Articles | Volume 14, issue 11
https://doi.org/10.5194/gmd-14-7001-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-14-7001-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper
| 
18 Nov 2021
Model description paper |
| 18 Nov 2021
| 18 Nov 2021
Black carbon modeling in urban areas: investigating the influence of resuspension and non-exhaust emissions in streets using the Street-in-Grid model for inert particles (SinG-inert)
CEREA, École des Ponts ParisTech, EDF R&D, Champs-sur-Marne, France
Paris City, Department of Green Spaces and Environment, Paris, France
Jérémy Vigneron
AIRPARIF, Paris, France
Christophe Debert
AIRPARIF, Paris, France
Olivier Chrétien
Paris City, Department of Green Spaces and Environment, Paris, France
CEREA, École des Ponts ParisTech, EDF R&D, Champs-sur-Marne, France
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Atmos. Chem. Phys., 25, 3363–3387, https://doi.org/10.5194/acp-25-3363-2025, https://doi.org/10.5194/acp-25-3363-2025, 2025
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To accurately represent the population exposure to outdoor concentrations of pollutants of interest to health (NO2, PM2.5, black carbon, and ultrafine particles), multi-scale modelling down to the street scale is set up and evaluated using measurements from field campaigns. An exposure scaling factor is defined, allowing regional-scale simulations to be corrected to evaluate population exposure. Urban heterogeneities strongly influence NO2, black carbon, and ultrafine particles but less strongly PM2.5.
Alexis Squarcioni, Yelva Roustan, Myrto Valari, Youngseob Kim, Karine Sartelet, Lya Lugon, Fabrice Dugay, and Robin Voitot
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This study highlights the interest of using a street-network model to estimate pollutant concentrations of NOx, NO2, and PM2.5 in heterogeneous urban areas, particularly those adjacent to highways, compared with the subgrid-scale approach embedded in the 3D Eulerian model CHIMERE. However, the study also reveals comparable performances between the two approaches for the aforementioned pollutants in areas near the city center, where urban characteristics are more uniform.
Laurent Menut, Arineh Cholakian, Romain Pennel, Guillaume Siour, Sylvain Mailler, Myrto Valari, Lya Lugon, and Yann Meurdesoif
Geosci. Model Dev., 17, 5431–5457, https://doi.org/10.5194/gmd-17-5431-2024, https://doi.org/10.5194/gmd-17-5431-2024, 2024
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A new version of the CHIMERE model is presented. This version contains both computational and physico-chemical changes. The computational changes make it easy to choose the variables to be extracted as a result, including values of maximum sub-hourly concentrations. Performance tests show that the model is 1.5 to 2 times faster than the previous version for the same setup. Processes such as turbulence, transport schemes and dry deposition have been modified and updated.
Alice Maison, Lya Lugon, Soo-Jin Park, Alexia Baudic, Christopher Cantrell, Florian Couvidat, Barbara D'Anna, Claudia Di Biagio, Aline Gratien, Valérie Gros, Carmen Kalalian, Julien Kammer, Vincent Michoud, Jean-Eudes Petit, Marwa Shahin, Leila Simon, Myrto Valari, Jérémy Vigneron, Andrée Tuzet, and Karine Sartelet
Atmos. Chem. Phys., 24, 6011–6046, https://doi.org/10.5194/acp-24-6011-2024, https://doi.org/10.5194/acp-24-6011-2024, 2024
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This study presents the development of a bottom-up inventory of urban tree biogenic emissions. Emissions are computed for each tree based on their location and characteristics and are integrated in the regional air quality model WRF-CHIMERE. The impact of these biogenic emissions on air quality is quantified for June–July 2022. Over Paris city, urban trees increase the concentrations of particulate organic matter by 4.6 %, of PM2.5 by 0.6 %, and of ozone by 1.0 % on average over 2 months.
