Articles | Volume 13, issue 4
Geosci. Model Dev., 13, 2095–2107, 2020
Geosci. Model Dev., 13, 2095–2107, 2020

Development and technical paper 28 Apr 2020

Development and technical paper | 28 Apr 2020

Bayesian spatio-temporal inference of trace gas emissions using an integrated nested Laplacian approximation and Gaussian Markov random fields

Luke M. Western et al.

Related authors

Global Emissions of Perfluorocyclobutane (PFC-318, c-C4F8) Resulting from the Use of Hydrochlorofluorocarbon-22 (HCFC-22) Feedstock to Produce Polytetrafluoroethylene (PTFE) and related Fluorochemicals
Jens Mühle, Lambert J. M. Kuijpers, Kieran M. Stanley, Matthew Rigby, Luke M. Western, Jooil Kim, Sunyoung Park, Christina M. Harth, Paul B. Krummel, Paul J. Fraser, Simon O’Doherty, Peter K. Salameh, Roland Schmidt, Dickon Young, Ronald G. Prinn, Ray H. J. Wang, and Ray F. Weiss
Atmos. Chem. Phys. Discuss.,,, 2021
Preprint under review for ACP
Short summary
Quantifying fossil fuel methane emissions using observations of atmospheric ethane and an uncertain emission ratio
Alice E. Ramsden, Anita L. Ganesan, Luke M. Western, Matthew Rigby, Alistair J. Manning, Amy Foulds, James L. France, Patrick Barker, Peter Levy, Daniel Say, Adam Wisher, Tim Arnold, Chris Rennick, Kieran M. Stanley, Dickon Young, and Simon O'Doherty
Atmos. Chem. Phys. Discuss.,,, 2021
Revised manuscript accepted for ACP
Short summary
Global trends and European emissions of tetrafluoromethane (CF4), hexafluoroethane (C2F6) and octafluoropropane (C3F8)
Daniel Say, Alistair J. Manning, Luke M. Western, Dickon Young, Adam Wisher, Matthew Rigby, Stefan Reimann, Martin K. Vollmer, Michela Maione, Jgor Arduini, Paul B. Krummel, Jens Mühle, Christina M. Harth, Brendan Evans, Ray F. Weiss, Ronald G. Prinn, and Simon O'Doherty
Atmos. Chem. Phys., 21, 2149–2164,,, 2021
Short summary
Atmospheric-methane source and sink sensitivity analysis using Gaussian process emulation
Angharad C. Stell, Luke M. Western, Tomás Sherwen, and Matthew Rigby
Atmos. Chem. Phys., 21, 1717–1736,,, 2021
Short summary
Perfluorocyclobutane (PFC-318, c-C4F8) in the global atmosphere
Jens Mühle, Cathy M. Trudinger, Luke M. Western, Matthew Rigby, Martin K. Vollmer, Sunyoung Park, Alistair J. Manning, Daniel Say, Anita Ganesan, L. Paul Steele, Diane J. Ivy, Tim Arnold, Shanlan Li, Andreas Stohl, Christina M. Harth, Peter K. Salameh, Archie McCulloch, Simon O'Doherty, Mi-Kyung Park, Chun Ok Jo, Dickon Young, Kieran M. Stanley, Paul B. Krummel, Blagoj Mitrevski, Ove Hermansen, Chris Lunder, Nikolaos Evangeliou, Bo Yao, Jooil Kim, Benjamin Hmiel, Christo Buizert, Vasilii V. Petrenko, Jgor Arduini, Michela Maione, David M. Etheridge, Eleni Michalopoulou, Mike Czerniak, Jeffrey P. Severinghaus, Stefan Reimann, Peter G. Simmonds, Paul J. Fraser, Ronald G. Prinn, and Ray F. Weiss
Atmos. Chem. Phys., 19, 10335–10359,,, 2019
Short summary

