the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 02 Jul 2024
Modeling of PAHs From Global to Regional Scales: Model Development and Investigation of Health Risks from 2013 to 2018 in China
Abstract. Polycyclic aromatic hydrocarbons (PAHs) significantly impact human health due to their persistence, toxicity, and potential carcinogenicity. Their global distribution and regional changes caused by emission changes, especially over areas in developing countries, remain to be understood along with their health impacts. This study implemented a PAH module in the global-regional nested Atmospheric Aerosol and Chemistry Model (IAP-AACM) to investigate the global distribution of PAHs and the change in their health risks from 2013 to 2018 in China. An evaluation against observations showed that the model could capture well the spatial distribution and seasonal variation of Benzo[a]pyrene (BaP), the typical indicator species of PAHs. At a global scale, the annual mean concentrations are highest in China, followed by Europe and India, with high values exceeding the target values of 1 ng m-3 over some areas. Compared with 2013, the concentration of BaP in China decreased in 2018 due to emission reductions, whereas it increased in India and Southern Africa. However, the decline is much smaller than for PM2.5 during the same period. The concentration of BaP decreased by 8.5 % in Beijing-Tianjin-Hebei (BTH) and 9.4 % in the Yangtze River Delta (YRD). It even increased over areas in the Sichuan Basin due to changes in meteorological conditions. The total incremental lifetime cancer risk (ILCR) posed by BaP only showed a slight decrease in 2018 and the population in East China still faced significant potential health risks. The results indicate that strict additional control measures should be taken to reduce the pollution and health risks of PAHs effectively. The study also highlights the importance of considering changes in meteorological conditions when evaluating emission changes from concentration monitoring.
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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
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Supplement
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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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(2096 KB) - BibTeX
- EndNote
- Final revised paper
Journal article(s) based on this preprint
Interactive discussion
Status: closed
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CEC1: 'Comment on egusphere-2024-1437', Astrid Kerkweg, 15 Jul 2024
Dear authors,
in my role as Executive editor of GMD, I would like to bring to your attention our Editorial version 1.2: https://www.geosci-model-dev.net/12/2215/2019/
This highlights some requirements of papers published in GMD, which is also available on the GMD website in the ‘Manuscript Types’ section: http://www.geoscientific-model-development.net/submission/manuscript_types.html
In particular, please note that for your paper, the following requirements have not been met in the Discussions paper:
- "The main paper must give the model name and version number (or other unique identifier) in the title."
- “If the model development relates to a single model then the model name and the version number must be included in the title of the paper. If the main intention of an article is to make a general (i.e. model independent) statement about the usefulness of a new development, but the usefulness is shown with the help of one specific model, the model name and version number must be stated in the title. The title could have a form such as, “Title outlining amazing generic advance: a case study with Model XXX (version Y)”.''
Thus, please add the model name and the version identifier to the title of you manuscript in your revised submission to GMD.
Yours, Astrid Kerkweg
Citation: https://doi.org/10.5194/egusphere-2024-1437-CEC1 - AC3: 'Reply on CEC1', Xueshun Chen, 17 Oct 2024
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RC1: 'Comment on egusphere-2024-1437', Anonymous Referee #1, 17 Jul 2024
This study employed an improved global-regional nested Atmospheric Aerosol and Chemistry Model (IAP-AACM) to investigate the global distribution of PAHs and the health risk in 2013 and 2018, respectively. The new developed model includes more parameterized processes and shows satisfied simulation results. The results reveal a decline of PAH concentration in most area of China except Sichuan Basin, attributed to meteorology conditions. However, the total incremental lifetime cancer risk posed by BaP only show a slight decrease and the health risks still exist especially in East China. All the findings indicate more tough control measures for PAH when considering both pollution and public health. Besides, meteorology factors play an important role when assessing the control measures for concentration measuring.
The paper is well structured and contributes importance for air pollution and health risks. However, there are several limitations outlined below that need to be addressed before considering it for publication.
