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https://doi.org/10.5194/egusphere-2025-1931
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/egusphere-2025-1931
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
25 Jun 2025
| 25 Jun 2025
Drivers and implications of declining fossil fuel CO2 in Chinese cities revealed by radiocarbon measurements
Abstract. China’s clean air policies have successfully mitigated fossil fuel CO2 (CO2ff) emissions in bottom-up inventories since 2013. Yet, evidence from top-down measurements and their underlying drivers remains lacking. Here, we quantify CO2ff concentrations and fuel-specific contributions using atmospheric Δ(14CO2) and δ(13CO2) measurements across representative Chinese cities. We found distinct regional trends: megacities like Guangzhou show significant CO2ff declines (35 % decrease from 2011 to 2022) along with their source regions, while smaller cities have yet to demonstrate similar reductions. These improvements can be attributed to a 23 % coal consumption reduction, 17 % increased natural gas use (evidenced by stable isotope analysis), and improved combustion efficiency (indicated by 63 % falling RCO/CO2ff ratios). Notably, the three-decade observational record shows steeper declines in urban RCO/CO2ff ratios than inventory estimates, suggesting current emission inventories may underestimate combustion efficiency improvements and CO emission reductions relative to CO2ff mitigations. These findings indicate nationwide progress toward CO2ff emission peaks, with megacities leading the transition. They also underscore how coal-to-gas transitions and technological upgrades simultaneously advance air quality and climate goals. Importantly, our results highlight the critical need to integrate top-down observational frameworks (e.g. radiocarbon measurements) with traditional inventories to better capture rapid, policy-driven emission changes and inform future co-benefit optimization strategies.
How to cite. Li, P., Lin, B., Cheng, Z., Li, J., Li, J., Chen, D., Zhang, T., Lin, R., Zhu, S., Liu, J., Lin, Y., Zhao, S., Zhong, G., Niu, Z., Ding, P., and Zhang, G.: Drivers and implications of declining fossil fuel CO2 in Chinese cities revealed by radiocarbon measurements, EGUsphere [preprint], https://doi.org/10.5194/egusphere-2025-1931, 2025.
Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this paper. While Copernicus Publications makes every effort to include appropriate place names, the final responsibility lies with the authors. Views expressed in the text are those of the authors and do not necessarily reflect the views of the publisher.
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Journal article(s) based on this preprint
16 Apr 2026
| Highlight paper
Drivers and implications of declining fossil fuel CO2 concentrations in Chinese cities revealed by radiocarbon measurements
Pingyang Li, Boji Lin, Zhineng Cheng, Jing Li, Jun Li, Duohong Chen, Tao Zhang, Run Lin, Sanyuan Zhu, Jun Liu, Yujun Lin, Shizhen Zhao, Guangcai Zhong, Zhenchuan Niu, Ping Ding, and Gan Zhang
Atmos. Chem. Phys., 26, 5085–5122, https://doi.org/10.5194/acp-26-5085-2026, https://doi.org/10.5194/acp-26-5085-2026, 2026
Short summary
Editorial statement
Short summary
Our study indicates fossil fuel CO2 (CO2ff) reductions in Chinese megacities via atmospheric Δ(14CO2) and δ(13CO2) measurements, driven by coal-to-gas transitions and combustion efficiency improvement. The 24-year record show steeper declined urban RCO/CO2ff ratios than inventory estimates, implying underestimation of efficiency improvements and CO reductions. Integrating top-down observations with inventories is critical to track policy-driven emission shifts and optimize co-benefit strategies.
Editorial statement
This study presents the first multi-city observational assessment of fossil-fuel CO₂ emissions in major and mid-sized Chinese cities using Δ(¹⁴C) and δ(¹³C). The measurements reveal substantial declines in fossil-fuel CO₂ concentrations, consistent with documented reductions in coal consumption, increased reliance on natural gas, and notable improvements in combustion efficiency. However, the observed decreases are larger than those reported by bottom‑up emission inventories, suggesting that current inventories may systematically underestimate real-world CO₂ mitigation. These findings hold important policy implications for evaluating the effectiveness of China’s clean‑air measures and for advancing accurate urban emissions monitoring.
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Interactive discussion
Status: closed
Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor
| : Report abuse
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RC1: 'Comment on egusphere-2025-1931', Anonymous Referee #1, 01 Aug 2025
Dear authors,
please find my review comments in the attached pdf file.
