Articles | Volume 19, issue 7
https://doi.org/10.5194/acp-19-4345-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-19-4345-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
04 Apr 2019
Research article |
| 04 Apr 2019
| 04 Apr 2019
Quantifying the UK's carbon dioxide flux: an atmospheric inverse modelling approach using a regional measurement network
School of Chemistry, University of Bristol, Bristol, BS8 1TS, UK
School of Chemistry, University of Bristol, Bristol, BS8 1TS, UK
Mark F. Lunt
School of Chemistry, University of Bristol, Bristol, BS8 1TS, UK
School of GeoSciences, University of Edinburgh, Edinburgh, EH9 3FF, UK
T. Luke Smallman
School of GeoSciences, University of Edinburgh, Edinburgh, EH9 3FF, UK
National Centre for Earth Observation, Edinburgh, EH9 3FF, UK
Edward Comyn-Platt
Centre for Ecology and Hydrology, Wallingford, OX10 8BB, UK
Alistair J. Manning
Hadley Centre, Met. Office, Exeter, EX1 3PB, UK
Anita L. Ganesan
School of Geographical Sciences, University of Bristol, Bristol, BS8 1SS, UK
Simon O'Doherty
School of Chemistry, University of Bristol, Bristol, BS8 1TS, UK
Ann R. Stavert
School of Chemistry, University of Bristol, Bristol, BS8 1TS, UK
Climate Science Centre, CSIRO Oceans and Atmosphere, Aspendale, VIC 3195, Australia
Kieran Stanley
School of Chemistry, University of Bristol, Bristol, BS8 1TS, UK
Mathew Williams
School of GeoSciences, University of Edinburgh, Edinburgh, EH9 3FF, UK
National Centre for Earth Observation, Edinburgh, EH9 3FF, UK
Peter Levy
Centre for Ecology and Hydrology (Edinburgh Research Station), Penicuik, E26 0QB, UK
Michel Ramonet
Laboratoire des Sciences du Climat et de l'Environnement, CEA-CNRS-UVSQ, Gif-sur-Yvette, 91198, France
Grant L. Forster
Centre for Ocean and Atmospheric Sciences, School of Environmental Sciences, University of East Anglia, Norwich, NR4 7TJ, UK
National Centre for Atmospheric Science, School of Environmental Sciences, University of East Anglia, Norwich, NR4 7TJ, UK
Andrew C. Manning
Centre for Ocean and Atmospheric Sciences, School of Environmental Sciences, University of East Anglia, Norwich, NR4 7TJ, UK
Paul I. Palmer
School of GeoSciences, University of Edinburgh, Edinburgh, EH9 3FF, UK
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Cited
17 citations as recorded by crossref.
- The regional European atmospheric transport inversion comparison, EUROCOM: first results on European-wide terrestrial carbon fluxes for the period 2006–2015 G. Monteil et al. 10.5194/acp-20-12063-2020
- Parameter uncertainty dominates C-cycle forecast errors over most of Brazil for the 21st century T. Smallman et al. 10.5194/esd-12-1191-2021
- Evidence of a recent decline in UK emissions of hydrofluorocarbons determined by the InTEM inverse model and atmospheric measurements A. Manning et al. 10.5194/acp-21-12739-2021
- Verifying national inventory-based combustion emissions of CO2 across the UK and mainland Europe using satellite observations of atmospheric CO and CO2 T. Scarpelli et al. 10.5194/acp-24-10773-2024
- Greenhouse gas observation network design for Africa A. Nickless et al. 10.1080/16000889.2020.1824486
- Comparing national greenhouse gas budgets reported in UNFCCC inventories against atmospheric inversions Z. Deng et al. 10.5194/essd-14-1639-2022
- Changes in net ecosystem exchange over Europe during the 2018 drought based on atmospheric observations R. Thompson et al. 10.1098/rstb.2019.0512
- Development of an urban greenhouse gas modelling system to support a London monitoring network T. Hoare et al. 10.1002/wea.3795
- Variations of Terrestrial Net Ecosystem Productivity in China Driven by Climate Change and Human Activity from 2010 to 2020 M. Xu et al. 10.3390/f15091484
- Uncertainty of hourly-average concentration values derived from non-continuous measurements L. Haszpra & E. Prácser 10.5194/amt-14-3561-2021
- Radiocarbon Measurements Reveal Underestimated Fossil CH4 and CO2 Emissions in London G. Zazzeri et al. 10.1029/2023GL103834
- Scale variance in the carbon dynamics of fragmented, mixed-use landscapes estimated using model–data fusion D. Milodowski et al. 10.5194/bg-20-3301-2023
- Bayesian atmospheric tomography for detection and quantification of methane emissions: application to data from the 2015 Ginninderra release experiment L. Cartwright et al. 10.5194/amt-12-4659-2019
- Effect of assimilating CO2 observations in the Korean Peninsula on the inverse modeling to estimate surface CO2 flux over Asia M. Cho et al. 10.1371/journal.pone.0263925
- Atmospheric oxygen as a tracer for fossil fuel carbon dioxide: a sensitivity study in the UK H. Chawner et al. 10.5194/acp-24-4231-2024
- A model for urban biogenic CO<sub>2</sub> fluxes: Solar-Induced Fluorescence for Modeling Urban biogenic Fluxes (SMUrF v1) D. Wu et al. 10.5194/gmd-14-3633-2021
- Challenges in Scaling Up Greenhouse Gas Fluxes: Experience From the UK Greenhouse Gas Emissions and Feedbacks Program P. Levy et al. 10.1029/2021JG006743
16 citations as recorded by crossref.
