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1. 12 years of continuous atmospheric O2, CO2 and APO data from Weybourne Atmospheric Observatory in the United Kingdom

Author

Adcock, Karina E., primary, Pickers, Penelope A., additional, Manning, Andrew C., additional, Forster, Grant L., additional, Fleming, Leigh S., additional, Barningham, Thomas, additional, Wilson, Philip A., additional, Kozlova, Elena A., additional, Hewitt, Marica, additional, Etchells, Alex J., additional, and Macdonald, Andy J., additional

Published
2023
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3. Supplementary material to "12 years of continuous atmospheric O2, CO2 and APO data from Weybourne Atmospheric Observatory in the United Kingdom"

Author

Adcock, Karina E., primary, Pickers, Penelope A., additional, Manning, Andrew C., additional, Forster, Grant L., additional, Fleming, Leigh S., additional, Barningham, Thomas, additional, Wilson, Philip A., additional, Kozlova, Elena A., additional, Hewitt, Marica, additional, Etchells, Alex J., additional, and Macdonald, Andy J., additional

Published
2023
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4. 12 years of continuous atmospheric O2, CO2 and APO data from Weybourne Atmospheric Observatory in the United Kingdom

Author

Adcock, Karina E., Pickers, Penelope A., Manning, Andrew C., Forster, Grant L., Fleming, Leigh S., Barningham, Thomas, Wilson, Philip A., Kozlova, Elena A., Hewitt, Marica, Etchells, Alex J., Macdonald, Andy J., Adcock, Karina E., Pickers, Penelope A., Manning, Andrew C., Forster, Grant L., Fleming, Leigh S., Barningham, Thomas, Wilson, Philip A., Kozlova, Elena A., Hewitt, Marica, Etchells, Alex J., and Macdonald, Andy J.

Abstract

We present a 12-year time series of continuous atmospheric measurements of O2 and CO2 at the Weybourne Atmospheric Observatory in the United Kingdom. These measurements are combined into the term atmospheric potential oxygen (APO), a tracer that is invariant to terrestrial biosphere fluxes. The CO2, O2 and APO datasets discussed are hourly averages between May 2010 and December 2021. We include details of our measurement system and calibration procedures, and describe the main long-term and seasonal features of the time series. The 2 min repeatability of the measurement system is approximately ±3 per meg for O2 and approximately ±0.005 ppm for CO2. The time series shows average long-term trends of 2.40 ppm yr−1 (2.38 to 2.42) for CO2, −24.0 per meg yr−1 for O2 (−24.3 to −23.8) and −11.4 per meg yr−1 (−11.7 to −11.3) for APO, over the 12-year period. The average seasonal cycle peak-to-peak amplitudes are 16 ppm for CO2, 134 per meg for O2 and 68 per meg for APO. The diurnal cycles of CO2 and O2 vary considerably between seasons. The datasets are publicly available at https://doi.org/10.18160/Z0GF-MCWH (Adcock et al., 2023) and have many current and potential scientific applications in constraining carbon cycle processes, such as investigating air–sea exchange of CO2 and O2 and top-down quantification of fossil fuel CO2.

Published
2023

5. Diurnal variability of atmospheric O2, CO2, and their exchange ratio above a boreal forest in southern Finland

Author

Faassen, Kim A.P., Nguyen, Linh N.T., Broekema, Eadin R., Kers, Bert A.M., Mammarella, Ivan, Vesala, Timo, Pickers, Penelope A., Manning, Andrew C., Vilà-Guerau De Arellano, Jordi, Meijer, Harro A.J., Peters, Wouter, Luijkx, Ingrid T., Faassen, Kim A.P., Nguyen, Linh N.T., Broekema, Eadin R., Kers, Bert A.M., Mammarella, Ivan, Vesala, Timo, Pickers, Penelope A., Manning, Andrew C., Vilà-Guerau De Arellano, Jordi, Meijer, Harro A.J., Peters, Wouter, and Luijkx, Ingrid T.

Abstract

The exchange ratio (ER) between atmospheric O2 and CO2 is a useful tracer for better understanding the carbon budget on global and local scales. The variability of ER (in molO2permolCO2) between terrestrial ecosystems is not well known, and there is no consensus on how to derive the ER signal of an ecosystem, as there are different approaches available, either based on concentration (ERatmos) or flux measurements (ERforest). In this study we measured atmospheric O2 and CO2 concentrations at two heights (23 and 125m) above the boreal forest in Hyytiälä, Finland. Such measurements of O2 are unique and enable us to potentially identify which forest carbon loss and production mechanisms dominate over various hours of the day. We found that the ERatmos signal at 23m not only represents the diurnal cycle of the forest exchange but also includes other factors, including entrainment of air masses in the atmospheric boundary layer before midday, with different thermodynamic and atmospheric composition characteristics. To derive ERforest, we infer O2 fluxes using multiple theoretical and observation-based micro-meteorological formulations to determine the most suitable approach. Our resulting ERforest shows a distinct difference in behaviour between daytime (0.92±0.17molmol-1) and nighttime (1.03±0.05molmol-1). These insights demonstrate the diurnal variability of different ER signals above a boreal forest, and we also confirmed that the signals of ERatmos and ERforest cannot be used interchangeably. Therefore, we recommend measurements on multiple vertical levels to derive O2 and CO2 fluxes for the ERforest signal instead of a single level time series of the concentrations for the ERatmos signal. We show that ERforest can be further split into specific signals for respiration (1.03±0.05molmol-1) and photosynthesis (0.96±0.12molmol-1). This estimation allows us to separate the net ecosystem exchange (NEE) into gross primary production (GPP) and total ecosystem respiration (TE

Published
2023

6. The suitability of atmospheric oxygen measurements to constrain western European fossil-fuel CO2 emissions and their trends.

Author

Rödenbeck, Christian, Adcock, Karina E., Eritt, Markus, Gachkivskyi, Maksym, Gerbig, Christoph, Hammer, Samuel, Jordan, Armin, Keeling, Ralph F., Levin, Ingeborg, Maier, Fabian, Manning, Andrew C., Moossen, Heiko, Munassar, Saqr, Pickers, Penelope A., Rothe, Michael, Tohjima, Yasunori, and Zaehle, Sönke

Subjects
CARBON emissions, ATMOSPHERIC carbon dioxide, ATMOSPHERIC oxygen, ATMOSPHERIC methane, ATMOSPHERIC transport, BURNING of land, MEASUREMENT errors
Abstract

Atmospheric measurements of the O2/N2 ratio and the CO2 mole fraction (combined into the conceptual tracer "Atmospheric Potential Oxygen", APO) over continents have been proposed as a constraint on CO2 emissions from fossil-fuel burning. Here we assess the suitability of such APO data to constrain anthropogenic CO2 emissions in western Europe, with particular focus on their decadal trends. We use an inversion of atmospheric transport to estimate spatially and temporally explicit scaling factors on a bottom-up fossil-fuel emissions inventory. Based on the small number of currently available observational records, our CO2 emissions estimates show relatively large apparent year-to-year variations, exceeding the expected uncertainty of the bottom-up inventory and precluding the calculation of statistically significant trends. We were not able to trace the apparent year-to-year variations back to particular properties of the APO data. Inversion of synthetic APO data, however, confirms that data information content and degrees of freedom are sufficient to successfully correct a counterfactual prior. Larger sets of measurement stations, such as the recently started APO observations from the Integrated Carbon Observation System (ICOS) European research infrastructure, improve the constraint and may ameliorate possible problems with local signals or with measurement or model errors at the stations. We further tested the impact of uncertainties in the O2:CO2 stoichiometries of fossil-fuel burning and land biospheric exchange and found they are not fundamental obstacles to estimating decadal trends in fossil-fuel CO2 emissions, though further work on fossil-fuel O2:CO2 stoichiometries seems necessary. [ABSTRACT FROM AUTHOR]

Published
2023
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9. Diurnal variability of atmospheric O2, CO2, and their exchange ratio above a boreal forest in southern Finland

Author

Faassen, Kim A. P., primary, Nguyen, Linh N. T., additional, Broekema, Eadin R., additional, Kers, Bert A. M., additional, Mammarella, Ivan, additional, Vesala, Timo, additional, Pickers, Penelope A., additional, Manning, Andrew C., additional, Vilà-Guerau de Arellano, Jordi, additional, Meijer, Harro A. J., additional, Peters, Wouter, additional, and Luijkx, Ingrid T., additional

Published
2023
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10. The suitability of atmospheric oxygen measurements to constrain Western European fossil-fuel CO2 emissions and their trends.

Author

Rödenbeck, Christian, Adcock, Karina E., Eritt, Markus, Gachkivsky, Maksym, Gerbig, Christoph, Hammer, Samuel, Jordan, Armin, Keeling, Ralph F., Levin, Ingeborg, Maier, Fabian, Manning, Andrew C., Moossen, Heiko, Munassar, Saqr, Pickers, Penelope A., Rothe, Michael, Tohjima, Yasunori, and Zaehle, Sönke

Subjects
ATMOSPHERIC oxygen, ATMOSPHERIC methane, EMISSION inventories, ATMOSPHERIC transport, MEASUREMENT errors, BURNING of land, MOLE fraction
Abstract

Atmospheric measurements of the O2/N2 ratio and the CO2 mole fraction (combined into the conceptual tracer 'Atmospheric Potential Oxygen', APO) over continents have been proposed as a constraint on CO2 emissions from fossil-fuel burning. Here we assess the suitability of such APO data to constrain anthropogenic CO2 emissions in Western Europe, with particular focus on their decadal trends. We use an inversion of atmospheric transport to estimate spatially and temporally explicit scaling factors on a bottom-up fossil-fuel emissions inventory. Based on the small number of currently available observational records, our CO2 emissions estimates show relatively large apparent year-to-year variations, exceeding the expected uncertainty of the bottom-up inventory and precluding the calculation of statistically significant trends. We were not able to trace the apparent year-to-year variations back to particular properties of the APO data. Inversion of synthetic APO data, however, confirms that data information content and degrees of freedom are sufficient to successfully correct a counterfactual prior. Larger sets of measurement stations, such as the recently started APO observations from the Integrated Carbon Observation System (ICOS) European research infrastructure, improve the constraint and may ameliorate possible problems with local signals or with measurement or model errors at the stations. We further tested the impact of uncertainties in the O2:CO2 stoichiometries of fossil-fuel burning and land biospheric exchange and found they are not fundamental obstacles to estimating decadal trends in fossil-fuel CO2 emissions, though further work on fossil-fuel O2:CO2 stoichiometries seems necessary. [ABSTRACT FROM AUTHOR]

Published
2023
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11. 12 years of continuous atmospheric O2, CO2 and APO data from Weybourne Atmospheric Observatory in the United Kingdom.

Author

Adcock, Karina E., Pickers, Penelope A., Manning, Andrew C., Forster, Grant L., Fleming, Leigh S., Barningham, Thomas, Wilson, Philip A., Kozlova, Elena A., Hewitt, Marica, Etchells, Alex J., and Macdonald, Andy J.

