Articles | Volume 19, issue 13
https://doi.org/10.5194/gmd-19-6259-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-19-6259-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper
| 
13 Jul 2026
Model description paper |
| 13 Jul 2026
| 13 Jul 2026
The Boundary Layer Dispersion and Footprint Model: a fast numerical solver of the Eulerian steady-state advection-diffusion equation
Mark Schlutow
CORRESPONDING AUTHOR
Max Planck Institute for Biogeochemistry, Jena, Germany
California Institute of Technology, Division of Geological and Planetary Sciences, Pasadena, CA, USA
Mathias Göckede
Max Planck Institute for Biogeochemistry, Jena, Germany
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Methane is a key greenhouse gas, and identifying its sources is crucial for reducing emissions. This study enhances methane detection at oil and gas sites by combining sensor data with advanced modeling tools. Tests in real-world and simulated conditions showed high accuracy, particularly in favorable atmospheric conditions. These findings improve methane monitoring and support better emission detection in Continuous Emission Monitoring systems.
Barbara Widhalm, Annett Bartsch, Tazio Strozzi, Nina Jones, Artem Khomutov, Elena Babkina, Marina Leibman, Rustam Khairullin, Mathias Göckede, Helena Bergstedt, Clemens von Baeckmann, and Xaver Muri
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Jacob A. Nelson, Sophia Walther, Fabian Gans, Basil Kraft, Ulrich Weber, Kimberly Novick, Nina Buchmann, Mirco Migliavacca, Georg Wohlfahrt, Ladislav Šigut, Andreas Ibrom, Dario Papale, Mathias Göckede, Gregory Duveiller, Alexander Knohl, Lukas Hörtnagl, Russell L. Scott, Jiří Dušek, Weijie Zhang, Zayd Mahmoud Hamdi, Markus Reichstein, Sergio Aranda-Barranco, Jonas Ardö, Maarten Op de Beeck, Dave Billesbach, David Bowling, Rosvel Bracho, Christian Brümmer, Gustau Camps-Valls, Shiping Chen, Jamie Rose Cleverly, Ankur Desai, Gang Dong, Tarek S. El-Madany, Eugenie Susanne Euskirchen, Iris Feigenwinter, Marta Galvagno, Giacomo A. Gerosa, Bert Gielen, Ignacio Goded, Sarah Goslee, Christopher Michael Gough, Bernard Heinesch, Kazuhito Ichii, Marcin Antoni Jackowicz-Korczynski, Anne Klosterhalfen, Sara Knox, Hideki Kobayashi, Kukka-Maaria Kohonen, Mika Korkiakoski, Ivan Mammarella, Mana Gharun, Riccardo Marzuoli, Roser Matamala, Stefan Metzger, Leonardo Montagnani, Giacomo Nicolini, Thomas O'Halloran, Jean-Marc Ourcival, Matthias Peichl, Elise Pendall, Borja Ruiz Reverter, Marilyn Roland, Simone Sabbatini, Torsten Sachs, Marius Schmidt, Christopher R. Schwalm, Ankit Shekhar, Richard Silberstein, Maria Lucia Silveira, Donatella Spano, Torbern Tagesson, Gianluca Tramontana, Carlo Trotta, Fabio Turco, Timo Vesala, Caroline Vincke, Domenico Vitale, Enrique R. Vivoni, Yi Wang, William Woodgate, Enrico A. Yepez, Junhui Zhang, Donatella Zona, and Martin Jung
Biogeosciences, 21, 5079–5115, https://doi.org/10.5194/bg-21-5079-2024, https://doi.org/10.5194/bg-21-5079-2024, 2024
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Abdullah Bolek, Martin Heimann, and Mathias Göckede
Atmos. Meas. Tech., 17, 5619–5636, https://doi.org/10.5194/amt-17-5619-2024, https://doi.org/10.5194/amt-17-5619-2024, 2024
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Sandra Raab, Karel Castro-Morales, Anke Hildebrandt, Martin Heimann, Jorien Elisabeth Vonk, Nikita Zimov, and Mathias Goeckede
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Peter Stimmler, Mathias Goeckede, Bo Elberling, Susan Natali, Peter Kuhry, Nia Perron, Fabrice Lacroix, Gustaf Hugelius, Oliver Sonnentag, Jens Strauss, Christina Minions, Michael Sommer, and Jörg Schaller
Earth Syst. Sci. Data, 15, 1059–1075, https://doi.org/10.5194/essd-15-1059-2023, https://doi.org/10.5194/essd-15-1059-2023, 2023
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Arctic soils store large amounts of carbon and nutrients. The availability of nutrients, such as silicon, calcium, iron, aluminum, phosphorus, and amorphous silica, is crucial to understand future carbon fluxes in the Arctic. Here, we provide, for the first time, a unique dataset of the availability of the abovementioned nutrients for the different soil layers, including the currently frozen permafrost layer. We relate these data to several geographical and geological parameters.