- The regional European atmospheric transport inversion comparison, EUROCOM: first results on European-wide terrestrial carbon fluxes for the period 2006–2015 G. Monteil et al. 10.5194/acp-20-12063-2020
- Parameter uncertainty dominates C-cycle forecast errors over most of Brazil for the 21st century T. Smallman et al. 10.5194/esd-12-1191-2021
- Evidence of a recent decline in UK emissions of hydrofluorocarbons determined by the InTEM inverse model and atmospheric measurements A. Manning et al. 10.5194/acp-21-12739-2021
- Verifying national inventory-based combustion emissions of CO2 across the UK and mainland Europe using satellite observations of atmospheric CO and CO2 T. Scarpelli et al. 10.5194/acp-24-10773-2024
- Greenhouse gas observation network design for Africa A. Nickless et al. 10.1080/16000889.2020.1824486
- Comparing national greenhouse gas budgets reported in UNFCCC inventories against atmospheric inversions Z. Deng et al. 10.5194/essd-14-1639-2022
- Changes in net ecosystem exchange over Europe during the 2018 drought based on atmospheric observations R. Thompson et al. 10.1098/rstb.2019.0512
- Development of an urban greenhouse gas modelling system to support a London monitoring network T. Hoare et al. 10.1002/wea.3795
- Variations of Terrestrial Net Ecosystem Productivity in China Driven by Climate Change and Human Activity from 2010 to 2020 M. Xu et al. 10.3390/f15091484
- Uncertainty of hourly-average concentration values derived from non-continuous measurements L. Haszpra & E. Prácser 10.5194/amt-14-3561-2021
- Radiocarbon Measurements Reveal Underestimated Fossil CH4 and CO2 Emissions in London G. Zazzeri et al. 10.1029/2023GL103834
- Scale variance in the carbon dynamics of fragmented, mixed-use landscapes estimated using model–data fusion D. Milodowski et al. 10.5194/bg-20-3301-2023
- Bayesian atmospheric tomography for detection and quantification of methane emissions: application to data from the 2015 Ginninderra release experiment L. Cartwright et al. 10.5194/amt-12-4659-2019
- Effect of assimilating CO2 observations in the Korean Peninsula on the inverse modeling to estimate surface CO2 flux over Asia M. Cho et al. 10.1371/journal.pone.0263925
- Atmospheric oxygen as a tracer for fossil fuel carbon dioxide: a sensitivity study in the UK H. Chawner et al. 10.5194/acp-24-4231-2024
- A model for urban biogenic CO<sub>2</sub> fluxes: Solar-Induced Fluorescence for Modeling Urban biogenic Fluxes (SMUrF v1) D. Wu et al. 10.5194/gmd-14-3633-2021
Latest update: 20 Nov 2024
Short summary
Understanding carbon dioxide (CO2) fluxes from the terrestrial biosphere on a national scale is important for evaluating land use strategies to mitigate climate change. We estimate emissions of CO2 from the UK biosphere using atmospheric data in a top-down approach. Our findings show that bottom-up estimates from models of biospheric fluxes overestimate the amount of CO2 uptake in summer. This suggests these models wrongly estimate or omit key processes, e.g. land disturbance due to harvest.
Understanding carbon dioxide (CO2) fluxes from the terrestrial biosphere on a national scale is...
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