Spatiotemporal variation in near-surface $ CH_{4} $ concentrations in China over the last two decades
Abstract Methane is one of the main greenhouse trace gases and seriously affects the radiation balance of Earth systems due to its strong heat absorption capacity and long atmospheric retention time. Based on the methane stratification data simulated by the community atmospheric model with chemistry...
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Gespeichert in:
| Autor*in: |
Xu, Jianhui [verfasserIn] |
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| Format: |
Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2021 |
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| Schlagwörter: |
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| Anmerkung: |
© The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2021 |
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| Übergeordnetes Werk: |
Enthalten in: Environmental science and pollution research - Springer Berlin Heidelberg, 1994, 28(2021), 34 vom: 23. Apr., Seite 47239-47250 |
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| Übergeordnetes Werk: |
volume:28 ; year:2021 ; number:34 ; day:23 ; month:04 ; pages:47239-47250 |
| Links: |
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| DOI / URN: |
10.1007/s11356-021-14007-0 |
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| Katalog-ID: |
OLC2127389859 |
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| 520 | |a Abstract Methane is one of the main greenhouse trace gases and seriously affects the radiation balance of Earth systems due to its strong heat absorption capacity and long atmospheric retention time. Based on the methane stratification data simulated by the community atmospheric model with chemistry (CAM-chem), near-surface methane concentrations were estimated by utilizing the Gaussian function, and the spatiotemporal variation in the near-surface methane concentration in China from 2001 to 2019 was discussed in this research. The results show that (1) based on the methane stratification concentration data simulated by the atmospheric chemical model, the near-surface $ CH_{4} $ concentration estimated by Gaussian function model is reliable, which provides a new method to estimate the near-surface $ CH_{4} $ concentration over China; (2) from 2001 to 2019, the near-surface methane concentration in China showed an increasing trend with an annual growth rate of 7.20±0.23 ppb·$ a^{−1} $. The annual maximum near-surface methane concentration was measured in winter, and the minimum was measured in summer; (3) the spatial distribution differences are obvious: the methane concentration in the east was higher than that in the west, and the methane concentration in the north was higher than that in the south. Moreover, the distributions of methane in the east and west are consistent with the division of Hu Huanyong population line. | ||
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10.1007/s11356-021-14007-0 doi (DE-627)OLC2127389859 (DE-He213)s11356-021-14007-0-p DE-627 ger DE-627 rakwb eng 570 360 333.7 VZ 690 333.7 540 VZ BIODIV DE-30 fid Xu, Jianhui verfasserin (orcid)0000-0002-5742-0810 aut Spatiotemporal variation in near-surface $ CH_{4} $ concentrations in China over the last two decades 2021 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2021 Abstract Methane is one of the main greenhouse trace gases and seriously affects the radiation balance of Earth systems due to its strong heat absorption capacity and long atmospheric retention time. Based on the methane stratification data simulated by the community atmospheric model with chemistry (CAM-chem), near-surface methane concentrations were estimated by utilizing the Gaussian function, and the spatiotemporal variation in the near-surface methane concentration in China from 2001 to 2019 was discussed in this research. The results show that (1) based on the methane stratification concentration data simulated by the atmospheric chemical model, the near-surface $ CH_{4} $ concentration estimated by Gaussian function model is reliable, which provides a new method to estimate the near-surface $ CH_{4} $ concentration over China; (2) from 2001 to 2019, the near-surface methane concentration in China showed an increasing trend with an annual growth rate of 7.20±0.23 ppb·$ a^{−1} $. The annual maximum near-surface methane concentration was measured in winter, and the minimum was measured in summer; (3) the spatial distribution differences are obvious: the methane concentration in the east was higher than that in the west, and the methane concentration in the north was higher than that in the south. Moreover, the distributions of methane in the east and west are consistent with the division of Hu Huanyong population line. Methane Atmospheric chemistry model CAM-chem model Multiple Gaussian functions Spatiotemporal variations China Liu, Qingfang aut Wang, Kai aut Wang, Qiulong aut Wang, Li aut Liu, Yuchan aut Li, Maoyu aut Enthalten in Environmental science and pollution research Springer Berlin Heidelberg, 1994 28(2021), 34 vom: 23. Apr., Seite 47239-47250 (DE-627)171335805 (DE-600)1178791-0 (DE-576)038875101 0944-1344 nnns volume:28 year:2021 number:34 day:23 month:04 pages:47239-47250 https://doi.org/10.1007/s11356-021-14007-0 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC FID-BIODIV SSG-OLC-UMW SSG-OLC-ARC SSG-OLC-TEC SSG-OLC-CHE SSG-OLC-FOR GBV_ILN_252 GBV_ILN_267 GBV_ILN_2018 GBV_ILN_4277 AR 28 2021 34 23 04 47239-47250 |