Subjects
TIME series analysis, OBSERVATORIES, ATMOSPHERIC oxygen, FOSSIL fuels
Abstract

We present analyses of a 12-year time series of continuous atmospheric measurements of O2 and CO2 at the Weybourne Atmospheric Observatory in the United Kingdom. These measurements are combined into the term Atmospheric Potential Oxygen (APO), a tracer that is conservative with respect to terrestrial biosphere processes. The CO2, O2 and APO datasets discussed are hourly averages between May 2010 and December 2021. We include details of our measurement system and calibration procedures, and describe the main long-term and seasonal features of the time series. The 2-minute repeatability of the measurement system is approximately ±3 per meg for O2 and approximately ±0.005 ppm for CO2. The time series shows average long-term trends of 2.40 ppm yr-1 (2.38 to 2.42) for CO2, -24.0 per meg yr-1 for O2 (-24.3 to -23.8) and -11.4 per meg yr-1 (-11.7 to -11.3) for APO, over the 12-year period. The average seasonal cycle peak-to-peak amplitudes are 16 ppm for CO2, 134 per meg for O2, and 68 per meg for APO. The diurnal cycles of CO2 and O2 vary considerably between seasons. The datasets are publicly available at https://doi.org/10.18160/Z0GF-MCWH (Adcock et al., 2023) and have many current and potential scientific applications in constraining carbon cycle processes, such as investigating air-sea exchange of CO2 and O2, and top-down quantification of fossil fuel CO2. [ABSTRACT FROM AUTHOR]

Published
2023
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14. Diurnal variability of atmospheric O2, CO2 and their exchange ratio above a boreal forest in southern Finland

Author

Faassen, Kim A. P., primary, Nguyen, Linh N. T., additional, Broekema, Eadin R., additional, Kers, Bert A. M., additional, Mammarella, Ivan, additional, Vesala, Timo, additional, Pickers, Penelopy A., additional, Manning, Andrew C., additional, Vilà-Guerau de Arellano, Jordi, additional, Meijer, Harro A. J., additional, Peters, Wouter, additional, and Luijkx, Ingrid T., additional

Published
2022
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17. Two decades of flask observations of atmospheric δO2/N2, CO2, and APO at stations Lutjewad (the Netherlands) and Mace Head (Ireland) plus 3 years from Halley station (Antarctica)

Author

Nguyen, Linh N.T., Meijer, Harro A.J., van Leeuwen, Charlotte, Kers, Bert A.M., Scheeren, Hubertus A., Jones, Anna E., Brough, Neil, Barningham, Thomas, Pickers, Penelope A., Manning, Andrew C., and Luijkx, Ingrid T.

Abstract

We present 20-year flask sample records of atmospheric CO2, δ(O2/N2), and atmospheric potential oxygen (APO) from the stations Lutjewad (the Netherlands) and Mace Head (Ireland), and a 3-year record from Halley station (Antarctica). We include details of our calibration procedures and the stability of our calibration scale over time, which we estimate to be 3 per meg over the 11 years of calibration, and our compatibility with the international Scripps O2 scale. The measurement records from Lutjewad and Mace Head show similar long-term trends during the period 2002–2018 of 2.31 ± 0.07 ppm yr−1 for CO2 and −21.2 ± 0.8 per meg yr−1 for δ(O2/N2) at Lutjewad, and 2.22 ± 0.04 ppm yr−1 for CO2 and −21.3 ± 0.9 per meg yr−1 for δ(O2/N2) at Mace Head. They also show a similar δ(O2/N2) seasonal cycle with an amplitude of 54 ± 4 per meg at Lutjewad and 61 ± 5 per meg at Mace Head, while the CO2 seasonal amplitude at Lutjewad (16.8 ± 0.5 ppm) is slightly higher than that at Mace Head (14.8 ± 0.3 ppm). We show that the observed long-term trends and seasonal cycles are in good agreement with the measurements from various other stations, especially the measurements from the Weybourne Atmospheric Observatory (United Kingdom). However, there are remarkable differences in the progression of annual trends between the Mace Head and Lutjewad records for δ(O2/N2) and APO, which might in part be caused by sampling differences, but also by environmental effects, such as North Atlantic Ocean oxygen ventilation changes to which Mace Head is more sensitive. The Halley record shows clear trends and seasonality in δ(O2/N2) and APO, the latter agreeing especially well with continuous measurements at the same location made by the University of East Anglia (UEA), while CO2 and δ(O2/N2) present slight disagreements, most likely caused by small leakages during sampling. From our 2002–2018 records, we find a good agreement with Global Carbon Budget 2021 (Friedlingstein et al. (2021) for the global ocean carbon sink: 2.1 ± 0.8 PgC yr−1 , based on the Lutjewad record. The data presented in this work are available at https://doi.org/10.18160/qq7d-t060 (Nguyen et al., 2021).

Published
2022

18. Two decades of flask observations of atmospheric δ(O2∕N2), CO2, and APO at stations Lutjewad (the Netherlands) and Mace Head (Ireland), and 3 years from Halley station (Antarctica)

Author

Nguyen, Linh N. T., Meijer, Harro A. J., Leeuwen, Charlotte, Kers, Bert A. M., Scheeren, Hubertus A., Jones, Anna E., Brough, Neil, Barningham, Thomas, Pickers, Penelope A., Manning, Andrew C., and Luijkx, Ingrid T.

Abstract

We present 20-year flask sample records of atmospheric CO2, δ(O2/N2), and atmospheric potential oxygen (APO) from the stations Lutjewad (the Netherlands) and Mace Head (Ireland), and a 3-year record from Halley station (Antarctica). We include details of our calibration procedures and the stability of our calibration scale over time, which we estimate to be 3 per meg over the 11 years of calibration, and our compatibility with the international Scripps O2 scale. The measurement records from Lutjewad and Mace Head show similar long-term trends during the period 2002–2018 of 2.31 ± 0.07 ppm yr−1 for CO2 and −21.2 ± 0.8 per meg yr−1 for δ(O2/N2) at Lutjewad, and 2.22 ± 0.04 ppm yr−1 for CO2 and −21.3 ± 0.9 per meg yr−1 for δ(O2/N2) at Mace Head. They also show a similar δ(O2/N2) seasonal cycle with an amplitude of 54 ± 4 per meg at Lutjewad and 61 ± 5 per meg at Mace Head, while the CO2 seasonal amplitude at Lutjewad (16.8 ± 0.5 ppm) is slightly higher than that at Mace Head (14.8 ± 0.3 ppm). We show that the observed long-term trends and seasonal cycles are in good agreement with the measurements from various other stations, especially the measurements from the Weybourne Atmospheric Observatory (United Kingdom). However, there are remarkable differences in the progression of annual trends between the Mace Head and Lutjewad records for δ(O2/N2) and APO, which might in part be caused by sampling differences, but also by environmental effects, such as North Atlantic Ocean oxygen ventilation changes to which Mace Head is more sensitive. The Halley record shows clear trends and seasonality in δ(O2/N2) and APO, the latter agreeing especially well with continuous measurements at the same location made by the University of East Anglia (UEA), while CO2 and δ(O2/N2) present slight disagreements, most likely caused by small leakages during sampling. From our 2002–2018 records, we find a good agreement with Global Carbon Budget 2021 (Friedlingstein et al. (2021) for the global ocean carbon sink: 2.1 ± 0.8 PgC yr−1, based on the Lutjewad record. The data presented in this work are available at https://doi.org/10.18160/qq7d-t060 (Nguyen et al., 2021).

Published
2022

19. Origin and magnitude of interannual variabilities in Southern Ocean air-sea O2 and CO2 fluxes

Author

Mayot, Nicolas, Le Quéré, Corinne, Manning, Andrew C., Bopp, Laurent, Gruber, Nicolas, Hauck, Judith, Ilyina, Tatiana, Keeling, R., Resplandy, Laure, Rödenbeck, Christian, Schwinger, Jörg, Séférian, Roland, Willis, David, Mayot, Nicolas, Le Quéré, Corinne, Manning, Andrew C., Bopp, Laurent, Gruber, Nicolas, Hauck, Judith, Ilyina, Tatiana, Keeling, R., Resplandy, Laure, Rödenbeck, Christian, Schwinger, Jörg, Séférian, Roland, and Willis, David

Published
2022

20. Novel quantification of regional fossil fuel CO2 reductions during COVID-19 lockdowns using atmospheric oxygen measurements

Author

Pickers, Penelope A., Manning, Andrew C., Quéré, Corinne Le, Forster, Grant L., Luijkx, Ingrid T., Gerbig, Christoph, Fleming, Leigh S., Sturges, William T., Pickers, Penelope A., Manning, Andrew C., Quéré, Corinne Le, Forster, Grant L., Luijkx, Ingrid T., Gerbig, Christoph, Fleming, Leigh S., and Sturges, William T.

Abstract

It is not currently possible to quantify regional-scale fossil fuel carbon dioxide (ffCO2) emissions with high accuracy in near real time. Existing atmospheric methods for separating ffCO2 from large natural carbon dioxide variations are constrained by sampling limitations, so that estimates of regional changes in ffCO2 emissions, such as those occurring in response to coronavirus disease 2019 (COVID-19) lockdowns, rely on indirect activity data. We present a method for quantifying regional signals of ffCO2 based on continuous atmospheric measurements of oxygen and carbon dioxide combined into the tracer "atmospheric potential oxygen"(APO). We detect and quantify ffCO2 reductions during 2020-2021 caused by the two U.K. COVID-19 lockdowns individually using APO data from Weybourne Atmospheric Observatory in the United Kingdom and a machine learning algorithm. Our APO-based assessment has near-real-time potential and provides high-frequency information that is in good agreement with the spread of ffCO2 emissions reductions from three independent lower-frequency U.K. estimates.

Published
2022

21. Two decades of flask observations of atmospheric (O2/N2), CO2, and APO at stations Lutjewad (the Netherlands) and Mace Head (Ireland), and 3 years from Halley station (Antarctica)

Author

Nguyen, Linh N.T., Meijer, Harro A.J., Van Leeuwen, Charlotte, Kers, Bert A.M., Scheeren, Hubertus A., Jones, Anna E., Brough, Neil, Barningham, Thomas, Pickers, Penelope A., Manning, Andrew C., Luijkx, Ingrid T., Nguyen, Linh N.T., Meijer, Harro A.J., Van Leeuwen, Charlotte, Kers, Bert A.M., Scheeren, Hubertus A., Jones, Anna E., Brough, Neil, Barningham, Thomas, Pickers, Penelope A., Manning, Andrew C., and Luijkx, Ingrid T.

Abstract

We present 20-year flask sample records of atmospheric CO2, (O2/N2), and atmospheric potential oxygen (APO) from the stations Lutjewad (the Netherlands) and Mace Head (Ireland), and a 3-year record from Halley station (Antarctica). We include details of our calibration procedures and the stability of our calibration scale over time, which we estimate to be 3 per meg over the 11 years of calibration, and our compatibility with the international Scripps O2 scale. The measurement records from Lutjewad and Mace Head show similar long-Term trends during the period 2002-2018 of 2.31g0.07g ppmg yr-1 for CO2 and-21.2g0.8 per megg yr-1 for (O2/N2) at Lutjewad, and 2.22g0.04g ppmg yr-1 for CO2 and-21.3g0.9 per megg yr-1 for (O2/N2) at Mace Head. They also show a similar (O2/N2) seasonal cycle with an amplitude of 54g4 per meg at Lutjewad and 61g5 per meg at Mace Head, while the CO2 seasonal amplitude at Lutjewad (16.8g0.5g ppm) is slightly higher than that at Mace Head (14.8g0.3g ppm). We show that the observed long-Term trends and seasonal cycles are in good agreement with the measurements from various other stations, especially the measurements from the Weybourne Atmospheric Observatory (United Kingdom). However, there are remarkable differences in the progression of annual trends between the Mace Head and Lutjewad records for (O2/N2) and APO, which might in part be caused by sampling differences, but also by environmental effects, such as North Atlantic Ocean oxygen ventilation changes to which Mace Head is more sensitive. The Halley record shows clear trends and seasonality in (O2/N2) and APO, the latter agreeing especially well with continuous measurements at the same location made by the University of East Anglia (UEA), while CO2 and (O2/N2) present slight disagreements, most likely caused by small leakages during sampling. From our 2002-2018 records, we find a good agreement with Global Carbon Budget 2021 (Friedlingstein et al. (2021) for the global ocean carbon sink

Published
2022

23. Two decades of flask observations of atmospheric <i>δ</i>(O<sub>2</sub>∕N<sub>2</sub>), CO<sub>2</sub>, and APO at stations Lutjewad (the Netherlands) and Mace Head (Ireland), and 3 years from Halley station (Antarctica)

Author

Nguyen, Linh N. T., primary, Meijer, Harro A. J., additional, van Leeuwen, Charlotte, additional, Kers, Bert A. M., additional, Scheeren, Hubertus A., additional, Jones, Anna E., additional, Brough, Neil, additional, Barningham, Thomas, additional, Pickers, Penelope A., additional, Manning, Andrew C., additional, and Luijkx, Ingrid T., additional

Published
2022
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24. A Modeling Approach to Investigate Drivers, Variability and Uncertainties in O2 Fluxes and the O2:CO2 Exchange Ratios in a Temperate Forest.

