Articles | Volume 9, issue 12
https://doi.org/10.5194/gmd-9-4475-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/gmd-9-4475-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Development and technical paper
| 
16 Dec 2016
Development and technical paper |
| 16 Dec 2016
Improving the spatial resolution of air-quality modelling at a European scale – development and evaluation of the Air Quality Re-gridder Model (AQR v1.1)
Atmospheric Pollution Division, Research Centre for Energy,
Environment and Technology (CIEMAT), Madrid, 28040, Spain
Dept. Agricultural Chemistry and Analysis, Higher Technical School of
Agricultural Engineering, Technical University of Madrid, 28040, Spain
David Simpson
EMEP MSC-W, Norwegian Meteorological Institute, Oslo, 0313, Norway
Dept. Earth & Space Sciences, Chalmers University of Technology,
Gothenburg, 412 96, Sweden
Massimo Vieno
Centre for Ecology & Hydrology, Edinburgh Research Station,
Penicuik, EH26 0QB, UK
Related authors
Svetlana Tsyro, Wenche Aas, Augustin Colette, Camilla Andersson, Bertrand Bessagnet, Giancarlo Ciarelli, Florian Couvidat, Kees Cuvelier, Astrid Manders, Kathleen Mar, Mihaela Mircea, Noelia Otero, Maria-Teresa Pay, Valentin Raffort, Yelva Roustan, Mark R. Theobald, Marta G. Vivanco, Hilde Fagerli, Peter Wind, Gino Briganti, Andrea Cappelletti, Massimo D'Isidoro, and Mario Adani
Atmos. Chem. Phys., 22, 7207–7257, https://doi.org/10.5194/acp-22-7207-2022, https://doi.org/10.5194/acp-22-7207-2022, 2022
Short summary
Short summary
Particulate matter (PM) air pollution causes adverse health effects. In Europe, the emissions caused by anthropogenic activities have been reduced in the last decades. To assess the efficiency of emission reductions in improving air quality, we have studied the evolution of PM pollution in Europe. Simulations with six air quality models and observational data indicate a decrease in PM concentrations by 10 % to 30 % across Europe from 2000 to 2010, which is mainly a result of emission reductions.
Mark R. Theobald, Marta G. Vivanco, Wenche Aas, Camilla Andersson, Giancarlo Ciarelli, Florian Couvidat, Kees Cuvelier, Astrid Manders, Mihaela Mircea, Maria-Teresa Pay, Svetlana Tsyro, Mario Adani, Robert Bergström, Bertrand Bessagnet, Gino Briganti, Andrea Cappelletti, Massimo D'Isidoro, Hilde Fagerli, Kathleen Mar, Noelia Otero, Valentin Raffort, Yelva Roustan, Martijn Schaap, Peter Wind, and Augustin Colette
Atmos. Chem. Phys., 19, 379–405, https://doi.org/10.5194/acp-19-379-2019, https://doi.org/10.5194/acp-19-379-2019, 2019
Short summary
Short summary
Model estimates of the mean European wet deposition of nitrogen and sulfur for 1990 to 2010 were within 40 % of the observed values. As a result of systematic biases, the models were better at estimating relative trends for the periods 1990–2000 and 2000–2010 than the absolute trends. Although the predominantly decreasing trends were mostly due to emission reductions, they were partially offset by other factors (e.g. changes in precipitation) during the first period, but not the second.
Noelia Otero, Jana Sillmann, Kathleen A. Mar, Henning W. Rust, Sverre Solberg, Camilla Andersson, Magnuz Engardt, Robert Bergström, Bertrand Bessagnet, Augustin Colette, Florian Couvidat, Cournelius Cuvelier, Svetlana Tsyro, Hilde Fagerli, Martijn Schaap, Astrid Manders, Mihaela Mircea, Gino Briganti, Andrea Cappelletti, Mario Adani, Massimo D'Isidoro, María-Teresa Pay, Mark Theobald, Marta G. Vivanco, Peter Wind, Narendra Ojha, Valentin Raffort, and Tim Butler
Atmos. Chem. Phys., 18, 12269–12288, https://doi.org/10.5194/acp-18-12269-2018, https://doi.org/10.5194/acp-18-12269-2018, 2018
Short summary
Short summary
This paper evaluates the capability of air-quality models to capture the observed relationship between surface ozone concentrations and meteorology over Europe. The air-quality models tended to overestimate the influence of maximum temperature and surface solar radiation. None of the air-quality models captured the strength of the observed relationship between ozone and relative humidity appropriately, underestimating the effect of relative humidity, a key factor in the ozone removal processes.
Marta G. Vivanco, Mark R. Theobald, Héctor García-Gómez, Juan Luis Garrido, Marje Prank, Wenche Aas, Mario Adani, Ummugulsum Alyuz, Camilla Andersson, Roberto Bellasio, Bertrand Bessagnet, Roberto Bianconi, Johannes Bieser, Jørgen Brandt, Gino Briganti, Andrea Cappelletti, Gabriele Curci, Jesper H. Christensen, Augustin Colette, Florian Couvidat, Cornelis Cuvelier, Massimo D'Isidoro, Johannes Flemming, Andrea Fraser, Camilla Geels, Kaj M. Hansen, Christian Hogrefe, Ulas Im, Oriol Jorba, Nutthida Kitwiroon, Astrid Manders, Mihaela Mircea, Noelia Otero, Maria-Teresa Pay, Luca Pozzoli, Efisio Solazzo, Svetlana Tsyro, Alper Unal, Peter Wind, and Stefano Galmarini
Atmos. Chem. Phys., 18, 10199–10218, https://doi.org/10.5194/acp-18-10199-2018, https://doi.org/10.5194/acp-18-10199-2018, 2018
Short summary
Short summary
European wet and dry atmospheric deposition of N and S estimated by 14 air quality models was found to vary substantially. An ensemble of models meeting acceptability criteria was used to estimate the exceedances of the critical loads for N in habitats within the Natura 2000 network, as well as their lower and upper limits. Scenarios with 20 % emission reductions in different regions of the world showed that European emissions are responsible for most of the N and S deposition in Europe.
Per Erik Karlsson, Patrick Büker, Sam Bland, David Simpson, Katrina Sharps, Felicity Hayes, and Lisa Emberson
EGUsphere, https://doi.org/10.5194/egusphere-2024-3742, https://doi.org/10.5194/egusphere-2024-3742, 2024
Short summary
Short summary
Stomatal ozone uptake and the negative impacts on forest growth rates were estimated for European forests. This was translated to annual increments in the forest living biomass carbon stocks, with and without ozone exposure. In the absence of O3 exposure, European forest growth rates would on average increase by 9 %, but the sequestration to the living biomass carbon stocks would increase by 31 %, since the sequestration depends on the difference between growth and harvest rates.
Augustin Colette, Gaëlle Collin, François Besson, Etienne Blot, Vincent Guidard, Frederik Meleux, Adrien Royer, Valentin Petiot, Claire Miller, Oihana Fermond, Alizé Jeant, Mario Adani, Joaquim Arteta, Anna Benedictow, Robert Bergström, Dene Bowdalo, Jorgen Brandt, Gino Briganti, Ana C. Carvalho, Jesper Heile Christensen, Florian Couvidat, Ilia D’Elia, Massimo D’Isidoro, Hugo Denier van der Gon, Gaël Descombes, Enza Di Tomaso, John Douros, Jeronimo Escribano, Henk Eskes, Hilde Fagerli, Yalda Fatahi, Johannes Flemming, Elmar Friese, Lise Frohn, Michael Gauss, Camilla Geels, Guido Guarnieri, Marc Guevara, Antoine Guion, Jonathan Guth, Risto Hänninen, Kaj Hansen, Ulas Im, Ruud Janssen, Marine Jeoffrion, Mathieu Joly, Luke Jones, Oriol Jorba, Evgeni Kadantsev, Michael Kahnert, Jacek W. Kaminski, Rostislav Kouznetsov, Richard Kranenburg, Jeroen Kuenen, Anne Caroline Lange, Joachim Langner, Victor Lannuque, Francesca Macchia, Astrid Manders, Mihaela Mircea, Agnes Nyiri, Miriam Olid, Carlos Pérez García-Pando, Yuliia Palamarchuk, Antonio Piersanti, Blandine Raux, Miha Razinger, Lennard Robertson, Arjo Segers, Martijn Schaap, Pilvi Siljamo, David Simpson, Mikhail Sofiev, Anders Stangel, Joanna Struzewska, Carles Tena, Renske Timmermans, Thanos Tsikerdekis, Svetlana Tsyro, Svyatoslav Tyuryakov, Anthony Ung, Andreas Uppstu, Alvaro Valdebenito, Peter van Velthoven, Lina Vitali, Zhuyun Ye, Vincent-Henri Peuch, and Laurence Rouïl
EGUsphere, https://doi.org/10.5194/egusphere-2024-3744, https://doi.org/10.5194/egusphere-2024-3744, 2024
Short summary
Short summary
The Copernicus Atmosphere Monitoring Service – Regional Production delivers daily forecasts, analyses, and reanalyses of air quality in Europe. The Service relies on a distributed modelling production by eleven leading European modelling teams following stringent requirements with an operational design which has no equivalent in the world. All the products are full, free, open and quality assured and disseminated with a high level of reliability.
Yao Ge, Sverre Solberg, Mathew R. Heal, Stefan Reimann, Willem van Caspel, Bryan Hellack, Thérèse Salameh, and David Simpson
Atmos. Chem. Phys., 24, 7699–7729, https://doi.org/10.5194/acp-24-7699-2024, https://doi.org/10.5194/acp-24-7699-2024, 2024
Short summary
Short summary
Atmospheric volatile organic compounds (VOCs) constitute many species, acting as precursors to ozone and aerosol. Given the uncertainties in VOC emissions, lack of evaluation studies, and recent changes in emissions, this work adapts the EMEP MSC-W to evaluate emission inventories in Europe. We focus on the varying agreement between modelled and measured VOCs across different species and underscore potential inaccuracies in total and sector-specific emission estimates.
Lily Gouldsbrough, Ryan Hossaini, Emma Eastoe, Paul J. Young, and Massimo Vieno
Atmos. Chem. Phys., 24, 3163–3196, https://doi.org/10.5194/acp-24-3163-2024, https://doi.org/10.5194/acp-24-3163-2024, 2024
Short summary
Short summary
High-resolution spatial fields of surface ozone are used to understand spikes in ozone concentration and predict their impact on public health. Such fields are routinely output from complex mathematical models for atmospheric conditions. These outputs are on a coarse spatial resolution and the highest concentrations tend to be biased. Using a novel data-driven machine learning methodology, we show how such output can be corrected to produce fields with both lower bias and higher resolution.
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
Short summary
We discuss carbonaceous aerosol (CA) observed at the high Arctic Zeppelin Observatory (2017 to 2020). We find that organic aerosol is a significant fraction of the Arctic aerosol, though less than sea salt aerosol and mineral dust, as well as non-sea-salt sulfate, originating mainly from anthropogenic sources in winter and from natural sources in summer, emphasizing the importance of wildfires for biogenic secondary organic aerosol and primary biological aerosol particles observed in the Arctic.
Willem E. van Caspel, David Simpson, Jan Eiof Jonson, Anna M. K. Benedictow, Yao Ge, Alcide di Sarra, Giandomenico Pace, Massimo Vieno, Hannah L. Walker, and Mathew R. Heal
Geosci. Model Dev., 16, 7433–7459, https://doi.org/10.5194/gmd-16-7433-2023, https://doi.org/10.5194/gmd-16-7433-2023, 2023
Short summary
Short summary
Radiation coming from the sun is essential to atmospheric chemistry, driving the breakup, or photodissociation, of atmospheric molecules. This in turn affects the chemical composition and reactivity of the atmosphere. The representation of photodissociation effects is therefore essential in atmospheric chemistry modeling. One such model is the EMEP MSC-W model, for which a new way of calculating the photodissociation rates is tested and evaluated in this paper.
Gemma Purser, Mathew R. Heal, Edward J. Carnell, Stephen Bathgate, Julia Drewer, James I. L. Morison, and Massimo Vieno
Atmos. Chem. Phys., 23, 13713–13733, https://doi.org/10.5194/acp-23-13713-2023, https://doi.org/10.5194/acp-23-13713-2023, 2023
Short summary
Short summary
Forest expansion is a ″net-zero“ pathway, but change in land cover alters air quality in many ways. This study combines tree planting suitability data with UK measured emissions of biogenic volatile organic compounds to simulate spatial and temporal changes in atmospheric composition for planting scenarios of four species. Decreases in fine particulate matter are relatively larger than increases in ozone, which may indicate a net benefit of tree planting on human health aspects of air quality.