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10.1007/s11356-021-14007-0 doi (DE-627)OLC2127389859 (DE-He213)s11356-021-14007-0-p DE-627 ger DE-627 rakwb eng 570 360 333.7 VZ 690 333.7 540 VZ BIODIV DE-30 fid Xu, Jianhui verfasserin (orcid)0000-0002-5742-0810 aut Spatiotemporal variation in near-surface $ CH_{4} $ concentrations in China over the last two decades 2021 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2021 Abstract Methane is one of the main greenhouse trace gases and seriously affects the radiation balance of Earth systems due to its strong heat absorption capacity and long atmospheric retention time. Based on the methane stratification data simulated by the community atmospheric model with chemistry (CAM-chem), near-surface methane concentrations were estimated by utilizing the Gaussian function, and the spatiotemporal variation in the near-surface methane concentration in China from 2001 to 2019 was discussed in this research. The results show that (1) based on the methane stratification concentration data simulated by the atmospheric chemical model, the near-surface $ CH_{4} $ concentration estimated by Gaussian function model is reliable, which provides a new method to estimate the near-surface $ CH_{4} $ concentration over China; (2) from 2001 to 2019, the near-surface methane concentration in China showed an increasing trend with an annual growth rate of 7.20±0.23 ppb·$ a^{−1} $. The annual maximum near-surface methane concentration was measured in winter, and the minimum was measured in summer; (3) the spatial distribution differences are obvious: the methane concentration in the east was higher than that in the west, and the methane concentration in the north was higher than that in the south. Moreover, the distributions of methane in the east and west are consistent with the division of Hu Huanyong population line. Methane Atmospheric chemistry model CAM-chem model Multiple Gaussian functions Spatiotemporal variations China Liu, Qingfang aut Wang, Kai aut Wang, Qiulong aut Wang, Li aut Liu, Yuchan aut Li, Maoyu aut Enthalten in Environmental science and pollution research Springer Berlin Heidelberg, 1994 28(2021), 34 vom: 23. Apr., Seite 47239-47250 (DE-627)171335805 (DE-600)1178791-0 (DE-576)038875101 0944-1344 nnns volume:28 year:2021 number:34 day:23 month:04 pages:47239-47250 https://doi.org/10.1007/s11356-021-14007-0 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC FID-BIODIV SSG-OLC-UMW SSG-OLC-ARC SSG-OLC-TEC SSG-OLC-CHE SSG-OLC-FOR GBV_ILN_252 GBV_ILN_267 GBV_ILN_2018 GBV_ILN_4277 AR 28 2021 34 23 04 47239-47250 |
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10.1007/s11356-021-14007-0 doi (DE-627)OLC2127389859 (DE-He213)s11356-021-14007-0-p DE-627 ger DE-627 rakwb eng 570 360 333.7 VZ 690 333.7 540 VZ BIODIV DE-30 fid Xu, Jianhui verfasserin (orcid)0000-0002-5742-0810 aut Spatiotemporal variation in near-surface $ CH_{4} $ concentrations in China over the last two decades 2021 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2021 Abstract Methane is one of the main greenhouse trace gases and seriously affects the radiation balance of Earth systems due to its strong heat absorption capacity and long atmospheric retention time. Based on the methane stratification data simulated by the community atmospheric model with chemistry (CAM-chem), near-surface methane concentrations were estimated by utilizing the Gaussian function, and the spatiotemporal variation in the near-surface methane concentration in China from 2001 to 2019 was discussed in this research. The results show that (1) based on the methane stratification concentration data simulated by the atmospheric chemical model, the near-surface $ CH_{4} $ concentration estimated by Gaussian function model is reliable, which provides a new method to estimate the near-surface $ CH_{4} $ concentration over China; (2) from 2001 to 2019, the near-surface methane concentration in China showed an increasing trend with an annual growth rate of 7.20±0.23 ppb·$ a^{−1} $. The annual maximum near-surface methane concentration was measured in winter, and the minimum was measured in summer; (3) the spatial distribution differences are obvious: the methane concentration in the east was higher than that in the west, and the methane concentration in the north was higher than that in the south. Moreover, the distributions of methane in the east and west are consistent with the division of Hu Huanyong population line. Methane Atmospheric chemistry model CAM-chem model Multiple Gaussian functions Spatiotemporal variations China Liu, Qingfang aut Wang, Kai aut Wang, Qiulong aut Wang, Li aut Liu, Yuchan aut Li, Maoyu aut Enthalten in Environmental science and pollution research Springer Berlin Heidelberg, 1994 28(2021), 34 vom: 23. Apr., Seite 47239-47250 (DE-627)171335805 (DE-600)1178791-0 (DE-576)038875101 0944-1344 nnns volume:28 year:2021 number:34 day:23 month:04 pages:47239-47250 https://doi.org/10.1007/s11356-021-14007-0 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC FID-BIODIV SSG-OLC-UMW SSG-OLC-ARC SSG-OLC-TEC SSG-OLC-CHE SSG-OLC-FOR GBV_ILN_252 GBV_ILN_267 GBV_ILN_2018 GBV_ILN_4277 AR 28 2021 34 23 04 47239-47250 |