Karel Castro-Morales, Anna Canning, Sophie Arzberger, Will A. Overholt, Kirsten Küsel, Olaf Kolle, Mathias Göckede, Nikita Zimov, and Arne Körtzinger
Biogeosciences, 19, 5059–5077, https://doi.org/10.5194/bg-19-5059-2022, https://doi.org/10.5194/bg-19-5059-2022, 2022
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Permafrost thaw releases methane that can be emitted into the atmosphere or transported by Arctic rivers. Methane measurements are lacking in large Arctic river regions. In the Kolyma River (northeast Siberia), we measured dissolved methane to map its distribution with great spatial detail. The river’s edge and river junctions had the highest methane concentrations compared to other river areas. Microbial communities in the river showed that the river’s methane likely is from the adjacent land.
Wolfgang Fischer, Christoph K. Thomas, Nikita Zimov, and Mathias Göckede
Biogeosciences, 19, 1611–1633, https://doi.org/10.5194/bg-19-1611-2022, https://doi.org/10.5194/bg-19-1611-2022, 2022
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Arctic permafrost ecosystems may release large amounts of carbon under warmer future climates and may therefore accelerate global climate change. Our study investigated how long-term grazing by large animals influenced ecosystem characteristics and carbon budgets at a Siberian permafrost site. Our results demonstrate that such management can contribute to stabilizing ecosystems to keep carbon in the ground, particularly through drying soils and reducing methane emissions.
Martijn M. T. A. Pallandt, Jitendra Kumar, Marguerite Mauritz, Edward A. G. Schuur, Anna-Maria Virkkala, Gerardo Celis, Forrest M. Hoffman, and Mathias Göckede
Biogeosciences, 19, 559–583, https://doi.org/10.5194/bg-19-559-2022, https://doi.org/10.5194/bg-19-559-2022, 2022
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Thawing of Arctic permafrost soils could trigger the release of vast amounts of carbon to the atmosphere, thus enhancing climate change. Our study investigated how well the current network of eddy covariance sites to monitor greenhouse gas exchange at local scales captures pan-Arctic flux patterns. We identified large coverage gaps, e.g., in Siberia, but also demonstrated that a targeted addition of relatively few sites can significantly improve network performance.
Anna-Maria Virkkala, Susan M. Natali, Brendan M. Rogers, Jennifer D. Watts, Kathleen Savage, Sara June Connon, Marguerite Mauritz, Edward A. G. Schuur, Darcy Peter, Christina Minions, Julia Nojeim, Roisin Commane, Craig A. Emmerton, Mathias Goeckede, Manuel Helbig, David Holl, Hiroki Iwata, Hideki Kobayashi, Pasi Kolari, Efrén López-Blanco, Maija E. Marushchak, Mikhail Mastepanov, Lutz Merbold, Frans-Jan W. Parmentier, Matthias Peichl, Torsten Sachs, Oliver Sonnentag, Masahito Ueyama, Carolina Voigt, Mika Aurela, Julia Boike, Gerardo Celis, Namyi Chae, Torben R. Christensen, M. Syndonia Bret-Harte, Sigrid Dengel, Han Dolman, Colin W. Edgar, Bo Elberling, Eugenie Euskirchen, Achim Grelle, Juha Hatakka, Elyn Humphreys, Järvi Järveoja, Ayumi Kotani, Lars Kutzbach, Tuomas Laurila, Annalea Lohila, Ivan Mammarella, Yojiro Matsuura, Gesa Meyer, Mats B. Nilsson, Steven F. Oberbauer, Sang-Jong Park, Roman Petrov, Anatoly S. Prokushkin, Christopher Schulze, Vincent L. St. Louis, Eeva-Stiina Tuittila, Juha-Pekka Tuovinen, William Quinton, Andrej Varlagin, Donatella Zona, and Viacheslav I. Zyryanov
Earth Syst. Sci. Data, 14, 179–208, https://doi.org/10.5194/essd-14-179-2022, https://doi.org/10.5194/essd-14-179-2022, 2022
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The effects of climate warming on carbon cycling across the Arctic–boreal zone (ABZ) remain poorly understood due to the relatively limited distribution of ABZ flux sites. Fortunately, this flux network is constantly increasing, but new measurements are published in various platforms, making it challenging to understand the ABZ carbon cycle as a whole. Here, we compiled a new database of Arctic–boreal CO2 fluxes to help facilitate large-scale assessments of the ABZ carbon cycle.