Author

Yuan Yan, Klosterhalfen, Anne, Moyano, Fernando, Cuntz, Matthias, Manning, Andrew C., and Knohl, Alexander

Subjects
LATENT heat, CIRCADIAN rhythms, MOLE fraction, ATMOSPHERE, HEAT flux, TEMPERATE forests
Abstract

The O2:CO2 exchange ratio (ER) between terrestrial ecosystems and the atmosphere is a key parameter for partitioning global ocean and land carbon fluxes. The long-term terrestrial ER is considered to be close to 1.10 moles of O2 consumed per mole of CO2 produced. Due to the technical challenge in measuring directly the ER of entire terrestrial ecosystems (EReco), little is known about the variations in ER at the hourly and seasonal scales as well as how different components contribute to EReco. In this modeling study, we explore the variability and drivers of EReco and evaluate the hypothetical uncertainty in determining ecosystem O2 fluxes based on current instrument precision. We adapted the onedimensional, multi-layer atmosphere-biosphere gas exchange model, CANVEG, to simulate hourly EReco from modeled O2 and CO2 fluxes in a temperate beech forest in Germany. We found that the annual mean EReco ranged from 1.06 to 1.12 mol mol -1 within the five years’ study period. Hourly EReco showed strong variations over diel and seasonal cycles and within the vertical canopy profile. Determination of ER from O2 and CO2 mole fractions in air above and within the canopy (ERconc) varied between 1.115 and 1.15 mol mol-1 . CANVEG simulations also indicated that ecosystem O2 fluxes could be derived using the flux-gradient method in combination with measurements of vertical scalar gradients and CO2, sensible heat or latent heat fluxes obtained with the eddy covariance technique. Owing to measurement uncertainties, however, the uncertainty in estimated O2 fluxes derived with the flux-gradient approach could be as high as 15 μmol m-2 s -1, which represented the 90% quantile of the uncertainty in hourly data with a highaccuracy instrument. We also demonstrated that O2 fluxes can be used to partition net CO2 exchange fluxes into their component fluxes of photosynthesis and respiration, if EReco is known. The uncertainty of the partitioned gross assimilation ranged from 1.43 to 4.88 μmol m-2 s -1 assuming a measurement uncertainty of 0.1 or 2.5 μmol m-2 s -1 for net ecosystem CO2 exchange and from 0.1 to 15 μmol m-2 s -1 for net ecosystem O2 exchange, respectively. Our analysis suggests that O2 measurements at ecosystem scale have the potential for partitioning net CO2 fluxes into their component fluxes, but further improvement in instrument precision is needed. [ABSTRACT FROM AUTHOR]

Published
2023
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25. Global Carbon Budget 2016

Author

Quéré, Corinne Le, Andrew, Robbie M, Canadell, Josep G, Sitch, Stephen, Korsbakken, Jan Ivar, Peters, Glen P, Manning, Andrew C, Boden, Thomas A, Tans, Pieter P, Houghton, Richard A, Keeling, Ralph F, Alin, Simone, Andrews, Oliver D, Anthoni, Peter, Barbero, Leticia, Bopp, Laurent, Chevallier, Frédéric, Chini, Louise P, Ciais, Philippe, Currie, Kim, Delire, Christine, Doney, Scott C, Friedlingstein, Pierre, Gkritzalis, Thanos, Harris, Ian, Hauck, Judith, Haverd, Vanessa, Hoppema, Mario, Goldewijk, Kees Klein, Jain, Atul K, Kato, Etsushi, Koertzinger, Arne, Landschuetzer, Peter, Lefèvre, Nathalie, Lenton, Andrew, Lienert, Sebastian, Lombardozzi, Danica, Melton, Joe R, Metzl, Nicolas, Millero, Frank, Monteiro, Pedro M. S, Munro, David R, Nabel, Julia E. M. S, Nakaoka, Shin-ichiro, O’Brien, Kevin, Olsen, Are, Omar, Abdirahman M, Ono, Tsuneo, Pierrot, Denis, Poulter, Benjamin, Roedenbeck, Christian, Salisbury, Joe, Schuster, Ute, Schwinger, Joerg, Séférian, Roland, Skjelvan, Ingunn, Stocker, Benjamin D, Sutton, Adrienne J, Takahashi, Taro, Tian, Hanqin, Tilbrook, Bronte, van der Laan-Luijkx, Ingrid T, van der Werf, Guido R, Viovy, Nicolas, Walker, Anthony P, Wiltshire, Andrew J, and Zaehle, Soenke

Subjects
Meteorology And Climatology
Abstract

Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere the global carbon budget is important to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe data sets and methodology to quantify all major components of the global carbon budget, including their uncertainties, based on the combination of a range of data, algorithms, statistics, and model estimates and their interpretation by a broad scientific community. We discuss changes compared to previous estimates and consistency within and among components, alongside methodology and data limitations. CO2 emissions from fossil fuels and industry (EFF) are based on energy statistics and cement production data, respectively, while emissions from land-use change (ELUC), mainly deforestation, are based on combined evidence from land-cover change data, fire activity associated with deforestation, and models. The global atmospheric CO2 concentration is measured directly and its rate of growth (GATM) is computed from the annual changes in concentration. The mean ocean CO2 sink (SOCEAN) is based on observations from the 1990s, while the annual anomalies and trends are estimated with ocean models. The variability in SOCEAN is evaluated with data products based on surveys of ocean CO2 measurements. The global residual terrestrial CO2 sink (SLAND) is estimated by the difference of the other terms of the global carbon budget and compared to results of independent dynamic global vegetation models. We compare the mean land and ocean fluxes and their variability to estimates from three atmospheric inverse methods for three broad latitude bands. All uncertainties are reported as +/- 1(sigma), reflecting the current capacity to characterize the annual estimates of each component of the global carbon budget. For the last decade available (2006-2015), EFF was 9.3+/-0.5 GtC/yr, ELUC 1.0+/-0.5 GtC/yr,GATM 4.5+/-0.1 GtC/yr, SOCEAN 2.6+/-0.5 GtC/yr, and SLAND 3.1+/-0.9 GtC/yr. For year 2015 alone, the growth in EFF was approximately zero and emissions remained at 9.9+/-0.5 GtC/yr, showing a slowdown in growth of these emissions compared to the average growth of 1.8/yr that took place during 2006-2015.Also, for 2015, ELUC was 1.3+/-0.5 GtC/yr, GATM was 6.3+/-0.2 GtC/yr, SOCEAN was 3.0+/-0.5 GtC/yr, and SLAND was 1.9+/-0.9 GtC/yr. GATM was higher in 2015 compared to the past decade (2006-2015), reflecting a smaller SLAND for that year. The global atmospheric CO2 concentration reached 399.4+/-0.1 ppm averaged over 2015. For 2016, preliminary data indicate the continuation of low growth in EFF with +0.2% (range of -1.0 to +1.8% ) based on national emissions projections for China and USA, and projections of gross domestic product corrected for recent changes in the carbon intensity of the economy for the rest of the world. In spite of the low growth of EFF in 2016, the growth rate in atmospheric CO2 concentration is expected to be relatively high because of the persistence of the smaller residual terrestrial sink (SLAND) in response to El Nino conditions of 2015-2016. From this projection of EFF and assumed constant ELUC for 2016, cumulative emissions of CO2 will reach 565+/-55 GtC (2075+/-205 GtCO2) for 1870-2016, about 75% from EFF and 25% from ELUC. This living data update documents changes in the methods and data sets used in this new carbon budget compared with previous publications of this data set.

Published
2016
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26. Two decades of flask observations of atmospheric δO2/N2, CO2, and APO at stations Lutjewad (the Netherlands) and Mace Head (Ireland) plus 3 years from Halley station (Antarctica)

Author

Nguyen, Linh N. T., Meijer, Harro A. J., Leeuwen, Charlotte, Kers, Bert A. M., Scheeren, Bert A., Jones, Anna E., Brough, Neil, Barningham, Thomas, Pickers, Penelope A., Manning, Andrew C., and Luijkx, Ingrid T.

Abstract

We present 20-year flask sample records of atmospheric CO2, δO2/N2 and APO from the stations Lutjewad (the Netherlands) and Mace Head (Ireland) and a 3-year record from Halley station (Antarctica), including details of the extensive calibration procedure and its stability over time. The results of our inter-comparison involving gas cylinders from various research laboratories worldwide also show that our calibration is of high quality and compatible with the internationally recognised Scripps scale. The measurement records from Lutjewad and Mace Head show similar long-term trends during the period 2002–2018 of 2.31 ± 0.07 ppm yr−1 for CO2 and −21.2 ± 0.8 per meg yr−1 for δO2/N2 at Lutjewad, and 2.22 ± 0.04 ppm yr−1 for CO2 and −21.3 ± 0.9 per meg yr−1 for δO2/N2 at Mace Head. They also show a similar δO2/N2 seasonal cycle with an amplitude of 54 ± 4 per meg at Lutjewad and 61 ± 5 per meg at Mace Head, while CO2 seasonal amplitude at Lutjewad (16.8 ± 0.5 ppm) is slightly higher than that at Mace Head (14.8 ± 0.3 ppm). We show that the observed trends and seasonal cycles are compatible with the measurements from various stations, especially the measurements from Weybourne Atmospheric Observatory (United Kingdom). However, there are remarkable differences in the progression of annual trends between the Mace Head and Lutjewad records for δO2/N2 and APO, which might in part be caused by sampling differences, but also by environmental effects, such as the North Atlantic Ocean oxygen ventilation changes to which Mace Head is more sensitive. The Halley record shows clear trends and seasonality in δO2/N2 and APO, where especially APO agrees well with the continuous measurements at Halley by the University of East Anglia, while CO2 and δO2/N2 present slight disagreements, most likely caused by small leakages during sampling. From our 2002–2018 records, we find good agreement for the global ocean sink: 2.0 ± 0.8 PgC yr−1 and 2.2 ± 0.9 PgC yr−1, based on Lutjewad and Mace Head, respectively. The data presented in this work are available at https://doi.org/10.18160/qq7d-t060 (Nguyen et al., 2021).

Published
2021

27. Two decades of flask observations of atmospheric δO<sub>2</sub>/N<sub>2</sub>, CO<sub>2</sub>, and APO at stations Lutjewad (the Netherlands) and Mace Head (Ireland) plus 3 years from Halley station (Antarctica)

Author

Nguyen, Linh N. T., primary, Meijer, Harro A. J., additional, van Leeuwen, Charlotte, additional, Kers, Bert A. M., additional, Scheeren, Bert A., additional, Jones, Anna E., additional, Brough, Neil, additional, Barningham, Thomas, additional, Pickers, Penelope A., additional, Manning, Andrew C., additional, and Luijkx, Ingrid T., additional

Published
2021
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28. Evaluating the performance of a Picarro G2207-i analyser for highprecision atmospheric O2 measurements.