Major comments:
- The title as well as main text of this paper shows the analysis results “ from 2013 to 2018”, while the simulation tests were performed for 2013 and 2018, respectively. Therefore, the expression is ambiguous.
- In abstract, Line 28-29, the study concluded the decrease for BaP is smaller than PM2.5 during the same period. However, it seems no analysis was performed in section4 to support this conclusion.
- Is the computation for TILCR consider the population data for each simulation resolution? From formulation 14-18, there are no population data related but in Line 214-216, the population data were used.
- 9 shows the distribution of TILCR. As shown in formula (18), the TILCR is calculated for children, women and men, respectively. Is the TILSR in Fig.9 calculated with the number of children, women and men as weight? If so, please clarify how to obtain the TILCR in this figure.
- Line 436-437, “It can be seen that the spatial distribution of TILCR (Fig. 9a) is consistent with the spatial distribution of the BaP annual concentrations”. According to the formula (14)-(18), the TILCR seems to be proportional with the concentration of PAHs, as the other parameters have fixed values, so the TILCR should be consistent with Fig.7. The same problem also exists regard to Fig.10. The differences between children, women and men depends on the coefficients in formula (14)-(17). In my understanding, the conclusion can be obtained directly from these formulas. Please elaborate more about the meaning of these two figures.
- In part 4.3, the author wants to show the health risks of PAHs. I think it’s better to add a figure of the distribution of health risk grade in China for a more intuitive understanding.
- Formulation (14) lacks the explanation for parameter AF and CF.
- Line 507, it should be YRD, not YRH.
- 7, the figure annotation has some errors. Simulated concentrations are in orange not red and observed values are in blue not lack, please check.
Citation: https://doi.org/10.5194/egusphere-2024-1437-RC1 -
AC1: 'Reply on RC1', Xueshun Chen, 17 Oct 2024
Dear Editor and Reviewer:
Thank you very much for your insightful comments and valuable suggestions concerning our manuscript “Modeling of PAHs From Global to Regional Scales: Model Development and Investigation of Health Risks from 2013 to 2018 in China” (MS No.: EGUSPHERE-2024-1437). Those positive comments are all very valuable and helpful for revising and improving our manuscript. The detailed point-by-point responses are presented in the supplement.
On behalf of all authors, best regards,
Xueshun Chen
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RC2: 'Comment on egusphere-2024-1437', Anonymous Referee #2, 22 Sep 2024
Title: Modeling of PAHs From Global to Regional Scales: Model Development and Investigation of Health Risks from 2013 to 2018 in China
The study investigates the global distribution of polycyclic aromatic hydrocarbons (PAHs) and their health risks, focusing on China from 2013 to 2018. Using the IAP-AACM model, the authors evaluate the spatial and seasonal distribution of BaP, a key PAH indicator. The authors show BaP concentrations have decreased in China due to emission reductions but increased in India and Southern Africa. Despite the reductions, the health risks in China, particularly in East China, remain significant.
By developing a PAH module, the study offers significant insights into PAH distribution and health risks, providing valuable insights into PAH trends across developing regions. I am happy to see its publication in due course. I would like to suggest some minor revisions after addressing the following questions:
（1）The authors should justify the capability of the EDGAR inventory to capture the short-term emission changes between 2013-2018 at the regional scale.
（2）Figure 8 looks like just a zooming in of Figure 4 with a focus over China. Again, how to verify the very local changes in Figure 8?
（3）In Figures10-12, it is not easy for the readers to understand the abbreviation of each province.
（4）I am wondering what’s the motivation to focus on the PAH health risks over China, and it is possible to include more developing regions?
（5）In terms of PAH control, I suggest to add more policy-related discussions. For example, more specific measures could be proposed.