Yao Ge, Massimo Vieno, David S. Stevenson, Peter Wind, and Mathew R. Heal
Atmos. Chem. Phys., 23, 6083–6112, https://doi.org/10.5194/acp-23-6083-2023, https://doi.org/10.5194/acp-23-6083-2023, 2023
Short summary
Short summary
The sensitivity of fine particles and reactive N and S species to reductions in precursor emissions is investigated using the EMEP MSC-W (European Monitoring and Evaluation Programme Meteorological Synthesizing Centre – West) atmospheric chemistry transport model. This study reveals that the individual emissions reduction has multiple and geographically varying co-benefits and small disbenefits on different species, demonstrating the importance of prioritizing regional emissions controls.
Yao Ge, Massimo Vieno, David S. Stevenson, Peter Wind, and Mathew R. Heal
Atmos. Chem. Phys., 22, 8343–8368, https://doi.org/10.5194/acp-22-8343-2022, https://doi.org/10.5194/acp-22-8343-2022, 2022
Short summary
Short summary
Reactive N and S gases and aerosols are critical determinants of air quality. We report a comprehensive analysis of the concentrations, wet and dry deposition, fluxes, and lifetimes of these species globally as well as for 10 world regions. We used the EMEP MSC-W model coupled with WRF meteorology and 2015 global emissions. Our work demonstrates the substantial regional variation in these quantities and the need for modelling to simulate atmospheric responses to precursor emissions.
Svetlana Tsyro, Wenche Aas, Augustin Colette, Camilla Andersson, Bertrand Bessagnet, Giancarlo Ciarelli, Florian Couvidat, Kees Cuvelier, Astrid Manders, Kathleen Mar, Mihaela Mircea, Noelia Otero, Maria-Teresa Pay, Valentin Raffort, Yelva Roustan, Mark R. Theobald, Marta G. Vivanco, Hilde Fagerli, Peter Wind, Gino Briganti, Andrea Cappelletti, Massimo D'Isidoro, and Mario Adani
Atmos. Chem. Phys., 22, 7207–7257, https://doi.org/10.5194/acp-22-7207-2022, https://doi.org/10.5194/acp-22-7207-2022, 2022
Short summary
Short summary
Particulate matter (PM) air pollution causes adverse health effects. In Europe, the emissions caused by anthropogenic activities have been reduced in the last decades. To assess the efficiency of emission reductions in improving air quality, we have studied the evolution of PM pollution in Europe. Simulations with six air quality models and observational data indicate a decrease in PM concentrations by 10 % to 30 % across Europe from 2000 to 2010, which is mainly a result of emission reductions.
Katerina Sindelarova, Jana Markova, David Simpson, Peter Huszar, Jan Karlicky, Sabine Darras, and Claire Granier
Earth Syst. Sci. Data, 14, 251–270, https://doi.org/10.5194/essd-14-251-2022, https://doi.org/10.5194/essd-14-251-2022, 2022
Short summary
Short summary
Three new datasets of global emissions of biogenic volatile organic compounds (BVOCs) emitted into the atmosphere from terrestrial vegetation were developed for air quality modelling using the Model of Emissions of Gases and Aerosols from Nature (MEGANv2.1) driven by European Centre for Medium-Range Weather Forecasts meteorological reanalyses for the years 2000–2019. The datasets include updates of the isoprene emission factors in Europe and study the impact of land cover change on emissions.
Yao Ge, Mathew R. Heal, David S. Stevenson, Peter Wind, and Massimo Vieno
Geosci. Model Dev., 14, 7021–7046, https://doi.org/10.5194/gmd-14-7021-2021, https://doi.org/10.5194/gmd-14-7021-2021, 2021
Short summary
Short summary
This study reports the first evaluation of the global EMEP MSC-W ACTM driven by WRF meteorology, with a focus on surface concentrations and wet deposition of reactive N and S species. The model–measurement comparison is conducted both spatially and temporally, covering 10 monitoring networks worldwide. The statistics from the comprehensive evaluations presented in this study support the application of this model framework for global analysis of the budgets and fluxes of reactive N and SIA.
David Simpson and Sabine Darras
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2021-221, https://doi.org/10.5194/essd-2021-221, 2021
Manuscript not accepted for further review
Short summary
Short summary
We present a dataset of global soil NO emissions suitable for atmospheric chemistry modelling. Data are provided globally at 0.5° × 0.5° degrees horizontal resolution, and with monthly time resolution over the period 2000–2018. This paper presents the emission algorithms and their data-sources, some comments on the availability of soil NO emissions in other inventories (and how to avoid double-counting), and finally some preliminary modelling results and comparison with observed data.
Karl Espen Yttri, Francesco Canonaco, Sabine Eckhardt, Nikolaos Evangeliou, Markus Fiebig, Hans Gundersen, Anne-Gunn Hjellbrekke, Cathrine Lund Myhre, Stephen Matthew Platt, André S. H. Prévôt, David Simpson, Sverre Solberg, Jason Surratt, Kjetil Tørseth, Hilde Uggerud, Marit Vadset, Xin Wan, and Wenche Aas
Atmos. Chem. Phys., 21, 7149–7170, https://doi.org/10.5194/acp-21-7149-2021, https://doi.org/10.5194/acp-21-7149-2021, 2021
Short summary
Short summary
Carbonaceous aerosol sources and trends were studied at the Birkenes Observatory. A large decrease in elemental carbon (EC; 2001–2018) and a smaller decline in levoglucosan (2008–2018) suggest that organic carbon (OC)/EC from traffic/industry is decreasing, whereas the abatement of OC/EC from biomass burning has been less successful. Positive matrix factorization apportioned 72 % of EC to fossil fuel sources and 53 % (PM2.5) and 78 % (PM10–2.5) of OC to biogenic sources.
David Simpson, Robert Bergström, Alan Briolat, Hannah Imhof, John Johansson, Michael Priestley, and Alvaro Valdebenito
Geosci. Model Dev., 13, 6447–6465, https://doi.org/10.5194/gmd-13-6447-2020, https://doi.org/10.5194/gmd-13-6447-2020, 2020
Short summary
Short summary
This paper outlines the structure and usage of the GenChem system, which includes a chemical pre-processor (GenChem.py) and a simple box model (boxChem). GenChem provides scripts and input files for converting chemical equations into differential form for use in atmospheric chemical transport models (CTMs) and/or the boxChem system. Although GenChem is primarily intended for users of the EMEP MSC-W CTM and related systems, boxChem can be run as a stand-alone chemical solver.
Christopher P. O. Reyer, Ramiro Silveyra Gonzalez, Klara Dolos, Florian Hartig, Ylva Hauf, Matthias Noack, Petra Lasch-Born, Thomas Rötzer, Hans Pretzsch, Henning Meesenburg, Stefan Fleck, Markus Wagner, Andreas Bolte, Tanja G. M. Sanders, Pasi Kolari, Annikki Mäkelä, Timo Vesala, Ivan Mammarella, Jukka Pumpanen, Alessio Collalti, Carlo Trotta, Giorgio Matteucci, Ettore D'Andrea, Lenka Foltýnová, Jan Krejza, Andreas Ibrom, Kim Pilegaard, Denis Loustau, Jean-Marc Bonnefond, Paul Berbigier, Delphine Picart, Sébastien Lafont, Michael Dietze, David Cameron, Massimo Vieno, Hanqin Tian, Alicia Palacios-Orueta, Victor Cicuendez, Laura Recuero, Klaus Wiese, Matthias Büchner, Stefan Lange, Jan Volkholz, Hyungjun Kim, Joanna A. Horemans, Friedrich Bohn, Jörg Steinkamp, Alexander Chikalanov, Graham P. Weedon, Justin Sheffield, Flurin Babst, Iliusi Vega del Valle, Felicitas Suckow, Simon Martel, Mats Mahnken, Martin Gutsch, and Katja Frieler
Earth Syst. Sci. Data, 12, 1295–1320, https://doi.org/10.5194/essd-12-1295-2020, https://doi.org/10.5194/essd-12-1295-2020, 2020
Short summary
Short summary
Process-based vegetation models are widely used to predict local and global ecosystem dynamics and climate change impacts. Due to their complexity, they require careful parameterization and evaluation to ensure that projections are accurate and reliable. The PROFOUND Database provides a wide range of empirical data to calibrate and evaluate vegetation models that simulate climate impacts at the forest stand scale to support systematic model intercomparisons and model development in Europe.
Chris R. Flechard, Andreas Ibrom, Ute M. Skiba, Wim de Vries, Marcel van Oijen, David R. Cameron, Nancy B. Dise, Janne F. J. Korhonen, Nina Buchmann, Arnaud Legout, David Simpson, Maria J. Sanz, Marc Aubinet, Denis Loustau, Leonardo Montagnani, Johan Neirynck, Ivan A. Janssens, Mari Pihlatie, Ralf Kiese, Jan Siemens, André-Jean Francez, Jürgen Augustin, Andrej Varlagin, Janusz Olejnik, Radosław Juszczak, Mika Aurela, Daniel Berveiller, Bogdan H. Chojnicki, Ulrich Dämmgen, Nicolas Delpierre, Vesna Djuricic, Julia Drewer, Eric Dufrêne, Werner Eugster, Yannick Fauvel, David Fowler, Arnoud Frumau, André Granier, Patrick Gross, Yannick Hamon, Carole Helfter, Arjan Hensen, László Horváth, Barbara Kitzler, Bart Kruijt, Werner L. Kutsch, Raquel Lobo-do-Vale, Annalea Lohila, Bernard Longdoz, Michal V. Marek, Giorgio Matteucci, Marta Mitosinkova, Virginie Moreaux, Albrecht Neftel, Jean-Marc Ourcival, Kim Pilegaard, Gabriel Pita, Francisco Sanz, Jan K. Schjoerring, Maria-Teresa Sebastià, Y. Sim Tang, Hilde Uggerud, Marek Urbaniak, Netty van Dijk, Timo Vesala, Sonja Vidic, Caroline Vincke, Tamás Weidinger, Sophie Zechmeister-Boltenstern, Klaus Butterbach-Bahl, Eiko Nemitz, and Mark A. Sutton
Biogeosciences, 17, 1583–1620, https://doi.org/10.5194/bg-17-1583-2020, https://doi.org/10.5194/bg-17-1583-2020, 2020
Short summary
Short summary
Experimental evidence from a network of 40 monitoring sites in Europe suggests that atmospheric nitrogen deposition to forests and other semi-natural vegetation impacts the carbon sequestration rates in ecosystems, as well as the net greenhouse gas balance including other greenhouse gases such as nitrous oxide and methane. Excess nitrogen deposition in polluted areas also leads to other environmental impacts such as nitrogen leaching to groundwater and other pollutant gaseous emissions.
Karl Espen Yttri, David Simpson, Robert Bergström, Gyula Kiss, Sönke Szidat, Darius Ceburnis, Sabine Eckhardt, Christoph Hueglin, Jacob Klenø Nøjgaard, Cinzia Perrino, Ignazio Pisso, Andre Stephan Henry Prevot, Jean-Philippe Putaud, Gerald Spindler, Milan Vana, Yan-Lin Zhang, and Wenche Aas
Atmos. Chem. Phys., 19, 4211–4233, https://doi.org/10.5194/acp-19-4211-2019, https://doi.org/10.5194/acp-19-4211-2019, 2019
Short summary
Short summary
Carbonaceous aerosols from natural sources were abundant regardless of season. Residential wood burning (RWB) emissions were occasionally equally as large as or larger than of fossil-fuel sources, depending on season and region. RWB emissions are poorly constrained; thus emissions inventories need improvement. Harmonizing emission factors between countries is likely the most important step to improve model calculations for biomass burning emissions and European PM2.5 concentrations in general.