Author

Fleming, Leigh S., Manning, Andrew C., Pickers, Penelope A., Forster, Grant L., and Etchells, Alex J.

Subjects
*CAVITY-ringdown spectroscopy, *ATMOSPHERE, *GAS cylinders, *CARBON cycle, *MOLE fraction, *AIR cylinders, *WATER vapor
Abstract

Fluxes of oxygen (O2) and carbon dioxide (CO2) in and out of the atmosphere are strongly coupled for terrestrial biospheric exchange processes and fossil fuel combustion but are uncoupled for oceanic air-sea gas exchange. High-precision measurements of both species can therefore provide constraints on the carbon cycle and can be used to quantify fossil fuel CO2 (ffCO2) emission estimates. In the case of O2, however, due to its large atmospheric mole fraction of O2 (~20.9 %) it is very challenging to measure small variations to the degree of precision and accuracy required for these applications. We have tested an atmospheric O2 analyser based on the principle of cavity ring-down spectroscopy (Picarro Inc., model G2207- i), both in the laboratory and at the Weybourne Atmospheric Observatory (WAO) field station in the UK, in comparisons to well-established, pre-existing atmospheric O2 and CO2 measurement systems. In laboratory tests analysing air in high-pressure cylinders, from the Allan deviation we calculated a precision of ± 1 ppm (1σ standard deviation of 300 seconds mean), and a 24-hour peak-to-peak range of hourly averaged values of 1.2 ppm. These results are close to atmospheric O2 compatibility goals as set by the UN World Meteorological Organization. From measurements of ambient air conducted at WAO we found that the built-in water correction of the G2207-i does not sufficiently correct for the influence of water vapour on the O2 mole fraction. When sample air was pre-dried and employing a 5-hourly baseline correction with a reference gas cylinder, the G2207-i’s results showed an average difference from the established O2 analyser of 13.6 ± 7.5 per meg (over two weeks of continuous measurements). Over the same period, based on measurements of a so-called “target tank” (sometimes known as a “surveillance tank”), analysed for 12 minutes every 7 hours, we calculated a repeatability of ± 5.7 ± 5.6 per meg and a compatibility of ± 10.0 ± 6.7 per meg for the G2207-i . To further examine the G2207-i’s performance in real-world applications we used ambient air measurements of O2 together with concurrent CO2 measurements to calculate ffCO2. Due to the imprecision of the G2207-i, the ffCO2 calculated showed large differences from that calculated from the established system, and had a large uncertainty of ± 13.0 ppm, which was roughly double that from the established system (± 5.8 ppm). [ABSTRACT FROM AUTHOR]

Published
2022
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29. Diurnal variability of atmospheric O2, CO2 and their exchange ratio above a boreal forest in southern Finland.

Author

Faassen, Kim A. P., Nguyen, Linh N. T., Broekema, Eadin R., Kers, Bert A. M., Mammarella, Ivan, Vesala, Timo, Pickers, Penelope A., Manning, Andrew C., Vilà-Guerau de Arellano, Jordi, Meijer, Harro A. J., Peters, Wouter, and Luijkx, Ingrid T.

Abstract

The exchange ratio (ER) between atmospheric O2 and CO2 is a useful tracer on global and local scales to better understand the carbon budget. The variability of ER (in mol O2 per mol CO2) between terrestrial ecosystems is not well-known, and there is no consensus on how to derive the ER signal to represent an ecosystem, as there are different approaches available, either based on concentration (ERatmos) or flux measurements (ERforest). In this study we measured atmospheric O2 and CO2 concentrations at two heights above the boreal forest in Hyytiälä, Finland. Such measurements of O2 are unique and enable us to potentially identify which forest carbon loss and production mechanisms dominate over various hours of the day. We found that the ERatmos signal at 23 m is not representative for the forest exchange alone but is also influenced by other factors, including for example entrainment of air masses with different thermodynamic and atmospheric composition characteristics in the atmospheric boundary layer. To derive ERforest we infer O2 fluxes using multiple theoretical and observation-based micro-meteorological formulations to determine the most suitable approach. Our resulting ERforest shows a distinct difference in behaviour between daytime (0.92 ± 0.17 mol/mol) and nighttime (1.03 ± 0.05 mol/mol). These insights demonstrate the diurnal variability of different ER signals above a boreal forest and we also confirmed that the signals of ERatmos and ERforest can not be used interchangeably. Therefore, we recommend measurements on multiple vertical levels to derive O2 and CO2 fluxes for the ERforest signal, instead of a single level time series of the concentrations for the ERatmos signal. We show that ERforest can be further split into specific signals for respiration (1.03 ± 0.05 mol/mol) and photosynthesis (0.96 ± 0.12 mol/mol). This estimation allows us to separate the Net Ecosystem Exchange (NEE) into Gross Primary Production (GPP) and Total Ecosystem Respiration (TER), giving comparable results to the more commonly used eddy covariance approach. Our study shows the potential of using atmospheric O2 as an alternative method to gain new insights on the different CO2 signals that contribute to the forest carbon budget. [ABSTRACT FROM AUTHOR]

Published
2022
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31. Two decades of flask observations of atmospheric δ(O2/N2), CO2, and APO at stations Lutjewad (the Netherlands) and Mace Head (Ireland), and 3 years from Halley station (Antarctica).

Author

Nguyen, Linh N. T., Meijer, Harro A. J., van Leeuwen, Charlotte, Kers, Bert A. M., Scheeren, Hubertus A., Jones, Anna E., Brough, Neil, Barningham, Thomas, Pickers, Penelope A., Manning, Andrew C., and Luijkx, Ingrid T.

Subjects
ATMOSPHERIC carbon dioxide, CARBON cycle, CARBON dioxide, ATMOSPHERIC oxygen
Abstract

We present 20-year flask sample records of atmospheric CO 2 , δ (O2/N2), and atmospheric potential oxygen (APO) from the stations Lutjewad (the Netherlands) and Mace Head (Ireland), and a 3-year record from Halley station (Antarctica). We include details of our calibration procedures and the stability of our calibration scale over time, which we estimate to be 3 per meg over the 11 years of calibration, and our compatibility with the international Scripps O 2 scale. The measurement records from Lutjewad and Mace Head show similar long-term trends during the period 2002–2018 of 2.31 ± 0.07 ppm yr -1 for CO 2 and - 21.2 ± 0.8 per meg yr -1 for δ (O2/N2) at Lutjewad, and 2.22 ± 0.04 ppm yr -1 for CO 2 and - 21.3 ± 0.9 per meg yr -1 for δ (O2/N2) at Mace Head. They also show a similar δ (O2/N2) seasonal cycle with an amplitude of 54 ± 4 per meg at Lutjewad and 61 ± 5 per meg at Mace Head, while the CO 2 seasonal amplitude at Lutjewad (16.8 ± 0.5 ppm) is slightly higher than that at Mace Head (14.8 ± 0.3 ppm). We show that the observed long-term trends and seasonal cycles are in good agreement with the measurements from various other stations, especially the measurements from the Weybourne Atmospheric Observatory (United Kingdom). However, there are remarkable differences in the progression of annual trends between the Mace Head and Lutjewad records for δ (O2/N2) and APO, which might in part be caused by sampling differences, but also by environmental effects, such as North Atlantic Ocean oxygen ventilation changes to which Mace Head is more sensitive. The Halley record shows clear trends and seasonality in δ (O2/N2) and APO, the latter agreeing especially well with continuous measurements at the same location made by the University of East Anglia (UEA), while CO 2 and δ (O2/N2) present slight disagreements, most likely caused by small leakages during sampling. From our 2002–2018 records, we find a good agreement with Global Carbon Budget 2021 (Friedlingstein et al. (2021) for the global ocean carbon sink: 2.1 ± 0.8 PgC yr -1 , based on the Lutjewad record. The data presented in this work are available at 10.18160/qq7d-t060 (Nguyen et al., 2021). [ABSTRACT FROM AUTHOR]

Published
2022
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32. Quantifying the UK's carbon dioxide flux: an atmospheric inverse modelling approach using a regional measurement network

Author

White, Emily D., primary, Rigby, Matthew, additional, Lunt, Mark F., additional, Smallman, T. Luke, additional, Comyn-Platt, Edward, additional, Manning, Alistair J., additional, Ganesan, Anita L., additional, O'Doherty, Simon, additional, Stavert, Ann R., additional, Stanley, Kieran, additional, Williams, Mathew, additional, Levy, Peter, additional, Ramonet, Michel, additional, Forster, Grant L., additional, Manning, Andrew C., additional, and Palmer, Paul I., additional

Published
2019
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33. Two decades of flask observations of atmospheric δO2/N2, CO2, and APO at stations Lutjewad (the Netherlands) and Mace Head (Ireland) plus 3 years from Halley station (Antarctica).

Author

Nguyen, Linh N. T., Meijer, Harro A. J., Leeuwen, Charlotte van, Kers, Bert A. M., Scheeren, Bert A., Jones, Anna E., Brough, Neil, Barningham, Thomas, Pickers, Penelope A., Manning, Andrew C., and Luijkx, Ingrid T.

Subjects
GAS cylinders, SEASONS, BOTTLES
Abstract

We present 20-year flask sample records of atmospheric CO2, δO2/N2 and APO from the stations Lutjewad (the Netherlands) and Mace Head (Ireland) and a 3-year record from Halley station (Antarctica), including details of the extensive calibration procedure and its stability over time. The results of our inter-comparison involving gas cylinders from various research laboratories worldwide also show that our calibration is of high quality and compatible with the internationally recognised Scripps scale. The measurement records from Lutjewad and Mace Head show similar long-term trends during the period 2002-2018 of 2.31 ± 0.07 ppm yr−1 for CO2 and −21.2 ± 0.8 per meg yr−1 for δO2/N2 at Lutjewad, and 2.22 ± 0.04 ppm yr−1 for CO2 and −21.3 ± 0.9 per meg yr−1 for δO2/N2 at Mace Head. They also show a similar δO2/N2 seasonal cycle with an amplitude of 54 ± 4 per meg at Lutjewad and 61 ± 5 per meg at Mace Head, while CO2 seasonal amplitude at Lutjewad (16.8 ± 0.5 ppm) is slightly higher than that at Mace Head (14.8 ± 0.3 ppm). We show that the observed trends and seasonal cycles are compatible with the measurements from various stations, especially the measurements from Weybourne Atmospheric Observatory (United Kingdom). However, there are remarkable differences in the progression of annual trends between the Mace Head and Lutjewad records for δO2/N2 and APO, which might in part be caused by sampling differences, but also by environmental effects, such as the North Atlantic Ocean oxygen ventilation changes to which Mace Head is more sensitive. The Halley record shows clear trends and seasonality in δO2/N2 and APO, where especially APO agrees well with the continuous measurements at Halley by the University of East Anglia, while CO2 and δO2/N2 present slight disagreements, most likely caused by small leakages during sampling. From our 2002-2018 records, we find good agreement for the global ocean sink: 2.0 ± 0.8 PgC yr−1 and 2.2 ± 0.9 PgC yr−1, based on Lutjewad and Mace Head, respectively. The data presented in this work are available at https://doi.org/10.18160/qq7d-t060 (Nguyen et al., 2021). [ABSTRACT FROM AUTHOR]

Published
2021
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34. Quantifying the UK’s carbon dioxide flux: an atmospheric inverse modelling approach using a regional measurement network

Author

White, Emily D., Rigby, Matthew, Lunt, Mark F., Smallman, T. Luke, Comyn-Platt, Edward, Manning, Alistair J., Ganesan, Anita L., O'Doherty, Simon, Stavert, Ann R., Stanley, Kieran, Williams, Mathew, Levy, Peter, Ramonet, Michel, Forster, Grant L., Manning, Andrew C., Palmer, Paul I., White, Emily D., Rigby, Matthew, Lunt, Mark F., Smallman, T. Luke, Comyn-Platt, Edward, Manning, Alistair J., Ganesan, Anita L., O'Doherty, Simon, Stavert, Ann R., Stanley, Kieran, Williams, Mathew, Levy, Peter, Ramonet, Michel, Forster, Grant L., Manning, Andrew C., and Palmer, Paul I.

