Articles | Volume 10, issue 12
https://doi.org/10.5194/gmd-10-4605-2017
https://doi.org/10.5194/gmd-10-4605-2017
Development and technical paper
 | 
18 Dec 2017
Development and technical paper |  | 18 Dec 2017

Source–receptor matrix calculation for deposited mass with the Lagrangian particle dispersion model FLEXPART v10.2 in backward mode

Sabine Eckhardt, Massimo Cassiani, Nikolaos Evangeliou, Espen Sollum, Ignacio Pisso, and Andreas Stohl

Related authors

FLEXPART version 11: Improved accuracy, efficiency, and flexibility
Lucie Bakels, Daria Tatsii, Anne Tipka, Rona Thompson, Marina Dütsch, Michael Blaschek, Petra Seibert, Katharina Baier, Silvia Bucci, Massimo Cassiani, Sabine Eckhardt, Christine Groot Zwaaftink, Stephan Henne, Pirmin Kaufmann, Vincent Lechner, Christian Maurer, Marie D. Mulder, Ignacio Pisso, Andreas Plach, Rakesh Subramanian, Martin Vojta, and Andreas Stohl
EGUsphere, https://doi.org/10.5194/egusphere-2024-1713,https://doi.org/10.5194/egusphere-2024-1713, 2024
Short summary
Composition and sources of carbonaceous aerosol in the European Arctic at Zeppelin Observatory, Svalbard (2017 to 2020)
Karl Espen Yttri, Are Bäcklund, Franz Conen, Sabine Eckhardt, Nikolaos Evangeliou, Markus Fiebig, Anne Kasper-Giebl, Avram Gold, Hans Gundersen, Cathrine Lund Myhre, Stephen Matthew Platt, David Simpson, Jason D. Surratt, Sönke Szidat, Martin Rauber, Kjetil Tørseth, Martin Album Ytre-Eide, Zhenfa Zhang, and Wenche Aas
Atmos. Chem. Phys., 24, 2731–2758, https://doi.org/10.5194/acp-24-2731-2024,https://doi.org/10.5194/acp-24-2731-2024, 2024
Short summary
Decreasing trends of ammonia emissions over Europe seen from remote sensing and inverse modelling
Ondřej Tichý, Sabine Eckhardt, Yves Balkanski, Didier Hauglustaine, and Nikolaos Evangeliou
Atmos. Chem. Phys., 23, 15235–15252, https://doi.org/10.5194/acp-23-15235-2023,https://doi.org/10.5194/acp-23-15235-2023, 2023
Short summary
The atmospheric fate of 1,2-dibromo-4-(1,2-dibromoethyl)cyclohexane (TBECH): spatial patterns, seasonal variability, and deposition to Canadian coastal regions
Jenny Oh, Chubashini Shunthirasingham, Ying Duan Lei, Faqiang Zhan, Yuening Li, Abigaëlle Dalpé Castilloux, Amina Ben Chaaben, Zhe Lu, Kelsey Lee, Frank A. P. C. Gobas, Sabine Eckhardt, Nick Alexandrou, Hayley Hung, and Frank Wania
Atmos. Chem. Phys., 23, 10191–10205, https://doi.org/10.5194/acp-23-10191-2023,https://doi.org/10.5194/acp-23-10191-2023, 2023
Short summary
Consistent histories of anthropogenic western European air pollution preserved in different Alpine ice cores
Anja Eichler, Michel Legrand, Theo M. Jenk, Susanne Preunkert, Camilla Andersson, Sabine Eckhardt, Magnuz Engardt, Andreas Plach, and Margit Schwikowski
The Cryosphere, 17, 2119–2137, https://doi.org/10.5194/tc-17-2119-2023,https://doi.org/10.5194/tc-17-2119-2023, 2023
Short summary