Carole Helfter, Neil Mullinger, Massimo Vieno, Simon O'Doherty, Michel Ramonet, Paul I. Palmer, and Eiko Nemitz
Atmos. Chem. Phys., 19, 3043–3063, https://doi.org/10.5194/acp-19-3043-2019, https://doi.org/10.5194/acp-19-3043-2019, 2019
Short summary
Short summary
We present a novel approach to estimate the annual budgets of carbon dioxide (881.0 ± 128.5 Tg) and methane (2.55 ± 0.48 Tg) of the British Isles from shipborne measurements taken over a 3-year period (2015–2017). This study brings independent verification of the emission budgets estimated using alternative products and investigates the seasonality of these emissions, which is usually not possible.
Ksenia Aleksankina, Stefan Reis, Massimo Vieno, and Mathew R. Heal
Atmos. Chem. Phys., 19, 2881–2898, https://doi.org/10.5194/acp-19-2881-2019, https://doi.org/10.5194/acp-19-2881-2019, 2019
Short summary
Short summary
Atmospheric chemistry transport models are widely used to underpin policies to mitigate the detrimental effects of air pollution on human health and ecosystems. Understanding the level of confidence in model predictions is thus vital. We present a comprehensive approach for uncertainty assessment and global variance-based sensitivity analysis to propagate uncertainty from model input data and identify the extent to which uncertainty in different emissions drives the model output uncertainty.
Mark R. Theobald, Marta G. Vivanco, Wenche Aas, Camilla Andersson, Giancarlo Ciarelli, Florian Couvidat, Kees Cuvelier, Astrid Manders, Mihaela Mircea, Maria-Teresa Pay, Svetlana Tsyro, Mario Adani, Robert Bergström, Bertrand Bessagnet, Gino Briganti, Andrea Cappelletti, Massimo D'Isidoro, Hilde Fagerli, Kathleen Mar, Noelia Otero, Valentin Raffort, Yelva Roustan, Martijn Schaap, Peter Wind, and Augustin Colette
Atmos. Chem. Phys., 19, 379–405, https://doi.org/10.5194/acp-19-379-2019, https://doi.org/10.5194/acp-19-379-2019, 2019
Short summary
Short summary
Model estimates of the mean European wet deposition of nitrogen and sulfur for 1990 to 2010 were within 40 % of the observed values. As a result of systematic biases, the models were better at estimating relative trends for the periods 1990–2000 and 2000–2010 than the absolute trends. Although the predominantly decreasing trends were mostly due to emission reductions, they were partially offset by other factors (e.g. changes in precipitation) during the first period, but not the second.
Michael Le Breton, Åsa M. Hallquist, Ravi Kant Pathak, David Simpson, Yujue Wang, John Johansson, Jing Zheng, Yudong Yang, Dongjie Shang, Haichao Wang, Qianyun Liu, Chak Chan, Tao Wang, Thomas J. Bannan, Michael Priestley, Carl J. Percival, Dudley E. Shallcross, Keding Lu, Song Guo, Min Hu, and Mattias Hallquist
Atmos. Chem. Phys., 18, 13013–13030, https://doi.org/10.5194/acp-18-13013-2018, https://doi.org/10.5194/acp-18-13013-2018, 2018
Short summary
Short summary
We apply state-of-the-art chemical characterization to determine the chloride radical production in Beijing via measurement of inorganic halogens at a semi-rural site. The high concentration of inorganic halogens, namely nitryl chloride, enables the production of chlorinated volatile organic compounds which are measured in both the gas and particle phases simultaneously. This enables the secondary production of aerosols via chlorine oxidation to be directly observed in ambient air.
Noelia Otero, Jana Sillmann, Kathleen A. Mar, Henning W. Rust, Sverre Solberg, Camilla Andersson, Magnuz Engardt, Robert Bergström, Bertrand Bessagnet, Augustin Colette, Florian Couvidat, Cournelius Cuvelier, Svetlana Tsyro, Hilde Fagerli, Martijn Schaap, Astrid Manders, Mihaela Mircea, Gino Briganti, Andrea Cappelletti, Mario Adani, Massimo D'Isidoro, María-Teresa Pay, Mark Theobald, Marta G. Vivanco, Peter Wind, Narendra Ojha, Valentin Raffort, and Tim Butler
Atmos. Chem. Phys., 18, 12269–12288, https://doi.org/10.5194/acp-18-12269-2018, https://doi.org/10.5194/acp-18-12269-2018, 2018
Short summary
Short summary
This paper evaluates the capability of air-quality models to capture the observed relationship between surface ozone concentrations and meteorology over Europe. The air-quality models tended to overestimate the influence of maximum temperature and surface solar radiation. None of the air-quality models captured the strength of the observed relationship between ozone and relative humidity appropriately, underestimating the effect of relative humidity, a key factor in the ozone removal processes.
Christina Hood, Ian MacKenzie, Jenny Stocker, Kate Johnson, David Carruthers, Massimo Vieno, and Ruth Doherty
Atmos. Chem. Phys., 18, 11221–11245, https://doi.org/10.5194/acp-18-11221-2018, https://doi.org/10.5194/acp-18-11221-2018, 2018
Short summary
Short summary
A coupled atmospheric dispersion modelling system has been developed, comprising a regional chemical transport model and a street-scale urban dispersion model. It was applied in London for 2012 and for all common regulated air quality pollutants, with evaluation against measurements. The modelling demonstrates the interaction between local and regional scales, which differs between pollutants. Real-world estimates of emissions have been used to adjust standard factors and improve model results.
Marta G. Vivanco, Mark R. Theobald, Héctor García-Gómez, Juan Luis Garrido, Marje Prank, Wenche Aas, Mario Adani, Ummugulsum Alyuz, Camilla Andersson, Roberto Bellasio, Bertrand Bessagnet, Roberto Bianconi, Johannes Bieser, Jørgen Brandt, Gino Briganti, Andrea Cappelletti, Gabriele Curci, Jesper H. Christensen, Augustin Colette, Florian Couvidat, Cornelis Cuvelier, Massimo D'Isidoro, Johannes Flemming, Andrea Fraser, Camilla Geels, Kaj M. Hansen, Christian Hogrefe, Ulas Im, Oriol Jorba, Nutthida Kitwiroon, Astrid Manders, Mihaela Mircea, Noelia Otero, Maria-Teresa Pay, Luca Pozzoli, Efisio Solazzo, Svetlana Tsyro, Alper Unal, Peter Wind, and Stefano Galmarini
Atmos. Chem. Phys., 18, 10199–10218, https://doi.org/10.5194/acp-18-10199-2018, https://doi.org/10.5194/acp-18-10199-2018, 2018
Short summary
Short summary
European wet and dry atmospheric deposition of N and S estimated by 14 air quality models was found to vary substantially. An ensemble of models meeting acceptability criteria was used to estimate the exceedances of the critical loads for N in habitats within the Natura 2000 network, as well as their lower and upper limits. Scenarios with 20 % emission reductions in different regions of the world showed that European emissions are responsible for most of the N and S deposition in Europe.
Rebecca J. Oliver, Lina M. Mercado, Stephen Sitch, David Simpson, Belinda E. Medlyn, Yan-Shih Lin, and Gerd A. Folberth
Biogeosciences, 15, 4245–4269, https://doi.org/10.5194/bg-15-4245-2018, https://doi.org/10.5194/bg-15-4245-2018, 2018
Short summary
Short summary
Potential gains in terrestrial carbon sequestration over Europe from elevated CO2 can be partially offset by concurrent rises in tropospheric O3. The land surface model JULES was run in a factorial suite of experiments showing that by 2050 simulated GPP was reduced by 4 to 9 % due to plant O3 damage. Large regional variations exist with larger impacts identified for temperate compared to boreal regions. Plant O3 damage was greatest over the twentieth century and declined into the future.
Riinu Ots, Mathew R. Heal, Dominique E. Young, Leah R. Williams, James D. Allan, Eiko Nemitz, Chiara Di Marco, Anais Detournay, Lu Xu, Nga L. Ng, Hugh Coe, Scott C. Herndon, Ian A. Mackenzie, David C. Green, Jeroen J. P. Kuenen, Stefan Reis, and Massimo Vieno
Atmos. Chem. Phys., 18, 4497–4518, https://doi.org/10.5194/acp-18-4497-2018, https://doi.org/10.5194/acp-18-4497-2018, 2018
Short summary
Short summary
The main hypothesis of this paper is that people who live in large cities in the UK disobey the
smoke control lawas it has not been actively enforced for decades now. However, the use of wood in residential heating has increased, partly due to renewable energy targets, but also for discretionary (i.e. pleasant fireplaces) reasons. Our study is based mainly in London, but similar struggles with urban air quality due to residential wood and coal burning are seen in other major European cities.
Scarlet Stadtler, David Simpson, Sabine Schröder, Domenico Taraborrelli, Andreas Bott, and Martin Schultz
Atmos. Chem. Phys., 18, 3147–3171, https://doi.org/10.5194/acp-18-3147-2018, https://doi.org/10.5194/acp-18-3147-2018, 2018
Matthieu Pommier, Hilde Fagerli, Michael Gauss, David Simpson, Sumit Sharma, Vinay Sinha, Sachin D. Ghude, Oskar Landgren, Agnes Nyiri, and Peter Wind
Atmos. Chem. Phys., 18, 103–127, https://doi.org/10.5194/acp-18-103-2018, https://doi.org/10.5194/acp-18-103-2018, 2018
Short summary
Short summary
India has to cope with a poor air quality, and this work shows a predicted increase in pollution (O3 & PM2.5) if no further policy efforts are made in the future. Climate change will modify the soil moisture leading to changes in O3. Changes in PM2.5 are related to changes in precipitation, biogenic emissions and wind speed. It is also shown that in the 2050s, the secondary inorganic aerosols will become the main component of PM2.5 over India related to the increase in anthropogenic emissions.
Andrea Móring, Massimo Vieno, Ruth M. Doherty, Celia Milford, Eiko Nemitz, Marsailidh M. Twigg, László Horváth, and Mark A. Sutton
Biogeosciences, 14, 4161–4193, https://doi.org/10.5194/bg-14-4161-2017, https://doi.org/10.5194/bg-14-4161-2017, 2017
Short summary
Short summary
This study describes and evaluates a new ammonia (NH3) exchange model for grazed fields (GAG_field). GAG_field is able to simulate the main features of the observed NH3 fluxes. A sensitivity analysis for the non-meteorological model parameters showed that the sensitivity of the NH3 fluxes to a parameter varies among urine patches. Moreover, the fluxes modelled with a dynamic soil pH are similar if a constant pH 7.5 is used, suggesting a useful simplification for regional-scale model application.
Chun Lin, Mathew R. Heal, Massimo Vieno, Ian A. MacKenzie, Ben G. Armstrong, Barbara K. Butland, Ai Milojevic, Zaid Chalabi, Richard W. Atkinson, David S. Stevenson, Ruth M. Doherty, and Paul Wilkinson
Geosci. Model Dev., 10, 1767–1787, https://doi.org/10.5194/gmd-10-1767-2017, https://doi.org/10.5194/gmd-10-1767-2017, 2017
Short summary
Short summary
We evaluated EMEP4UK-WRF v4.3 atmospheric chemistry transport simulations at 5 km horizontal resolution over the UK for use in air pollution epidemiology and health burden assessment. Model-measurement comparison focused on daily and annual means for NO2, O3, PM10, and PM2.5. Important statistics for evaluation of air-quality model output against policy (and hence health)-relevant standards – correlation, bias, and root mean square error – were evaluated by site type, year, month and day-of-week.
Martina Franz, David Simpson, Almut Arneth, and Sönke Zaehle
Biogeosciences, 14, 45–71, https://doi.org/10.5194/bg-14-45-2017, https://doi.org/10.5194/bg-14-45-2017, 2017
Short summary
Short summary
Ozone is a toxic air pollutant that can damage plant leaves and impact their carbon uptake from the atmosphere. We extend a terrestrial biosphere model to account for ozone damage of plants and investigate the impact on the terrestrial carbon cycle. Our approach accounts for ozone transport from the free troposphere to leaf level. We find that this substantially affects simulated ozone uptake into the plants. Simulations indicate that ozone damages plants less than expected from previous studies
Riinu Ots, Massimo Vieno, James D. Allan, Stefan Reis, Eiko Nemitz, Dominique E. Young, Hugh Coe, Chiara Di Marco, Anais Detournay, Ian A. Mackenzie, David C. Green, and Mathew R. Heal
Atmos. Chem. Phys., 16, 13773–13789, https://doi.org/10.5194/acp-16-13773-2016, https://doi.org/10.5194/acp-16-13773-2016, 2016
Short summary
Short summary
Emissions of cooking organic aerosol (COA; from charbroiling, frying, etc.) are currently absent in European emissions inventories yet measurements have pointed to significant COA concentrations. In this study, emissions of COA were developed for the UK by model iteration against year-long measurements at two sites in London. Modelled COA dropped rapidly outside of major urban areas, suggesting that although a notable component in UK urban air, COA does not have a significant effect on rural PM.