Citation: https://doi.org/10.5194/egusphere-2024-1437-RC2 -
AC2: 'Reply on RC2', Xueshun Chen, 17 Oct 2024
Dear Editor and Reviewer:
Thank you very much for your detailed and constructive comments and suggestions for our “Modeling of PAHs From Global to Regional Scales: Model Development and Investigation of Health Risks from 2013 to 2018 in China” (MS No.: EGUSPHERE-2024-1437). Those positive comments are all very valuable and helpful for revising and improving our manuscript. The detailed point-by-point responses are presented in the supplement.
On behalf of all authors, best regards,
Xueshun Chen
-
AC2: 'Reply on RC2', Xueshun Chen, 17 Oct 2024
Interactive discussion
Status: closed
-
CEC1: 'Comment on egusphere-2024-1437', Astrid Kerkweg, 15 Jul 2024
Dear authors,
in my role as Executive editor of GMD, I would like to bring to your attention our Editorial version 1.2: https://www.geosci-model-dev.net/12/2215/2019/
This highlights some requirements of papers published in GMD, which is also available on the GMD website in the ‘Manuscript Types’ section: http://www.geoscientific-model-development.net/submission/manuscript_types.html
In particular, please note that for your paper, the following requirements have not been met in the Discussions paper:
- "The main paper must give the model name and version number (or other unique identifier) in the title."
- “If the model development relates to a single model then the model name and the version number must be included in the title of the paper. If the main intention of an article is to make a general (i.e. model independent) statement about the usefulness of a new development, but the usefulness is shown with the help of one specific model, the model name and version number must be stated in the title. The title could have a form such as, “Title outlining amazing generic advance: a case study with Model XXX (version Y)”.''
Thus, please add the model name and the version identifier to the title of you manuscript in your revised submission to GMD.
Yours, Astrid Kerkweg
Citation: https://doi.org/10.5194/egusphere-2024-1437-CEC1 - AC3: 'Reply on CEC1', Xueshun Chen, 17 Oct 2024
-
RC1: 'Comment on egusphere-2024-1437', Anonymous Referee #1, 17 Jul 2024
This study employed an improved global-regional nested Atmospheric Aerosol and Chemistry Model (IAP-AACM) to investigate the global distribution of PAHs and the health risk in 2013 and 2018, respectively. The new developed model includes more parameterized processes and shows satisfied simulation results. The results reveal a decline of PAH concentration in most area of China except Sichuan Basin, attributed to meteorology conditions. However, the total incremental lifetime cancer risk posed by BaP only show a slight decrease and the health risks still exist especially in East China. All the findings indicate more tough control measures for PAH when considering both pollution and public health. Besides, meteorology factors play an important role when assessing the control measures for concentration measuring.
The paper is well structured and contributes importance for air pollution and health risks. However, there are several limitations outlined below that need to be addressed before considering it for publication.
Major comments:
- The title as well as main text of this paper shows the analysis results “ from 2013 to 2018”, while the simulation tests were performed for 2013 and 2018, respectively. Therefore, the expression is ambiguous.
- In abstract, Line 28-29, the study concluded the decrease for BaP is smaller than PM2.5 during the same period. However, it seems no analysis was performed in section4 to support this conclusion.
- Is the computation for TILCR consider the population data for each simulation resolution? From formulation 14-18, there are no population data related but in Line 214-216, the population data were used.
- 9 shows the distribution of TILCR. As shown in formula (18), the TILCR is calculated for children, women and men, respectively. Is the TILSR in Fig.9 calculated with the number of children, women and men as weight? If so, please clarify how to obtain the TILCR in this figure.
- Line 436-437, “It can be seen that the spatial distribution of TILCR (Fig. 9a) is consistent with the spatial distribution of the BaP annual concentrations”. According to the formula (14)-(18), the TILCR seems to be proportional with the concentration of PAHs, as the other parameters have fixed values, so the TILCR should be consistent with Fig.7. The same problem also exists regard to Fig.10. The differences between children, women and men depends on the coefficients in formula (14)-(17). In my understanding, the conclusion can be obtained directly from these formulas. Please elaborate more about the meaning of these two figures.