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10.1007/s11356-021-14007-0 doi (DE-627)OLC2127389859 (DE-He213)s11356-021-14007-0-p DE-627 ger DE-627 rakwb eng 570 360 333.7 VZ 690 333.7 540 VZ BIODIV DE-30 fid Xu, Jianhui verfasserin (orcid)0000-0002-5742-0810 aut Spatiotemporal variation in near-surface $ CH_{4} $ concentrations in China over the last two decades 2021 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2021 Abstract Methane is one of the main greenhouse trace gases and seriously affects the radiation balance of Earth systems due to its strong heat absorption capacity and long atmospheric retention time. Based on the methane stratification data simulated by the community atmospheric model with chemistry (CAM-chem), near-surface methane concentrations were estimated by utilizing the Gaussian function, and the spatiotemporal variation in the near-surface methane concentration in China from 2001 to 2019 was discussed in this research. The results show that (1) based on the methane stratification concentration data simulated by the atmospheric chemical model, the near-surface $ CH_{4} $ concentration estimated by Gaussian function model is reliable, which provides a new method to estimate the near-surface $ CH_{4} $ concentration over China; (2) from 2001 to 2019, the near-surface methane concentration in China showed an increasing trend with an annual growth rate of 7.20±0.23 ppb·$ a^{−1} $. The annual maximum near-surface methane concentration was measured in winter, and the minimum was measured in summer; (3) the spatial distribution differences are obvious: the methane concentration in the east was higher than that in the west, and the methane concentration in the north was higher than that in the south. Moreover, the distributions of methane in the east and west are consistent with the division of Hu Huanyong population line. Methane Atmospheric chemistry model CAM-chem model Multiple Gaussian functions Spatiotemporal variations China Liu, Qingfang aut Wang, Kai aut Wang, Qiulong aut Wang, Li aut Liu, Yuchan aut Li, Maoyu aut Enthalten in Environmental science and pollution research Springer Berlin Heidelberg, 1994 28(2021), 34 vom: 23. Apr., Seite 47239-47250 (DE-627)171335805 (DE-600)1178791-0 (DE-576)038875101 0944-1344 nnns volume:28 year:2021 number:34 day:23 month:04 pages:47239-47250 https://doi.org/10.1007/s11356-021-14007-0 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC FID-BIODIV SSG-OLC-UMW SSG-OLC-ARC SSG-OLC-TEC SSG-OLC-CHE SSG-OLC-FOR GBV_ILN_252 GBV_ILN_267 GBV_ILN_2018 GBV_ILN_4277 AR 28 2021 34 23 04 47239-47250 |
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10.1007/s11356-021-14007-0 doi (DE-627)OLC2127389859 (DE-He213)s11356-021-14007-0-p DE-627 ger DE-627 rakwb eng 570 360 333.7 VZ 690 333.7 540 VZ BIODIV DE-30 fid Xu, Jianhui verfasserin (orcid)0000-0002-5742-0810 aut Spatiotemporal variation in near-surface $ CH_{4} $ concentrations in China over the last two decades 2021 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2021 Abstract Methane is one of the main greenhouse trace gases and seriously affects the radiation balance of Earth systems due to its strong heat absorption capacity and long atmospheric retention time. Based on the methane stratification data simulated by the community atmospheric model with chemistry (CAM-chem), near-surface methane concentrations were estimated by utilizing the Gaussian function, and the spatiotemporal variation in the near-surface methane concentration in China from 2001 to 2019 was discussed in this research. The results show that (1) based on the methane stratification concentration data simulated by the atmospheric chemical model, the near-surface $ CH_{4} $ concentration estimated by Gaussian function model is reliable, which provides a new method to estimate the near-surface $ CH_{4} $ concentration over China; (2) from 2001 to 2019, the near-surface methane concentration in China showed an increasing trend with an annual growth rate of 7.20±0.23 ppb·$ a^{−1} $. The annual maximum near-surface methane concentration was measured in winter, and the minimum was measured in summer; (3) the spatial distribution differences are obvious: the methane concentration in the east was higher than that in the west, and the methane concentration in the north was higher than that in the south. Moreover, the distributions of methane in the east and west are consistent with the division of Hu Huanyong population line. Methane Atmospheric chemistry model CAM-chem model Multiple Gaussian functions Spatiotemporal variations China Liu, Qingfang aut Wang, Kai aut Wang, Qiulong aut Wang, Li aut Liu, Yuchan aut Li, Maoyu aut Enthalten in Environmental science and pollution research Springer Berlin Heidelberg, 1994 28(2021), 34 vom: 23. Apr., Seite 47239-47250 (DE-627)171335805 (DE-600)1178791-0 (DE-576)038875101 0944-1344 nnns volume:28 year:2021 number:34 day:23 month:04 pages:47239-47250 https://doi.org/10.1007/s11356-021-14007-0 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC FID-BIODIV SSG-OLC-UMW SSG-OLC-ARC SSG-OLC-TEC SSG-OLC-CHE SSG-OLC-FOR GBV_ILN_252 GBV_ILN_267 GBV_ILN_2018 GBV_ILN_4277 AR 28 2021 34 23 04 47239-47250 |
