Near-real-time estimation of fossil fuel CO2 emissions from China based on atmospheric observations on Hateruma and Yonaguni Islands, Japan
We developed a near-real-time estimation method for temporal changes in fossil fuel CO 2 (FFCO 2 ) emissions from China for 3 months [January, February, March (JFM)] based on atmospheric CO 2 and CH 4 observations on Hateruma Island (HAT, 24.06° N, 123.81° E) and Yonaguni Island (YON, 24.47° N, 123....
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Published in | Progress in earth and planetary science Vol. 10; no. 1; pp. 10 - 14 |
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Main Authors | , , , , , , , , |
Format | Journal Article |
Language | English |
Published |
Berlin/Heidelberg
Springer Berlin Heidelberg
02.03.2023
Springer Nature B.V SpringerOpen |
Subjects | |
Online Access | Get full text |
ISSN | 2197-4284 2197-4284 |
DOI | 10.1186/s40645-023-00542-6 |
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Abstract | We developed a near-real-time estimation method for temporal changes in fossil fuel CO
2
(FFCO
2
) emissions from China for 3 months [January, February, March (JFM)] based on atmospheric CO
2
and CH
4
observations on Hateruma Island (HAT, 24.06° N, 123.81° E) and Yonaguni Island (YON, 24.47° N, 123.01° E), Japan. These two remote islands are in the downwind region of continental East Asia during winter because of the East Asian monsoon. Previous studies have revealed that monthly averages of synoptic-scale variability ratios of atmospheric CO
2
and CH
4
(ΔCO
2
/ΔCH
4
) observed at HAT and YON in JFM are sensitive to changes in continental emissions. From the analysis based on an atmospheric transport model with all components of CO
2
and CH
4
fluxes, we found that the ΔCO
2
/ΔCH
4
ratio was linearly related to the FFCO
2
/CH
4
emission ratio in China because calculating the variability ratio canceled out the transport influences. Using the simulated linear relationship, we converted the observed ΔCO
2
/ΔCH
4
ratios into FFCO
2
/CH
4
emission ratios in China. The change rates of the emission ratios for 2020–2022 were calculated relative to those for the preceding 9-year period (2011–2019), during which relatively stable ΔCO
2
/ΔCH
4
ratios were observed. These changes in the emission ratios can be read as FFCO
2
emission changes under the assumption of no interannual variations in CH
4
emissions and biospheric CO
2
fluxes for JFM. The resulting average changes in the FFCO
2
emissions in January, February, and March 2020 were 17 ± 8%, − 36 ± 7%, and − 12 ± 8%, respectively, (− 10 ± 9% for JFM overall) relative to 2011–2019. These results were generally consistent with previous estimates. The emission changes for January, February, and March were 18 ± 8%, − 2 ± 10%, and 29 ± 12%, respectively, in 2021 (15 ± 10% for JFM overall) and 20 ± 9%, − 3 ± 10%, and − 10 ± 9%, respectively, in 2022 (2 ± 9% for JFM overall). These results suggest that the FFCO
2
emissions from China rebounded to the normal level or set a new high record in early 2021 after a reduction during the COVID-19 lockdown. In addition, the estimated reduction in March 2022 might be attributed to the influence of a new wave of COVID-19 infections in Shanghai. |
---|---|
AbstractList | We developed a near-real-time estimation method for temporal changes in fossil fuel CO
2
(FFCO
2
) emissions from China for 3 months [January, February, March (JFM)] based on atmospheric CO
2
and CH
4
observations on Hateruma Island (HAT, 24.06° N, 123.81° E) and Yonaguni Island (YON, 24.47° N, 123.01° E), Japan. These two remote islands are in the downwind region of continental East Asia during winter because of the East Asian monsoon. Previous studies have revealed that monthly averages of synoptic-scale variability ratios of atmospheric CO
2
and CH
4
(ΔCO
2
/ΔCH
4
) observed at HAT and YON in JFM are sensitive to changes in continental emissions. From the analysis based on an atmospheric transport model with all components of CO
2
and CH
4
fluxes, we found that the ΔCO
2
/ΔCH
4
ratio was linearly related to the FFCO
2
/CH
4