Related subject area

Atmospheric sciences
Evaluation of the COSMO model (v5.1) in polarimetric radar space – impact of uncertainties in model microphysics, retrievals and forward operators
Prabhakar Shrestha, Jana Mendrok, Velibor Pejcic, Silke Trömel, Ulrich Blahak, and Jacob T. Carlin
Geosci. Model Dev., 15, 291–313,,, 2022
Short summary
Development of aerosol optical properties for improving the MESSy photolysis module in the GEM-MACH v2.4 air quality model and application for calculating photolysis rates in a biomass burning plume
Mahtab Majdzadeh, Craig A. Stroud, Christopher Sioris, Paul A. Makar, Ayodeji Akingunola, Chris McLinden, Xiaoyi Zhao, Michael D. Moran, Ihab Abboud, and Jack Chen
Geosci. Model Dev., 15, 219–249,,, 2022
Short summary
The sensitivity of simulated aerosol climatic impact to domain size using regional model (WRF-Chem v3.6)
Xiaodong Wang, Chun Zhao, Mingyue Xu, Qiuyan Du, Jianqiu Zheng, Yun Bi, Shengfu Lin, and Yali Luo
Geosci. Model Dev., 15, 199–218,,, 2022
Short summary
WOMBAT v1.0: a fully Bayesian global flux-inversion framework
Andrew Zammit-Mangion, Michael Bertolacci, Jenny Fisher, Ann Stavert, Matthew Rigby, Yi Cao, and Noel Cressie
Geosci. Model Dev., 15, 45–73,,, 2022
Short summary
Analysis of the MODIS above-cloud aerosol retrieval algorithm using MCARS
Galina Wind, Arlindo M. da Silva, Kerry G. Meyer, Steven Platnick, and Peter M. Norris
Geosci. Model Dev., 15, 1–14,,, 2022
Short summary

Cited articles

Berchet, A., Pison, I., Chevallier, F., Bousquet, P., Bonne, J.-L., and Paris, J.-D.: Objectified quantification of uncertainties in Bayesian atmospheric inversions, Geosci. Model Dev., 8, 1525–1546,, 2015. a
Bergamaschi, P., Frankenberg, C., Meirink, J. F., Krol, M., Dentener, F., Wagner, T., Platt, U., Kaplan, J. O., Körner, S., Heimann, M., Dlugokencky, E. J., and Goede, A.: Satellite chartography of atmospheric methane from SCIAMACHY on board ENVISAT: 2. Evaluation based on inverse model simulations, J. Geophys. Res.-Atmos., D02304, 112,, 2007. a
Brioude, J., Angevine, W. M., Ahmadov, R., Kim, S.-W., Evan, S., McKeen, S. A., Hsie, E.-Y., Frost, G. J., Neuman, J. A., Pollack, I. B., Peischl, J., Ryerson, T. B., Holloway, J., Brown, S. S., Nowak, J. B., Roberts, J. M., Wofsy, S. C., Santoni, G. W., Oda, T., and Trainer, M.: Top-down estimate of surface flux in the Los Angeles Basin using a mesoscale inverse modeling technique: assessing anthropogenic emissions of CO, NOx and CO2 and their impacts, Atmos. Chem. Phys., 13, 3661–3677,, 2013. a
Brunner, D., Henne, S., Keller, C. A., Reimann, S., Vollmer, M. K., O'Doherty, S., and Maione, M.: An extended Kalman-filter for regional scale inverse emission estimation, Atmos. Chem. Phys., 12, 3455–3478,, 2012. a
Brunner, D., Arnold, T., Henne, S., Manning, A., Thompson, R. L., Maione, M., O'Doherty, S., and Reimann, S.: Comparison of four inverse modelling systems applied to the estimation of HFC-125, HFC-134a, and SF6 emissions over Europe, Atmos. Chem. Phys., 17, 10651–10674,, 2017. a
Short summary
Assessments of greenhouse gas emissions using atmospheric measurements and meteorological models, or top-down methods, are important to verify national inventories or produce a stand-alone estimate where no inventory exists. We present a novel top-down method to estimate emissions. This approach uses a fast method called an integrated nested Laplacian approximation to estimate how these emissions are correlated with other emissions in different locations and at different times.