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

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Quantifying the UK's carbon dioxide flux : An atmospheric inverse modelling approach using a regional measurement network. / White, Emily D.; Rigby, Matthew; Lunt, Mark F.; Luke Smallman, T.; 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.

In: Atmospheric Chemistry and Physics, Vol. 19, No. 7, 04.04.2019, p. 4345-4365.

Research output: Contribution to journalArticle

Harvard

White, ED, Rigby, M, Lunt, MF, Luke Smallman, T, Comyn-Platt, E, Manning, AJ, Ganesan, AL, O'Doherty, S, Stavert, AR, Stanley, K, Williams, M, Levy, P, Ramonet, M, Forster, GL, Manning, AC & Palmer, PI 2019, 'Quantifying the UK's carbon dioxide flux: An atmospheric inverse modelling approach using a regional measurement network', Atmospheric Chemistry and Physics, vol. 19, no. 7, pp. 4345-4365. https://doi.org/10.5194/acp-19-4345-2019

APA

White, E. D., Rigby, M., Lunt, M. F., Luke Smallman, T., Comyn-Platt, E., Manning, A. J., ... Palmer, P. I. (2019). Quantifying the UK's carbon dioxide flux: An atmospheric inverse modelling approach using a regional measurement network. Atmospheric Chemistry and Physics, 19(7), 4345-4365. https://doi.org/10.5194/acp-19-4345-2019

Vancouver

White ED, Rigby M, Lunt MF, Luke Smallman T, Comyn-Platt E, Manning AJ et al. Quantifying the UK's carbon dioxide flux: An atmospheric inverse modelling approach using a regional measurement network. Atmospheric Chemistry and Physics. 2019 Apr 4;19(7):4345-4365. https://doi.org/10.5194/acp-19-4345-2019

Author

White, Emily D. ; Rigby, Matthew ; Lunt, Mark F. ; Luke Smallman, T. ; 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. / Quantifying the UK's carbon dioxide flux : An atmospheric inverse modelling approach using a regional measurement network. In: Atmospheric Chemistry and Physics. 2019 ; Vol. 19, No. 7. pp. 4345-4365.

Bibtex

@article{0fed3122344d46089896968504d4d906,
title = "Quantifying the UK's carbon dioxide flux: An atmospheric inverse modelling approach using a regional measurement network",
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.",
author = "White, {Emily D.} and Matthew Rigby and Lunt, {Mark F.} and {Luke Smallman}, T. and Edward Comyn-Platt and Manning, {Alistair J.} and Ganesan, {Anita L.} and Simon O'Doherty and Stavert, {Ann R.} and Kieran Stanley and Mathew Williams and Peter Levy and Michel Ramonet and Forster, {Grant L.} and Manning, {Andrew C.} and Palmer, {Paul I.}",
year = "2019",
month = "4",
day = "4",
doi = "10.5194/acp-19-4345-2019",
language = "English",
volume = "19",
pages = "4345--4365",
journal = "Atmospheric Chemistry and Physics",
issn = "1680-7316",
publisher = "Copernicus GmbH",
number = "7",

}

RIS - suitable for import to EndNote

TY - JOUR

T1 - Quantifying the UK's carbon dioxide flux

T2 - An atmospheric inverse modelling approach using a regional measurement network

AU - White, Emily D.

AU - Rigby, Matthew

AU - Lunt, Mark F.

AU - Luke Smallman, T.

AU - Comyn-Platt, Edward

AU - Manning, Alistair J.

AU - Ganesan, Anita L.

AU - O'Doherty, Simon

AU - Stavert, Ann R.

AU - Stanley, Kieran

AU - Williams, Mathew

AU - Levy, Peter

AU - Ramonet, Michel

AU - Forster, Grant L.

AU - Manning, Andrew C.

AU - Palmer, Paul I.

PY - 2019/4/4

Y1 - 2019/4/4

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=85063879337&partnerID=8YFLogxK

U2 - 10.5194/acp-19-4345-2019

DO - 10.5194/acp-19-4345-2019

M3 - Article

VL - 19

SP - 4345

EP - 4365

JO - Atmospheric Chemistry and Physics

JF - Atmospheric Chemistry and Physics

SN - 1680-7316

IS - 7

ER -