Abstract

We present a method to derive atmospheric-observation-based estimates of carbon dioxide (CO2) fluxes at the national scale, demonstrated using data from a network of surface tall-tower sites across the UK and Ireland over the period 2013–2014. The inversion is carried out using simulations from a Lagrangian chemical transport model and an innovative hierarchical Bayesian Markov chain Monte Carlo (MCMC) framework, which addresses some of the traditional problems faced by inverse modelling studies, such as subjectivity in the specification of model and prior uncertainties. Biospheric fluxes related to gross primary productivity and terrestrial ecosystem respiration are solved separately in the inversion and then combined a posteriori to determine net ecosystem exchange of CO2. Two different models, Data Assimilation Linked Ecosystem Carbon (DALEC) and Joint UK Land Environment Simulator (JULES), provide prior estimates for these fluxes. We carry out separate inversions to assess the impact of these different priors on the posterior flux estimates and evaluate the differences between the prior and posterior estimates in terms of missing model components. The Numerical Atmospheric dispersion Modelling Environment (NAME) is used to relate fluxes to the measurements taken across the regional network. Posterior CO2 estimates from the two inversions agree within estimated uncertainties, despite large differences in the prior fluxes from the different models. With our method, averaging results from 2013 and 2014, we find a total annual net biospheric flux for the UK of 8±79 Tg CO2 yr−1 (DALEC prior) and 64±85 Tg CO2 yr−1 (JULES prior), where negative values represent an uptake of CO2. These biospheric CO2 estimates show that annual UK biospheric sources and sinks are roughly in balance. These annual mean estimates consistently indicate a greater net release of CO2 than the prior estimates, which show much more pronounced uptake in summer months.

Published
2019

35. Global Carbon Budget 2017

Author

Le Quéré, Corinne, Andrew, Robbie M., Friedlingstein, Pierre, Sitch, Stephen, Pongratz, Julia, Manning, Andrew C., Korsbakken, Jan Ivar, Peters, Glen P., Canadell, Josep G., Jackson, Robert B., Boden, Thomas A., Tans, Pieter P., Andrews, Oliver D., Arora, Vivek, Bakker, Dorothee C. E., Barbero, Leticia, Becker, Meike, Betts, Richard, Bopp, Laurent, Chevallier, Frédéric, Chini, Louise P., Ciais, Philippe, Cosca, Catherine E., Cross, Jessica, Currie, Kim, Gasser, Thomas, Harris, Ian, Hauck, Judith, Haverd, Vanessa, Houghton, Richard A., Hunt, Christopher W., Hurtt, George, Ilyina, Tatiana, Jain, Atul K., Kato, Etsushi, Kautz, Markus, Keeling, Ralph F., Klein Goldewijk, Kees, Körtzinger, Arne, Landschützer, Peter, Lefèvre, Nathalie, Lenton, Andrew, Lienert, Sebastian, Lima, Ivan D., Lombardozzi, Danica, Metzl, Nicolas, Millero, Frank J., Monteiro, Pedro M. S., Munro, David R., Nabel, Julia E. M. S., Nakaoka, Shin-ichiro, Nojiri, Yukihiro, Padin, X. Antonio, Peregon, Anna, Pfeil, Benjamin, Pierrot, Denis, Poulter, Benjamin, Rehder, Gregor, Reimer, Janet, Rödenbeck, Christian, Schwinger, Jörg, Séférian, Roland, Skjelvan, Ingunn, Stocker, Benjamin D., Tian, Hanqin, Tilbrook, Bronte, Tubiello, Francesco, van der Laan-Luijkx, Ingrid T., Van Der Werf, Guido R., Van Heuven, Steven M. A. C., Viovy, Nicolas, Vuichard, Nicolas, Walker, Anthony P., Watson, Andrew J., Wiltshire, Andrew J., Zaehle, Sönke, Zhu, Dan, Tyndall Centre for Climate Change Research, University of East Anglia [Norwich] (UEA), Center for International Climate and Environmental Research [Oslo] (CICERO), University of Oslo (UiO), College of Engineering, Mathematics and Physical Sciences, University of Exeter, College of Life and Environmental Sciences, University of Exeter, Max Planck Institute for Meteorology (MPI-M), Max-Planck-Gesellschaft, Global Carbon Project, CSIRO Marine and Atmospheric Research, Department of Earth System Science [Stanford] (ESS), Stanford EARTH, Stanford University-Stanford University, Climate Change Science Institute [Oak Ridge] (CCSI), Oak Ridge National Laboratory [Oak Ridge] (ORNL), UT-Battelle, LLC-UT-Battelle, LLC, ESRL Chemical Sciences Division [Boulder] (CSD), NOAA Earth System Research Laboratory (ESRL), National Oceanic and Atmospheric Administration (NOAA)-National Oceanic and Atmospheric Administration (NOAA), Canadian Centre for Climate Modelling and Analysis (CCCma), Environment and Climate Change Canada, Cooperative Institute for Marine and Atmospheric Studies, Rosenstiel School for Marine and Atmospheric Science (CIMAS), Rosenstiel School of Marine and Atmospheric Science (RSMAS), University of Miami [Coral Gables]-University of Miami [Coral Gables], NOAA Atlantic Oceanographic and Meteorological Laboratory (AOML), National Oceanic and Atmospheric Administration (NOAA), Bjerknes Centre for Climate Research (BCCR), Department of Biological Sciences [Bergen] (BIO / UiB), University of Bergen (UiB)-University of Bergen (UiB), Geophysical Institute [Bergen] (GFI / BiU), University of Bergen (UiB), Laboratoire de Météorologie Dynamique (UMR 8539) (LMD), Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-École des Ponts ParisTech (ENPC)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Département des Géosciences - ENS Paris, École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL), Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] (LSCE), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Modélisation INVerse pour les mesures atmosphériques et SATellitaires (SATINV), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Department of Geographical Sciences, University of Maryland [College Park], University of Maryland System-University of Maryland System, ICOS-ATC (ICOS-ATC), NOAA Pacific Marine Environmental Laboratory [Seattle] (PMEL), National Institute of Water and Atmospheric Research [Wellington] (NIWA), International Institute for Applied Systems Analysis [Laxenburg] (IIASA), Climatic Research Unit, Alfred-Wegener-Institut, Helmholtz-Zentrum für Polar- und Meeresforschung (AWI), Commonwealth Scientific and Industrial Research Organisation (CSIRO), Woods Hole Oceanographic Institution (WHOI), Ocean Process Analysis Laboratory, University of New Hampshire (UNH), Department of Atmospheric Sciences [Urbana], University of Illinois at Urbana-Champaign [Urbana], University of Illinois System-University of Illinois System, The Institute of Applied Energy (IAE), Karlsruher Institut für Technologie (KIT), University of California [San Diego] (UC San Diego), University of California, PBL Netherlands Environmental Assessment Agency, Christian-Albrechts-Universität zu Kiel (CAU), Austral, Boréal et Carbone (ABC), Laboratoire d'Océanographie et du Climat : Expérimentations et Approches Numériques (LOCEAN), Institut Pierre-Simon-Laplace (IPSL (FR_636)), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université de Paris (UP)-École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université de Paris (UP)-Institut de Recherche pour le Développement (IRD)-Muséum national d'Histoire naturelle (MNHN)-Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université (SU)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université de Paris (UP)-Institut de Recherche pour le Développement (IRD)-Muséum national d'Histoire naturelle (MNHN)-Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université (SU), CISRO Oceans and Atmosphere, Antarctic Climate & Ecosystem Cooperative Research Centre, University of Tasmania [Hobart, Australia] (UTAS), Climate and Environmental Physics [Bern] (CEP), Physikalisches Institut [Bern], Universität Bern [Bern]-Universität Bern [Bern], Oeschger Centre for Climate Change Research (OCCR), University of Bern, National Center for Atmospheric Research [Boulder] (NCAR), Cycles biogéochimiques marins : processus et perturbations (CYBIOM), Department of Ocean Sciences, University of Miami [Coral Gables], Instituto de Engenharia de Sistemas e Computadores Investigação e Desenvolvimento em Lisboa (INESC-ID), Instituto Superior Técnico, Universidade Técnica de Lisboa (IST)-Instituto de Engenharia de Sistemas e Computadores (INESC), University of Wisconsin Whitewater, National Institute for Environmental Studies (NIES), Montana State University (MSU), Max-Planck-Institut für Biogeochemie (MPI-BGC), Groupe d'étude de l'atmosphère météorologique (CNRM-GAME), Institut national des sciences de l'Univers (INSU - CNRS)-Météo France-Centre National de la Recherche Scientifique (CNRS), Shandong Agricultural University (SDAU), Antarctic Climate and Ecosystems Cooperative Research Centre (ACE-CRC), Wageningen University and Research [Wageningen] (WUR), Faculty of Earth and Life Sciences [Amsterdam] (FALW), Vrije Universiteit Amsterdam [Amsterdam] (VU), Modélisation des Surfaces et Interfaces Continentales (MOSAIC), NASA Ames Research Center (ARC), Biogeochemical Systems Department [Jena], Max Planck Institute for Biogeochemistry (MPI-BGC), Max-Planck-Gesellschaft-Max-Planck-Gesellschaft, and Huazhong University of Science and Technology [Wuhan] (HUST)

Subjects
[PHYS.PHYS.PHYS-GEO-PH]Physics [physics]/Physics [physics]/Geophysics [physics.geo-ph]
Abstract

International audience; Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere – the "global carbon budget" – is important to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe data sets and methodology to quantify the five major components of the global carbon budget and their uncertainties. CO2 emissions from fossil fuels and industry (EFF) are based on energy statistics and cement production data, respectively, while emissions from land-use change (ELUC), mainly deforestation, are based on land-cover change data and bookkeeping models. The global atmospheric CO2 concentration is measured directly and its rate of growth (GATM) is computed from the annual changes in concentration. The ocean CO2 sink (SOCEAN) and terrestrial CO2 sink (SLAND) are estimated with global process models constrained by observations. The resulting carbon budget imbalance (BIM), the difference between the estimated total emissions and the estimated changes in the atmosphere, ocean, and terrestrial biosphere, is a measure of imperfect data and understanding of the contemporary carbon cycle. All uncertainties are reported as ±1σ. For the last decade available (2007–2016), EFF was 9.4 ± 0.5 GtC yr−1, ELUC 1.3 ± 0.7 GtC yr−1, GATM 4.7 ± 0.1 GtC yr−1, SOCEAN 2.4 ± 0.5 GtC yr−1, and SLAND 3.0 ± 0.8 GtC yr−1, with a budget imbalance BIM of 0.6 GtC yr−1 indicating overestimated emissions and/or underestimated sinks. For year 2016 alone, the growth in EFF was approximately zero and emissions remained at 9.9 ± 0.5 GtC yr−1. Also for 2016, ELUC was 1.3 ± 0.7 GtC yr−1, GATM was 6.1 ± 0.2 GtC yr−1, SOCEAN was 2.6 ± 0.5 GtC yr−1, and SLAND was 2.7 ± 1.0 GtC yr−1, with a small BIM of −0.3 GtC. GATM continued to be higher in 2016 compared to the past decade (2007–2016), reflecting in part the high fossil emissions and the small SLAND consistent with El Niño conditions. The global atmospheric CO2 concentration reached 402.8 ± 0.1 ppm averaged over 2016. For 2017, preliminary data for the first 6–9 months indicate a renewed growth in EFF of +2.0 % (range of 0.8 to 3.0 %) based on national emissions projections for China, USA, and India, and projections of gross domestic product (GDP) corrected for recent changes in the carbon intensity of the economy for the rest of the world. This living data update documents changes in the methods and data sets used in this new global carbon budget compared with previous publications of this data set (Le Quéré et al., 2016, 2015b, a, 2014, 2013). All results presented here can be downloaded from https://doi.org/10.18160/GCP-2017 (GCP, 2017).