Torben Windirsch, Guido Grosse, Mathias Ulrich, Bruce C. Forbes, Mathias Göckede, Juliane Wolter, Marc Macias-Fauria, Johan Olofsson, Nikita Zimov, and Jens Strauss
Biogeosciences Discuss., https://doi.org/10.5194/bg-2021-227, https://doi.org/10.5194/bg-2021-227, 2021
Revised manuscript not accepted
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With global warming, permafrost thaw and associated carbon release are of increasing importance. We examined how large herbivorous animals affect Arctic landscapes and how they might contribute to reduction of these emissions. We show that over a short timespan of roughly 25 years, these animals have already changed the vegetation and landscape. On pastures in a permafrost area in Siberia we found smaller thaw depth and higher carbon content than in surrounding non-pasture areas.
Kyle B. Delwiche, Sara Helen Knox, Avni Malhotra, Etienne Fluet-Chouinard, Gavin McNicol, Sarah Feron, Zutao Ouyang, Dario Papale, Carlo Trotta, Eleonora Canfora, You-Wei Cheah, Danielle Christianson, Ma. Carmelita R. Alberto, Pavel Alekseychik, Mika Aurela, Dennis Baldocchi, Sheel Bansal, David P. Billesbach, Gil Bohrer, Rosvel Bracho, Nina Buchmann, David I. Campbell, Gerardo Celis, Jiquan Chen, Weinan Chen, Housen Chu, Higo J. Dalmagro, Sigrid Dengel, Ankur R. Desai, Matteo Detto, Han Dolman, Elke Eichelmann, Eugenie Euskirchen, Daniela Famulari, Kathrin Fuchs, Mathias Goeckede, Sébastien Gogo, Mangaliso J. Gondwe, Jordan P. Goodrich, Pia Gottschalk, Scott L. Graham, Martin Heimann, Manuel Helbig, Carole Helfter, Kyle S. Hemes, Takashi Hirano, David Hollinger, Lukas Hörtnagl, Hiroki Iwata, Adrien Jacotot, Gerald Jurasinski, Minseok Kang, Kuno Kasak, John King, Janina Klatt, Franziska Koebsch, Ken W. Krauss, Derrick Y. F. Lai, Annalea Lohila, Ivan Mammarella, Luca Belelli Marchesini, Giovanni Manca, Jaclyn Hatala Matthes, Trofim Maximov, Lutz Merbold, Bhaskar Mitra, Timothy H. Morin, Eiko Nemitz, Mats B. Nilsson, Shuli Niu, Walter C. Oechel, Patricia Y. Oikawa, Keisuke Ono, Matthias Peichl, Olli Peltola, Michele L. Reba, Andrew D. Richardson, William Riley, Benjamin R. K. Runkle, Youngryel Ryu, Torsten Sachs, Ayaka Sakabe, Camilo Rey Sanchez, Edward A. Schuur, Karina V. R. Schäfer, Oliver Sonnentag, Jed P. Sparks, Ellen Stuart-Haëntjens, Cove Sturtevant, Ryan C. Sullivan, Daphne J. Szutu, Jonathan E. Thom, Margaret S. Torn, Eeva-Stiina Tuittila, Jessica Turner, Masahito Ueyama, Alex C. Valach, Rodrigo Vargas, Andrej Varlagin, Alma Vazquez-Lule, Joseph G. Verfaillie, Timo Vesala, George L. Vourlitis, Eric J. Ward, Christian Wille, Georg Wohlfahrt, Guan Xhuan Wong, Zhen Zhang, Donatella Zona, Lisamarie Windham-Myers, Benjamin Poulter, and Robert B. Jackson
Earth Syst. Sci. Data, 13, 3607–3689, https://doi.org/10.5194/essd-13-3607-2021, https://doi.org/10.5194/essd-13-3607-2021, 2021
Short summary
Short summary
Methane is an important greenhouse gas, yet we lack knowledge about its global emissions and drivers. We present FLUXNET-CH4, a new global collection of methane measurements and a critical resource for the research community. We use FLUXNET-CH4 data to quantify the seasonality of methane emissions from freshwater wetlands, finding that methane seasonality varies strongly with latitude. Our new database and analysis will improve wetland model accuracy and inform greenhouse gas budgets.