emission ratio in China because calculating the variability ratio canceled out the transport influences. Using the simulated linear relationship, we converted the observed ΔCO
2
/ΔCH
4
ratios into FFCO
2
/CH
4
emission ratios in China. The change rates of the emission ratios for 2020–2022 were calculated relative to those for the preceding 9-year period (2011–2019), during which relatively stable ΔCO
2
/ΔCH
4
ratios were observed. These changes in the emission ratios can be read as FFCO
2
emission changes under the assumption of no interannual variations in CH
4
emissions and biospheric CO
2
fluxes for JFM. The resulting average changes in the FFCO
2
emissions in January, February, and March 2020 were 17 ± 8%, − 36 ± 7%, and − 12 ± 8%, respectively, (− 10 ± 9% for JFM overall) relative to 2011–2019. These results were generally consistent with previous estimates. The emission changes for January, February, and March were 18 ± 8%, − 2 ± 10%, and 29 ± 12%, respectively, in 2021 (15 ± 10% for JFM overall) and 20 ± 9%, − 3 ± 10%, and − 10 ± 9%, respectively, in 2022 (2 ± 9% for JFM overall). These results suggest that the FFCO
2
emissions from China rebounded to the normal level or set a new high record in early 2021 after a reduction during the COVID-19 lockdown. In addition, the estimated reduction in March 2022 might be attributed to the influence of a new wave of COVID-19 infections in Shanghai. Abstract We developed a near-real-time estimation method for temporal changes in fossil fuel CO2 (FFCO2) emissions from China for 3 months [January, February, March (JFM)] based on atmospheric CO2 and CH4 observations on Hateruma Island (HAT, 24.06° N, 123.81° E) and Yonaguni Island (YON, 24.47° N, 123.01° E), Japan. These two remote islands are in the downwind region of continental East Asia during winter because of the East Asian monsoon. Previous studies have revealed that monthly averages of synoptic-scale variability ratios of atmospheric CO2 and CH4 (ΔCO2/ΔCH4) observed at HAT and YON in JFM are sensitive to changes in continental emissions. From the analysis based on an atmospheric transport model with all components of CO2 and CH4 fluxes, we found that the ΔCO2/ΔCH4 ratio was linearly related to the FFCO2/CH4 emission ratio in China because calculating the variability ratio canceled out the transport influences. Using the simulated linear relationship, we converted the observed ΔCO2/ΔCH4 ratios into FFCO2/CH4 emission ratios in China. The change rates of the emission ratios for 2020–2022 were calculated relative to those for the preceding 9-year period (2011–2019), during which relatively stable ΔCO2/ΔCH4 ratios were observed. These changes in the emission ratios can be read as FFCO2 emission changes under the assumption of no interannual variations in CH4 emissions and biospheric CO2 fluxes for JFM. The resulting average changes in the FFCO2 emissions in January, February, and March 2020 were 17 ± 8%, − 36 ± 7%, and − 12 ± 8%, respectively, (− 10 ± 9% for JFM overall) relative to 2011–2019. These results were generally consistent with previous estimates. The emission changes for January, February, and March were 18 ± 8%, − 2 ± 10%, and 29 ± 12%, respectively, in 2021 (15 ± 10% for JFM overall) and 20 ± 9%, − 3 ± 10%, and − 10 ± 9%, respectively, in 2022 (2 ± 9% for JFM overall). These results suggest that the FFCO2 emissions from China rebounded to the normal level or set a new high record in early 2021 after a reduction during the COVID-19 lockdown. In addition, the estimated reduction in March 2022 might be attributed to the influence of a new wave of COVID-19 infections in Shanghai. We developed a near-real-time estimation method for temporal changes in fossil fuel CO2 (FFCO2) emissions from China for 3 months [January, February, March (JFM)] based on atmospheric CO2 and CH4 observations on Hateruma Island (HAT, 24.06° N, 123.81° E) and Yonaguni Island (YON, 24.47° N, 123.01° E), Japan. These two remote islands are in the downwind region of continental East Asia during winter because of the East Asian monsoon. Previous studies have revealed that monthly averages of synoptic-scale variability ratios of atmospheric CO2 and CH4 (ΔCO2/ΔCH4) observed at HAT and