Youngseob Kim, Lya Lugon, Alice Maison, Thibaud Sarica, Yelva Roustan, Myrto Valari, Yang Zhang, Michel André, and Karine Sartelet
Geosci. Model Dev., 15, 7371–7396, https://doi.org/10.5194/gmd-15-7371-2022, https://doi.org/10.5194/gmd-15-7371-2022, 2022
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This paper presents the latest version of the street-network model MUNICH, v2.0. The description of MUNICH v1.0, which models gas-phase pollutants in a street network, was published in GMD in 2018. Since then, major modifications have been made to MUNICH. The comprehensive aerosol model SSH-aerosol is now coupled to MUNICH to simulate primary and secondary aerosol concentrations. New parameterisations have also been introduced. Test cases are defined to illustrate the new model functionalities.
Lya Lugon, Karine Sartelet, Youngseob Kim, Jérémy Vigneron, and Olivier Chrétien
Atmos. Chem. Phys., 20, 7717–7740, https://doi.org/10.5194/acp-20-7717-2020, https://doi.org/10.5194/acp-20-7717-2020, 2020
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This study presents a new version of the multi-scale model Street-in-Grid (SinG) that interconnects regional and local scales in air-quality modeling in urban areas. The new version of SinG performs the finest coupling between transport and chemistry, leading to a numerically stable partitioning between NO and NO2. Multi-scale, local-scale and regional-scale simulations of NO, NO2 and NOx over Paris are compared to observations, and SinG shows good performance for both local and regional scales.
Karine Sartelet, Zhizhao Wang, Youngseob Kim, Victor Lannuque, and Florian Couvidat
EGUsphere, https://doi.org/10.5194/egusphere-2025-2191, https://doi.org/10.5194/egusphere-2025-2191, 2025
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
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SSH-aerosol v2 simulates the evolution of primary and secondary pollutants via gas-phase chemistry, aerosol dynamics (including ultrafine particles), and intra-particle reactions. It uses a sectional approach for size and composition, includes a wall-loss module, and links gas-phase mechanisms of different complexity to secondary organic aerosol formation. Representation of particle phase composition allows viscosity and non-ideality to be taken into account.
Soo-Jin Park, Lya Lugon, Oscar Jacquot, Youngseob Kim, Alexia Baudic, Barbara D'Anna, Ludovico Di Antonio, Claudia Di Biagio, Fabrice Dugay, Olivier Favez, Véronique Ghersi, Aline Gratien, Julien Kammer, Jean-Eudes Petit, Olivier Sanchez, Myrto Valari, Jérémy Vigneron, and Karine Sartelet
Atmos. Chem. Phys., 25, 3363–3387, https://doi.org/10.5194/acp-25-3363-2025, https://doi.org/10.5194/acp-25-3363-2025, 2025
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To accurately represent the population exposure to outdoor concentrations of pollutants of interest to health (NO2, PM2.5, black carbon, and ultrafine particles), multi-scale modelling down to the street scale is set up and evaluated using measurements from field campaigns. An exposure scaling factor is defined, allowing regional-scale simulations to be corrected to evaluate population exposure. Urban heterogeneities strongly influence NO2, black carbon, and ultrafine particles but less strongly PM2.5.
Alexis Squarcioni, Yelva Roustan, Myrto Valari, Youngseob Kim, Karine Sartelet, Lya Lugon, Fabrice Dugay, and Robin Voitot
Atmos. Chem. Phys., 25, 93–117, https://doi.org/10.5194/acp-25-93-2025, https://doi.org/10.5194/acp-25-93-2025, 2025
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This study highlights the interest of using a street-network model to estimate pollutant concentrations of NOx, NO2, and PM2.5 in heterogeneous urban areas, particularly those adjacent to highways, compared with the subgrid-scale approach embedded in the 3D Eulerian model CHIMERE. However, the study also reveals comparable performances between the two approaches for the aforementioned pollutants in areas near the city center, where urban characteristics are more uniform.