Marsailidh M. Twigg, Evgenia Ilyinskaya, Sonya Beccaceci, David C. Green, Matthew R. Jones, Ben Langford, Sarah R. Leeson, Justin J. N. Lingard, Gloria M. Pereira, Heather Carter, Jan Poskitt, Andreas Richter, Stuart Ritchie, Ivan Simmons, Ron I. Smith, Y. Sim Tang, Netty Van Dijk, Keith Vincent, Eiko Nemitz, Massimo Vieno, and Christine F. Braban
Atmos. Chem. Phys., 16, 11415–11431, https://doi.org/10.5194/acp-16-11415-2016, https://doi.org/10.5194/acp-16-11415-2016, 2016
Short summary
Short summary
This study integrates high and low resolution temporal measurements to assess the impact of the Holuhraun effusive eruption in 2014 across the UK. Measurements, modelling and satellite analysis provides details on the transport and chemistry of both gases and particulates during this unique event. The results of the study can be used verify existing atmospheric chemistry models of volcano plumes in order to carry improved risk assessments for future volcanic eruptions.
Riinu Ots, Dominique E. Young, Massimo Vieno, Lu Xu, Rachel E. Dunmore, James D. Allan, Hugh Coe, Leah R. Williams, Scott C. Herndon, Nga L. Ng, Jacqueline F. Hamilton, Robert Bergström, Chiara Di Marco, Eiko Nemitz, Ian A. Mackenzie, Jeroen J. P. Kuenen, David C. Green, Stefan Reis, and Mathew R. Heal
Atmos. Chem. Phys., 16, 6453–6473, https://doi.org/10.5194/acp-16-6453-2016, https://doi.org/10.5194/acp-16-6453-2016, 2016
Short summary
Short summary
This study investigates the contribution of diesel vehicle emissions to organic aerosol formation and particulate matter concentrations in London. Comparisons of simulated pollutant concentrations with observations show good agreement and give confidence in the skill of the model applied. The contribution of diesel vehicle emissions, which are currently not included in official emissions inventories, is demonstrated to be substantial, indicating that more research on this topic is required.
Andrea Móring, Massimo Vieno, Ruth M. Doherty, Johannes Laubach, Arezoo Taghizadeh-Toosi, and Mark A. Sutton
Biogeosciences, 13, 1837–1861, https://doi.org/10.5194/bg-13-1837-2016, https://doi.org/10.5194/bg-13-1837-2016, 2016
Short summary
Short summary
A process-based, weather-driven model for ammonia emission from a urine patch has been developed and its sensitivity to various factors assessed. The model can simulate the ammoniacal nitrogen content, pH and the water content of the soil under a urine patch.
The simulated variables were in a good agreement with the measurements. The sensitivity analysis highlighted the vital role of temperature in ammonia exchange. The model is potentially suitable for larger scale application.
M. Vieno, M. R. Heal, M. L. Williams, E. J. Carnell, E. Nemitz, J. R. Stedman, and S. Reis
Atmos. Chem. Phys., 16, 265–276, https://doi.org/10.5194/acp-16-265-2016, https://doi.org/10.5194/acp-16-265-2016, 2016
D. Fowler, C. E. Steadman, D. Stevenson, M. Coyle, R. M. Rees, U. M. Skiba, M. A. Sutton, J. N. Cape, A. J. Dore, M. Vieno, D. Simpson, S. Zaehle, B. D. Stocker, M. Rinaldi, M. C. Facchini, C. R. Flechard, E. Nemitz, M. Twigg, J. W. Erisman, K. Butterbach-Bahl, and J. N. Galloway
Atmos. Chem. Phys., 15, 13849–13893, https://doi.org/10.5194/acp-15-13849-2015, https://doi.org/10.5194/acp-15-13849-2015, 2015
H. A. C. Denier van der Gon, R. Bergström, C. Fountoukis, C. Johansson, S. N. Pandis, D. Simpson, and A. J. H. Visschedijk
Atmos. Chem. Phys., 15, 6503–6519, https://doi.org/10.5194/acp-15-6503-2015, https://doi.org/10.5194/acp-15-6503-2015, 2015
Short summary
Short summary
Residential wood combustion (RWC) is increasing in Europe but may cause high emissions of particulate matter (PM). A revised bottom-up emission inventory was made which included the semi-volatile components. The revised RWC emissions are 2–3 times higher than the previous inventory. It significantly improved the modeling of PM and comparison with observations. Our results suggest primary PM2.5 emission from RWC as reported in Europe is underestimated and emission inventories need to be revised.
R. Bergström, M. Hallquist, D. Simpson, J. Wildt, and T. F. Mentel
Atmos. Chem. Phys., 14, 13643–13660, https://doi.org/10.5194/acp-14-13643-2014, https://doi.org/10.5194/acp-14-13643-2014, 2014
H. Pleijel, H. Danielsson, D. Simpson, and G. Mills
Biogeosciences, 11, 4521–4528, https://doi.org/10.5194/bg-11-4521-2014, https://doi.org/10.5194/bg-11-4521-2014, 2014
M. Karl, N. Castell, D. Simpson, S. Solberg, J. Starrfelt, T. Svendby, S.-E. Walker, and R. F. Wright
Atmos. Chem. Phys., 14, 8533–8557, https://doi.org/10.5194/acp-14-8533-2014, https://doi.org/10.5194/acp-14-8533-2014, 2014
D. Simpson, C. Andersson, J.H. Christensen, M. Engardt, C. Geels, A. Nyiri, M. Posch, J. Soares, M. Sofiev, P. Wind, and J. Langner
Atmos. Chem. Phys., 14, 6995–7017, https://doi.org/10.5194/acp-14-6995-2014, https://doi.org/10.5194/acp-14-6995-2014, 2014
E. von Schneidemesser, M. Vieno, and P. S. Monks
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acpd-14-1287-2014, https://doi.org/10.5194/acpd-14-1287-2014, 2014
Revised manuscript not accepted
J. Genberg, H. A. C. Denier van der Gon, D. Simpson, E. Swietlicki, H. Areskoug, D. Beddows, D. Ceburnis, M. Fiebig, H. C. Hansson, R. M. Harrison, S. G. Jennings, S. Saarikoski, G. Spindler, A. J. H. Visschedijk, A. Wiedensohler, K. E. Yttri, and R. Bergström
Atmos. Chem. Phys., 13, 8719–8738, https://doi.org/10.5194/acp-13-8719-2013, https://doi.org/10.5194/acp-13-8719-2013, 2013
C. R. Flechard, R.-S. Massad, B. Loubet, E. Personne, D. Simpson, J. O. Bash, E. J. Cooter, E. Nemitz, and M. A. Sutton
Biogeosciences, 10, 5183–5225, https://doi.org/10.5194/bg-10-5183-2013, https://doi.org/10.5194/bg-10-5183-2013, 2013
A. Sakalli and D. Simpson
Biogeosciences, 9, 5161–5179, https://doi.org/10.5194/bg-9-5161-2012, https://doi.org/10.5194/bg-9-5161-2012, 2012
O. Hertel, C. A. Skjøth, S. Reis, A. Bleeker, R. M. Harrison, J. N. Cape, D. Fowler, U. Skiba, D. Simpson, T. Jickells, M. Kulmala, S. Gyldenkærne, L. L. Sørensen, J. W. Erisman, and M. A. Sutton
Biogeosciences, 9, 4921–4954, https://doi.org/10.5194/bg-9-4921-2012, https://doi.org/10.5194/bg-9-4921-2012, 2012
Related subject area
Atmospheric sciences
Evaluation of dust emission and land surface schemes in predicting a mega Asian dust storm over South Korea using WRF-Chem
Sensitivity studies of a four-dimensional local ensemble transform Kalman filter coupled with WRF-Chem version 3.9.1 for improving particulate matter simulation accuracy
A Bayesian method for predicting background radiation at environmental monitoring stations in local-scale networks
Inclusion of the ECMWF ecRad radiation scheme (v1.5.0) in the MAR (v3.14), regional evaluation for Belgium, and assessment of surface shortwave spectral fluxes at Uccle
Development of a fast radiative transfer model for ground-based microwave radiometers (ARMS-gb v1.0): validation and comparison to RTTOV-gb
Indian Institute of Tropical Meteorology (IITM) High-Resolution Global Forecast Model version 1: an attempt to resolve monsoon prediction deadlock
Cell-tracking-based framework for assessing nowcasting model skill in reproducing growth and decay of convective rainfall
NeuralMie (v1.0): an aerosol optics emulator
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
FootNet v1.0: development of a machine learning emulator of atmospheric transport
Updates and evaluation of NOAA's online-coupled air quality model version 7 (AQMv7) within the Unified Forecast System
Quantifying the analysis uncertainty for nowcasting application
Improving the ensemble square root filter (EnSRF) in the Community Inversion Framework: a case study with ICON-ART 2024.01
The MESSy DWARF (based on MESSy v2.55.2)
An enhanced emission module for the PALM model system 23.10 with application for PM10 emission from urban domestic heating
Identifying lightning processes in ERA5 soundings with deep learning
Sensitivity of predicted ultrafine particle size distributions in Europe to different nucleation rate parameterizations using PMCAMx-UF v2.2
Explaining neural networks for detection of tropical cyclones and atmospheric rivers in gridded atmospheric simulation data
PALACE v1.0: Paranal Airglow Line And Continuum Emission model
Accurate space-based NOx emission estimates with the flux divergence approach require fine-scale model information on local oxidation chemistry and profile shapes
Exploring a high-level programming model for the NWP domain using ECMWF microphysics schemes
Quantifying uncertainties in satellite NO2 superobservations for data assimilation and model evaluation
ML-AMPSIT: Machine Learning-based Automated Multi-method Parameter Sensitivity and Importance analysis Tool
Coupling the urban canopy model TEB (SURFEXv9.0) with the radiation model SPARTACUS-Urbanv0.6.1 for more realistic urban radiative exchange calculation
Forecasting contrail climate forcing for flight planning and air traffic management applications: the CocipGrid model in pycontrails 0.51.0
Simulation of the heat mitigation potential of unsealing measures in cities by parameterizing grass grid pavers for urban microclimate modelling with ENVI-met (V5)
AI-NAOS: an AI-based nonspherical aerosol optical scheme for the chemical weather model GRAPES_Meso5.1/CUACE
Orbital-Radar v1.0.0: a tool to transform suborbital radar observations to synthetic EarthCARE cloud radar data
The Modular and Integrated Data Assimilation System at Environment and Climate Change Canada (MIDAS v3.9.1)
A new set of indicators for model evaluation complementing to FAIRMODE’s MQO
Modeling of polycyclic aromatic hydrocarbons (PAHs) from global to regional scales: model development (IAP-AACM_PAH v1.0) and investigation of health risks in 2013 and 2018 in China
LIMA (v2.0): A full two-moment cloud microphysical scheme for the mesoscale non-hydrostatic model Meso-NH v5-6
SLUCM+BEM (v1.0): a simple parameterisation for dynamic anthropogenic heat and electricity consumption in WRF-Urban (v4.3.2)
Carbon dioxide plume dispersion simulated at hectometer scale using DALES: model formulation and observational evaluation
NAQPMS-PDAF v2.0: a novel hybrid nonlinear data assimilation system for improved simulation of PM2.5 chemical components
Source-specific bias correction of US background and anthropogenic ozone modeled in CMAQ
Observational operator for fair model evaluation with ground NO2 measurements
Valid time shifting ensemble Kalman filter (VTS-EnKF) for dust storm forecasting
The third Met Office Unified Model-JULES Regional Atmosphere and Land Configuration, RAL3
Atmospheric moisture tracking with WAM2layers v3
An updated parameterization of the unstable atmospheric surface layer in the Weather Research and Forecasting (WRF) modeling system
The impact of cloud microphysics and ice nucleation on Southern Ocean clouds assessed with single-column modeling and instrument simulators
An updated aerosol simulation in the Community Earth System Model (v2.1.3): dust and marine aerosol emissions and secondary organic aerosol formation
Exploring ship track spreading rates with a physics-informed Langevin particle parameterization
Do data-driven models beat numerical models in forecasting weather extremes? A comparison of IFS HRES, Pangu-Weather, and GraphCast
Development of the MPAS-CMAQ coupled system (V1.0) for multiscale global air quality modeling
UA-ICON with NWP physics package (version: ua-icon-2.1): mean state and variability of the middle atmosphere
Assessment of object-based indices to identify convective organization
Diagnosis of winter precipitation types using Spectral Bin Model (SBM): Comparison of five methods using ICE-POP 2018 field experiment data
The Global Forest Fire Emissions Prediction System version 1.0
Ji Won Yoon, Seungyeon Lee, Ebony Lee, and Seon Ki Park
Geosci. Model Dev., 18, 2303–2328, https://doi.org/10.5194/gmd-18-2303-2025, https://doi.org/10.5194/gmd-18-2303-2025, 2025
Short summary
Short summary
This study evaluates the Weather Research and Forecasting Model (WRF) coupled with Chemistry (WRF-Chem) to predict a mega Asian dust storm (ADS) over South Korea on 28–29 March 2021. We assessed combinations of five dust emission and four land surface schemes by analyzing meteorological and air quality variables. The best scheme combination reduced the root mean square error (RMSE) for particulate matter 10 (PM10) by up to 29.6 %, demonstrating the highest performance.
