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DOI	10.5194/acp-19-4345-2019
	Quantifying the UK's carbon dioxide flux: An atmospheric inverse modelling approach using a regional measurement network
	White E.D.; Rigby M.; Lunt M.F.; Luke Smallman T.; Comyn-Platt E.; Manning A.J.; Ganesan A.L.; O'Doherty S.; Stavert A.R.; Stanley K.; Williams M.; Levy P.; Ramonet M.; Forster G.L.; Manning A.C.; Palmer P.I.
发表日期	2019
ISSN	16807316
起始页码	4345
结束页码	4365
卷号	19 期号:7
英文摘要	We present a method to derive atmosphericobservation-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 TgCO2 yr-1 (DALEC prior) and 64±85 TgCO2 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. © 2019 Author(s).
语种	英语
scopus关键词	atmospheric chemistry; atmospheric modeling; Bayesian analysis; biosphere; carbon dioxide; Markov chain; measurement method; Monte Carlo analysis; summer; Ireland; United Kingdom
来源期刊	Atmospheric Chemistry and Physics
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/144517
作者单位	School of Chemistry, University of Bristol, Bristol, BS8 1TS, United Kingdom; School of GeoSciences, University of Edinburgh, Edinburgh, EH93FF, United Kingdom; National Centre for Earth Observation, Edinburgh, EH93FF, United Kingdom; Centre for Ecology and Hydrology, Wallingford, OX 108BB, United Kingdom; Hadley Centre, Met. Office, Exeter, EX13PB, United Kingdom; School of Geographical Sciences, University of Bristol, Bristol, BS81SS, United Kingdom; Climate Science Centre, CSIRO Oceans and Atmosphere, Aspendale, VIC3195, Australia; Centre for Ecology and Hydrology, Edinburgh Research Station, Penicuik, E260QB, United Kingdom; Laboratoire des Sciences du Climat et de l'Environnement, CEA-CNRS-UVSQ, Gif-sur-Yvette, 91198, France; Centre for Ocean and Atmospheric Sciences, School of Environmental Sciences, University of East Anglia, Norwich, NR47TJ, United Kingdom; National Centre for Atmospheric Science, School of Environmental Sciences, University of East Anglia, Norwich, NR47TJ, United Kingdom
推荐引用方式 GB/T 7714	White E.D.,Rigby M.,Lunt M.F.,et al. Quantifying the UK's carbon dioxide flux: An atmospheric inverse modelling approach using a regional measurement network[J],2019,19(7).
APA	White E.D..,Rigby M..,Lunt M.F..,Luke Smallman T..,Comyn-Platt E..,...&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).
MLA	White E.D.,et al."Quantifying the UK's carbon dioxide flux: An atmospheric inverse modelling approach using a regional measurement network".Atmospheric Chemistry and Physics 19.7(2019).