Oscar Jacquot and Karine Sartelet
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-150, https://doi.org/10.5194/gmd-2024-150, 2024
Revised manuscript accepted for GMD
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As the health impact of ultrafine particles is better understood, modeling the size distribution and the number concentration becomes increasingly important. A new analytic formulation is presented to compute coagulation partition coefficients, allowing to lower down the numerical diffusion associated to the resolution of aerosol dynamics. The significance of this effect is assessed over Greater Paris with a chemistry transport model, using different size resolution of the particle distribution.
Victor Lannuque and Karine Sartelet
Atmos. Chem. Phys., 24, 8589–8606, https://doi.org/10.5194/acp-24-8589-2024, https://doi.org/10.5194/acp-24-8589-2024, 2024
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Large uncertainties remain in understanding secondary organic aerosol (SOA) formation and speciation from naphthalene oxidation. This study details the development of the first near-explicit chemical scheme for naphthalene oxidation by OH, which includes kinetic and mechanistic data, and is able to reproduce most of the experimentally identified products in both gas and particle phases.
Laurent Menut, Arineh Cholakian, Romain Pennel, Guillaume Siour, Sylvain Mailler, Myrto Valari, Lya Lugon, and Yann Meurdesoif
Geosci. Model Dev., 17, 5431–5457, https://doi.org/10.5194/gmd-17-5431-2024, https://doi.org/10.5194/gmd-17-5431-2024, 2024
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A new version of the CHIMERE model is presented. This version contains both computational and physico-chemical changes. The computational changes make it easy to choose the variables to be extracted as a result, including values of maximum sub-hourly concentrations. Performance tests show that the model is 1.5 to 2 times faster than the previous version for the same setup. Processes such as turbulence, transport schemes and dry deposition have been modified and updated.
Alice Maison, Lya Lugon, Soo-Jin Park, Alexia Baudic, Christopher Cantrell, Florian Couvidat, Barbara D'Anna, Claudia Di Biagio, Aline Gratien, Valérie Gros, Carmen Kalalian, Julien Kammer, Vincent Michoud, Jean-Eudes Petit, Marwa Shahin, Leila Simon, Myrto Valari, Jérémy Vigneron, Andrée Tuzet, and Karine Sartelet
Atmos. Chem. Phys., 24, 6011–6046, https://doi.org/10.5194/acp-24-6011-2024, https://doi.org/10.5194/acp-24-6011-2024, 2024
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This study presents the development of a bottom-up inventory of urban tree biogenic emissions. Emissions are computed for each tree based on their location and characteristics and are integrated in the regional air quality model WRF-CHIMERE. The impact of these biogenic emissions on air quality is quantified for June–July 2022. Over Paris city, urban trees increase the concentrations of particulate organic matter by 4.6 %, of PM2.5 by 0.6 %, and of ozone by 1.0 % on average over 2 months.
Evangelia Kostenidou, Baptiste Marques, Brice Temime-Roussel, Yao Liu, Boris Vansevenant, Karine Sartelet, and Barbara D'Anna
Atmos. Chem. Phys., 24, 2705–2729, https://doi.org/10.5194/acp-24-2705-2024, https://doi.org/10.5194/acp-24-2705-2024, 2024
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Secondary organic aerosol (SOA) from gasoline vehicles can be a significant source of particulate matter in urban areas. Here the chemical composition of secondary volatile organic compounds and SOA produced by photo-oxidation of Euro 5 gasoline vehicle emissions was studied. The volatility of the SOA formed was calculated. Except for the temperature and the concentration of the aerosol, additional parameters may play a role in the gas-to-particle partitioning.