Jianyu Lin, Tie Dai, Lifang Sheng, Weihang Zhang, Shangfei Hai, and Yawen Kong
Geosci. Model Dev., 18, 2231–2248, https://doi.org/10.5194/gmd-18-2231-2025, https://doi.org/10.5194/gmd-18-2231-2025, 2025
Short summary
Short summary
The effectiveness of this assimilation system and its sensitivity to the ensemble member size and length of the assimilation window are investigated. This study advances our understanding of the selection of basic parameters in the four-dimensional local ensemble transform Kalman filter assimilation system and the performance of ensemble simulation in a particulate-matter-polluted environment.
Jens Peter Karolus Wenceslaus Frankemölle, Johan Camps, Pieter De Meutter, and Johan Meyers
Geosci. Model Dev., 18, 1989–2003, https://doi.org/10.5194/gmd-18-1989-2025, https://doi.org/10.5194/gmd-18-1989-2025, 2025
Short summary
Short summary
To detect anomalous radioactivity in the environment, it is paramount that we understand the natural background level. In this work, we propose a statistical model to describe the most likely background level and the associated uncertainty in a network of dose rate detectors. We train, verify, and validate the model using real environmental data. Using the model, we show that we can correctly predict the background level in a subset of the detector network during a known
anomalous event.
Jean-François Grailet, Robin J. Hogan, Nicolas Ghilain, David Bolsée, Xavier Fettweis, and Marilaure Grégoire
Geosci. Model Dev., 18, 1965–1988, https://doi.org/10.5194/gmd-18-1965-2025, https://doi.org/10.5194/gmd-18-1965-2025, 2025
Short summary
Short summary
The MAR (Modèle Régional Atmosphérique) is a regional climate model used for weather forecasting and studying the climate over various regions. This paper presents an update of MAR thanks to which it can precisely decompose solar radiation, in particular in the UV (ultraviolet) and photosynthesis ranges, both being critical to human health and ecosystems. As a first application of this new capability, this paper presents a method for predicting UV indices with MAR.
Yi-Ning Shi, Jun Yang, Wei Han, Lujie Han, Jiajia Mao, Wanlin Kan, and Fuzhong Weng
Geosci. Model Dev., 18, 1947–1964, https://doi.org/10.5194/gmd-18-1947-2025, https://doi.org/10.5194/gmd-18-1947-2025, 2025
Short summary
Short summary
Direct assimilation of observations from ground-based microwave radiometers (GMRs) holds significant potential for improving forecast accuracy. Radiative transfer models (RTMs) play a crucial role in direct data assimilation. In this study, we introduce a new RTM, the Advanced Radiative Transfer Modeling System – Ground-Based (ARMS-gb), designed to simulate brightness temperatures observed by GMRs along with their Jacobians. Several enhancements have been incorporated to achieve higher accuracy.
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
Short summary
The High-Resolution Global Forecast Model (HGFM) is an advanced iteration of the operational Global Forecast System (GFS) model. HGFM can produce forecasts at a spatial scale of ~6 km in tropics. It demonstrates improved accuracy in short- to medium-range weather prediction over the Indian region, with notable success in predicting extreme events. Further, the model will be entrusted to operational forecasting agencies after validation and testing.
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
Short summary
Nowcasting models struggle with the rapid evolution of heavy rain, and common verification methods are unable to describe how accurately the models predict the growth and decay of heavy rain. We propose a framework to assess model performance. In the framework, convective cells are identified and tracked in the forecasts and observations, and the model skill is then evaluated by comparing differences between forecast and observed cells. We demonstrate the framework with four open-source models.
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
Short summary
Particles in the Earth's atmosphere strongly impact the planet's energy budget, and atmosphere simulations require accurate representation of their interaction with light. This work introduces two approaches to represent light scattering by small particles. The first is a scattering simulator based on Mie theory implemented in Python. The second is a neural network emulator that is more accurate than existing methods and is fast enough to be used in climate and weather simulations.
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
Short summary
This study evaluates the performance of four planetary boundary layer (PBL) schemes in near-surface wind fields over the Sichuan Basin, China. Using 112 sensitivity experiments with the Weather Research and Forecasting (WRF) model and focusing on 28 wind events, it is found that wind direction was less sensitive to the PBL schemes. The quasi-normal scale elimination (QNSE) scheme captured temporal variations best, while the Mellor–Yamada–Janjić (MYJ) scheme had the least error in wind speed.
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
Short summary
It is computationally expensive to infer greenhouse gas (GHG) emissions using atmospheric observations. This is partly due to the detailed model used to represent atmospheric transport. We demonstrate how a machine learning (ML) model can be used to simulate high-resolution atmospheric transport. This type of ML model will help estimate GHG emissions using dense observations, which are becoming increasingly common with the proliferation of urban monitoring networks and geostationary satellites.
Wei Li, Beiming Tang, Patrick C. Campbell, Youhua Tang, Barry Baker, Zachary Moon, Daniel Tong, Jianping Huang, Kai Wang, Ivanka Stajner, and Raffaele Montuoro
Geosci. Model Dev., 18, 1635–1660, https://doi.org/10.5194/gmd-18-1635-2025, https://doi.org/10.5194/gmd-18-1635-2025, 2025
Short summary
Short summary
The study describes the updates of NOAA's current UFS-AQMv7 air quality forecast model by incorporating the latest scientific and structural changes in CMAQv5.4. An evaluation during the summer of 2023 shows that the updated model overall improves the simulation of MDA8 O3 by reducing the bias by 8%–12% in the contiguous US. PM2.5 predictions have mixed results due to wildfire, highlighting the need for future refinements.
Yanwei Zhu, Aitor Atencia, Markus Dabernig, and Yong Wang
Geosci. Model Dev., 18, 1545–1559, https://doi.org/10.5194/gmd-18-1545-2025, https://doi.org/10.5194/gmd-18-1545-2025, 2025
Short summary
Short summary
Most works have delved into convective weather nowcasting, and only a few works have discussed the nowcasting uncertainty for variables at the surface level. Hence, we proposed a method to estimate uncertainty. Generating appropriate noises associated with the characteristic of the error in analysis can simulate the uncertainty of nowcasting. This method can contribute to the estimation of near–surface analysis uncertainty in both nowcasting applications and ensemble nowcasting development.
Joël Thanwerdas, Antoine Berchet, Lionel Constantin, Aki Tsuruta, Michael Steiner, Friedemann Reum, Stephan Henne, and Dominik Brunner
Geosci. Model Dev., 18, 1505–1544, https://doi.org/10.5194/gmd-18-1505-2025, https://doi.org/10.5194/gmd-18-1505-2025, 2025
Short summary
Short summary
The Community Inversion Framework (CIF) brings together methods for estimating greenhouse gas fluxes from atmospheric observations. The initial ensemble method implemented in CIF was found to be incomplete and could hardly be compared to other ensemble methods employed in the inversion community. In this paper, we present and evaluate a new implementation of the ensemble mode, building upon the initial developments.
Astrid Kerkweg, Timo Kirfel, Duong H. Do, Sabine Griessbach, Patrick Jöckel, and Domenico Taraborrelli
Geosci. Model Dev., 18, 1265–1286, https://doi.org/10.5194/gmd-18-1265-2025, https://doi.org/10.5194/gmd-18-1265-2025, 2025
Short summary
Short summary
Normally, the Modular Earth Submodel System (MESSy) is linked to complete dynamic models to create chemical climate models. However, the modular concept of MESSy and the newly developed DWARF component presented here make it possible to create simplified models that contain only one or a few process descriptions. This is very useful for technical optimisation, such as porting to GPUs, and can be used to create less complex models, such as a chemical box model.
Edward C. Chan, Ilona J. Jäkel, Basit Khan, Martijn Schaap, Timothy M. Butler, Renate Forkel, and Sabine Banzhaf
Geosci. Model Dev., 18, 1119–1139, https://doi.org/10.5194/gmd-18-1119-2025, https://doi.org/10.5194/gmd-18-1119-2025, 2025
Short summary
Short summary
An enhanced emission module has been developed for the PALM model system, improving flexibility and scalability of emission source representation across different sectors. A model for parametrized domestic emissions has also been included, for which an idealized model run is conducted for particulate matter (PM10). The results show that, in addition to individual sources and diurnal variations in energy consumption, vertical transport and urban topology play a role in concentration distribution.
Gregor Ehrensperger, Thorsten Simon, Georg J. Mayr, and Tobias Hell
Geosci. Model Dev., 18, 1141–1153, https://doi.org/10.5194/gmd-18-1141-2025, https://doi.org/10.5194/gmd-18-1141-2025, 2025
Short summary
Short summary
As lightning is a brief and localized event, it is not explicitly resolved in atmospheric models. Instead, expert-based auxiliary descriptions are used to assess it. This study explores how AI can improve our understanding of lightning without relying on traditional expert knowledge. We reveal that AI independently identified the key factors known to experts as essential for lightning in the Alps region. This shows how knowledge discovery could be sped up in areas with limited expert knowledge.
David Patoulias, Kalliopi Florou, and Spyros N. Pandis
Geosci. Model Dev., 18, 1103–1118, https://doi.org/10.5194/gmd-18-1103-2025, https://doi.org/10.5194/gmd-18-1103-2025, 2025
Short summary
Short summary
The effect of the assumed atmospheric nucleation mechanism on particle number concentrations and size distribution was investigated. Two quite different mechanisms involving sulfuric acid and ammonia or a biogenic organic vapor gave quite similar results which were consistent with measurements at 26 measurement stations across Europe. The number of larger particles that serve as cloud condensation nuclei showed little sensitivity to the assumed nucleation mechanism.
Tim Radke, Susanne Fuchs, Christian Wilms, Iuliia Polkova, and Marc Rautenhaus
Geosci. Model Dev., 18, 1017–1039, https://doi.org/10.5194/gmd-18-1017-2025, https://doi.org/10.5194/gmd-18-1017-2025, 2025
Short summary
Short summary
In our study, we built upon previous work to investigate the patterns artificial intelligence (AI) learns to detect atmospheric features like tropical cyclones (TCs) and atmospheric rivers (ARs). As primary objective, we adopt a method to explain the AI used and investigate the plausibility of learned patterns. We find that plausible patterns are learned for both TCs and ARs. Hence, the chosen method is very useful for gaining confidence in the AI-based detection of atmospheric features.
Stefan Noll, Carsten Schmidt, Patrick Hannawald, Wolfgang Kausch, and Stefan Kimeswenger
EGUsphere, https://doi.org/10.5194/egusphere-2024-3512, https://doi.org/10.5194/egusphere-2024-3512, 2025
Short summary
Short summary
Non-thermal emission from chemical reactions in the Earth's middle und upper atmosphere strongly contributes to the brightness of the night sky below about 2.3 µm. The new Paranal Airglow Line and Continuum Emission model calculates the emission spectrum and its variability with an unprecedented accuracy. Relying on a large spectroscopic data set from astronomical spectrographs and theoretical molecular/atomic data, it is valuable for airglow research and astronomical observatories.