Published
2018
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36. In situ measurements of atmospheric O2 and CO2 reveal an unexpected O2 signal over the tropical Atlantic Ocean

Author

Pickers, Penelope A., Manning, Andrew C., Sturges, William T., Le Quéré, Corinne, Mikaloff Fletcher, Sara E., Wilson, Philip A., and Etchells, Alex J.

Abstract

We present the first meridional transects of atmospheric O2 and CO2 over the Atlantic Ocean. We combine these measurements into the tracer atmospheric potential oxygen (APO), which is a measure of the oceanic contribution to atmospheric O2 variations. Our new in situ measurement system, deployed on board a commercial container ship during 2015, performs as well as or better than existing similar measurement systems. The data show small short-term variability (hours to days), a step-change corresponding to the position of the Intertropical Convergence Zone (ITCZ), and seasonal cycles that vary with latitude. In contrast to data from the Pacific Ocean and to previous modeling studies, our Atlantic Ocean APO data show no significant bulge in the tropics. This difference cannot be accounted for by interannual variability in the position of the ITCZ or the Atlantic Meridional Mode Index and appears to be a persistent feature of the Atlantic Ocean system. Modeled APO using the TM3 atmospheric transport model does exhibit a significant bulge over the Atlantic and overestimates the interhemispheric gradient in APO over the Atlantic Ocean. These results indicate that either there are inaccuracies in the oceanic flux data products in the equatorial Atlantic Ocean region, or that there are atmospheric transport inaccuracies in the model, or a combination of both. Our shipboard O2 and CO2 measurements are ongoing and will reveal the long-term nature of equatorial APO outgassing over the Atlantic as more data become available.

Published
2017

37. Global Carbon Budget 2017

Author

Quéré, Corinne, Le, Andrew, Robbie M., Friedlingstein, Pierre, Sitch, Stephen, Pongratz, Julia, Manning, Andrew C., Ivar Korsbakken, Jan, Peters, Glen P., Canadell, Josep G., Jackson, Robert B., Boden, Thomas A., Tans, Pieter P., Andrews, Oliver D., Arora, Vivek K., Bakker, Dorothee C.E., Barbero, Leticia, Becker, Meike, Betts, Richard A., Bopp, Laurent, Chevallier, Frédéric, Chini, Louise P., Ciais, Philippe, Cosca, Catherine E., Cross, Jessica, Currie, Kim, Gasser, Thomas, Harris, Ian, Hauck, Judith, Haverd, Vanessa, Houghton, Richard A., Hunt, Christopher W., Hurtt, George, Ilyina, Tatiana, Jain, Atul K., Kato, Etsushi, Kautz, Markus, Keeling, Ralph F., Klein Goldewijk, Kees, Körtzinger, Arne, Landschützer, Peter, Lefèvre, Nathalie, Lenton, Andrew, Lienert, Sebastian, Lima, Ivan, Lombardozzi, Danica, Metzl, Nicolas, Millero, Frank, Monteiro, Pedro M.S., Munro, David R., Nabel, Julia E.M.S., Nakaoka, Shin Ichiro, Nojiri, Yukihiro, Padin, X.A., Peregon, Anna, Pfeil, Benjamin, Pierrot, Denis, Poulter, Benjamin, Rehder, Gregor, Reimer, Janet, Rödenbeck, Christian, Schwinger, Jörg, Séférian, Roland, Skjelvan, Ingunn, Stocker, Benjamin D., Tian, Hanqin, Tilbrook, Bronte, Tubiello, Francesco N., Laan-Luijkx, Ingrid T., van der, Werf, Guido R., van der, Heuven, Steven, Van, Viovy, Nicolas, Vuichard, Nicolas, Walker, Anthony P., Watson, Andrew J., Wiltshire, Andrew J., Zaehle, Sönke, Zhu, Dan, Quéré, Corinne, Le, Andrew, Robbie M., Friedlingstein, Pierre, Sitch, Stephen, Pongratz, Julia, Manning, Andrew C., Ivar Korsbakken, Jan, Peters, Glen P., Canadell, Josep G., Jackson, Robert B., Boden, Thomas A., Tans, Pieter P., Andrews, Oliver D., Arora, Vivek K., Bakker, Dorothee C.E., Barbero, Leticia, Becker, Meike, Betts, Richard A., Bopp, Laurent, Chevallier, Frédéric, Chini, Louise P., Ciais, Philippe, Cosca, Catherine E., Cross, Jessica, Currie, Kim, Gasser, Thomas, Harris, Ian, Hauck, Judith, Haverd, Vanessa, Houghton, Richard A., Hunt, Christopher W., Hurtt, George, Ilyina, Tatiana, Jain, Atul K., Kato, Etsushi, Kautz, Markus, Keeling, Ralph F., Klein Goldewijk, Kees, Körtzinger, Arne, Landschützer, Peter, Lefèvre, Nathalie, Lenton, Andrew, Lienert, Sebastian, Lima, Ivan, Lombardozzi, Danica, Metzl, Nicolas, Millero, Frank, Monteiro, Pedro M.S., Munro, David R., Nabel, Julia E.M.S., Nakaoka, Shin Ichiro, Nojiri, Yukihiro, Padin, X.A., Peregon, Anna, Pfeil, Benjamin, Pierrot, Denis, Poulter, Benjamin, Rehder, Gregor, Reimer, Janet, Rödenbeck, Christian, Schwinger, Jörg, Séférian, Roland, Skjelvan, Ingunn, Stocker, Benjamin D., Tian, Hanqin, Tilbrook, Bronte, Tubiello, Francesco N., Laan-Luijkx, Ingrid T., van der, Werf, Guido R., van der, Heuven, Steven, Van, Viovy, Nicolas, Vuichard, Nicolas, Walker, Anthony P., Watson, Andrew J., Wiltshire, Andrew J., Zaehle, Sönke, and Zhu, Dan

Abstract

Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere-the "global carbon budget"-is important to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe data sets and methodology to quantify the five major components of the global carbon budget and their uncertainties. CO2 emissions from fossil fuels and industry (EFF) are based on energy statistics and cement production data, respectively, while emissions from land-use change (ELUC), mainly deforestation, are based on land-cover change data and bookkeeping models. The global atmospheric CO2 concentration is measured directly and its rate of growth (GATM) is computed from the annual changes in concentration. The ocean CO2 sink (SOCEAN) and terrestrial CO2 sink (SLAND) are estimated with global process models constrained by observations. The resulting carbon budget imbalance (BIM), the difference between the estimated total emissions and the estimated changes in the atmosphere, ocean, and terrestrial biosphere, is a measure of imperfect data and understanding of the contemporary carbon cycle. All uncertainties are reported as ±1δ. For the last decade available (2007-2016), EFF was 9.4±0.5 GtC yr-1, ELUC 1.3±0.7 GtC yr-1, GATM 4.7±0.1 GtC yr-1, SOCEAN 2.4±0.5 GtC yr-1, and SLAND 3.0±0.8 GtC yr-1, with a budget imbalance BIM of 0.6 GtC yr-1 indicating overestimated emissions and/or underestimated sinks. For year 2016 alone, the growth in EFF was approximately zero and emissions remained at 9.9±0.5 GtC yr-1. Also for 2016, ELUC was 1.3±0.7 GtC yr-1, GATM was 6.1±0.2 GtC yr-1, SOCEAN was 2.6±0.5 GtC yr-1, and SLAND was 2.7±1.0 GtC yr-1, with a small BIM of-0.3 GtC. GATM continued to be higher in 2016 compared to the past decade (2007-2016), reflecting in part the high fossil emissions and the small SLAND consistent with El Ninõ conditions. The gl

Published
2018

38. Global Carbon Budget 2017

Author

Environmental Sciences, Le Quéré, Corinne, Andrew, Robbie M., Friedlingstein, Pierre, Sitch, Stephen, Pongratz, Julia, Manning, Andrew C., Ivar Korsbakken, Jan, Peters, Glen P., Canadell, Josep G., Jackson, Robert B., Boden, Thomas A., Tans, Pieter P., Andrews, Oliver D., Arora, Vivek K., Bakker, Dorothee C.E., Barbero, Leticia, Becker, Meike, Betts, Richard A., Bopp, Laurent, Chevallier, Frédéric, Chini, Louise P., Ciais, Philippe, Cosca, Catherine E., Cross, Jessica, Currie, Kim, Gasser, Thomas, Harris, Ian, Hauck, Judith, Haverd, Vanessa, Houghton, Richard A., Hunt, Christopher W., Hurtt, George, Ilyina, Tatiana, Jain, Atul K., Kato, Etsushi, Kautz, Markus, Keeling, Ralph F., Klein Goldewijk, Kees, Körtzinger, Arne, Landschützer, Peter, Lefèvre, Nathalie, Lenton, Andrew, Lienert, Sebastian, Lima, Ivan, Lombardozzi, Danica, Metzl, Nicolas, Millero, Frank, Monteiro, Pedro M.S., Munro, David R., Nabel, Julia E.M.S., Nakaoka, Shin Ichiro, Nojiri, Yukihiro, Antonio Padin, X., Peregon, Anna, Pfeil, Benjamin, Pierrot, Denis, Poulter, Benjamin, Rehder, Gregor, Reimer, Janet, Rödenbeck, Christian, Schwinger, Jörg, Séférian, Roland, Skjelvan, Ingunn, Stocker, Benjamin D., Tian, Hanqin, Tilbrook, Bronte, Tubiello, Francesco N., Laan-Luijkx, Ingrid T.Vander, Werf, Guido R.Vander, van Heuven, Steven M.A.C., Viovy, Nicolas, Vuichard, Nicolas, Walker, Anthony P., Watson, Andrew J., Wiltshire, Andrew J., Zaehle, Sönke, Zhu, Dan, Environmental Sciences, Le Quéré, Corinne, Andrew, Robbie M., Friedlingstein, Pierre, Sitch, Stephen, Pongratz, Julia, Manning, Andrew C., Ivar Korsbakken, Jan, Peters, Glen P., Canadell, Josep G., Jackson, Robert B., Boden, Thomas A., Tans, Pieter P., Andrews, Oliver D., Arora, Vivek K., Bakker, Dorothee C.E., Barbero, Leticia, Becker, Meike, Betts, Richard A., Bopp, Laurent, Chevallier, Frédéric, Chini, Louise P., Ciais, Philippe, Cosca, Catherine E., Cross, Jessica, Currie, Kim, Gasser, Thomas, Harris, Ian, Hauck, Judith, Haverd, Vanessa, Houghton, Richard A., Hunt, Christopher W., Hurtt, George, Ilyina, Tatiana, Jain, Atul K., Kato, Etsushi, Kautz, Markus, Keeling, Ralph F., Klein Goldewijk, Kees, Körtzinger, Arne, Landschützer, Peter, Lefèvre, Nathalie, Lenton, Andrew, Lienert, Sebastian, Lima, Ivan, Lombardozzi, Danica, Metzl, Nicolas, Millero, Frank, Monteiro, Pedro M.S., Munro, David R., Nabel, Julia E.M.S., Nakaoka, Shin Ichiro, Nojiri, Yukihiro, Antonio Padin, X., Peregon, Anna, Pfeil, Benjamin, Pierrot, Denis, Poulter, Benjamin, Rehder, Gregor, Reimer, Janet, Rödenbeck, Christian, Schwinger, Jörg, Séférian, Roland, Skjelvan, Ingunn, Stocker, Benjamin D., Tian, Hanqin, Tilbrook, Bronte, Tubiello, Francesco N., Laan-Luijkx, Ingrid T.Vander, Werf, Guido R.Vander, van Heuven, Steven M.A.C., Viovy, Nicolas, Vuichard, Nicolas, Walker, Anthony P., Watson, Andrew J., Wiltshire, Andrew J., Zaehle, Sönke, and Zhu, Dan

