the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 08 Aug 2024
Accounting for Black Carbon Aging Process in a Two-way Coupled Meteorology – Air Quality Model
Abstract. Black carbon (BC) exerts significant impacts on both climate and environment. BC aging process alters its hygroscopicity and light absorption properties. Current models, like the Weather Research and Forecasting – Community Multiscale Air Quality (WRF-CMAQ) two-way coupled model, inadequately characterize these alterations. In this study, we accounted for BC aging process in the WRF-CMAQ model (WRF-CMAQ-BCG). We introduced two new species (Bare BC and Coated BC) in the model and implemented a module to simulate the conversion from Bare BC to Coated BC, thereby characterizing the aging process. Furthermore, we improved the cloud chemistry and aerosol optics modules to analyze the effects of BC aging on hydrophobicity and light absorption. The simulated results indicate a spatial distribution pattern with Bare BC prevalent near emission sources and Coated BC more common farther from sources. The average Number Fraction of Coated BC (NFcoated) is approximately 57 %. Temporal variation exhibits a distinct diurnal pattern, with NFcoated increasing during the daytime. The spatial distribution of wet deposition varies significantly between Bare and Coated BC. Bare BC exhibits a point-like deposition pattern, whereas Coated BC displays a zonal distribution. Notably, Coated BC dominates the BC wet deposition process. Additionally, incorporating BC aging process reduces BC wet deposition by 17.7 % and increases BC column concentration by 10.5 %. The simulated Mass Absorption Cross-section (MAC) value improved agreement with observed measurements. Overall, the WRF-CMAQ-BCG model enhances the capability to analyze aging-related variables and BC mixing state, while also improving performance in wet deposition and optical properties.
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Notice on discussion status
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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Preprint
(2433 KB)
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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.
- Preprint
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- Final revised paper
Journal article(s) based on this preprint
Interactive discussion
Status: closed
-
RC1: 'Review Comment on egusphere-2024-2372', Anonymous Referee #1, 27 Aug 2024
The authors implemented a BC aging scheme into the WRF-CMAQ model and found that accounting for BC aging process improves simulated BC optical properties. They also found that adding the aging process significantly affect BC concentration distribution and wet deposition. Overall, the manuscript is well organized and the study fits well into the journal scope. However, there are a few places that require further descriptions and clarifications. I have a few comments and suggestions below for the authors to consider.
Major comments:
- The major concern I have is the insufficient model evaluation. Currently, the authors only evaluated the model simulation at one measurement sites, while all their modeling analysis and conclusions come from regional results. Thus, regional-scale evaluation is needed, such as evaluations using IMPROVE aerosol measurement network, AERONET AOD/AAOD measurement network, EPA AirNow network, and/or MODIS AOD data.
Specific comments:
- Lines 87-88: This “limited impact” is not accurate, since different BC mixing states affect aerosol hygroscopicity and hence wet deposition, which subsequently change the mass concentration.
- Line 103: “… coated with scattering aerosol component”. This is not very accurate since BC can also be coated by some absorbing organics.
- Line 108: Even for two-way coupled WRF-CMAQ model, there is no aerosol indirect effect considered? Did the authors mean the standard EPA-version of WRF-CMAQ? There might be a WRF-CMAQ version from individual research group that may already have this capability. Please double check.
- In Figures 1 and 2, the authors showed that the model includes aerosol-cloud interaction, but in the description of Section 2.1, it seems that the model does not account for the aerosol indirect effect. This needs further clarification.
- Equation (3): Which term is for condensation (fast-aging)? It seems that the first beta*[OH] term represents chemical aging and alpha represents coagulation.
- Section 2.3: the use of “cloud chemistry” is confusing since BC does not undergo any chemical process in the cloud droplets in the model. Also, the description of this part is not very clear. How did the authors set the hydrophobicity of coated BC? What scheme did the authors use to compute CCN from aerosol number concentration and hygroscopicity? What equations did the authors use to compute the impact scavenging of BC aerosol? More details are needed.
- Section 2.4: It is not clear that how the authors compute the number concentrations of bare and coated BC. (1) Are these number concentrations two new prognostic variables tracked by the model? What are the size distributions of bare and coated BC particles used during the mass-to-number conversion? More clarifications are needed. (2) Another key uncertainty factor related to the calculation of BC optics is the particle structure. Many previous studies have shown that using core-shell assumption for coated BC and spherical shape for bare BC cannot realistically represent BC particle optics (e.g., https://doi.org/10.1029/2021GL096437; https://doi-org.cuucar.idm.oclc.org/10.1021/acs.estlett.7b00418; https://doi.org/10.5194/acp-15-11967-2015). It may be challenging to add the particle structure info into the model, but some discussions on this uncertainty factor will be helpful.