Victor Lannuque, Barbara D'Anna, Evangelia Kostenidou, Florian Couvidat, Alvaro Martinez-Valiente, Philipp Eichler, Armin Wisthaler, Markus Müller, Brice Temime-Roussel, Richard Valorso, and Karine Sartelet
Atmos. Chem. Phys., 23, 15537–15560, https://doi.org/10.5194/acp-23-15537-2023, https://doi.org/10.5194/acp-23-15537-2023, 2023
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Large uncertainties remain in understanding secondary organic aerosol (SOA) formation from toluene oxidation. In this study, speciation measurements in gaseous and particulate phases were carried out, providing partitioning and volatility data on individual toluene SOA components at different temperatures. A new detailed oxidation mechanism was developed to improve modeled speciation, and effects of different processes involved in gas–particle partitioning at the molecular scale are explored.
Thibaud Sarica, Alice Maison, Yelva Roustan, Matthias Ketzel, Steen Solvang Jensen, Youngseob Kim, Christophe Chaillou, and Karine Sartelet
Geosci. Model Dev., 16, 5281–5303, https://doi.org/10.5194/gmd-16-5281-2023, https://doi.org/10.5194/gmd-16-5281-2023, 2023
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A new version of the Model of Urban Network of Intersecting Canyons and Highways (MUNICH) is developed to represent heterogeneities of concentrations in streets. The street volume is discretized vertically and horizontally to limit the artificial dilution of emissions and concentrations. This new version is applied to street networks in Copenhagen and Paris. The comparisons to observations are improved, with higher concentrations of pollutants emitted by traffic at the bottom of the street.
Chao Lin, Yunyi Wang, Ryozo Ooka, Cédric Flageul, Youngseob Kim, Hideki Kikumoto, Zhizhao Wang, and Karine Sartelet
Atmos. Chem. Phys., 23, 1421–1436, https://doi.org/10.5194/acp-23-1421-2023, https://doi.org/10.5194/acp-23-1421-2023, 2023
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In this study, SSH-aerosol, a modular box model that simulates the evolution of gas, primary, and secondary aerosols, is coupled with the computational fluid dynamics (CFD) software, OpenFOAM and Code_Saturne. The transient dispersion of pollutants emitted from traffic in a street canyon of Greater Paris is simulated. The coupled model achieved better agreement in NO2 and PM10 with measurement data than the conventional CFD simulation which regards pollutants as passive scalars.
Zhizhao Wang, Florian Couvidat, and Karine Sartelet
Geosci. Model Dev., 15, 8957–8982, https://doi.org/10.5194/gmd-15-8957-2022, https://doi.org/10.5194/gmd-15-8957-2022, 2022
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Air quality models need to reliably predict secondary organic aerosols (SOAs) at a reasonable computational cost. Thus, we developed GENOA v1.0, a mechanism reduction algorithm that preserves the accuracy of detailed gas-phase chemical mechanisms for SOA formation, thereby improving the practical use of actual chemistry in SOA models. With GENOA, a near-explicit chemical scheme was reduced to 2 % of its original size and computational time, with an average error of less than 3 %.
Youngseob Kim, Lya Lugon, Alice Maison, Thibaud Sarica, Yelva Roustan, Myrto Valari, Yang Zhang, Michel André, and Karine Sartelet
Geosci. Model Dev., 15, 7371–7396, https://doi.org/10.5194/gmd-15-7371-2022, https://doi.org/10.5194/gmd-15-7371-2022, 2022
Short summary
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This paper presents the latest version of the street-network model MUNICH, v2.0. The description of MUNICH v1.0, which models gas-phase pollutants in a street network, was published in GMD in 2018. Since then, major modifications have been made to MUNICH. The comprehensive aerosol model SSH-aerosol is now coupled to MUNICH to simulate primary and secondary aerosol concentrations. New parameterisations have also been introduced. Test cases are defined to illustrate the new model functionalities.