Published
2018

41. Global Carbon Budget 2017

Author

Le Quéré, Corinne, primary, Andrew, Robbie M., additional, Friedlingstein, Pierre, additional, Sitch, Stephen, additional, Pongratz, Julia, additional, Manning, Andrew C., additional, Korsbakken, Jan Ivar, additional, Peters, Glen P., additional, Canadell, Josep G., additional, Jackson, Robert B., additional, Boden, Thomas A., additional, Tans, Pieter P., additional, Andrews, Oliver D., additional, Arora, Vivek K., additional, Bakker, Dorothee C. E., additional, Barbero, Leticia, additional, Becker, Meike, additional, Betts, Richard A., additional, Bopp, Laurent, additional, Chevallier, Frédéric, additional, Chini, Louise P., additional, Ciais, Philippe, additional, Cosca, Catherine E., additional, Cross, Jessica, additional, Currie, Kim, additional, Gasser, Thomas, additional, Harris, Ian, additional, Hauck, Judith, additional, Haverd, Vanessa, additional, Houghton, Richard A., additional, Hunt, Christopher W., additional, Hurtt, George, additional, Ilyina, Tatiana, additional, Jain, Atul K., additional, Kato, Etsushi, additional, Kautz, Markus, additional, Keeling, Ralph F., additional, Klein Goldewijk, Kees, additional, Körtzinger, Arne, additional, Landschützer, Peter, additional, Lefèvre, Nathalie, additional, Lenton, Andrew, additional, Lienert, Sebastian, additional, Lima, Ivan, additional, Lombardozzi, Danica, additional, Metzl, Nicolas, additional, Millero, Frank, additional, Monteiro, Pedro M. S., additional, Munro, David R., additional, Nabel, Julia E. M. S., additional, Nakaoka, Shin-ichiro, additional, Nojiri, Yukihiro, additional, Padín, X. Antoni, additional, Peregon, Anna, additional, Pfeil, Benjamin, additional, Pierrot, Denis, additional, Poulter, Benjamin, additional, Rehder, Gregor, additional, Reimer, Janet, additional, Rödenbeck, Christian, additional, Schwinger, Jörg, additional, Séférian, Roland, additional, Skjelvan, Ingunn, additional, Stocker, Benjamin D., additional, Tian, Hanqin, additional, Tilbrook, Bronte, additional, van der Laan-Luijkx, Ingrid T., additional, van der Werf, Guido R., additional, van Heuven, Steven, additional, Viovy, Nicolas, additional, Vuichard, Nicolas, additional, Walker, Anthony P., additional, Watson, Andrew J., additional, Wiltshire, Andrew J., additional, Zaehle, Sönke, additional, and Zhu, Dan, additional

Published
2017
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43. Global Carbon Budget 2017

Author

Le Quéré, Corinne, Andrew, Robbie M., Friedlingstein, Pierre, Sitch, Stephen, Pongratz, Julia, Manning, Andrew C., Korsbakken, Jan Ivar, Peters, Glen P., Canadell, Josep G., Jackson, Robert B., Boden, Thomas A., Tans, Pieter P., Andrews, Oliver D., Arora, Vivek K., Bakker, Dorothee C. E., Barbero, Leticia, Becker, Meike, Betts, Richard A., Bopp, Laurent, Chevallier, Frédéric, Chini, Louise P., Ciais, Philippe, Cosca, Catherine E., Cross, Jessica, Currie, Kim, Gasser, Thomas, Harris, Ian, Hauck, Judith, Haverd, Vanessa, Houghton, Richard A., Hunt, Christopher W., Hurtt, George, Ilyina, Tatiana, Jain, Atul K., Kato, Etsushi, Kautz, Markus, Keeling, Ralph F., Klein Goldewijk, Kees, Körtzinger, Arne, Landschützer, Peter, Lefèvre, Nathalie, Lenton, Andrew, Lienert, Sebastian, Lima, Ivan, Lombardozzi, Danica, Metzl, Nicolas, Millero, Frank, Monteiro, Pedro M. S., Munro, David R., Nabel, Julia E. M. S., Nakaoka, Shin-ichiro, Nojiri, Yukihiro, Padín, X. Antoni, Peregon, Anna, Pfeil, Benjamin, Pierrot, Denis, Poulter, Benjamin, Rehder, Gregor, Reimer, Janet, Rödenbeck, Christian, Schwinger, Jörg, Séférian, Roland, Skjelvan, Ingunn, Stocker, Benjamin D., Tian, Hanqin, Tilbrook, Bronte, van der Laan-Luijkx, Ingrid T., van der Werf, Guido R., van Heuven, Steven, Viovy, Nicolas, Vuichard, Nicolas, Walker, Anthony P., Watson, Andrew J., Wiltshire, Andrew J., Zaehle, Sönke, Zhu, Dan, Le Quéré, Corinne, Andrew, Robbie M., Friedlingstein, Pierre, Sitch, Stephen, Pongratz, Julia, Manning, Andrew C., Korsbakken, Jan Ivar, Peters, Glen P., Canadell, Josep G., Jackson, Robert B., Boden, Thomas A., Tans, Pieter P., Andrews, Oliver D., Arora, Vivek K., Bakker, Dorothee C. E., Barbero, Leticia, Becker, Meike, Betts, Richard A., Bopp, Laurent, Chevallier, Frédéric, Chini, Louise P., Ciais, Philippe, Cosca, Catherine E., Cross, Jessica, Currie, Kim, Gasser, Thomas, Harris, Ian, Hauck, Judith, Haverd, Vanessa, Houghton, Richard A., Hunt, Christopher W., Hurtt, George, Ilyina, Tatiana, Jain, Atul K., Kato, Etsushi, Kautz, Markus, Keeling, Ralph F., Klein Goldewijk, Kees, Körtzinger, Arne, Landschützer, Peter, Lefèvre, Nathalie, Lenton, Andrew, Lienert, Sebastian, Lima, Ivan, Lombardozzi, Danica, Metzl, Nicolas, Millero, Frank, Monteiro, Pedro M. S., Munro, David R., Nabel, Julia E. M. S., Nakaoka, Shin-ichiro, Nojiri, Yukihiro, Padín, X. Antoni, Peregon, Anna, Pfeil, Benjamin, Pierrot, Denis, Poulter, Benjamin, Rehder, Gregor, Reimer, Janet, Rödenbeck, Christian, Schwinger, Jörg, Séférian, Roland, Skjelvan, Ingunn, Stocker, Benjamin D., Tian, Hanqin, Tilbrook, Bronte, van der Laan-Luijkx, Ingrid T., van der Werf, Guido R., van Heuven, Steven, Viovy, Nicolas, Vuichard, Nicolas, Walker, Anthony P., Watson, Andrew J., Wiltshire, Andrew J., Zaehle, Sönke, and Zhu, Dan

Published
2017

44. Global Carbon Budget 2016

Author

Le Quéré, Corinne, Andrew, Robbie M., Canadell, Josep G., Sitch, Stephen, Korsbakken, Jan Ivar, Peters, Glen P., Manning, Andrew C., Boden, Thomas A., Tans, Pieter P., Houghton, Richard A., Keeling, Ralph F., Alin, Simone, Andrews, Oliver D., Anthoni, Peter, Barbero, Leticia, Bopp, Laurent, Chevallier, Frédéric, Chini, Louise P., Ciais, Philippe, Currie, Kim, Delire, Christine, Doney, Scott C., Friedlingstein, Pierre, Gkritzalis, Thanos, Harris, Ian, Hauck, Judith, Haverd, Vanessa, Hoppema, Mario, Klein Goldewijk, Kees, Jain, Atul K., Kato, Etsushi, Körtzinger, Arne, Landschützer, Peter, Lefèvre, Nathalie, Lenton, Andrew, Lienert, Sebastian, Lombardozzi, Danica, Melton, Joe R., Metzl, Nicolas, Millero, Frank, Monteiro, Pedro M. S., Munro, David R., Nabel, Julia E. M. S., Nakaoka, Shin-ichiro, O'Brien, Kevin, Olsen, Are, Omar, Abdirahman M., Ono, Tsuneo, Pierrot, Denis, Poulter, Benjamin, Rödenbeck, Christian, Salisbury, Joe, Schuster, Ute, Schwinger, Jörg, Séférian, Roland, Skjelvan, Ingunn, Stocker, Benjamin D., Sutton, Adrienne J., Takahashi, Taro, Tian, Hanqin, Tilbrook, Bronte, van der Laan-Luijkx, Ingrid T., van der Werf, Guido R., Viovy, Nicolas, Walker, Anthony P., Wiltshire, Andrew J., Zaehle, Sönke, Le Quéré, Corinne, Andrew, Robbie M., Canadell, Josep G., Sitch, Stephen, Korsbakken, Jan Ivar, Peters, Glen P., Manning, Andrew C., Boden, Thomas A., Tans, Pieter P., Houghton, Richard A., Keeling, Ralph F., Alin, Simone, Andrews, Oliver D., Anthoni, Peter, Barbero, Leticia, Bopp, Laurent, Chevallier, Frédéric, Chini, Louise P., Ciais, Philippe, Currie, Kim, Delire, Christine, Doney, Scott C., Friedlingstein, Pierre, Gkritzalis, Thanos, Harris, Ian, Hauck, Judith, Haverd, Vanessa, Hoppema, Mario, Klein Goldewijk, Kees, Jain, Atul K., Kato, Etsushi, Körtzinger, Arne, Landschützer, Peter, Lefèvre, Nathalie, Lenton, Andrew, Lienert, Sebastian, Lombardozzi, Danica, Melton, Joe R., Metzl, Nicolas, Millero, Frank, Monteiro, Pedro M. S., Munro, David R., Nabel, Julia E. M. S., Nakaoka, Shin-ichiro, O'Brien, Kevin, Olsen, Are, Omar, Abdirahman M., Ono, Tsuneo, Pierrot, Denis, Poulter, Benjamin, Rödenbeck, Christian, Salisbury, Joe, Schuster, Ute, Schwinger, Jörg, Séférian, Roland, Skjelvan, Ingunn, Stocker, Benjamin D., Sutton, Adrienne J., Takahashi, Taro, Tian, Hanqin, Tilbrook, Bronte, van der Laan-Luijkx, Ingrid T., van der Werf, Guido R., Viovy, Nicolas, Walker, Anthony P., Wiltshire, Andrew J., and Zaehle, Sönke

Published
2016
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45. Global Carbon Budget 2016

