Climate costs functions CCF, which is not comprehensibly derived in any of the sources mentioned. The errors of the CCF are not discussed. The transferability to other time periods is very questionable and is not discussed. The scientific amount of Figure 1 to the paper is not made clear. Equations 1 and 2 were copied from Manen and Grewe and should be properly cited. The constant factor 0.0151 K/W/m2 in line 244 should be critically questioned and its error should be critically discussed. The sole distinction between day and night is not sufficient in the context of the Contrail RF and ignores cooling effects during sunrise and sunset. The extreme heterogeneity of the contrail CCFs in Figure 6 supports the assumption that the developed CCFs are extremely weather-dependent and thus not applicable to other time periods. Please explain why the effectiveness in line 285 is not included in the CCF and derive the uncertainty of the effectiveness. In Figure 9, your definition of a cost-optimal and a climate-optimal trajectory is absolutely necessary to understand the procedure. The dents and ripples in the optimised trajectories in Figures 10 and 11 should definitely be explained and critically questioned. All results and assumptions should have been critically questioned and discussed in the conclusions at the latest. An error analysis of such a strongly empirically driven model is absolutely necessary.Citation: https://doi.org/10.5194/gmd-2022-220-RC2 - AC2: 'Reply on RC2', Feijia Yin, 03 Mar 2023
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