YON in JFM are sensitive to changes in continental emissions. From the analysis based on an atmospheric transport model with all components of CO2 and CH4 fluxes, we found that the ΔCO2/ΔCH4 ratio was linearly related to the FFCO2/CH4 emission ratio in China because calculating the variability ratio canceled out the transport influences. Using the simulated linear relationship, we converted the observed ΔCO2/ΔCH4 ratios into FFCO2/CH4 emission ratios in China. The change rates of the emission ratios for 2020–2022 were calculated relative to those for the preceding 9-year period (2011–2019), during which relatively stable ΔCO2/ΔCH4 ratios were observed. These changes in the emission ratios can be read as FFCO2 emission changes under the assumption of no interannual variations in CH4 emissions and biospheric CO2 fluxes for JFM. The resulting average changes in the FFCO2 emissions in January, February, and March 2020 were 17 ± 8%, − 36 ± 7%, and − 12 ± 8%, respectively, (− 10 ± 9% for JFM overall) relative to 2011–2019. These results were generally consistent with previous estimates. The emission changes for January, February, and March were 18 ± 8%, − 2 ± 10%, and 29 ± 12%, respectively, in 2021 (15 ± 10% for JFM overall) and 20 ± 9%, − 3 ± 10%, and − 10 ± 9%, respectively, in 2022 (2 ± 9% for JFM overall). These results suggest that the FFCO2 emissions from China rebounded to the normal level or set a new high record in early 2021 after a reduction during the COVID-19 lockdown. In addition, the estimated reduction in March 2022 might be attributed to the influence of a new wave of COVID-19 infections in Shanghai. We developed a near-real-time estimation method for temporal changes in fossil fuel CO2 (FFCO2) emissions from China for 3 months [January, February, March (JFM)] based on atmospheric CO2 and CH4 observations on Hateruma Island (HAT, 24.06° N, 123.81° E) and Yonaguni Island (YON, 24.47° N, 123.01° E), Japan. These two remote islands are in the downwind region of continental East Asia during winter because of the East Asian monsoon. Previous studies have revealed that monthly averages of synoptic-scale variability ratios of atmospheric CO2 and CH4 (ΔCO2/ΔCH4) observed at HAT and YON in JFM are sensitive to changes in continental emissions. From the analysis based on an atmospheric transport model with all components of CO2 and CH4 fluxes, we found that the ΔCO2/ΔCH4 ratio was linearly related to the FFCO2/CH4 emission ratio in China because calculating the variability ratio canceled out the transport influences. Using the simulated linear relationship, we converted the observed ΔCO2/ΔCH4 ratios into FFCO2/CH4 emission ratios in China. The change rates of the emission ratios for 2020-2022 were calculated relative to those for the preceding 9-year period (2011-2019), during which relatively stable ΔCO2/ΔCH4 ratios were observed. These changes in the emission ratios can be read as FFCO2 emission changes under the assumption of no interannual variations in CH4 emissions and biospheric CO2 fluxes for JFM. The resulting average changes in the FFCO2 emissions in January, February, and March 2020 were 17 ± 8%, - 36 ± 7%, and - 12 ± 8%, respectively, (- 10 ± 9% for JFM overall) relative to 2011-2019. These results were generally consistent with previous estimates. The emission changes for January, February, and March were 18 ± 8%, - 2 ± 10%, and 29 ± 12%, respectively, in 2021 (15 ± 10% for JFM overall) and 20 ± 9%, - 3 ± 10%, and - 10 ± 9%, respectively, in 2022 (2 ± 9% for JFM overall). These results suggest that the FFCO2 emissions from China rebounded to the normal level or set a new high record in early 2021 after a reduction during the COVID-19 lockdown. In addition, the estimated reduction in March 2022 might be attributed to the influence of a new wave of COVID-19 infections in Shanghai.We developed a near-real-time estimation method for temporal changes in fossil fuel CO2 (FFCO2) emissions from China for 3 months [January, February, March (JFM)] based on atmospheric CO2 and CH4 observations on Hateruma Island (HAT, 24.06° N, 123.81° E) and Yonaguni Island (YON, 24.47° N, 123.01° E), Japan. These