- Lines 220-221: How sensitive the model results are to the assumption of equal fraction of bare and coated BC in the initial and boundary conditions?
- Line 223: “the model assimilated data” Did the authors mean they also used data assimilation in their model simulations? Did the authors conduct 3 different simulations by using these 3 datasets (FNL, NAM, and NARR), respectively?
- Figures 4-5: It seems that including BC aging only has negligible benefits on model performance. How to better justify the need to include this aging scheme?
Citation: https://doi.org/10.5194/egusphere-2024-2372-RC1 - AC1: 'Reply on RC1', Jiandong Wang, 20 Nov 2024
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RC2: 'Comment on egusphere-2024-2372', Anonymous Referee #2, 08 Oct 2024
Review of “Accounting for black carbon aging process in a two-way coupled meteorology – air quality model” by Y. Jin et al.
In this study, a BC aging parameterization was implemented into the WRF-CMAQ model. BC aging processes are important for accurately estimating the spatial distribution, atmospheric lifetime, optical properties, and activation to cloud particles of BC. While BC has been treated as internally mixed particles in CMAQ, the authors have classified BC into externally mixed and internally mixed particles and introduced an aging parameterization for converting externally mixed particles to internally mixed particles, as well as a scheme for calculating the differences in cloud activation and optical properties between externally mixed and internally mixed BC particles. This study contains interesting aspects as a BC modeling study. However, many similar studies have been published in the last 15 years, and this study lacks scientific novelty. Considering this point, I cannot recommend this study as an ACP paper.
Major comments:
1) The introduction is generally well structured and covers the important previous studies. However, the model developed in this study has already been developed and used in the papers listed in the introduction, indicating that this study lacks scientific originality. It can be said that the optical property part is relatively new, but there have already been many studies focusing on the differences in light absorption efficiency caused by the mixing state of BC particles.
Is it considered that this research is not new scientifically, but new to the CMAQ model? Or does it contain some new scientific findings? I think this research falls into the former category. In that case, this study is not appropriate for ACP. I strongly recommend that the authors submit this study to another model development journal (e.g., GMD).2) Related to the comment above, the BC aging parameterization used in this study is the same as that developed and used in previous studies, and there is nothing new about it. In addition, the methods section needs substantial revision because there are many things that are not adequately described. For example, does the model treat aerosols that do not contain BC (BC-free particles) in the accumulation mode? Considering BC-free particles is important for estimating the mixing state and optical properties of BC, but it is not clear from the text how the model distinguishes non-BC species between BC-containing particles (used for coating) and BC-free particles (see comment 4 below).
Other comments:
3) L41: formation or altering -> formation and altering
4) L144: Figure 2: Are BC-free particles considered in the accumulation mode? In Figure 2, it appears that BC-free particles are treated as scattering aerosols. If so, how are scattering aerosols in coated BC and scattering aerosols (BC-free particles) treated in the model? Are they treated as separate aerosol variables?
5) L167-168: It is not correct to assume that the aging speed of coagulation is constant. Coagulation occurs very fast near sources and has a large contribution to BC aging. The speed of coagulation aging is highly dependent on aerosol concentrations.
6) L178: What are the particle size distributions of Bare BC and Coated BC? They should have different dry deposition speed because their particle size distributions are different due to the coating species and water uptake.
7) L181: Do you use “precipitation scavenging” and “impact scavenging” with different meanings or the same meaning?
8) L194: in direct radiative forcing -> in estimating direct radiative effect
9) L221: Are all BC emissions treated as externally mixed particles?
10) L267-269: Figure 6a: Why is this spatial distribution obtained?
11) L278-279: Again, are all BC emissions treated as externally mixed particles?
12) Figure 8: The unit of the vertical axis is unclear. This is only a qualitative evaluation, and a quantitative evaluation is needed.
13) L319-320: This description is probably incorrect. Aerosols are transported over long distances in a few days, so I think the speed of aging is not related to Fig. 9a. I think this is because in-cloud scavenging is not considered (only below-cloud scavenging is considered).
14) Figure 13: Why don't you show the time series plot for MAC?