Related subject area

Atmospheric sciences
WRF-Comfort: simulating microscale variability in outdoor heat stress at the city scale with a mesoscale model
Alberto Martilli, Negin Nazarian, E. Scott Krayenhoff, Jacob Lachapelle, Jiachen Lu, Esther Rivas, Alejandro Rodriguez-Sanchez, Beatriz Sanchez, and José Luis Santiago
Geosci. Model Dev., 17, 5023–5039, https://doi.org/10.5194/gmd-17-5023-2024,https://doi.org/10.5194/gmd-17-5023-2024, 2024
Short summary
Representing effects of surface heterogeneity in a multi-plume eddy diffusivity mass flux boundary layer parameterization
Nathan P. Arnold
Geosci. Model Dev., 17, 5041–5056, https://doi.org/10.5194/gmd-17-5041-2024,https://doi.org/10.5194/gmd-17-5041-2024, 2024
Short summary
Can TROPOMI NO2 satellite data be used to track the drop in and resurgence of NOx emissions in Germany between 2019–2021 using the multi-source plume method (MSPM)?
Enrico Dammers, Janot Tokaya, Christian Mielke, Kevin Hausmann, Debora Griffin, Chris McLinden, Henk Eskes, and Renske Timmermans
Geosci. Model Dev., 17, 4983–5007, https://doi.org/10.5194/gmd-17-4983-2024,https://doi.org/10.5194/gmd-17-4983-2024, 2024
Short summary
A spatiotemporally separated framework for reconstructing the sources of atmospheric radionuclide releases
Yuhan Xu, Sheng Fang, Xinwen Dong, and Shuhan Zhuang
Geosci. Model Dev., 17, 4961–4982, https://doi.org/10.5194/gmd-17-4961-2024,https://doi.org/10.5194/gmd-17-4961-2024, 2024
Short summary
A parameterization scheme for the floating wind farm in a coupled atmosphere–wave model (COAWST v3.7)
Shaokun Deng, Shengmu Yang, Shengli Chen, Daoyi Chen, Xuefeng Yang, and Shanshan Cui
Geosci. Model Dev., 17, 4891–4909, https://doi.org/10.5194/gmd-17-4891-2024,https://doi.org/10.5194/gmd-17-4891-2024, 2024
Short summary

Cited articles

Bory, A. J. M., Biscaye, P. E., Svensson, A., and Grousset, F. E.: Seasonal variability in the origin of recent atmospheric mineral dust at NorthGRIP, Greenland, Earth Planet. Sc. Lett., 196, 123–134, https://doi.org/10.1016/s0012-821x(01)00609-4, 2002.
Brioude, J., Arnold, D., Stohl, A., Cassiani, M., Morton, D., Seibert, P., Angevine, W., Evan, S., Dingwell, A., Fast, J. D., Easter, R. C., Pisso, I., Burkhart, J., and Wotawa, G.: The Lagrangian particle dispersion model FLEXPART-WRF version 3.1, Geosci. Model Dev., 6, 1889–1904, https://doi.org/10.5194/gmd-6-1889-2013, 2013.
Cassiani, M., Stohl, A., and Brioude, J.: Lagrangian Stochastic Modelling of Dispersion in the Convective Boundary Layer with Skewed Turbulence Conditions and a Vertical Density Gradient: formulation and Implementation in the FLEXPART Model, Bound.-Layer Meteorol., 154, 367–390, 2015.
Cassiani, M., Stohl, A., Olivié, D., Seland, Ø., Bethke, I., Pisso, I., and Iversen, T.: The offline Lagrangian particle model FLEXPART–NorESM/CAM (v1): model description and comparisons with the online NorESM transport scheme and with the reference FLEXPART model, Geosci. Model Dev., 9, 4029–4048, https://doi.org/10.5194/gmd-9-4029-2016, 2016.
Doherty, S. J., Warren, S. G., Grenfell, T. C., Clarke, A. D., and Brandt, R. E.: Light-absorbing impurities in Arctic snow, Atmos. Chem. Phys., 10, 11647–11680, https://doi.org/10.5194/acp-10-11647-2010, 2010.
Download
Short summary
We extend the backward modelling technique in the existing model FLEXPART to substances deposited at the Earth’s surface by wet scavenging and dry deposition. This means that for existing measurements of a substance in snow, ice cores or rain samples the source regions can be determined. This will help the interpretation of the measurement as well as gaining information of emission strength at the source of the deposited substance.