-
AC1: 'Reply on RC1', Gan Zhang, 11 Nov 2025
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2025/egusphere-2025-1931/egusphere-2025-1931-AC1-supplement.pdf
-
AC3: 'Reply on AC1', Gan Zhang, 09 Mar 2026
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2025/egusphere-2025-1931/egusphere-2025-1931-AC3-supplement.pdf
-
AC3: 'Reply on AC1', Gan Zhang, 09 Mar 2026
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AC1: 'Reply on RC1', Gan Zhang, 11 Nov 2025
-
RC2: 'Comment on egusphere-2025-1931', Anonymous Referee #2, 02 Sep 2025
I reviewed two previous versions of this manuscript that was submitted to another journal. This new version has incorporated some of my recommendations in a cursory way, but unfortunately major scientific flaws remain, and I have no choice but to recommend rejection of the paper. While this paper has very interesting data and results, the current presentation and interpretation is not of sufficient quality for publication.
Because these are so many major issues, I found it difficult to go line-by-line, instead giving my overall view of the paper:
- This paper presents a set of atmospheric ∆14C measurements, from which fossil fuel CO2 (CO2ff) can be calculated. The authors have made some problematic assumptions in their CO2ff calculation, particularly regarding the choice of background. Figure 3 shows very clearly that winds are very different in summer and winter in this region, and therefore using a single background site is likely to be problematic.
- The ∂13C analysis is difficult, because there is not much separation between isotopic values of sources, the biogenic CO2 ∂13C value is not well constrained, and the atmospheric signals are also small, which results in very large uncertainties of ~25% for the partitioning. Thus, the interpretations of changing source sectors made in Figure 5 are not valid.
- In the discussion of the CO2ff spatial variability shown in Figure 1, the authors seem to equate the patterns of CO2ff mole fractions to spatial patterns in emissions. Since mole fractions are influenced by emissions and atmospheric variability, there is no direct connection between mole fractions and emissions, and therefore this analysis is not valid. The authors include FLEXPART footprints (Figure 3), but do not attempt to use them to relate emissions to the observations – this would be a sensible way to make such a comparison.
- The authors compare their CO2ff mole fractions with other datasets measured in the same cities in earlier years, and claim that they can observe changes in CO2ff emission rates. Again, mole fractions are influenced by emissions and atmospheric variability, and for this comparison, the specific locations of the measurements much also be taken into consideration. Therefore this comparison is also not valid.
- The examination of CO:CO2ff ratios is more compelling, and the authors could reformulate a paper that removes the problematic points and focuses on these results.
Citation: https://doi.org/10.5194/egusphere-2025-1931-RC2 -
AC2: 'Reply on RC2', Gan Zhang, 11 Nov 2025
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2025/egusphere-2025-1931/egusphere-2025-1931-AC2-supplement.pdf
-
AC4: 'Reply on AC2', Gan Zhang, 09 Mar 2026
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2025/egusphere-2025-1931/egusphere-2025-1931-AC4-supplement.pdf
-
AC4: 'Reply on AC2', Gan Zhang, 09 Mar 2026
Interactive discussion
Status: closed
Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor
| : Report abuse
-
RC1: 'Comment on egusphere-2025-1931', Anonymous Referee #1, 01 Aug 2025
Dear authors,
please find my review comments in the attached pdf file.
-
AC1: 'Reply on RC1', Gan Zhang, 11 Nov 2025
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2025/egusphere-2025-1931/egusphere-2025-1931-AC1-supplement.pdf
-
AC3: 'Reply on AC1', Gan Zhang, 09 Mar 2026
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2025/egusphere-2025-1931/egusphere-2025-1931-AC3-supplement.pdf
-
AC3: 'Reply on AC1', Gan Zhang, 09 Mar 2026
-
AC1: 'Reply on RC1', Gan Zhang, 11 Nov 2025
-
RC2: 'Comment on egusphere-2025-1931', Anonymous Referee #2, 02 Sep 2025
I reviewed two previous versions of this manuscript that was submitted to another journal. This new version has incorporated some of my recommendations in a cursory way, but unfortunately major scientific flaws remain, and I have no choice but to recommend rejection of the paper. While this paper has very interesting data and results, the current presentation and interpretation is not of sufficient quality for publication.
Because these are so many major issues, I found it difficult to go line-by-line, instead giving my overall view of the paper:
- This paper presents a set of atmospheric ∆14C measurements, from which fossil fuel CO2 (CO2ff) can be calculated. The authors have made some problematic assumptions in their CO2ff calculation, particularly regarding the choice of background. Figure 3 shows very clearly that winds are very different in summer and winter in this region, and therefore using a single background site is likely to be problematic.
- The ∂13C analysis is difficult, because there is not much separation between isotopic values of sources, the biogenic CO2 ∂13C value is not well constrained, and the atmospheric signals are also small, which results in very large uncertainties of ~25% for the partitioning. Thus, the interpretations of changing source sectors made in Figure 5 are not valid.