Citation: https://doi.org/10.5194/egusphere-2024-2372-RC2 - AC2: 'Reply on RC2', Jiandong Wang, 20 Nov 2024
-
EC1: 'Comment on egusphere-2024-2372 from Editor', Pablo Saide, 14 Oct 2024
I advise the authors to provide an extended discussion considering all referees comments, especially considering one of the referee's criticism of novelty associated to BC ageing being previously modeled with similar methods.
Citation: https://doi.org/10.5194/egusphere-2024-2372-EC1 - AC3: 'Reply on EC1', Jiandong Wang, 20 Nov 2024
Interactive discussion
Status: closed
-
RC1: 'Review Comment on egusphere-2024-2372', Anonymous Referee #1, 27 Aug 2024
The authors implemented a BC aging scheme into the WRF-CMAQ model and found that accounting for BC aging process improves simulated BC optical properties. They also found that adding the aging process significantly affect BC concentration distribution and wet deposition. Overall, the manuscript is well organized and the study fits well into the journal scope. However, there are a few places that require further descriptions and clarifications. I have a few comments and suggestions below for the authors to consider.
Major comments:
- The major concern I have is the insufficient model evaluation. Currently, the authors only evaluated the model simulation at one measurement sites, while all their modeling analysis and conclusions come from regional results. Thus, regional-scale evaluation is needed, such as evaluations using IMPROVE aerosol measurement network, AERONET AOD/AAOD measurement network, EPA AirNow network, and/or MODIS AOD data.
Specific comments:
- Lines 87-88: This “limited impact” is not accurate, since different BC mixing states affect aerosol hygroscopicity and hence wet deposition, which subsequently change the mass concentration.
- Line 103: “… coated with scattering aerosol component”. This is not very accurate since BC can also be coated by some absorbing organics.
- Line 108: Even for two-way coupled WRF-CMAQ model, there is no aerosol indirect effect considered? Did the authors mean the standard EPA-version of WRF-CMAQ? There might be a WRF-CMAQ version from individual research group that may already have this capability. Please double check.
- In Figures 1 and 2, the authors showed that the model includes aerosol-cloud interaction, but in the description of Section 2.1, it seems that the model does not account for the aerosol indirect effect. This needs further clarification.
- Equation (3): Which term is for condensation (fast-aging)? It seems that the first beta*[OH] term represents chemical aging and alpha represents coagulation.
- Section 2.3: the use of “cloud chemistry” is confusing since BC does not undergo any chemical process in the cloud droplets in the model. Also, the description of this part is not very clear. How did the authors set the hydrophobicity of coated BC? What scheme did the authors use to compute CCN from aerosol number concentration and hygroscopicity? What equations did the authors use to compute the impact scavenging of BC aerosol? More details are needed.
- Section 2.4: It is not clear that how the authors compute the number concentrations of bare and coated BC. (1) Are these number concentrations two new prognostic variables tracked by the model? What are the size distributions of bare and coated BC particles used during the mass-to-number conversion? More clarifications are needed. (2) Another key uncertainty factor related to the calculation of BC optics is the particle structure. Many previous studies have shown that using core-shell assumption for coated BC and spherical shape for bare BC cannot realistically represent BC particle optics (e.g., https://doi.org/10.1029/2021GL096437; https://doi-org.cuucar.idm.oclc.org/10.1021/acs.estlett.7b00418; https://doi.org/10.5194/acp-15-11967-2015). It may be challenging to add the particle structure info into the model, but some discussions on this uncertainty factor will be helpful.
- Lines 220-221: How sensitive the model results are to the assumption of equal fraction of bare and coated BC in the initial and boundary conditions?
- Line 223: “the model assimilated data” Did the authors mean they also used data assimilation in their model simulations? Did the authors conduct 3 different simulations by using these 3 datasets (FNL, NAM, and NARR), respectively?
- Figures 4-5: It seems that including BC aging only has negligible benefits on model performance. How to better justify the need to include this aging scheme?
Citation: https://doi.org/10.5194/egusphere-2024-2372-RC1 - AC1: 'Reply on RC1', Jiandong Wang, 20 Nov 2024
-
RC2: 'Comment on egusphere-2024-2372', Anonymous Referee #2, 08 Oct 2024
Review of “Accounting for black carbon aging process in a two-way coupled meteorology – air quality model” by Y. Jin et al.