Alice Maison, Cédric Flageul, Bertrand Carissimo, Yunyi Wang, Andrée Tuzet, and Karine Sartelet
Atmos. Chem. Phys., 22, 9369–9388, https://doi.org/10.5194/acp-22-9369-2022, https://doi.org/10.5194/acp-22-9369-2022, 2022
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This paper presents a parameterization of the tree crown effect on air flow and pollutant dispersion in a street network model used to simulate air quality at the street level. The new parameterization is built using a finer-scale model (computational fluid dynamics). The tree effect increases with the leaf area index and the crown volume fraction of the trees; the street horizontal velocity is reduced by up to 68 % and the vertical transfer into or out of the street by up to 23 %.
Karine Sartelet, Youngseob Kim, Florian Couvidat, Maik Merkel, Tuukka Petäjä, Jean Sciare, and Alfred Wiedensohler
Atmos. Chem. Phys., 22, 8579–8596, https://doi.org/10.5194/acp-22-8579-2022, https://doi.org/10.5194/acp-22-8579-2022, 2022
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A methodology is defined to estimate number emissions from an inventory providing mass emissions. Number concentrations are simulated over Greater Paris using different nucleation parameterisations (binary, ternary involving sulfuric acid and ammonia, and heteromolecular involving sulfuric acid and extremely low-volatility organics, ELVOCs). The comparisons show that ternary nucleation may not be a dominant process for new particle formation in cities, but they stress the role of ELVOCs.
Boris Vansevenant, Cédric Louis, Corinne Ferronato, Ludovic Fine, Patrick Tassel, Pascal Perret, Evangelia Kostenidou, Brice Temime-Roussel, Barbara D'Anna, Karine Sartelet, Véronique Cerezo, and Yao Liu
Atmos. Meas. Tech., 14, 7627–7655, https://doi.org/10.5194/amt-14-7627-2021, https://doi.org/10.5194/amt-14-7627-2021, 2021
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A new method was developed to correct wall losses of particles on Teflon walls using a new environmental chamber. It was applied to experiments with six diesel vehicles (Euro 3 to 6), tested on a chassis dynamometer. Emissions of particles and precursors were obtained under urban and motorway conditions. The chamber experiments help understand the role of physical processes in diesel particle evolutions in the dark. These results can be applied to situations such as tunnels or winter rush hours.
Eve-Agnès Fiorentino, Henri Wortham, and Karine Sartelet
Geosci. Model Dev., 14, 2747–2780, https://doi.org/10.5194/gmd-14-2747-2021, https://doi.org/10.5194/gmd-14-2747-2021, 2021
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Indoor air quality (IAQ) is strongly influenced by reactivity with surfaces, which is called heterogeneous reactivity. To date, this reactivity is barely integrated into numerical models due to the strong uncertainties it is subjected to. In this work, an open-source IAQ model, called the H2I model, is developed to consider both gas-phase and heterogeneous reactivity and simulate indoor concentrations of inorganic compounds.
Eve-Agnès Fiorentino, Henri Wortham, and Karine Sartelet
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2020-192, https://doi.org/10.5194/gmd-2020-192, 2020
Preprint withdrawn
Lya Lugon, Karine Sartelet, Youngseob Kim, Jérémy Vigneron, and Olivier Chrétien
Atmos. Chem. Phys., 20, 7717–7740, https://doi.org/10.5194/acp-20-7717-2020, https://doi.org/10.5194/acp-20-7717-2020, 2020
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This study presents a new version of the multi-scale model Street-in-Grid (SinG) that interconnects regional and local scales in air-quality modeling in urban areas. The new version of SinG performs the finest coupling between transport and chemistry, leading to a numerically stable partitioning between NO and NO2. Multi-scale, local-scale and regional-scale simulations of NO, NO2 and NOx over Paris are compared to observations, and SinG shows good performance for both local and regional scales.
