Fluxes of carbon dioxide from managed ecosystems estimated by national inventories compared to atmospheric inverse modelling

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 primary productivity. Two different models, CARDAMOM and 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 (CARDAMOM prior) and −64 ± 85 Tg CO2 yr−1 (JULES prior), where -ve 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 are consistently higher than the prior estimates, which show much more pronounced uptake in the summer months.

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

Atmospheric Chemistry and Physics ◽

10.5194/acp-19-4345-2019 ◽

2019 ◽

Vol 19 (7) ◽

pp. 4345-4365 ◽

Cited By ~ 5

Author(s):

Emily D. White ◽

Matthew Rigby ◽

Mark F. Lunt ◽

T. Luke Smallman ◽

Edward Comyn-Platt ◽

...

Keyword(s):

Carbon Dioxide ◽

Transport Model ◽

Ecosystem Respiration ◽

Atmospheric Dispersion ◽

Terrestrial Ecosystem ◽

Carbon Dioxide Flux ◽

Inverse Modelling ◽

Chemical Transport Model ◽

The Uk ◽

The Impact

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.

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Implications of Increasing Carbon Dioxide and Climate Change for Plant Communities and Competition in Natural and Managed Ecosystems

Impact of Carbon Dioxide, Trace Gases, and Climate Change on Global Agriculture - ASA Special Publications ◽

10.2134/asaspecpub53.c7 ◽

2016 ◽

pp. 83-110 ◽

Cited By ~ 4

Author(s):

David T. Patterson ◽

Elizabeth P. Flint

Keyword(s):

Climate Change ◽

Carbon Dioxide ◽

Plant Communities ◽

Managed Ecosystems

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Atmospheric greenhouse gases retrieved from SCIAMACHY: comparison to ground-based FTS measurements and model results

Atmospheric Chemistry and Physics ◽

10.5194/acp-12-1527-2012 ◽

2012 ◽

Vol 12 (3) ◽

pp. 1527-1540 ◽

Cited By ~ 69

Author(s):

O. Schneising ◽

P. Bergamaschi ◽

H. Bovensmann ◽

M. Buchwitz ◽

J. P. Burrows ◽

...

Keyword(s):

Carbon Dioxide ◽

Standard Deviation ◽

Greenhouse Gases ◽

Seasonal Cycle ◽

Relative Accuracy ◽

Total Carbon ◽

Inverse Modelling ◽

Data Sets ◽

Relative Precision ◽

Data Set

Abstract. SCIAMACHY onboard ENVISAT (launched in 2002) enables the retrieval of global long-term column-averaged dry air mole fractions of the two most important anthropogenic greenhouse gases carbon dioxide and methane (denoted XCO2 and XCH4). In order to assess the quality of the greenhouse gas data obtained with the recently introduced v2 of the scientific retrieval algorithm WFM-DOAS, we present validations with ground-based Fourier Transform Spectrometer (FTS) measurements and comparisons with model results at eight Total Carbon Column Observing Network (TCCON) sites providing realistic error estimates of the satellite data. Such validation is a prerequisite to assess the suitability of data sets for their use in inverse modelling. It is shown that there are generally no significant differences between the carbon dioxide annual increases of SCIAMACHY and the assimilation system CarbonTracker (2.00 &pm; 0.16 ppm yr−1 compared to 1.94 &pm; 0.03 ppm yr−1 on global average). The XCO2 seasonal cycle amplitudes derived from SCIAMACHY are typically larger than those from TCCON which are in turn larger than those from CarbonTracker. The absolute values of the northern hemispheric TCCON seasonal cycle amplitudes are closer to SCIAMACHY than to CarbonTracker and the corresponding differences are not significant when compared with SCIAMACHY, whereas they can be significant for a subset of the analysed TCCON sites when compared with CarbonTracker. At Darwin we find discrepancies of the seasonal cycle derived from SCIAMACHY compared to the other data sets which can probably be ascribed to occurrences of undetected thin clouds. Based on the comparison with the reference data, we conclude that the carbon dioxide data set can be characterised by a regional relative precision (mean standard deviation of the differences) of about 2.2 ppm and a relative accuracy (standard deviation of the mean differences) of 1.1–1.2 ppm for monthly average composites within a radius of 500 km. For methane, prior to November 2005, the regional relative precision amounts to 12 ppb and the relative accuracy is about 3 ppb for monthly composite averages within the same radius. The loss of some spectral detector pixels results in a degradation of performance thereafter in the spectral range currently used for the methane column retrieval. This leads to larger scatter and lower XCH4 values are retrieved in the tropics for the subsequent time period degrading the relative accuracy. As a result, the overall relative precision is estimated to be 17 ppb and the relative accuracy is in the range of about 10–20 ppb for monthly averages within a radius of 500 km. The derived estimates show that the SCIAMACHY XCH4 data set before November 2005 is suitable for regional source/sink determination and regional-scale flux uncertainty reduction via inverse modelling worldwide. In addition, the XCO2 monthly data potentially provide valuable information in continental regions, where there is sparse sampling by surface flask measurements.

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Atmospheric greenhouse gases retrieved from SCIAMACHY: comparison to ground-based FTS measurements and model results

Atmospheric Chemistry and Physics Discussions ◽

10.5194/acpd-11-28713-2011 ◽

2011 ◽

Vol 11 (10) ◽

pp. 28713-28745 ◽

Cited By ~ 1

Author(s):

O. Schneising ◽

P. Bergamaschi ◽

H. Bovensmann ◽

M. Buchwitz ◽

J. P. Burrows ◽

...