- In the discussion of the CO2ff spatial variability shown in Figure 1, the authors seem to equate the patterns of CO2ff mole fractions to spatial patterns in emissions. Since mole fractions are influenced by emissions and atmospheric variability, there is no direct connection between mole fractions and emissions, and therefore this analysis is not valid. The authors include FLEXPART footprints (Figure 3), but do not attempt to use them to relate emissions to the observations – this would be a sensible way to make such a comparison.
- The authors compare their CO2ff mole fractions with other datasets measured in the same cities in earlier years, and claim that they can observe changes in CO2ff emission rates. Again, mole fractions are influenced by emissions and atmospheric variability, and for this comparison, the specific locations of the measurements much also be taken into consideration. Therefore this comparison is also not valid.
- The examination of CO:CO2ff ratios is more compelling, and the authors could reformulate a paper that removes the problematic points and focuses on these results.
Citation: https://doi.org/10.5194/egusphere-2025-1931-RC2 -
AC2: 'Reply on RC2', Gan Zhang, 11 Nov 2025
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2025/egusphere-2025-1931/egusphere-2025-1931-AC2-supplement.pdf
-
AC4: 'Reply on AC2', Gan Zhang, 09 Mar 2026
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2025/egusphere-2025-1931/egusphere-2025-1931-AC4-supplement.pdf
-
AC4: 'Reply on AC2', Gan Zhang, 09 Mar 2026
Peer review completion
AR – Author's response | RR – Referee report | ED – Editor decision | EF – Editorial file upload
AR by Gan Zhang on behalf of the Authors (11 Nov 2025)
Author's response
Author's tracked changes
Manuscript
ED: Referee Nomination & Report Request started (12 Nov 2025) by Jan Kaiser
RR by Anonymous Referee #1 (02 Dec 2025)
RR by Anonymous Referee #3 (27 Jan 2026)
ED: Publish subject to minor revisions (review by editor) (10 Feb 2026) by Jan Kaiser
AR by Gan Zhang on behalf of the Authors (09 Mar 2026)
Author's response
Author's tracked changes
Manuscript
ED: Publish as is (09 Mar 2026) by Jan Kaiser
AR by Gan Zhang on behalf of the Authors (20 Mar 2026)
Author's response
Manuscript
Journal article(s) based on this preprint
16 Apr 2026
| Highlight paper
Drivers and implications of declining fossil fuel CO2 concentrations in Chinese cities revealed by radiocarbon measurements
Pingyang Li, Boji Lin, Zhineng Cheng, Jing Li, Jun Li, Duohong Chen, Tao Zhang, Run Lin, Sanyuan Zhu, Jun Liu, Yujun Lin, Shizhen Zhao, Guangcai Zhong, Zhenchuan Niu, Ping Ding, and Gan Zhang
Atmos. Chem. Phys., 26, 5085–5122, https://doi.org/10.5194/acp-26-5085-2026, https://doi.org/10.5194/acp-26-5085-2026, 2026
Short summary
Editorial statement
Short summary
Our study indicates fossil fuel CO2 (CO2ff) reductions in Chinese megacities via atmospheric Δ(14CO2) and δ(13CO2) measurements, driven by coal-to-gas transitions and combustion efficiency improvement. The 24-year record show steeper declined urban RCO/CO2ff ratios than inventory estimates, implying underestimation of efficiency improvements and CO reductions. Integrating top-down observations with inventories is critical to track policy-driven emission shifts and optimize co-benefit strategies.
Editorial statement
This study presents the first multi-city observational assessment of fossil-fuel CO₂ emissions in major and mid-sized Chinese cities using Δ(¹⁴C) and δ(¹³C). The measurements reveal substantial declines in fossil-fuel CO₂ concentrations, consistent with documented reductions in coal consumption, increased reliance on natural gas, and notable improvements in combustion efficiency. However, the observed decreases are larger than those reported by bottom‑up emission inventories, suggesting that current inventories may systematically underestimate real-world CO₂ mitigation. These findings hold important policy implications for evaluating the effectiveness of China’s clean‑air measures and for advancing accurate urban emissions monitoring.