Cited articles
Aubinet, M., Vesala, T., and Papale, D. (Eds.): Eddy Covariance: A Practical Guide to Measurement and Data Analysis, Springer Netherlands, Dordrecht, ISBN 978-94-007-2350-4 978-94-007-2351-1, https://doi.org/10.1007/978-94-007-2351-1, 2012. a
Baldocchi, D.: “Breathing” of the Terrestrial Biosphere: Lessons Learned from a Global Network of Carbon Dioxide Flux Measurement Systems, Austr. J. Bot., 56, 1, https://doi.org/10.1071/BT07151, 2008. a
Businger, J. A., Wyngaard, J. C., Izumi, Y., and Bradley, E. F.: Flux-Profile Relationships in the Atmospheric Surface Layer, J. Atmos. Sci., 28, 181–189, https://doi.org/10.1175/1520-0469(1971)028<0181:FPRITA>2.0.CO;2, 1971. a
Cai, X., Chen, J., and Desjardins, R. L.: Flux Footprints in the Convective Boundary Layer: Large-Eddy Simulation and Lagrangian Stochastic Modelling, Bound.-Lay. Meteorol., 137, 31–47, https://doi.org/10.1007/s10546-010-9519-7, 2010. a
Crawford, B. and Christen, A.: Spatial Source Attribution of Measured Urban Eddy Covariance CO2 Fluxes, Theor. Appl. Climatol., 119, 733–755, https://doi.org/10.1007/s00704-014-1124-0, 2015. a
Dyer, A. J.: A Review of Flux-Profile Relationships, Bound.-Lay. Meteorol., 7, 363–372, https://doi.org/10.1007/BF00240838, 1974. a
Evans, L. C.: Partial Differential Equations, American Mathematical Soc., ISBN 978-0-8218-4974-3, 2010. a
Göckede, M., Foken, T., Aubinet, M., Aurela, M., Banza, J., Bernhofer, C., Bonnefond, J. M., Brunet, Y., Carrara, A., Clement, R., Dellwik, E., Elbers, J., Eugster, W., Fuhrer, J., Granier, A., Grünwald, T., Heinesch, B., Janssens, I. A., Knohl, A., Koeble, R., Laurila, T., Longdoz, B., Manca, G., Marek, M., Markkanen, T., Mateus, J., Matteucci, G., Mauder, M., Migliavacca, M., Minerbi, S., Moncrieff, J., Montagnani, L., Moors, E., Ourcival, J.-M., Papale, D., Pereira, J., Pilegaard, K., Pita, G., Rambal, S., Rebmann, C., Rodrigues, A., Rotenberg, E., Sanz, M. J., Sedlak, P., Seufert, G., Siebicke, L., Soussana, J. F., Valentini, R., Vesala, T., Verbeeck, H., and Yakir, D.: Quality control of CarboEurope flux data – Part 1: Coupling footprint analyses with flux data quality assessment to evaluate sites in forest ecosystems, Biogeosciences, 5, 433–450, https://doi.org/10.5194/bg-5-433-2008, 2008. a
Hochbruck, M. and Ostermann, A.: Exponential Integrators, Acta Numer., 19, 209–286, https://doi.org/10.1017/S0962492910000048, 2010. a, b
Hsieh, C.-I., Katul, G., and Chi, T.-W.: An Approximate Analytical Model for Footprint Estimation of Scalar Fluxes in Thermally Stratified Atmospheric Flows, Adv. Water Resour., 23, 765–772, https://doi.org/10.1016/S0309-1708(99)00042-1, 2000. a
Kljun, N., Rotach, M., and Schmid, H.: A Three-Dimensional Backward Lagrangian Footprint Model For A Wide Range Of Boundary-Layer Stratifications, Bounda.-Lay. Meteorol., 103, 205–226, https://doi.org/10.1023/A:1014556300021, 2002. a
