Articles | Volume 13, issue 4
https://doi.org/10.5194/gmd-13-2095-2020
https://doi.org/10.5194/gmd-13-2095-2020
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, Zhe Sha, Matthew Rigby, Anita L. Ganesan, Alistair J. Manning, Kieran M. Stanley, Simon J. O'Doherty, Dickon Young, and Jonathan Rougier

Related authors

A new production-based model for estimating emissions and banks of ODSs: Application to HCFC-141b
Helen Walter-Terrinoni, John S. Daniel, Chelsea R. Thompson, and Luke M. Western
EGUsphere, https://doi.org/10.5194/egusphere-2025-297,https://doi.org/10.5194/egusphere-2025-297, 2025
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
Short summary
Global nitrous oxide budget (1980–2020)
Hanqin Tian, Naiqing Pan, Rona L. Thompson, Josep G. Canadell, Parvadha Suntharalingam, Pierre Regnier, Eric A. Davidson, Michael Prather, Philippe Ciais, Marilena Muntean, Shufen Pan, Wilfried Winiwarter, Sönke Zaehle, Feng Zhou, Robert B. Jackson, Hermann W. Bange, Sarah Berthet, Zihao Bian, Daniele Bianchi, Alexander F. Bouwman, Erik T. Buitenhuis, Geoffrey Dutton, Minpeng Hu, Akihiko Ito, Atul K. Jain, Aurich Jeltsch-Thömmes, Fortunat Joos, Sian Kou-Giesbrecht, Paul B. Krummel, Xin Lan, Angela Landolfi, Ronny Lauerwald, Ya Li, Chaoqun Lu, Taylor Maavara, Manfredi Manizza, Dylan B. Millet, Jens Mühle, Prabir K. Patra, Glen P. Peters, Xiaoyu Qin, Peter Raymond, Laure Resplandy, Judith A. Rosentreter, Hao Shi, Qing Sun, Daniele Tonina, Francesco N. Tubiello, Guido R. van der Werf, Nicolas Vuichard, Junjie Wang, Kelley C. Wells, Luke M. Western, Chris Wilson, Jia Yang, Yuanzhi Yao, Yongfa You, and Qing Zhu
Earth Syst. Sci. Data, 16, 2543–2604, https://doi.org/10.5194/essd-16-2543-2024,https://doi.org/10.5194/essd-16-2543-2024, 2024
Short summary
The interhemispheric gradient of SF6 in the upper troposphere
Tanja J. Schuck, Johannes Degen, Eric Hintsa, Peter Hoor, Markus Jesswein, Timo Keber, Daniel Kunkel, Fred Moore, Florian Obersteiner, Matt Rigby, Thomas Wagenhäuser, Luke M. Western, Andreas Zahn, and Andreas Engel
Atmos. Chem. Phys., 24, 689–705, https://doi.org/10.5194/acp-24-689-2024,https://doi.org/10.5194/acp-24-689-2024, 2024
Short summary
Western European emission estimates of CFC-11, CFC-12 and CCl4 derived from atmospheric measurements from 2008 to 2021
Alison L. Redington, Alistair J. Manning, Stephan Henne, Francesco Graziosi, Luke M. Western, Jgor Arduini, Anita L. Ganesan, Christina M. Harth, Michela Maione, Jens Mühle, Simon O'Doherty, Joseph Pitt, Stefan Reimann, Matthew Rigby, Peter K. Salameh, Peter G. Simmonds, T. Gerard Spain, Kieran Stanley, Martin K. Vollmer, Ray F. Weiss, and Dickon Young
Atmos. Chem. Phys., 23, 7383–7398, https://doi.org/10.5194/acp-23-7383-2023,https://doi.org/10.5194/acp-23-7383-2023, 2023
Short summary
A renewed rise in global HCFC-141b emissions between 2017–2021
Luke M. Western, Alison L. Redington, Alistair J. Manning, Cathy M. Trudinger, Lei Hu, Stephan Henne, Xuekun Fang, Lambert J. M. Kuijpers, Christina Theodoridi, David S. Godwin, Jgor Arduini, Bronwyn Dunse, Andreas Engel, Paul J. Fraser, Christina M. Harth, Paul B. Krummel, Michela Maione, Jens Mühle, Simon O'Doherty, Hyeri Park, Sunyoung Park, Stefan Reimann, Peter K. Salameh, Daniel Say, Roland Schmidt, Tanja Schuck, Carolina Siso, Kieran M. Stanley, Isaac Vimont, Martin K. Vollmer, Dickon Young, Ronald G. Prinn, Ray F. Weiss, Stephen A. Montzka, and Matthew Rigby
Atmos. Chem. Phys., 22, 9601–9616, https://doi.org/10.5194/acp-22-9601-2022,https://doi.org/10.5194/acp-22-9601-2022, 2022
Short summary

Related subject area

Atmospheric sciences
Indian Institute of Tropical Meteorology (IITM) High-Resolution Global Forecast Model version 1: an attempt to resolve monsoon prediction deadlock
R. Phani Murali Krishna, Siddharth Kumar, A. Gopinathan Prajeesh, Peter Bechtold, Nils Wedi, Kumar Roy, Malay Ganai, B. Revanth Reddy, Snehlata Tirkey, Tanmoy Goswami, Radhika Kanase, Sahadat Sarkar, Medha Deshpande, and Parthasarathi Mukhopadhyay
Geosci. Model Dev., 18, 1879–1894, https://doi.org/10.5194/gmd-18-1879-2025,https://doi.org/10.5194/gmd-18-1879-2025, 2025
Short summary
Cell-tracking-based framework for assessing nowcasting model skill in reproducing growth and decay of convective rainfall
Jenna Ritvanen, Seppo Pulkkinen, Dmitri Moisseev, and Daniele Nerini
Geosci. Model Dev., 18, 1851–1878, https://doi.org/10.5194/gmd-18-1851-2025,https://doi.org/10.5194/gmd-18-1851-2025, 2025
Short summary
NeuralMie (v1.0): an aerosol optics emulator
Andrew Geiss and Po-Lun Ma
Geosci. Model Dev., 18, 1809–1827, https://doi.org/10.5194/gmd-18-1809-2025,https://doi.org/10.5194/gmd-18-1809-2025, 2025
Short summary
Simulation performance of planetary boundary layer schemes in WRF v4.3.1 for near-surface wind over the western Sichuan Basin: a single-site assessment
Qin Wang, Bo Zeng, Gong Chen, and Yaoting Li
Geosci. Model Dev., 18, 1769–1784, https://doi.org/10.5194/gmd-18-1769-2025,https://doi.org/10.5194/gmd-18-1769-2025, 2025
Short summary
FootNet v1.0: development of a machine learning emulator of atmospheric transport
Tai-Long He, Nikhil Dadheech, Tammy M. Thompson, and Alexander J. Turner
Geosci. Model Dev., 18, 1661–1671, https://doi.org/10.5194/gmd-18-1661-2025,https://doi.org/10.5194/gmd-18-1661-2025, 2025
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, https://doi.org/10.5194/gmd-8-1525-2015, 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, https://doi.org/10.1029/2006JD007268, 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, https://doi.org/10.5194/acp-13-3661-2013, 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, https://doi.org/10.5194/acp-12-3455-2012, 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, https://doi.org/10.5194/acp-17-10651-2017, 2017. a
Download
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.
Share