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Spatiotemporal variation in near-surface $ CH_{4} $ concentrations in China over the last two decades |
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Abstract Methane is one of the main greenhouse trace gases and seriously affects the radiation balance of Earth systems due to its strong heat absorption capacity and long atmospheric retention time. Based on the methane stratification data simulated by the community atmospheric model with chemistry (CAM-chem), near-surface methane concentrations were estimated by utilizing the Gaussian function, and the spatiotemporal variation in the near-surface methane concentration in China from 2001 to 2019 was discussed in this research. The results show that (1) based on the methane stratification concentration data simulated by the atmospheric chemical model, the near-surface $ CH_{4} $ concentration estimated by Gaussian function model is reliable, which provides a new method to estimate the near-surface $ CH_{4} $ concentration over China; (2) from 2001 to 2019, the near-surface methane concentration in China showed an increasing trend with an annual growth rate of 7.20±0.23 ppb·$ a^{−1} $. The annual maximum near-surface methane concentration was measured in winter, and the minimum was measured in summer; (3) the spatial distribution differences are obvious: the methane concentration in the east was higher than that in the west, and the methane concentration in the north was higher than that in the south. Moreover, the distributions of methane in the east and west are consistent with the division of Hu Huanyong population line. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2021 |
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Abstract Methane is one of the main greenhouse trace gases and seriously affects the radiation balance of Earth systems due to its strong heat absorption capacity and long atmospheric retention time. Based on the methane stratification data simulated by the community atmospheric model with chemistry (CAM-chem), near-surface methane concentrations were estimated by utilizing the Gaussian function, and the spatiotemporal variation in the near-surface methane concentration in China from 2001 to 2019 was discussed in this research. The results show that (1) based on the methane stratification concentration data simulated by the atmospheric chemical model, the near-surface $ CH_{4} $ concentration estimated by Gaussian function model is reliable, which provides a new method to estimate the near-surface $ CH_{4} $ concentration over China; (2) from 2001 to 2019, the near-surface methane concentration in China showed an increasing trend with an annual growth rate of 7.20±0.23 ppb·$ a^{−1} $. The annual maximum near-surface methane concentration was measured in winter, and the minimum was measured in summer; (3) the spatial distribution differences are obvious: the methane concentration in the east was higher than that in the west, and the methane concentration in the north was higher than that in the south. Moreover, the distributions of methane in the east and west are consistent with the division of Hu Huanyong population line. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2021 |
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Abstract Methane is one of the main greenhouse trace gases and seriously affects the radiation balance of Earth systems due to its strong heat absorption capacity and long atmospheric retention time. Based on the methane stratification data simulated by the community atmospheric model with chemistry (CAM-chem), near-surface methane concentrations were estimated by utilizing the Gaussian function, and the spatiotemporal variation in the near-surface methane concentration in China from 2001 to 2019 was discussed in this research. The results show that (1) based on the methane stratification concentration data simulated by the atmospheric chemical model, the near-surface $ CH_{4} $ concentration estimated by Gaussian function model is reliable, which provides a new method to estimate the near-surface $ CH_{4} $ concentration over China; (2) from 2001 to 2019, the near-surface methane concentration in China showed an increasing trend with an annual growth rate of 7.20±0.23 ppb·$ a^{−1} $. The annual maximum near-surface methane concentration was measured in winter, and the minimum was measured in summer; (3) the spatial distribution differences are obvious: the methane concentration in the east was higher than that in the west, and the methane concentration in the north was higher than that in the south. Moreover, the distributions of methane in the east and west are consistent with the division of Hu Huanyong population line. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2021 |
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