Kljun, N., Calanca, P., Rotach, M. W., and Schmid, H. P.: A simple two-dimensional parameterisation for Flux Footprint Prediction (FFP), Geosci. Model Dev., 8, 3695–3713, https://doi.org/10.5194/gmd-8-3695-2015, 2015. a
Kormann, R. and Meixner, F. X.: An Analytical Footprint Model For Non-Neutral Stratification, Bound.-Lay. Meteorol., 99, 207–224, https://doi.org/10.1023/A:1018991015119, 2001. a, b, c, d
Krapez, J.-C. and Ky, G. A.: Semi-Analytical Footprint Model Compliant with Arbitrary Atmospheric Stratification: Application to Monin–Obukhov Profiles, Bound.-Lay. Meteorol., 187, 743–791, https://doi.org/10.1007/s10546-023-00793-2, 2023. a
Leclerc, M. Y. and Foken, T.: Footprints in Micrometeorology and Ecology, Springer, Berlin, Heidelberg, ISBN 978-3-642-54544-3 978-3-642-54545-0, https://doi.org/10.1007/978-3-642-54545-0, 2014. a
Lin, J.-S. and Hildemann, L. M.: A Generalized Mathematical Scheme to Analytically Solve the Atmospheric Diffusion Equation with Dry Deposition, Atmos. Environ., 31, 59–71, https://doi.org/10.1016/S1352-2310(96)00148-3, 1997. a
Lindfield, G. and Penny, J.: Numerical Methods: Using MATLAB, Academic Press, ISBN 978-0-12-812370-6, 2018. a
Monin, A. S. and Obukhov, A. M.: Basic laws of turbulent mixing in the surface layer of the atmosphere, Tr. Akad. Nauk SSSR Geophiz. Inst., 24, 163–187, 1954. a
Moreira, D. M., Tirabassi, T., and Carvalho, J. C.: Plume Dispersion Simulation in Low Wind Conditions in Stable and Convective Boundary Layers, Atmos. Environ., 39, 3643–3650, https://doi.org/10.1016/j.atmosenv.2005.03.004, 2005. a
Pasquill, F.: Some aspects of boundary layer description, Q. J. Roy. Meteor. Soc., 98, 469–494, https://doi.org/10.1002/qj.49709841702, 1972. a
Pirk, N., Aalstad, K., Mannerfelt, E. S., Clayer, F., De Wit, H., Christiansen, C. T., Althuizen, I., Lee, H., and Westermann, S.: Disaggregating the Carbon Exchange of Degrading Permafrost Peatlands Using Bayesian Deep Learning, Geophys. Res. Lett., 51, e2024GL109283, https://doi.org/10.1029/2024GL109283, 2024. a
Rey-Sanchez, C., Arias-Ortiz, A., Kasak, K., Chu, H., Szutu, D., Verfaillie, J., and Baldocchi, D.: Detecting Hot Spots of Methane Flux Using Footprint-Weighted Flux Maps, J. Geophys. Res.-Biogeo., 127, e2022JG006977, https://doi.org/10.1029/2022JG006977, 2022. a
Schlutow, M. and Chew, R.: BLDFM: The Boundary Layer Dispersion and Footprint Model, Zenodo [code], https://doi.org/10.5281/zenodo.15487243, 2025. a
Schlutow, M., Stacke, T., Doerffel, T., Smolarkiewicz, P. K., and Göckede, M.: Large Eddy Simulations of the Interaction Between the Atmospheric Boundary Layer and Degrading Arctic Permafrost, J. Geophys. Res.-Atmos., 129, e2024JD040794, https://doi.org/10.1029/2024JD040794, 2024. a
Schmid, H. P.: Footprint Modeling for Vegetation Atmosphere Exchange Studies: A Review and Perspective, Agr. Forest Meteorol., 113, 159–183, https://doi.org/10.1016/S0168-1923(02)00107-7, 2002. a