Marwa Majdi, Karine Sartelet, Grazia Maria Lanzafame, Florian Couvidat, Youngseob Kim, Mounir Chrit, and Solene Turquety
Atmos. Chem. Phys., 19, 5543–5569, https://doi.org/10.5194/acp-19-5543-2019, https://doi.org/10.5194/acp-19-5543-2019, 2019
Youngseob Kim, Karine Sartelet, and Florian Couvidat
Atmos. Chem. Phys., 19, 1241–1261, https://doi.org/10.5194/acp-19-1241-2019, https://doi.org/10.5194/acp-19-1241-2019, 2019
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Assumptions (ideality and thermodynamic equilibrium) commonly made in 3-dimensional air quality models were reconsidered to evaluate their impacts on secondary organic aerosol (SOA) formation. Non-ideality (short-, medium- and long-range interactions of organics and inorganics) influences SOA concentrations by about 30 % over Europe. If SOA are highly viscous rather than inviscid, hydrophobic SOA concentrations increase by 6 % but can increase by an order of magnitude for volatile compounds.
Marwa Majdi, Solene Turquety, Karine Sartelet, Carole Legorgeu, Laurent Menut, and Youngseob Kim
Atmos. Chem. Phys., 19, 785–812, https://doi.org/10.5194/acp-19-785-2019, https://doi.org/10.5194/acp-19-785-2019, 2019
Mounir Chrit, Karine Sartelet, Jean Sciare, Marwa Majdi, José Nicolas, Jean-Eudes Petit, and François Dulac
Atmos. Chem. Phys., 18, 18079–18100, https://doi.org/10.5194/acp-18-18079-2018, https://doi.org/10.5194/acp-18-18079-2018, 2018
Mounir Chrit, Karine Sartelet, Jean Sciare, Jorge Pey, José B. Nicolas, Nicolas Marchand, Evelyn Freney, Karine Sellegri, Matthias Beekmann, and François Dulac
Atmos. Chem. Phys., 18, 9631–9659, https://doi.org/10.5194/acp-18-9631-2018, https://doi.org/10.5194/acp-18-9631-2018, 2018
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Fine particulate matter (PM) in the atmosphere is of concern due to its effects on health, climate, ecosystems and biological cycles, and visibility.
These effects are especially important in the Mediterranean region. In this study, the air quality model Polyphemus is used to understand the
sources of inorganic and organic particles in the western Mediterranean and evaluate the uncertainties linked to the model parameters and hypotheses related to condensation/evaporation in the model.
Arineh Cholakian, Matthias Beekmann, Augustin Colette, Isabelle Coll, Guillaume Siour, Jean Sciare, Nicolas Marchand, Florian Couvidat, Jorge Pey, Valerie Gros, Stéphane Sauvage, Vincent Michoud, Karine Sellegri, Aurélie Colomb, Karine Sartelet, Helen Langley DeWitt, Miriam Elser, André S. H. Prévot, Sonke Szidat, and François Dulac
Atmos. Chem. Phys., 18, 7287–7312, https://doi.org/10.5194/acp-18-7287-2018, https://doi.org/10.5194/acp-18-7287-2018, 2018
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In this work, four schemes for the simulation of organic aerosols in the western Mediterranean basin are added to the CHIMERE chemistry–transport model; the resulting simulations are then compared to measurements obtained from ChArMEx. It is concluded that the scheme taking into account the fragmentation and the formation of nonvolatile organic aerosols corresponds better to measurements; the major source of this aerosol in the western Mediterranean is found to be of biogenic origin.
Evelyn Freney, Karine Sellegri, Mounir Chrit, Kouji Adachi, Joel Brito, Antoine Waked, Agnès Borbon, Aurélie Colomb, Régis Dupuy, Jean-Marc Pichon, Laetitia Bouvier, Claire Delon, Corinne Jambert, Pierre Durand, Thierry Bourianne, Cécile Gaimoz, Sylvain Triquet, Anaïs Féron, Matthias Beekmann, François Dulac, and Karine Sartelet
Atmos. Chem. Phys., 18, 7041–7056, https://doi.org/10.5194/acp-18-7041-2018, https://doi.org/10.5194/acp-18-7041-2018, 2018
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The focus of these experiments, within the ChArMEx project, were to better understand the chemical properties of ambient aerosols over the Mediterranean region. A series of airborne measurements were performed aboard the French research aircraft, the ATR42, during the summer period. Aerosol and gas-phase chemical mass spectrometry allowed us to understand the sources and formation of organic aerosols. Numerical models were incorporated into this study to help interpret our observations.