two remote islands are in the downwind region of continental East Asia during winter because of the East Asian monsoon. Previous studies have revealed that monthly averages of synoptic-scale variability ratios of atmospheric CO2 and CH4 (ΔCO2/ΔCH4) observed at HAT and YON in JFM are sensitive to changes in continental emissions. From the analysis based on an atmospheric transport model with all components of CO2 and CH4 fluxes, we found that the ΔCO2/ΔCH4 ratio was linearly related to the FFCO2/CH4 emission ratio in China because calculating the variability ratio canceled out the transport influences. Using the simulated linear relationship, we converted the observed ΔCO2/ΔCH4 ratios into FFCO2/CH4 emission ratios in China. The change rates of the emission ratios for 2020-2022 were calculated relative to those for the preceding 9-year period (2011-2019), during which relatively stable ΔCO2/ΔCH4 ratios were observed. These changes in the emission ratios can be read as FFCO2 emission changes under the assumption of no interannual variations in CH4 emissions and biospheric CO2 fluxes for JFM. The resulting average changes in the FFCO2 emissions in January, February, and March 2020 were 17 ± 8%, - 36 ± 7%, and - 12 ± 8%, respectively, (- 10 ± 9% for JFM overall) relative to 2011-2019. These results were generally consistent with previous estimates. The emission changes for January, February, and March were 18 ± 8%, - 2 ± 10%, and 29 ± 12%, respectively, in 2021 (15 ± 10% for JFM overall) and 20 ± 9%, - 3 ± 10%, and - 10 ± 9%, respectively, in 2022 (2 ± 9% for JFM overall). These results suggest that the FFCO2 emissions from China rebounded to the normal level or set a new high record in early 2021 after a reduction during the COVID-19 lockdown. In addition, the estimated reduction in March 2022 might be attributed to the influence of a new wave of COVID-19 infections in Shanghai.The online version contains supplementary material available at 10.1186/s40645-023-00542-6.Supplementary InformationThe online version contains supplementary material available at 10.1186/s40645-023-00542-6. |
ArticleNumber | 10 |
Author | Tsuboi, Kazuhiro Ito, Akihiko Mukai, Hitoshi Tohjima, Yasunori Niwa, Yosuke Patra, Prabir K. Saito, Kazuyuki Sasakawa, Motoki Machida, Toshinobu |
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CitedBy_id | crossref_primary_10_1038_s41612_025_00991_4 crossref_primary_10_1016_j_scitotenv_2025_178884 crossref_primary_10_1016_j_apr_2025_102499 |
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Keywords | Synoptic-scale variations East Asian Monsoon COVID-19 lockdown Fossil fuel CO Atmospheric CO emissions Atmospheric CH |
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Snippet | We developed a near-real-time estimation method for temporal changes in fossil fuel CO
2
(FFCO
2
) emissions from China for 3 months [January, February, March... We developed a near-real-time estimation method for temporal changes in fossil fuel CO2 (FFCO2) emissions from China for 3 months [January, February, March... Abstract We developed a near-real-time estimation method for temporal changes in fossil fuel CO2 (FFCO2) emissions from China for 3 months [January, February,... |
SourceID | doaj pubmedcentral proquest crossref springer |
SourceType | Open Website Open Access Repository Aggregation Database Enrichment Source Index Database Publisher |
StartPage | 10 |
SubjectTerms | 2. Atmospheric and hydrospheric sciences Atmospheric CH4 Atmospheric CO2 Atmospheric Sciences Atmospheric transport Atmospheric transport models Biogeosciences Carbon dioxide emissions Carbon dioxide flux Coronaviruses COVID-19 COVID-19 lockdown Earth and Environmental Science Earth Sciences East Asian Monsoon Fossil fuel CO2 emissions Fossil fuels Geophysics/Geodesy Hydrogeology Interannual variations Islands Methane Methodology Planetology Ratios Synoptic-scale variations |
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Title | Near-real-time estimation of fossil fuel CO2 emissions from China based on atmospheric observations on Hateruma and Yonaguni Islands, Japan |
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