Keyword(s):

Carbon Dioxide ◽

Greenhouse Gases ◽

Seasonal Cycle ◽

Relative Accuracy ◽

Total Carbon ◽

Inverse Modelling ◽

Retrieval Algorithm ◽

Data Sets ◽

Relative Precision ◽

Data Set

Abstract. SCIAMACHY onboard ENVISAT (launched in 2002) enables the retrieval of global long-term column-averaged dry air mole fractions of the two most important anthropogenic greenhouse gases carbon dioxide and methane (denoted XCO2 and XCH4). In order to assess the quality of the greenhouse gas data obtained with the recently introduced v2 of the scientific retrieval algorithm WFM-DOAS, we present validations with ground-based Fourier Transform Spectrometer (FTS) measurements and comparisons with model results at eight Total Carbon Column Observing Network (TCCON) sites providing realistic error estimates of the satellite data. Such validation is a prerequisite to assess the suitability of data sets for their use in inverse modelling. It is shown that there are generally no significant differences between the SCIAMACHY and CarbonTracker carbon dioxide annual increases (2.00 &pm; 0.16 ppm yr−1 compared to 1.94 &pm; 0.03 ppm yr−1 on global average). The XCO2 seasonal cycle amplitudes derived from SCIAMACHY are typically larger than those from TCCON which are in turn larger than those from CarbonTracker. The absolute values of the northern hemispheric TCCON seasonal cycle amplitudes are closer to SCIAMACHY than to CarbonTracker and the corresponding differences are not significant when compared with SCIAMACHY, whereas they can be significant when compared with CarbonTracker. At Darwin we find discrepancies of the seasonal cycle derived from SCIAMACHY compared to the other data sets which can probably be ascribed to occurrences of undetected thin clouds. Based on the comparison with the reference data, we conclude that the carbon dioxide data set can be characterised by a regional relative precision of about 2.2 ppm and a relative accuracy of 1.1–1.2 ppm for monthly average composites within a radius of 500 km. For methane, prior to November 2005, the regional relative precision amounts to 12 ppb and the relative accuracy is about 3 ppb with respect to model simulations for monthly composite averages within the same radius. The loss of some spectral detector pixels results in a degradation of performance thereafter in the spectral range currently used for the methane column retrieval. This leads to larger scatter and less methane retrieved in the tropics for the subsequent time period degrading the relative accuracy. As a result, the overall relative precision is estimated to be 17 ppb and the relative accuracy is in the range of about 10–20 ppb for monthly averages within a radius of 500 km. The derived estimates show that the SCIAMACHY XCH4 data set before November 2005 is suitable for regional source/sink determination via inverse modelling worldwide. In addition, the XCO2 monthly data potentially provide valuable information in continental regions, where there is sparse sampling by surface flask measurements.

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Supplementary material to "Quantifying the UK’s Carbon Dioxide Flux: An atmospheric inverse modelling approach using a regional measurement network"

10.5194/acp-2018-839-supplement ◽

2018 ◽

Author(s):

Emily D. White ◽

Matthew Rigby ◽

Mark F. Lunt ◽

Anita L. Ganesan ◽

Alistair J. Manning ◽

...

Keyword(s):

Carbon Dioxide ◽

Carbon Dioxide Flux ◽

Inverse Modelling ◽

Supplementary Material ◽

Modelling Approach

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Electron Cytochemical Study of Carbon Dioxide Laser Effect on Rhesus Monkey Cornea

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s042482010005113x ◽

1974 ◽

Vol 32 ◽

pp. 224-225

Author(s):

K. C. Tsou ◽

J. Morris ◽

P. Shawaluk ◽

B. Stuck ◽

E. Beatrice

Keyword(s):

Carbon Dioxide ◽

Electron Microscope ◽

Rhesus Monkey ◽

Carbon Dioxide Laser ◽

Cytochemical Study ◽

Laser Effect

While much is known regarding the effect of lasers on the retina, little study has been done on the effect of lasers on cornea, because of the limitation of the size of the material. Using a combination of electron microscope and several newly developed cytochemical methods, the effect of laser can now be studied on eye for the purpose of correlating functional and morphological damage. The present paper illustrates such study with CO2 laser on Rhesus monkey.

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The Critical Point Drying Method Applied to Scanning Electron Microscopy of L-929 Cells

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100068382 ◽

1970 ◽

Vol 28 ◽

pp. 278-279

Author(s):

Charles TurnbiLL ◽

Delbert E. Philpott

Keyword(s):

Electron Microscopy ◽

Carbon Dioxide ◽

Surface Tension ◽

Critical Point ◽

Freeze Drying ◽

Attractive Alternative ◽

Crystal Formation ◽

Critical Point Drying ◽

Time Required ◽

Scanning Electron

The advent of the scanning electron microscope (SCEM) has renewed interest in preparing specimens by avoiding the forces of surface tension. The present method of freeze drying by Boyde and Barger (1969) and Small and Marszalek (1969) does prevent surface tension but ice crystal formation and time required for pumping out the specimen to dryness has discouraged us. We believe an attractive alternative to freeze drying is the critical point method originated by Anderson (1951; for electron microscopy. He avoided surface tension effects during drying by first exchanging the specimen water with alcohol, amy L acetate and then with carbon dioxide. He then selected a specific temperature (36.5°C) and pressure (72 Atm.) at which carbon dioxide would pass from the liquid to the gaseous phase without the effect of surface tension This combination of temperature and, pressure is known as the "critical point" of the Liquid.

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