Articles | Volume 17, issue 22
Atmos. Chem. Phys., 17, 14145–14169, 2017
https://doi.org/10.5194/acp-17-14145-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Atmos. Chem. Phys., 17, 14145–14169, 2017
https://doi.org/10.5194/acp-17-14145-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
28 Nov 2017
Research article
| 28 Nov 2017
Spatiotemporal patterns of the fossil-fuel CO2 signal in central Europe: results from a high-resolution atmospheric transport model
Yu Liu et al.
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Cited
14 citations as recorded by crossref.
- On the diurnal, weekly, and seasonal cycles and annual trends in atmospheric CO<sub>2</sub> at Mount Zugspitze, Germany, during 1981–2016 Y. Yuan et al. 10.5194/acp-19-999-2019
- Pixel Size and Revisit Rate Requirements for Monitoring Power Plant CO2 Emissions from Space T. Hill & R. Nassar 10.3390/rs11131608
- Quantifying CO<sub>2</sub> emissions of a city with the Copernicus Anthropogenic CO<sub>2</sub> Monitoring satellite mission G. Kuhlmann et al. 10.5194/amt-13-6733-2020
- Multiscale analysis on spatiotemporal dynamics of energy consumption CO2 emissions in China: Utilizing the integrated of DMSP-OLS and NPP-VIIRS nighttime light datasets Q. Lv et al. 10.1016/j.scitotenv.2019.134394
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- Accounting for the vertical distribution of emissions in atmospheric CO<sub>2</sub> simulations D. Brunner et al. 10.5194/acp-19-4541-2019
- High-resolution simulation of wintertime fossil fuel CO2 in Beijing, China: Characteristics, sources, and regional transport T. Feng et al. 10.1016/j.atmosenv.2018.10.054
- A high-definition spatially explicit modelling approach for national greenhouse gas emissions from industrial processes: reducing the errors and uncertainties in global emission modelling N. Charkovska et al. 10.1007/s11027-018-9836-6
- Modeling the environmental implications of car ownership and energy consumption in the UK: Evidence from NARDL model O. Funsho Idowu et al. 10.1080/15568318.2021.1969708
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- Simulations of summertime fossil fuel CO2 in the Guanzhong basin, China T. Feng et al. 10.1016/j.scitotenv.2017.12.021
- Spatiotemporal Variations of City-Level Carbon Emissions in China during 2000–2017 Using Nighttime Light Data Y. Sun et al. 10.3390/rs12182916
- High-resolution spatiotemporal patterns of China’s FFCO2 emissions under the impact of LUCC from 2000 to 2015 J. Zhao et al. 10.1088/1748-9326/ab6edc
14 citations as recorded by crossref.
- On the diurnal, weekly, and seasonal cycles and annual trends in atmospheric CO<sub>2</sub> at Mount Zugspitze, Germany, during 1981–2016 Y. Yuan et al. 10.5194/acp-19-999-2019
- Pixel Size and Revisit Rate Requirements for Monitoring Power Plant CO2 Emissions from Space T. Hill & R. Nassar 10.3390/rs11131608
- Quantifying CO<sub>2</sub> emissions of a city with the Copernicus Anthropogenic CO<sub>2</sub> Monitoring satellite mission G. Kuhlmann et al. 10.5194/amt-13-6733-2020
- Multiscale analysis on spatiotemporal dynamics of energy consumption CO2 emissions in China: Utilizing the integrated of DMSP-OLS and NPP-VIIRS nighttime light datasets Q. Lv et al. 10.1016/j.scitotenv.2019.134394
- An inversion method for estimating strong point carbon dioxide emissions using a differential absorption Lidar T. Shi et al. 10.1016/j.jclepro.2020.122434
- An online emission module for atmospheric chemistry transport models: implementation in COSMO-GHG v5.6a and COSMO-ART v5.1-3.1 M. Jähn et al. 10.5194/gmd-13-2379-2020
- Accounting for the vertical distribution of emissions in atmospheric CO<sub>2</sub> simulations D. Brunner et al. 10.5194/acp-19-4541-2019
- High-resolution simulation of wintertime fossil fuel CO2 in Beijing, China: Characteristics, sources, and regional transport T. Feng et al. 10.1016/j.atmosenv.2018.10.054
- A high-definition spatially explicit modelling approach for national greenhouse gas emissions from industrial processes: reducing the errors and uncertainties in global emission modelling N. Charkovska et al. 10.1007/s11027-018-9836-6
- Modeling the environmental implications of car ownership and energy consumption in the UK: Evidence from NARDL model O. Funsho Idowu et al. 10.1080/15568318.2021.1969708
- Detectability of CO<sub>2</sub> emission plumes of cities and power plants with the Copernicus Anthropogenic CO<sub>2</sub> Monitoring (CO2M) mission G. Kuhlmann et al. 10.5194/amt-12-6695-2019
- Simulations of summertime fossil fuel CO2 in the Guanzhong basin, China T. Feng et al. 10.1016/j.scitotenv.2017.12.021
- Spatiotemporal Variations of City-Level Carbon Emissions in China during 2000–2017 Using Nighttime Light Data Y. Sun et al. 10.3390/rs12182916
- High-resolution spatiotemporal patterns of China’s FFCO2 emissions under the impact of LUCC from 2000 to 2015 J. Zhao et al. 10.1088/1748-9326/ab6edc
Latest update: 08 Aug 2022
Short summary
We analyze fossil fuel signals in atmospheric CO2 over Europe using a high-resolution atmospheric transport model and diurnal emission data. We find that fossil fuel CO2 accounts for more than half of the atmospheric CO2 variations, mainly at diurnal timescales. The covariance of diurnal emission and transport also leads to a substantial rectification effect. Thus, the consideration of diurnal emissions and high-resolution transport is paramount for accurately modeling the fossil fuel signal.
We analyze fossil fuel signals in atmospheric CO2 over Europe using a high-resolution...
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