In this study, a BC aging parameterization was implemented into the WRF-CMAQ model. BC aging processes are important for accurately estimating the spatial distribution, atmospheric lifetime, optical properties, and activation to cloud particles of BC. While BC has been treated as internally mixed particles in CMAQ, the authors have classified BC into externally mixed and internally mixed particles and introduced an aging parameterization for converting externally mixed particles to internally mixed particles, as well as a scheme for calculating the differences in cloud activation and optical properties between externally mixed and internally mixed BC particles. This study contains interesting aspects as a BC modeling study. However, many similar studies have been published in the last 15 years, and this study lacks scientific novelty. Considering this point, I cannot recommend this study as an ACP paper.
Major comments:
1) The introduction is generally well structured and covers the important previous studies. However, the model developed in this study has already been developed and used in the papers listed in the introduction, indicating that this study lacks scientific originality. It can be said that the optical property part is relatively new, but there have already been many studies focusing on the differences in light absorption efficiency caused by the mixing state of BC particles.
Is it considered that this research is not new scientifically, but new to the CMAQ model? Or does it contain some new scientific findings? I think this research falls into the former category. In that case, this study is not appropriate for ACP. I strongly recommend that the authors submit this study to another model development journal (e.g., GMD).2) Related to the comment above, the BC aging parameterization used in this study is the same as that developed and used in previous studies, and there is nothing new about it. In addition, the methods section needs substantial revision because there are many things that are not adequately described. For example, does the model treat aerosols that do not contain BC (BC-free particles) in the accumulation mode? Considering BC-free particles is important for estimating the mixing state and optical properties of BC, but it is not clear from the text how the model distinguishes non-BC species between BC-containing particles (used for coating) and BC-free particles (see comment 4 below).
Other comments:
3) L41: formation or altering -> formation and altering
4) L144: Figure 2: Are BC-free particles considered in the accumulation mode? In Figure 2, it appears that BC-free particles are treated as scattering aerosols. If so, how are scattering aerosols in coated BC and scattering aerosols (BC-free particles) treated in the model? Are they treated as separate aerosol variables?
5) L167-168: It is not correct to assume that the aging speed of coagulation is constant. Coagulation occurs very fast near sources and has a large contribution to BC aging. The speed of coagulation aging is highly dependent on aerosol concentrations.
6) L178: What are the particle size distributions of Bare BC and Coated BC? They should have different dry deposition speed because their particle size distributions are different due to the coating species and water uptake.
7) L181: Do you use “precipitation scavenging” and “impact scavenging” with different meanings or the same meaning?
8) L194: in direct radiative forcing -> in estimating direct radiative effect
9) L221: Are all BC emissions treated as externally mixed particles?
10) L267-269: Figure 6a: Why is this spatial distribution obtained?
11) L278-279: Again, are all BC emissions treated as externally mixed particles?
12) Figure 8: The unit of the vertical axis is unclear. This is only a qualitative evaluation, and a quantitative evaluation is needed.
13) L319-320: This description is probably incorrect. Aerosols are transported over long distances in a few days, so I think the speed of aging is not related to Fig. 9a. I think this is because in-cloud scavenging is not considered (only below-cloud scavenging is considered).
14) Figure 13: Why don't you show the time series plot for MAC?
Citation: https://doi.org/10.5194/egusphere-2024-2372-RC2 - AC2: 'Reply on RC2', Jiandong Wang, 20 Nov 2024
-
EC1: 'Comment on egusphere-2024-2372 from Editor', Pablo Saide, 14 Oct 2024
I advise the authors to provide an extended discussion considering all referees comments, especially considering one of the referee's criticism of novelty associated to BC ageing being previously modeled with similar methods.
Citation: https://doi.org/10.5194/egusphere-2024-2372-EC1 - AC3: 'Reply on EC1', Jiandong Wang, 20 Nov 2024
Peer review completion
Journal article(s) based on this preprint
Data sets
The WRF-CMAQ-BCG model data Yuzhi Jin et al. https://zenodo.org/doi/10.5281/zenodo.12798177
Model code and software
The WRF-CMAQ-BCG model code Yuzhi Jin et al. https://zenodo.org/doi/10.5281/zenodo.12798673
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Yuzhi Jin
David C. Wong
Chao Liu
Golam Sarwar
Kathleen M. Fahey
Shang Wu
Jiaping Wang
Jing Cai
Zeyuan Tian
Zhouyang Zhang
Jia Xing
Aijun Ding
Shuxiao Wang
The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
- Preprint
(2433 KB) - Metadata XML