Schuepp, P. H., Leclerc, M. Y., MacPherson, J. I., and Desjardins, R. L.: Footprint Prediction of Scalar Fluxes from Analytical Solutions of the Diffusion Equation, Bound.-Lay. Meteorol., 50, 355–373, https://doi.org/10.1007/BF00120530, 1990. a
Schumann, U.: Subgrid Length-Scales for Large-Eddy Simulation of Stratified Turbulence, Theor. Comput. Fluid Dynam., 2, 279–290, https://doi.org/10.1007/BF00271468, 1991. a, b, c
Seinfeld, J. H. and Pandis, S. N.: Atmospheric Chemistry and Physics: From Air Pollution to Climate Change, John Wiley & Sons, ISBN 978-1-118-59136-9, 2012. a
Steinfeld, G., Raasch, S., and Markkanen, T.: Footprints in Homogeneously and Heterogeneously Driven Boundary Layers Derived from a Lagrangian Stochastic Particle Model Embedded into Large-Eddy Simulation, Bound.-Lay. Meteorol., 129, 225–248, https://doi.org/10.1007/s10546-008-9317-7, 2008. a
Stockie, J. M.: The Mathematics of Atmospheric Dispersion Modeling, SIAM Rev., 53, 349–372, https://doi.org/10.1137/10080991X, 2011. a, b
Stull, R. B. (Ed.): An Introduction to Boundary Layer Meteorology, Springer Netherlands, Dordrecht, ISBN 978-90-277-2769-5 978-94-009-3027-8, https://doi.org/10.1007/978-94-009-3027-8, 1988. a, b
Thomson, D. J.: Criteria for the Selection of Stochastic Models of Particle Trajectories in Turbulent Flows, J. Fluid Mech., 180, 529–556, https://doi.org/10.1017/S0022112087001940, 1987. a
Tuovinen, J.-P., Aurela, M., Hatakka, J., Räsänen, A., Virtanen, T., Mikola, J., Ivakhov, V., Kondratyev, V., and Laurila, T.: Interpreting eddy covariance data from heterogeneous Siberian tundra: land-cover-specific methane fluxes and spatial representativeness, Biogeosciences, 16, 255–274, https://doi.org/10.5194/bg-16-255-2019, 2019. a
Vesala, T., Kljun, N., Rannik, Ü., Rinne, J., Sogachev, A., Markkanen, T., Sabelfeld, K., Foken, Th., and Leclerc, M.: Flux and Concentration Footprint Modelling: State of the Art, Environ. Pollut., 152, 653–666, https://doi.org/10.1016/j.envpol.2007.06.070, 2008. a, b, c
Wang, W., Davis, K. J., Cook, B. D., Butler, M. P., and Ricciuto, D. M.: Decomposing CO2 Fluxes Measured over a Mixed Ecosystem at a Tall Tower and Extending to a Region: A Case Study, J. Geophys. Res.-Biogeo., 111, https://doi.org/10.1029/2005JG000093, 2006. a
Short summary
Understanding how greenhouse gases and pollutants move through the atmosphere is crucial. A new model, the Boundary Layer Dispersion and Footprint Model (BLDFM), tracks their movement. Unlike previous models, BLDFM uses a numerical approach without simplifying assumptions. It is flexible and can be used for climate impact studies and industrial emissions monitoring. Our testing and comparison results show BLDFM's potential as a valuable research tool.
Understanding how greenhouse gases and pollutants move through the atmosphere is crucial. A new...