Mounir Chrit, Karine Sartelet, Jean Sciare, Jorge Pey, Nicolas Marchand, Florian Couvidat, Karine Sellegri, and Matthias Beekmann
Atmos. Chem. Phys., 17, 12509–12531, https://doi.org/10.5194/acp-17-12509-2017, https://doi.org/10.5194/acp-17-12509-2017, 2017
Kevin Berland, Clémence Rose, Jorge Pey, Anais Culot, Evelyn Freney, Nikolaos Kalivitis, Giorgios Kouvarakis, José Carlos Cerro, Marc Mallet, Karine Sartelet, Matthias Beckmann, Thierry Bourriane, Greg Roberts, Nicolas Marchand, Nikolaos Mihalopoulos, and Karine Sellegri
Atmos. Chem. Phys., 17, 9567–9583, https://doi.org/10.5194/acp-17-9567-2017, https://doi.org/10.5194/acp-17-9567-2017, 2017
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New particle formation (NPF) from gas-phase precursors is a process that is expected to drive the total number concentration of particles in the atmosphere. Here we use measurements performed simultaneously in Corsica, Crete and Mallorca to show that the spatial extent of the NPF events are several hundreds of kilometers large. Airborne measurements additionally show that nanoparticles in the marine atmosphere can either be of marine origin or from higher altitudes above the continent.
Jovanna Arndt, Jean Sciare, Marc Mallet, Greg C. Roberts, Nicolas Marchand, Karine Sartelet, Karine Sellegri, François Dulac, Robert M. Healy, and John C. Wenger
Atmos. Chem. Phys., 17, 6975–7001, https://doi.org/10.5194/acp-17-6975-2017, https://doi.org/10.5194/acp-17-6975-2017, 2017
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The chemical composition of individual PM2.5 particles was measured at a background site on Corsica in the Mediterranean to determine the contribution of different sources to background aerosol in the region. Most of the particles were from fossil fuel combustion and biomass burning, transported to the site from France, Italy and eastern Europe, and also accumulated other species en route. This work shows that largest impact on air quality in the Mediterranean is from anthropogenic emissions.
C. Di Biagio, L. Doppler, C. Gaimoz, N. Grand, G. Ancellet, J.-C. Raut, M. Beekmann, A. Borbon, K. Sartelet, J.-L. Attié, F. Ravetta, and P. Formenti
Atmos. Chem. Phys., 15, 9611–9630, https://doi.org/10.5194/acp-15-9611-2015, https://doi.org/10.5194/acp-15-9611-2015, 2015
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Observations from this study indicate that continental pollution largely affects the atmospheric composition and structure of the western Mediterranean basin. Pollution plumes reach 3000-4000 m in altitude and present a very complex and highly stratified structure, characterized by fresh and aged layers both in the boundary layer and in the free troposphere. Also we report the observations of high levels of ultrafine particles over the basin, possibly linked to new particle formation events.
S. Zhu, K. N. Sartelet, and C. Seigneur
Geosci. Model Dev., 8, 1595–1612, https://doi.org/10.5194/gmd-8-1595-2015, https://doi.org/10.5194/gmd-8-1595-2015, 2015
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This article presents the Size-Composition Resolved Aerosol Model (SCRAM) for simulating the dynamics of externally mixed atmospheric particles. The model is first validated by comparison with a reference solution and with results of simulations using internally mixed particles. Then, the importance of representing the mixing state when modelling atmospheric aerosol concentrations is investigated in a box model simulation using data representative of air pollution in Greater Paris.