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Pingyang Li
State Key Laboratory of Advanced Environmental Technology, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou 510640, People’s Republic of China
Guangdong Key Laboratory of Environmental Protection and Resources Utilization, and Joint Laboratory of the Guangdong-Hong Kong-Macao Greater Bay Area for the Environment, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou 510640, People’s Republic of China
Boji Lin
State Key Laboratory of Advanced Environmental Technology, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou 510640, People’s Republic of China
Guangdong Key Laboratory of Environmental Protection and Resources Utilization, and Joint Laboratory of the Guangdong-Hong Kong-Macao Greater Bay Area for the Environment, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou 510640, People’s Republic of China
University of Chinese Academy of Sciences, Beijing 100049, People’s Republic of China
Zhineng Cheng
State Key Laboratory of Advanced Environmental Technology, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou 510640, People’s Republic of China
Guangdong Key Laboratory of Environmental Protection and Resources Utilization, and Joint Laboratory of the Guangdong-Hong Kong-Macao Greater Bay Area for the Environment, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou 510640, People’s Republic of China
Jing Li
State Key Laboratory of Advanced Environmental Technology, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou 510640, People’s Republic of China
Guangdong Key Laboratory of Environmental Protection and Resources Utilization, and Joint Laboratory of the Guangdong-Hong Kong-Macao Greater Bay Area for the Environment, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou 510640, People’s Republic of China
State Key Laboratory of Advanced Environmental Technology, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou 510640, People’s Republic of China
Guangdong Key Laboratory of Environmental Protection and Resources Utilization, and Joint Laboratory of the Guangdong-Hong Kong-Macao Greater Bay Area for the Environment, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou 510640, People’s Republic of China
Duohong Chen
CORRESPONDING AUTHOR
Environmental Key Laboratory of Regional Air Quality Monitoring, Ministry of Ecology and Environment, Guangdong Ecological and Environmental Monitoring Center, Guangzhou 510308, People’s Republic of China
Tao Zhang
Environmental Key Laboratory of Regional Air Quality Monitoring, Ministry of Ecology and Environment, Guangdong Ecological and Environmental Monitoring Center, Guangzhou 510308, People’s Republic of China
Run Lin
State Key Laboratory of Advanced Environmental Technology, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou 510640, People’s Republic of China
Guangdong Key Laboratory of Environmental Protection and Resources Utilization, and Joint Laboratory of the Guangdong-Hong Kong-Macao Greater Bay Area for the Environment, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou 510640, People’s Republic of China
Sanyuan Zhu
State Key Laboratory of Advanced Environmental Technology, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou 510640, People’s Republic of China
Guangdong Key Laboratory of Environmental Protection and Resources Utilization, and Joint Laboratory of the Guangdong-Hong Kong-Macao Greater Bay Area for the Environment, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou 510640, People’s Republic of China
Jun Liu
Environmental Key Laboratory of Regional Air Quality Monitoring, Ministry of Ecology and Environment, Guangdong Ecological and Environmental Monitoring Center, Guangzhou 510308, People’s Republic of China
Yujun Lin
Environmental Key Laboratory of Regional Air Quality Monitoring, Ministry of Ecology and Environment, Guangdong Ecological and Environmental Monitoring Center, Guangzhou 510308, People’s Republic of China
Shizhen Zhao
State Key Laboratory of Advanced Environmental Technology, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou 510640, People’s Republic of China
Guangdong Key Laboratory of Environmental Protection and Resources Utilization, and Joint Laboratory of the Guangdong-Hong Kong-Macao Greater Bay Area for the Environment, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou 510640, People’s Republic of China
Guangcai Zhong
State Key Laboratory of Advanced Environmental Technology, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou 510640, People’s Republic of China
Guangdong Key Laboratory of Environmental Protection and Resources Utilization, and Joint Laboratory of the Guangdong-Hong Kong-Macao Greater Bay Area for the Environment, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou 510640, People’s Republic of China
Zhenchuan Niu
State Key Laboratory of Loess, Institute of Earth Environment, Chinese Academy of Sciences, Xi’an 710061, People’s Republic of China
Institute of Global Environmental Change, Xi’an Jiaotong University, Xi’an 710061, People’s Republic of China
Ping Ding
State Key Laboratory of Deep Earth Processes and Resources, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou 510640, People’s Republic of China
Gan Zhang
CORRESPONDING AUTHOR
State Key Laboratory of Advanced Environmental Technology, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou 510640, People’s Republic of China
Guangdong Key Laboratory of Environmental Protection and Resources Utilization, and Joint Laboratory of the Guangdong-Hong Kong-Macao Greater Bay Area for the Environment, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou 510640, People’s Republic of China
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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
(5673 KB) - Metadata XML
-
Supplement
(53 KB) - BibTeX
- EndNote
- Final revised paper
Short summary
Our study indicates fossil fuel CO2 (CO2ff) reductions in Chinese megacities via atmospheric Δ(14CO2) and δ(13CO2) measurements, driven by coal-to-gas transitions and combustion efficiency improvement. Three-decade data show steeper declined urban RCO/CO2ff ratios than inventory estimates, implying underestimation of efficiency improvements and CO reductions. Integrating top-down observations with inventories is critical to track policy-driven emission shifts and optimize co-benefit strategies.
Our study indicates fossil fuel CO2 (CO2ff) reductions in Chinese megacities via atmospheric...