Felipe Cifuentes, Henk Eskes, Enrico Dammers, Charlotte Bryan, and Folkert Boersma
Geosci. Model Dev., 18, 621–649, https://doi.org/10.5194/gmd-18-621-2025, https://doi.org/10.5194/gmd-18-621-2025, 2025
Short summary
Short summary
We tested the capability of the flux divergence approach (FDA) to reproduce known NOx emissions using synthetic NO2 satellite column retrievals from high-resolution model simulations. The FDA accurately reproduced NOx emissions when column observations were limited to the boundary layer and when the variability of the NO2 lifetime, the NOx : NO2 ratio, and NO2 profile shapes were correctly modeled. This introduces strong model dependency, reducing the simplicity of the original FDA formulation.
Stefano Ubbiali, Christian Kühnlein, Christoph Schär, Linda Schlemmer, Thomas C. Schulthess, Michael Staneker, and Heini Wernli
Geosci. Model Dev., 18, 529–546, https://doi.org/10.5194/gmd-18-529-2025, https://doi.org/10.5194/gmd-18-529-2025, 2025
Short summary
Short summary
We explore a high-level programming model for porting numerical weather prediction (NWP) model codes to graphics processing units (GPUs). We present a Python rewrite with the domain-specific library GT4Py (GridTools for Python) of two renowned cloud microphysics schemes and the associated tangent-linear and adjoint algorithms. We find excellent portability, competitive GPU performance, robust execution on diverse computing architectures, and enhanced code maintainability and user productivity.
Pieter Rijsdijk, Henk Eskes, Arlene Dingemans, K. Folkert Boersma, Takashi Sekiya, Kazuyuki Miyazaki, and Sander Houweling
Geosci. Model Dev., 18, 483–509, https://doi.org/10.5194/gmd-18-483-2025, https://doi.org/10.5194/gmd-18-483-2025, 2025
Short summary
Short summary
Clustering high-resolution satellite observations into superobservations improves model validation and data assimilation applications. In our paper, we derive quantitative uncertainties for satellite NO2 column observations based on knowledge of the retrievals, including a detailed analysis of spatial error correlations and representativity errors. The superobservations and uncertainty estimates are tested in a global chemical data assimilation system and are found to improve the forecasts.
Dario Di Santo, Cenlin He, Fei Chen, and Lorenzo Giovannini
Geosci. Model Dev., 18, 433–459, https://doi.org/10.5194/gmd-18-433-2025, https://doi.org/10.5194/gmd-18-433-2025, 2025
Short summary
Short summary
This paper presents the Machine Learning-based Automated Multi-method Parameter Sensitivity and Importance analysis Tool (ML-AMPSIT), a computationally efficient tool that uses machine learning algorithms for sensitivity analysis in atmospheric models. It is tested with the Weather Research and Forecasting (WRF) model coupled with the Noah-Multiparameterization (Noah-MP) land surface model to investigate sea breeze circulation sensitivity to vegetation-related parameters.
Robert Schoetter, Robin James Hogan, Cyril Caliot, and Valéry Masson
Geosci. Model Dev., 18, 405–431, https://doi.org/10.5194/gmd-18-405-2025, https://doi.org/10.5194/gmd-18-405-2025, 2025
Short summary
Short summary
Radiation is relevant to the atmospheric impact on people and infrastructure in cities as it can influence the urban heat island, building energy consumption, and human thermal comfort. A new urban radiation model, assuming a more realistic form of urban morphology, is coupled to the urban climate model Town Energy Balance (TEB). The new TEB is evaluated with a reference radiation model for a variety of urban morphologies, and an improvement in the simulated radiative observables is found.
Zebediah Engberg, Roger Teoh, Tristan Abbott, Thomas Dean, Marc E. J. Stettler, and Marc L. Shapiro
Geosci. Model Dev., 18, 253–286, https://doi.org/10.5194/gmd-18-253-2025, https://doi.org/10.5194/gmd-18-253-2025, 2025
Short summary
Short summary
Contrails forming in some atmospheric conditions may persist and become strongly warming cirrus, while in other conditions may be neutral or cooling. We develop a contrail forecast model to predict contrail climate forcing for any arbitrary point in space and time and explore integration into flight planning and air traffic management. This approach enables contrail interventions to target high-probability high-climate-impact regions and reduce unintended consequences of contrail management.
Nils Eingrüber, Alina Domm, Wolfgang Korres, and Karl Schneider
Geosci. Model Dev., 18, 141–160, https://doi.org/10.5194/gmd-18-141-2025, https://doi.org/10.5194/gmd-18-141-2025, 2025
Short summary
Short summary
Climate change adaptation measures like unsealings can reduce urban heat stress. As grass grid pavers have never been parameterized for microclimate model simulations with ENVI-met, a new parameterization was developed based on field measurements. To analyse the cooling potential, scenario analyses were performed for a densely developed area in Cologne. Statistically significant average cooling effects of up to −11.1 K were found for surface temperature and up to −2.9 K for 1 m air temperature.
Xuan Wang, Lei Bi, Hong Wang, Yaqiang Wang, Wei Han, Xueshun Shen, and Xiaoye Zhang
Geosci. Model Dev., 18, 117–139, https://doi.org/10.5194/gmd-18-117-2025, https://doi.org/10.5194/gmd-18-117-2025, 2025
Short summary
Short summary
The Artificial-Intelligence-based Nonspherical Aerosol Optical Scheme (AI-NAOS) was developed to improve the estimation of the aerosol direct radiation effect and was coupled online with a chemical weather model. The AI-NAOS scheme considers black carbon as fractal aggregates and soil dust as super-spheroids, encapsulated with hygroscopic aerosols. Real-case simulations emphasize the necessity of accurately representing nonspherical and inhomogeneous aerosols in chemical weather models.
Lukas Pfitzenmaier, Pavlos Kollias, Nils Risse, Imke Schirmacher, Bernat Puigdomenech Treserras, and Katia Lamer
Geosci. Model Dev., 18, 101–115, https://doi.org/10.5194/gmd-18-101-2025, https://doi.org/10.5194/gmd-18-101-2025, 2025
Short summary
Short summary
The Python tool Orbital-Radar transfers suborbital radar data (ground-based, airborne, and forward-simulated numerical weather prediction model) into synthetic spaceborne cloud profiling radar data, mimicking platform-specific instrument characteristics, e.g. EarthCARE or CloudSat. The tool's novelty lies in simulating characteristic errors and instrument noise. Thus, existing data sets are transferred into synthetic observations and can be used for satellite calibration–validation studies.
Mark Buehner, Jean-Francois Caron, Ervig Lapalme, Alain Caya, Ping Du, Yves Rochon, Sergey Skachko, Maziar Bani Shahabadi, Sylvain Heilliette, Martin Deshaies-Jacques, Weiguang Chang, and Michael Sitwell
Geosci. Model Dev., 18, 1–18, https://doi.org/10.5194/gmd-18-1-2025, https://doi.org/10.5194/gmd-18-1-2025, 2025
Short summary
Short summary
The Modular and Integrated Data Assimilation System (MIDAS) software is described. The flexible design of MIDAS enables both deterministic and ensemble prediction applications for the atmosphere and several other Earth system components. It is currently used for all main operational weather prediction systems in Canada and also for sea ice and sea surface temperature analysis. The use of MIDAS for multiple Earth system components will facilitate future research on coupled data assimilation.
Alexander de Meij, Cornelis Cuvelier, Philippe Thunis, and Enrico Pisoni
EGUsphere, https://doi.org/10.5194/egusphere-2024-3690, https://doi.org/10.5194/egusphere-2024-3690, 2025
Short summary
Short summary
We assess the relevance and utility indicators developed within FAIRMODE by evaluating 9 CAMS models in calculated air pollutant values. For NO2, the results highlight difficulties at traffic stations. For PM2.5 and PM10 the bias and Winter-Summer gradients reveal issues. O3 evaluation shows that e.g. seasonal gradients are useful. Overall, the indicators provide valuable insights into model limitations, yet there is a need to reconsider the strictness of some indicators for certain pollutants.
Zichen Wu, Xueshun Chen, Zifa Wang, Huansheng Chen, Zhe Wang, Qing Mu, Lin Wu, Wending Wang, Xiao Tang, Jie Li, Ying Li, Qizhong Wu, Yang Wang, Zhiyin Zou, and Zijian Jiang
Geosci. Model Dev., 17, 8885–8907, https://doi.org/10.5194/gmd-17-8885-2024, https://doi.org/10.5194/gmd-17-8885-2024, 2024
Short summary
Short summary
We developed a model to simulate polycyclic aromatic hydrocarbons (PAHs) from global to regional scales. The model can reproduce PAH distribution well. The concentration of BaP (indicator species for PAHs) could exceed the target values of 1 ng m-3 over some areas (e.g., in central Europe, India, and eastern China). The change in BaP is lower than that in PM2.5 from 2013 to 2018. China still faces significant potential health risks posed by BaP although the Action Plan has been implemented.
Marie Taufour, Jean-Pierre Pinty, Christelle Barthe, Benoît Vié, and Chien Wang
Geosci. Model Dev., 17, 8773–8798, https://doi.org/10.5194/gmd-17-8773-2024, https://doi.org/10.5194/gmd-17-8773-2024, 2024
Short summary
Short summary
We have developed a complete two-moment version of the LIMA (Liquid Ice Multiple Aerosols) microphysics scheme. We have focused on collection processes, where the hydrometeor number transfer is often estimated in proportion to the mass transfer. The impact of these parameterizations on a convective system and the prospects for more realistic estimates of secondary parameters (reflectivity, hydrometeor size) are shown in a first test on an idealized case.
Yuya Takane, Yukihiro Kikegawa, Ko Nakajima, and Hiroyuki Kusaka
Geosci. Model Dev., 17, 8639–8664, https://doi.org/10.5194/gmd-17-8639-2024, https://doi.org/10.5194/gmd-17-8639-2024, 2024
Short summary
Short summary
A new parameterisation for dynamic anthropogenic heat and electricity consumption is described. The model reproduced the temporal variation in and spatial distributions of electricity consumption and temperature well in summer and winter. The partial air conditioning was the most critical factor, significantly affecting the value of anthropogenic heat emission.
Arseniy Karagodin-Doyennel, Fredrik Jansson, Bart van Stratum, Hugo Denier van der Gon, Jordi Vilà-Guerau de Arellano, and Sander Houweling
EGUsphere, https://doi.org/10.5194/egusphere-2024-3721, https://doi.org/10.5194/egusphere-2024-3721, 2024
Short summary
Short summary
We introduce a new simulation platform based on the Dutch Large-Eddy Simulation (DALES) to simulate carbon dioxide (CO2) emissions and their dispersion in the turbulent environments with hectometer resolution. This model incorporates both anthropogenic emission inventory and ecosystem exchanges. Simulation results for the main urban area in the Netherlands demonstrate a strong potential of DALES to enhance CO2 emission modeling, which is important for refining their reduction strategies.
Hongyi Li, Ting Yang, Lars Nerger, Dawei Zhang, Di Zhang, Guigang Tang, Haibo Wang, Yele Sun, Pingqing Fu, Hang Su, and Zifa Wang
Geosci. Model Dev., 17, 8495–8519, https://doi.org/10.5194/gmd-17-8495-2024, https://doi.org/10.5194/gmd-17-8495-2024, 2024
Short summary
Short summary
To accurately characterize the spatiotemporal distribution of particulate matter <2.5 µm chemical components, we developed the Nested Air Quality Prediction Model System with the Parallel Data Assimilation Framework (NAQPMS-PDAF) v2.0 for chemical components with non-Gaussian and nonlinear properties. NAQPMS-PDAF v2.0 has better computing efficiency, excels when used with a small ensemble size, and can significantly improve the simulation performance of chemical components.
T. Nash Skipper, Christian Hogrefe, Barron H. Henderson, Rohit Mathur, Kristen M. Foley, and Armistead G. Russell
Geosci. Model Dev., 17, 8373–8397, https://doi.org/10.5194/gmd-17-8373-2024, https://doi.org/10.5194/gmd-17-8373-2024, 2024
Short summary
Short summary
Chemical transport model simulations are combined with ozone observations to estimate the bias in ozone attributable to US anthropogenic sources and individual sources of US background ozone: natural sources, non-US anthropogenic sources, and stratospheric ozone. Results indicate a positive bias correlated with US anthropogenic emissions during summer in the eastern US and a negative bias correlated with stratospheric ozone during spring.