- In part 4.3, the author wants to show the health risks of PAHs. I think it’s better to add a figure of the distribution of health risk grade in China for a more intuitive understanding.
- Formulation (14) lacks the explanation for parameter AF and CF.
- Line 507, it should be YRD, not YRH.
- 7, the figure annotation has some errors. Simulated concentrations are in orange not red and observed values are in blue not lack, please check.
Citation: https://doi.org/10.5194/egusphere-2024-1437-RC1 -
AC1: 'Reply on RC1', Xueshun Chen, 17 Oct 2024
Dear Editor and Reviewer:
Thank you very much for your insightful comments and valuable suggestions concerning our manuscript “Modeling of PAHs From Global to Regional Scales: Model Development and Investigation of Health Risks from 2013 to 2018 in China” (MS No.: EGUSPHERE-2024-1437). Those positive comments are all very valuable and helpful for revising and improving our manuscript. The detailed point-by-point responses are presented in the supplement.
On behalf of all authors, best regards,
Xueshun Chen
-
RC2: 'Comment on egusphere-2024-1437', Anonymous Referee #2, 22 Sep 2024
Title: Modeling of PAHs From Global to Regional Scales: Model Development and Investigation of Health Risks from 2013 to 2018 in China
The study investigates the global distribution of polycyclic aromatic hydrocarbons (PAHs) and their health risks, focusing on China from 2013 to 2018. Using the IAP-AACM model, the authors evaluate the spatial and seasonal distribution of BaP, a key PAH indicator. The authors show BaP concentrations have decreased in China due to emission reductions but increased in India and Southern Africa. Despite the reductions, the health risks in China, particularly in East China, remain significant.
By developing a PAH module, the study offers significant insights into PAH distribution and health risks, providing valuable insights into PAH trends across developing regions. I am happy to see its publication in due course. I would like to suggest some minor revisions after addressing the following questions:
（1）The authors should justify the capability of the EDGAR inventory to capture the short-term emission changes between 2013-2018 at the regional scale.
（2）Figure 8 looks like just a zooming in of Figure 4 with a focus over China. Again, how to verify the very local changes in Figure 8?
（3）In Figures10-12, it is not easy for the readers to understand the abbreviation of each province.
（4）I am wondering what’s the motivation to focus on the PAH health risks over China, and it is possible to include more developing regions?
（5）In terms of PAH control, I suggest to add more policy-related discussions. For example, more specific measures could be proposed.
Citation: https://doi.org/10.5194/egusphere-2024-1437-RC2 -
AC2: 'Reply on RC2', Xueshun Chen, 17 Oct 2024
Dear Editor and Reviewer:
Thank you very much for your detailed and constructive comments and suggestions for our “Modeling of PAHs From Global to Regional Scales: Model Development and Investigation of Health Risks from 2013 to 2018 in China” (MS No.: EGUSPHERE-2024-1437). Those positive comments are all very valuable and helpful for revising and improving our manuscript. The detailed point-by-point responses are presented in the supplement.
On behalf of all authors, best regards,
Xueshun Chen
-
AC2: 'Reply on RC2', Xueshun Chen, 17 Oct 2024
Peer review completion
Journal article(s) based on this preprint
Data sets
Results and Validation of Global-Regional Nested model for polycyclic aromatic hydrocarbons Zichen Wu, Xueshun Chen, and Zifa Wang https://doi.org/10.5281/zenodo.11595165
Model code and software
A Global-Regional Nested Model of Polycyclic aromatic hydrocarbons Zichen Wu, Xueshun Chen, and Zifa Wang https://doi.org/10.5281/zenodo.12214119
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- 1
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Zichen Wu
Xueshun Chen
Zifa Wang
Huansheng Chen
Lin Wu
Wending Wang
Xiao Tang
Jie Li
Qizhong Wu
Yang Wang
Zhiyin Zou
Zijian Jiang
The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
- Preprint
(4409 KB) - Metadata XML
-
Supplement
(2096 KB) - BibTeX
- EndNote
- Final revised paper