Author

Quéré, Corinne, Le, Andrew, Robbie M., Canadell, Josep G., Sitch, Stephen, Korsbakken, Jan Ivar, Peters, Glen P., Manning, Andrew C., Boden, Thomas A., Tans, Pieter P., Houghton, Richard A., Keeling, Ralph F., Alin, Simone, Andrews, Oliver D., Anthoni, Peter, Barbero, Leticia, Bopp, Laurent, Chevallier, Frédéric, Chini, Louise P., Ciais, Philippe, Currie, Kim, Delire, Christine, Doney, Scott C., Friedlingstein, Pierre, Gkritzalis, Thanos, Harris, Ian, Hauck, Judith, Haverd, Vanessa, Hoppema, Mario, Klein Goldewijk, Kees, Jain, Atul K., Kato, Etsushi, Körtzinger, Arne, Landschützer, Peter, Lefèvre, Nathalie, Lenton, Andrew, Lienert, Sebastian, Lombardozzi, Danica, Melton, Joe R., Metzl, Nicolas, Millero, Frank, Monteiro, Pedro M.S., Munro, David R., Nabel, Julia E.M.S., Nakaoka, S., O'Brien, Kevin, Olsen, Are, Omar, Abdirahman M., Ono, Tsuneo, Pierrot, Denis, Poulter, Benjamin, Rödenbeck, Christian, Salisbury, Joe, Schuster, Ute, Schwinger, Jörg, Séférian, Roland, Skjelvan, Ingunn, Stocker, Benjamin D., Sutton, Adrienne J., Takahashi, Taro, Tian, Hanqin, Tilbrook, Bronte, Laan-Luijkx, Ingrid T., van der, Werf, Guido R., van der, Viovy, Nicolas, Walker, Anthony P., Wiltshire, Andrew J., Zaehle, Sönke, Quéré, Corinne, Le, Andrew, Robbie M., Canadell, Josep G., Sitch, Stephen, Korsbakken, Jan Ivar, Peters, Glen P., Manning, Andrew C., Boden, Thomas A., Tans, Pieter P., Houghton, Richard A., Keeling, Ralph F., Alin, Simone, Andrews, Oliver D., Anthoni, Peter, Barbero, Leticia, Bopp, Laurent, Chevallier, Frédéric, Chini, Louise P., Ciais, Philippe, Currie, Kim, Delire, Christine, Doney, Scott C., Friedlingstein, Pierre, Gkritzalis, Thanos, Harris, Ian, Hauck, Judith, Haverd, Vanessa, Hoppema, Mario, Klein Goldewijk, Kees, Jain, Atul K., Kato, Etsushi, Körtzinger, Arne, Landschützer, Peter, Lefèvre, Nathalie, Lenton, Andrew, Lienert, Sebastian, Lombardozzi, Danica, Melton, Joe R., Metzl, Nicolas, Millero, Frank, Monteiro, Pedro M.S., Munro, David R., Nabel, Julia E.M.S., Nakaoka, S., O'Brien, Kevin, Olsen, Are, Omar, Abdirahman M., Ono, Tsuneo, Pierrot, Denis, Poulter, Benjamin, Rödenbeck, Christian, Salisbury, Joe, Schuster, Ute, Schwinger, Jörg, Séférian, Roland, Skjelvan, Ingunn, Stocker, Benjamin D., Sutton, Adrienne J., Takahashi, Taro, Tian, Hanqin, Tilbrook, Bronte, Laan-Luijkx, Ingrid T., van der, Werf, Guido R., van der, Viovy, Nicolas, Walker, Anthony P., Wiltshire, Andrew J., and Zaehle, Sönke

Abstract

Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere – the “global carbon budget” – is important to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe data sets and methodology to quantify all major components of the global carbon budget, including their uncertainties, based on the combination of a range of data, algorithms, statistics, and model estimates and their interpretation by a broad scientific community. We discuss changes compared to previous estimates and consistency within and among components, alongside methodology and data limitations. CO2 emissions from fossil fuels and industry (EFF) are based on energy statistics and cement production data, respectively, while emissions from land-use change (ELUC), mainly deforestation, are based on combined evidence from land-cover change data, fire activity associated with deforestation, and models. The global atmospheric CO2 concentration is measured directly and its rate of growth (GATM) is computed from the annual changes in concentration. The mean ocean CO2 sink (SOCEAN) is based on observations from the 1990s, while the annual anomalies and trends are estimated with ocean models. The variability in SOCEAN is evaluated with data products based on surveys of ocean CO2 measurements. The global residual terrestrial CO2 sink (SLAND) is estimated by the difference of the other terms of the global carbon budget and compared to results of independent dynamic global vegetation models. We compare the mean land and ocean fluxes and their variability to estimates from three atmospheric inverse methods for three broad latitude bands. All uncertainties are reported as ±1σ, reflecting the current capacity to characterise the annual estimates of each component of the global carbon budget. For the last decade available (2006–2015), EFF was 9.3 ±

Published
2016

46. Global Carbon Budget 2016

Author

Le Quéré, C., Andrew, R.M., Canadell, J.G., Sitch, Stephen, Korsbakken, Jan Ivar, Peters, Glen P., Manning, Andrew C., Boden, Thomas A., Tans, Pieter P., Houghton, Richard A., Keeling, Ralph F., Alin, Simone, Andrews, Oliver D., Anthoni, Peter, Barbero, Leticia, Bopp, Laurent, Chevallier, Frédéric, Chini, Louise P., Ciais, Philippe, Currie, Kim, Delire, Christine, Doney, Scott C., Friedlingstein, Pierre, Gkritzalis, Thanos, Harris, Ian, Hauck, Judith, Haverd, Vanessa, Hoppema, Mario, Klein Goldewijk, Kees, Jain, Atul K., Kato, Etsushi, Körtzinger, Arne, Landschützer, Peter, Lefèvre, Nathalie, Lenton, Andrew, Lienert, Sebastian, Lombardozzi, Danica, Melton, Joe R., Metzl, Nicolas, Millero, Frank, Monteiro, Pedro M.S., Munro, David R., Nabel, Julia E.M.S., Nakaoka, Shin-Ichiro, O'Brien, Kevin, Olsen, Are, Omar, Abdirahman M., Ono, Tsuneo, Pierrot, Denis, Poulter, Benjamin, Rödenbeck, Christian, Salisbury, Joe, Schuster, Ute, Séférian, Roland, Skjelvan, Ingunn, Stocker, Benjamin D., Sutton, Adrienne J., Takahashi, Taro, Tian, Hanqin, Tilbrook, Bronte, van der Laan-Luijkx, I.T., Van Der Werf, Guido R., Viovy, Nicolas, Walker, Anthony P., Wiltshire, Andrew J., Zaehle, Sönke, Le Quéré, C., Andrew, R.M., Canadell, J.G., Sitch, Stephen, Korsbakken, Jan Ivar, Peters, Glen P., Manning, Andrew C., Boden, Thomas A., Tans, Pieter P., Houghton, Richard A., Keeling, Ralph F., Alin, Simone, Andrews, Oliver D., Anthoni, Peter, Barbero, Leticia, Bopp, Laurent, Chevallier, Frédéric, Chini, Louise P., Ciais, Philippe, Currie, Kim, Delire, Christine, Doney, Scott C., Friedlingstein, Pierre, Gkritzalis, Thanos, Harris, Ian, Hauck, Judith, Haverd, Vanessa, Hoppema, Mario, Klein Goldewijk, Kees, Jain, Atul K., Kato, Etsushi, Körtzinger, Arne, Landschützer, Peter, Lefèvre, Nathalie, Lenton, Andrew, Lienert, Sebastian, Lombardozzi, Danica, Melton, Joe R., Metzl, Nicolas, Millero, Frank, Monteiro, Pedro M.S., Munro, David R., Nabel, Julia E.M.S., Nakaoka, Shin-Ichiro, O'Brien, Kevin, Olsen, Are, Omar, Abdirahman M., Ono, Tsuneo, Pierrot, Denis, Poulter, Benjamin, Rödenbeck, Christian, Salisbury, Joe, Schuster, Ute, Séférian, Roland, Skjelvan, Ingunn, Stocker, Benjamin D., Sutton, Adrienne J., Takahashi, Taro, Tian, Hanqin, Tilbrook, Bronte, van der Laan-Luijkx, I.T., Van Der Werf, Guido R., Viovy, Nicolas, Walker, Anthony P., Wiltshire, Andrew J., and Zaehle, Sönke

Published
2016

47. Global Carbon Budget 2016

Author

Le Quéré, Corinne, primary, Andrew, Robbie M., additional, Canadell, Josep G., additional, Sitch, Stephen, additional, Korsbakken, Jan Ivar, additional, Peters, Glen P., additional, Manning, Andrew C., additional, Boden, Thomas A., additional, Tans, Pieter P., additional, Houghton, Richard A., additional, Keeling, Ralph F., additional, Alin, Simone, additional, Andrews, Oliver D., additional, Anthoni, Peter, additional, Barbero, Leticia, additional, Bopp, Laurent, additional, Chevallier, Frédéric, additional, Chini, Louise P., additional, Ciais, Philippe, additional, Currie, Kim, additional, Delire, Christine, additional, Doney, Scott C., additional, Friedlingstein, Pierre, additional, Gkritzalis, Thanos, additional, Harris, Ian, additional, Hauck, Judith, additional, Haverd, Vanessa, additional, Hoppema, Mario, additional, Klein Goldewijk, Kees, additional, Jain, Atul K., additional, Kato, Etsushi, additional, Körtzinger, Arne, additional, Landschützer, Peter, additional, Lefèvre, Nathalie, additional, Lenton, Andrew, additional, Lienert, Sebastian, additional, Lombardozzi, Danica, additional, Melton, Joe R., additional, Metzl, Nicolas, additional, Millero, Frank, additional, Monteiro, Pedro M. S., additional, Munro, David R., additional, Nabel, Julia E. M. S., additional, Nakaoka, Shin-ichiro, additional, O'Brien, Kevin, additional, Olsen, Are, additional, Omar, Abdirahman M., additional, Ono, Tsuneo, additional, Pierrot, Denis, additional, Poulter, Benjamin, additional, Rödenbeck, Christian, additional, Salisbury, Joe, additional, Schuster, Ute, additional, Schwinger, Jörg, additional, Séférian, Roland, additional, Skjelvan, Ingunn, additional, Stocker, Benjamin D., additional, Sutton, Adrienne J., additional, Takahashi, Taro, additional, Tian, Hanqin, additional, Tilbrook, Bronte, additional, van der Laan-Luijkx, Ingrid T., additional, van der Werf, Guido R., additional, Viovy, Nicolas, additional, Walker, Anthony P., additional, Wiltshire, Andrew J., additional, and Zaehle, Sönke, additional

Published
2016
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49. A statistical gap-filling method to interpolate global monthly surface ocean carbon dioxide data

Author

Jones, Steve D., Le Quere, Corinne, Roedenbeck, Christian, Manning, Andrew C., Olsen, Are, Jones, Steve D., Le Quere, Corinne, Roedenbeck, Christian, Manning, Andrew C., and Olsen, Are

Abstract

We have developed a statistical gap-filling method adapted to the specific coverage and properties of observed fugacity of surface ocean CO2 (fCO2). We have used this method to interpolate the Surface Ocean CO2 Atlas (SOCAT) v2 database on a 2.5°×2.5° global grid (south of 70°N) for 1985–2011 at monthly resolution. The method combines a spatial interpolation based on a “radius of influence” to determine nearby similar fCO2 values with temporal harmonic and cubic spline curve-fitting, and also fits long-term trends and seasonal cycles. Interannual variability is established using deviations of observations from the fitted trends and seasonal cycles. An uncertainty is computed for all interpolated values based on the spatial and temporal range of the interpolation. Tests of the method using model data show that it performs as well as or better than previous regional interpolation methods, but in addition it provides a near-global and interannual coverage.

Published
2015
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