Li Fang, Jianbing Jin, Arjo Segers, Ke Li, Ji Xia, Wei Han, Baojie Li, Hai Xiang Lin, Lei Zhu, Song Liu, and Hong Liao
Geosci. Model Dev., 17, 8267–8282, https://doi.org/10.5194/gmd-17-8267-2024, https://doi.org/10.5194/gmd-17-8267-2024, 2024
Short summary
Short summary
Model evaluations against ground observations are usually unfair. The former simulates mean status over coarse grids and the latter the surrounding atmosphere. To solve this, we proposed the new land-use-based representative (LUBR) operator that considers intra-grid variance. The LUBR operator is validated to provide insights that align with satellite measurements. The results highlight the importance of considering fine-scale urban–rural differences when comparing models and observation.
Mijie Pang, Jianbing Jin, Arjo Segers, Huiya Jiang, Wei Han, Batjargal Buyantogtokh, Ji Xia, Li Fang, Jiandong Li, Hai Xiang Lin, and Hong Liao
Geosci. Model Dev., 17, 8223–8242, https://doi.org/10.5194/gmd-17-8223-2024, https://doi.org/10.5194/gmd-17-8223-2024, 2024
Short summary
Short summary
The ensemble Kalman filter (EnKF) improves dust storm forecasts but faces challenges with position errors. The valid time shifting EnKF (VTS-EnKF) addresses this by adjusting for position errors, enhancing accuracy in forecasting dust storms, as proven in tests on 2021 events, even with smaller ensembles and time intervals.
Mike Bush, David L. A. Flack, Huw W. Lewis, Sylvia I. Bohnenstengel, Chris J. Short, Charmaine Franklin, Adrian P. Lock, Martin Best, Paul Field, Anne McCabe, Kwinten Van Weverberg, Segolene Berthou, Ian Boutle, Jennifer K. Brooke, Seb Cole, Shaun Cooper, Gareth Dow, John Edwards, Anke Finnenkoetter, Kalli Furtado, Kate Halladay, Kirsty Hanley, Margaret A. Hendry, Adrian Hill, Aravindakshan Jayakumar, Richard W. Jones, Humphrey Lean, Joshua C. K. Lee, Andy Malcolm, Marion Mittermaier, Saji Mohandas, Stuart Moore, Cyril Morcrette, Rachel North, Aurore Porson, Susan Rennie, Nigel Roberts, Belinda Roux, Claudio Sanchez, Chun-Hsu Su, Simon Tucker, Simon Vosper, David Walters, James Warner, Stuart Webster, Mark Weeks, Jonathan Wilkinson, Michael Whitall, Keith D. Williams, and Hugh Zhang
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-201, https://doi.org/10.5194/gmd-2024-201, 2024
Revised manuscript accepted for GMD
Short summary
Short summary
RAL configurations define settings for the Unified Model atmosphere and Joint UK Land Environment Simulator. The third version of the Regional Atmosphere and Land (RAL3) science configuration for kilometre and sub-km scale modelling represents a major advance compared to previous versions (RAL2) by delivering a common science definition for applications in tropical and mid-latitude regions. RAL3 has more realistic precipitation distributions and improved representation of clouds and visibility.
Peter Kalverla, Imme Benedict, Chris Weijenborg, and Ruud J. van der Ent
EGUsphere, https://doi.org/10.5194/egusphere-2024-3401, https://doi.org/10.5194/egusphere-2024-3401, 2024
Short summary
Short summary
We introduce a new version of WAM2layers, a computer program that tracks how the weather brings water from one place to another. It uses data from weather and climate models, whose resolution is steadily increasing. Processing the latest data became a challenge, and the updates presented here ensure that WAM2layers runs smoothly again. We also made it easier to use the program and to understand its source code. This makes it more transparent and reliable, and easier to maintain.
Prabhakar Namdev, Maithili Sharan, Piyush Srivastava, and Saroj Kanta Mishra
Geosci. Model Dev., 17, 8093–8114, https://doi.org/10.5194/gmd-17-8093-2024, https://doi.org/10.5194/gmd-17-8093-2024, 2024
Short summary
Short summary
Inadequate representation of surface–atmosphere interaction processes is a major source of uncertainty in numerical weather prediction models. Here, an effort has been made to improve the Weather Research and Forecasting (WRF) model version 4.2.2 by introducing a unique theoretical framework under convective conditions. In addition, to enhance the potential applicability of the WRF modeling system, various commonly used similarity functions under convective conditions have also been installed.
Andrew Gettelman, Richard Forbes, Roger Marchand, Chih-Chieh Chen, and Mark Fielding
Geosci. Model Dev., 17, 8069–8092, https://doi.org/10.5194/gmd-17-8069-2024, https://doi.org/10.5194/gmd-17-8069-2024, 2024
Short summary
Short summary
Supercooled liquid clouds (liquid clouds colder than 0°C) are common at higher latitudes (especially over the Southern Ocean) and are critical for constraining climate projections. We compare a single-column version of a weather model to observations with two different cloud schemes and find that both the dynamical environment and atmospheric aerosols are important for reproducing observations.
Yujuan Wang, Peng Zhang, Jie Li, Yaman Liu, Yanxu Zhang, Jiawei Li, and Zhiwei Han
Geosci. Model Dev., 17, 7995–8021, https://doi.org/10.5194/gmd-17-7995-2024, https://doi.org/10.5194/gmd-17-7995-2024, 2024
Short summary
Short summary
This study updates the CESM's aerosol schemes, focusing on dust, marine aerosol emissions, and secondary organic aerosol (SOA) . Dust emission modifications make deflation areas more continuous, improving results in North America and the sub-Arctic. Humidity correction to sea-salt emissions has a minor effect. Introducing marine organic aerosol emissions, coupled with ocean biogeochemical processes, and adding aqueous reactions for SOA formation advance the CESM's aerosol modelling results.
Lucas A. McMichael, Michael J. Schmidt, Robert Wood, Peter N. Blossey, and Lekha Patel
Geosci. Model Dev., 17, 7867–7888, https://doi.org/10.5194/gmd-17-7867-2024, https://doi.org/10.5194/gmd-17-7867-2024, 2024
Short summary
Short summary
Marine cloud brightening (MCB) is a climate intervention technique to potentially cool the climate. Climate models used to gauge regional climate impacts associated with MCB often assume large areas of the ocean are uniformly perturbed. However, a more realistic representation of MCB application would require information about how an injected particle plume spreads. This work aims to develop such a plume-spreading model.
Leonardo Olivetti and Gabriele Messori
Geosci. Model Dev., 17, 7915–7962, https://doi.org/10.5194/gmd-17-7915-2024, https://doi.org/10.5194/gmd-17-7915-2024, 2024
Short summary
Short summary
Data-driven models are becoming a viable alternative to physics-based models for weather forecasting up to 15 d into the future. However, it is unclear whether they are as reliable as physics-based models when forecasting weather extremes. We evaluate their performance in forecasting near-surface cold, hot, and windy extremes globally. We find that data-driven models can compete with physics-based models and that the choice of the best model mainly depends on the region and type of extreme.
David C. Wong, Jeff Willison, Jonathan E. Pleim, Golam Sarwar, James Beidler, Russ Bullock, Jerold A. Herwehe, Rob Gilliam, Daiwen Kang, Christian Hogrefe, George Pouliot, and Hosein Foroutan
Geosci. Model Dev., 17, 7855–7866, https://doi.org/10.5194/gmd-17-7855-2024, https://doi.org/10.5194/gmd-17-7855-2024, 2024
Short summary
Short summary
This work describe how we linked the meteorological Model for Prediction Across Scales – Atmosphere (MPAS-A) with the Community Multiscale Air Quality (CMAQ) air quality model to form a coupled modelling system. This could be used to study air quality or climate and air quality interaction at a global scale. This new model scales well in high-performance computing environments and performs well with respect to ground surface networks in terms of ozone and PM2.5.
Markus Kunze, Christoph Zülicke, Tarique Adnan Siddiqui, Claudia Christine Stephan, Yosuke Yamazaki, Claudia Stolle, Sebastian Borchert, and Hauke Schmidt
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-191, https://doi.org/10.5194/gmd-2024-191, 2024
Revised manuscript accepted for GMD
Short summary
Short summary
We present the Icosahedral Nonhydrostatic (ICON) general circulation model with upper atmosphere extension with the physics package for numerical weather prediction (UA-ICON(NWP)). The parameters for the gravity wave parameterizations were optimized, and realistic modelling of the thermal and dynamic state of the mesopause regions was achieved. UA-ICON(NWP) now shows a realistic frequency of major sudden stratospheric warmings and well-represented solar tides in temperature.
Giulio Mandorli and Claudia J. Stubenrauch
Geosci. Model Dev., 17, 7795–7813, https://doi.org/10.5194/gmd-17-7795-2024, https://doi.org/10.5194/gmd-17-7795-2024, 2024
Short summary
Short summary
In recent years, several studies focused their attention on the disposition of convection. Lots of methods, called indices, have been developed to quantify the amount of convection clustering. These indices are evaluated in this study by defining criteria that must be satisfied and then evaluating the indices against these standards. None of the indices meet all criteria, with some only partially meeting them.
Wonbae Bang, Jacob Carlin, Kwonil Kim, Alexander Ryzhkov, Guosheng Liu, and Gyuwon Lee
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-179, https://doi.org/10.5194/gmd-2024-179, 2024
Revised manuscript accepted for GMD
Short summary
Short summary
Microphysics model-based diagnosis such as the spectral bin model (SBM) recently has been attempted to diagnose winter precipitation types. In this study, the accuracy of SBM-based precipitation type diagnosis is compared with other traditional methods. SBM have relatively higher accuracy about snow and wetsnow events whereas lower accuracy about rain event. When microphysics scheme in the SBM was optimized for the corresponding region, accuracy about rain events was improved.
Kerry Anderson, Jack Chen, Peter Englefield, Debora Griffin, Paul A. Makar, and Dan Thompson
Geosci. Model Dev., 17, 7713–7749, https://doi.org/10.5194/gmd-17-7713-2024, https://doi.org/10.5194/gmd-17-7713-2024, 2024
Short summary
Short summary
The Global Forest Fire Emissions Prediction System (GFFEPS) is a model that predicts smoke and carbon emissions from wildland fires. The model calculates emissions from the ground up based on satellite-detected fires, modelled weather and fire characteristics. Unlike other global models, GFFEPS uses daily weather conditions to capture changing burning conditions on a day-to-day basis. GFFEPS produced lower carbon emissions due to the changing weather not captured by the other models.
Cited articles
Aggarwal, P. and Jain, S.: Impact of air pollutants from surface transport sources on human health: A modeling and epidemiological approach, Environ. Int., 83, 146–157, 2015.
Amann, M., Bertok, I., Borken-Kleefeld, J., Cofala, J., Heyes, C., Höglund-Isaksson, L., Klimont, Z., Nguyen, B., Posch, M., and Rafaj, P.: Cost-effective control of air quality and greenhouse gases in Europe: Modeling and policy applications, Environ. Modell. Softw., 26, 1489–1501, 2011.
Bessagnet, B., Hodzic, A., Vautard, R., Beekmann, M., Cheinet, S., Honoré, C., Liousse, C., and Rouil, L.: Aerosol modeling with CHIMERE – preliminary evaluation at the continental scale, Atmos. Environ., 38, 2803–2817, 2004.
Cape, J. N., van der Eerden, L. J., Sheppard, L. J., Leith, I. D., and Sutton, M. A.: Evidence for changing the critical level for ammonia, Environ. Pollut., 157, 1033–1037, 2009.
Carruthers, D. J., Holroyd, R. J., Hunt, J. C. R., Weng, W. S., Robins, A. G., Apsley, D. D., Thompson, D. J., and Smith, F. B.: UK-ADMS: A new approach to modelling dispersion in the earth's atmospheric boundary layer, J. Wind. Eng. Ind. Aerod., 52, 139–153, 1994.
Carslaw, D. C. and Ropkins, K.: Openair – an R package for air quality data analysis, Environ. Modell. Softw., 27, 52–61, 2012.
Chang, J. C. and Hanna, S. R.: Air quality model performance evaluation, Meteorol. Atmos. Phys., 87, 167–196, 2004.
Ching, J., Isakov, V., Majeed, M., and Irwin, J.: An approach for incorporating sub-grid variability information into air quality modelling, Proceedings of the 14th Joint Conference on the Applications of Air Pollution Meteorology with the Air and Waste Management Association, Atlanta, USA, 27 January–3 February 2006.
Cimorelli, A. J., Perry, S. G., Venkatram, A., Weil, J. C., Paine, R. J., Wilson, R. B., Lee, R. F., Peters, W. D., Brode, R. W., and Pauimer, J. O.: AERMOD: Description of Model Formulation Version 02222. United States Environmental Protection Agency, Research Triangle Park, NC 27711, USA, 85 pp., 2002.
CLRTAP, Chapter 2 of the Draft Manual on Methodologies and Criteria for Modelling and Mapping Critical Loads & Levels and Air Pollution Effects, Risks and Trends, available at: http://www.rivm.nl/media/documenten/cce/manual/Ch2-MapMan-2014-08.pdf (last access: 12 December 2016), 2014.
Cuvelier, C., Thunis, P., Karam, D., Schaap, M., Hendriks, C., Kranenburg, R., Fagerli, H., Nyiri, A., Simpson, D., Wind, P., Schulz, M., Bessagnet, B., Colette, A., Terrenoire, E., Rouïl, L., Stern, R., Graff, A., Baldasano, J. M., and Pay, M. T.: ScaleDep: performance of European chemistry-transport models as function of horizontal special resolution, EMEP Technical report 1/2013, 63 pp., 2013.
Denby, B., Cassiani, M., de Smet, P., de Leeuw, F., and Horálek, J.: Sub-grid variability and its impact on European wide air quality exposure assessment, Atmos. Environ., 45, 4220–4229, 2011.
Dentener, F., Drevet, J., Lamarque, J. F., Bey, I., Eickhout, B., Fiore, A. M., Hauglustaine, D., Horowitz, L.W., Krol, M., Kulshrestha, U. C., Lawrence, M., Galy-Lacaux, C., Rast, S., Shindell, D., Stevenson, D., Van Noije, T., Atherton, C., Bell, N., Bergman, D., Butler, T., Cofala, J., Collins, B., Doherty, R., Ellingsen, K., Galloway, J., Gauss, M., Montanaro, V., Müller, J. F., Pitari, G., Rodriguez, J., Sanderson, M., Solmon, F., Strahan, S., Schultz, M., Sudo, K., Szopa, S., and Wild, O.: Nitrogen and sulfur deposition on regional and global scales: a multimodel evaluation, Global Biogeochem. Cy., 20, GB4003, https://doi.org/10.1029/2005GB002672, 2006.
de Smet, P., de Leeuw, F., Horálek, J., and Kurfürst, P.: A European compilation of national air quality maps based on modelling, ETC/ACM Technical Paper 2013/3, March 2013.
Dragosits, U., Theobald, M. R., Place, C. J., Lord, E., Webb, J., Hill, J., ApSimon, H. M., and Sutton, M. A.: Ammonia emission, deposition and impact assessment at the field scale: a case study of sub-grid spatial variability, Environ. Pollut., 117, 147–158, 2002.
EC4MACS.: The GAINS Integrated Assessment Model, EC4MACS Report, available at: http://www.ec4macs.eu/content/report/EC4MACS_Publications/MR_Final in pdf/GAINS_Methodologies_Final.pdf (last access: 12 December 2016), 2012.
EMEP: Transboundary particulate matter, photo-oxidants, acidifying and eutrophying components, Status Report 1/2015, EMEP MSC-W, The Norwegian Meteorological Institute, Oslo, Norway, 2015.
Fagerli, H. and Aas, W.: Trends of nitrogen in air and precipitation: Model results and observations at EMEP sites in Europe, 1980–2003, Environ. Pollut., 154, 448–461, 2008.
Galvis, B., Bergin, M., Boylan, J., Huang, Y., Bergin, M., and Russell, A. G.: Air quality impacts and health-benefit valuation of a low-emission technology for rail yard locomotives in Atlanta Georgia, Sci. Total Environ., 533, 156–164, 2015.
Hall, D. J., Spanton, A. M., Dunkerley, F., Bennett, M., and Griffiths, R. F.: An Intercomparison of the AERMOD, ADMS and ISC Dispersion Models for Regulatory Applications, Report No. P362. Environment Agency, Bristol, UK, 2000.
Hallsworth, S., Dore, A., Bealey, W., Dragosits, U., Vieno, M., Hellsten, S., Tang, Y., and Sutton, M.: The role of indicator choice in quantifying the threat of atmospheric ammonia to the “Natura 2000”network, Environ. Sci. Policy, 13, 671–687, 2010.
Hanna, S. R. and Chang, J.: Setting Acceptance Criteria for Air Quality Models, Air Pollution Modeling and its Application XXI, 479–484, 2012.
Isakov, V., Irwin, J. S. and Ching, J.: Using CMAQ for exposure modeling and characterizing the subgrid variability for exposure estimates, J. Appl. Meteorol. Clim., 46, 1354–1371, 2007.
Janssen, S. and Thunis, P.: Fairmode's composite mapping exercise, Proceedings of the 10th International Conference on Air Quality – Science and Application, Milan, Italy, 14–18 March 2016, available at: http://www.airqualityconference.org/, last access: 12 December 2016.
Janssen, S., Dumont, G., Fierens, F., Deutsch, F., Maiheu, B., Celis, D., Trimpeneers, E., and Mensink, C.: Land use to characterize spatial representativeness of air quality monitoring stations and its relevance for model validation, Atmos. Environ., 59, 492–500, 2012.
Kiesewetter, G., Borken-Kleefeld, J., Heyes, C., Bertok, I., Schoepp, W., Thunis, P., Bessagnet, B., Terrenoire, E., and Amann, M.: Modelling compliance with NO2 and PM10 air quality limit values in the GAINS model. TSAP Report no. 9, IIASA., 2013.
Kiesewetter, G., Borken-Kleefeld, J., Schöpp, W., Heyes, C., Thunis, P., Bessagnet, B., Terrenoire, E., Gsella, A., and Amann, M.: Modelling NO2 concentrations at the street level in the GAINS integrated assessment model: projections under current legislation, Atmos. Chem. Phys., 14, 813–829, https://doi.org/10.5194/acp-14-813-2014, 2014.
Kuenen, J. J. P., Visschedijk, A. J. H., Jozwicka, M., and Denier van der Gon, H. A. C.: TNO-MACC_II emission inventory; a multi-year (2003–2009) consistent high-resolution European emission inventory for air quality modelling, Atmos. Chem. Phys., 14, 10963–10976, https://doi.org/10.5194/acp-14-10963-2014, 2014.
Lolkema, D. E., Noordijk, H., Stolk, A. P., Hoogerbrugge, R., van Zanten, M. C., and van Pul, W. A. J.: The Measuring Ammonia in Nature (MAN) network in the Netherlands, Biogeosciences, 12, 5133–5142, https://doi.org/10.5194/bg-12-5133-2015, 2015.
Nguyen, P., Stefess, G., de Jonge, D., Snijder, A., Hermans, P., van Loon, S., and Hoogerbrugge, R.: Evaluation of the representativeness of the Dutch air quality monitoring stations: The national, Amsterdam, Noord-Holland, Rijnmond-area, Limburg and Noord-Brabant networks, RIVM report 680704021, 2013.
Oxley, T. and ApSimon, H.: Space, time and nesting integrated assessment models, Environ. Modell. Softw., 22, 1732–1749, 2007.
Schaap, M., Cuvelier, C., Hendriks, C., Bessagnet, B., Baldasano, J. M., Colette, A., Thunis, P., Karam, D., Fagerli, H., Graff, A., Kranenburg, R., Nyiri, A., Pay, M. T., Rouil, L., Schulz, M., Simpson, D., Stern, R., Terrenoire, E., and Wind, P.: Performance of European chemistry transport models as function of horizontal resolution, Atmos. Environ., 112, 90–105, 2015.
Simpson, D., Butterbach-Bahl, K., Fagerli, H., Kesik, M., Skiba, U., and Tang, S.: Deposition and emissions of reactive nitrogen over European forests: a modelling study, Atmos. Environ., 40, 5712–5726, 2006.
Simpson, D., Benedictow, A., Berge, H., Bergström, R., Emberson, L. D., Fagerli, H., Flechard, C. R., Hayman, G. D., Gauss, M., Jonson, J. E., Jenkin, M. E., Nyíri, A., Richter, C., Semeena, V. S., Tsyro, S., Tuovinen, J.-P., Valdebenito, Á., and Wind, P.: The EMEP MSC-W chemical transport model – technical description, Atmos. Chem. Phys., 12, 7825–7865, https://doi.org/10.5194/acp-12-7825-2012, 2012.
Spanton, A. M., Hall, D. J., Dunkerley, F., Griffiths, R. F., and Bennett, M.: A Dispersion Model Intercomparison Archive. Proceedings of 9th Int. Conf. on Harmonisation within Atmospheric Dispersion Modelling for Regulatory Purposes, Garmisch-Partenkirchen, Germany, 1–4 June 2004.
Sutton, M. A., Tang, Y. S., Dragosits, U., Fournier, N., Dore, A. J., Smith, R. I., Weston, K. J., and Fowler, D.: A spatial analysis of atmospheric ammonia and ammonium in the UK, The Scientific World Journal, 1 Suppl 2, 275–286, 2001.
Theobald, M. R., Løfstrøm, P., Walker, J., Andersen, H. V., Pedersen, P., Vallejo, A., and Sutton, M. A.: An intercomparison of models used to simulate the short-range atmospheric dispersion of agricultural ammonia emissions, Environ. Modell. Softw., 37, 90–102, 2012.
Vieno, M., Dore, A. J., Stevenson, D. S., Doherty, R., Heal, M. R., Reis, S., Hallsworth, S., Tarrason, L., Wind, P., Fowler, D., Simpson, D., and Sutton, M. A.: Modelling surface ozone during the 2003 heat-wave in the UK, Atmos. Chem. Phys., 10, 7963–7978, https://doi.org/10.5194/acp-10-7963-2010, 2010.
Vieno, M., Heal, M. R., Hallsworth, S., Famulari, D., Doherty, R. M., Dore, A. J., Tang, Y. S., Braban, C. F., Leaver, D., Sutton, M. A., and Reis, S.: The role of long-range transport and domestic emissions in determining atmospheric secondary inorganic particle concentrations across the UK, Atmos. Chem. Phys., 14, 8435–8447, https://doi.org/10.5194/acp-14-8435-2014, 2014.
Vogt, E., Dragosits, U., Braban, C. F., Theobald, M. R., Dore, A. J., van Dijk, N., Tang, Y. S., McDonald, C., Murray, S., Rees, R. M., and Sutton, M. A.: Heterogeneity of atmospheric ammonia at the landscape scale and consequences for environmental impact assessment, Environ. Pollut., 179, 120–131, 2013.
von Bobrutzki, K., Braban, C. F., Famulari, D., Jones, S. K., Blackall, T., Smith, T. E. L., Blom, M., Coe, H., Gallagher, M., Ghalaieny, M., McGillen, M. R., Percival, C. J., Whitehead, J. D., Ellis, R., Murphy, J., Mohacsi, A., Pogany, A., Junninen, H., Rantanen, S., Sutton, M. A., and Nemitz, E.: Field inter-comparison of eleven atmospheric ammonia measurement techniques, Atmos. Meas. Tech., 3, 91–112, https://doi.org/10.5194/amt-3-91-2010, 2010.
Zhang, Y. and Wu, S.: Understanding of the Fate of Atmospheric Pollutants Using a Process Analysis Tool in a 3-D Regional Air Quality Model at a Fine Grid Scale, Atmospheric and Climate Sciences, 3, 18-30, https://doi.org/10.4236/acs.2013.31004, 2013.
Short summary
Impacts of air pollution at a continental scale, estimated using air quality models, can potentially be greatly under- or overestimated due to the low spatial resolution used (grid cells of 10–50 km). We present a method to estimate the spatial variations in air quality within a model grid cell by combining high-resolution emission data with estimates of short range dispersion. This simple but robust technique has the potential to improve estimates of air quality impacts at a continental scale.
Impacts of air pollution at a continental scale, estimated using air quality models, can...