F. Couvidat and K. Sartelet
Geosci. Model Dev., 8, 1111–1138, https://doi.org/10.5194/gmd-8-1111-2015, https://doi.org/10.5194/gmd-8-1111-2015, 2015
Y. Wang, K. N. Sartelet, M. Bocquet, P. Chazette, M. Sicard, G. D'Amico, J. F. Léon, L. Alados-Arboledas, A. Amodeo, P. Augustin, J. Bach, L. Belegante, I. Binietoglou, X. Bush, A. Comerón, H. Delbarre, D. García-Vízcaino, J. L. Guerrero-Rascado, M. Hervo, M. Iarlori, P. Kokkalis, D. Lange, F. Molero, N. Montoux, A. Muñoz, C. Muñoz, D. Nicolae, A. Papayannis, G. Pappalardo, J. Preissler, V. Rizi, F. Rocadenbosch, K. Sellegri, F. Wagner, and F. Dulac
Atmos. Chem. Phys., 14, 12031–12053, https://doi.org/10.5194/acp-14-12031-2014, https://doi.org/10.5194/acp-14-12031-2014, 2014
Y. Wang, K. N. Sartelet, M. Bocquet, and P. Chazette
Atmos. Chem. Phys., 14, 3511–3532, https://doi.org/10.5194/acp-14-3511-2014, https://doi.org/10.5194/acp-14-3511-2014, 2014
Y. Zhang, K. Sartelet, S.-Y. Wu, and C. Seigneur
Atmos. Chem. Phys., 13, 6807–6843, https://doi.org/10.5194/acp-13-6807-2013, https://doi.org/10.5194/acp-13-6807-2013, 2013
Y. Zhang, K. Sartelet, S. Zhu, W. Wang, S.-Y. Wu, X. Zhang, K. Wang, P. Tran, C. Seigneur, and Z.-F. Wang
Atmos. Chem. Phys., 13, 6845–6875, https://doi.org/10.5194/acp-13-6845-2013, https://doi.org/10.5194/acp-13-6845-2013, 2013
A. Waked, C. Seigneur, F. Couvidat, Y. Kim, K. Sartelet, C. Afif, A. Borbon, P. Formenti, and S. Sauvage
Atmos. Chem. Phys., 13, 5873–5886, https://doi.org/10.5194/acp-13-5873-2013, https://doi.org/10.5194/acp-13-5873-2013, 2013
E. Solazzo, R. Bianconi, G. Pirovano, M. D. Moran, R. Vautard, C. Hogrefe, K. W. Appel, V. Matthias, P. Grossi, B. Bessagnet, J. Brandt, C. Chemel, J. H. Christensen, R. Forkel, X. V. Francis, A. B. Hansen, S. McKeen, U. Nopmongcol, M. Prank, K. N. Sartelet, A. Segers, J. D. Silver, G. Yarwood, J. Werhahn, J. Zhang, S. T. Rao, and S. Galmarini
Geosci. Model Dev., 6, 791–818, https://doi.org/10.5194/gmd-6-791-2013, https://doi.org/10.5194/gmd-6-791-2013, 2013
F. Couvidat, Y. Kim, K. Sartelet, C. Seigneur, N. Marchand, and J. Sciare
Atmos. Chem. Phys., 13, 983–996, https://doi.org/10.5194/acp-13-983-2013, https://doi.org/10.5194/acp-13-983-2013, 2013
Y. Wang, K. N. Sartelet, M. Bocquet, and P. Chazette
Atmos. Chem. Phys., 13, 269–283, https://doi.org/10.5194/acp-13-269-2013, https://doi.org/10.5194/acp-13-269-2013, 2013
Related subject area
Atmospheric sciences
ClimKern v1.2: a new Python package and kernel repository for calculating radiative feedbacks
Accounting for effects of coagulation and model uncertainties in particle number concentration estimates based on measurements from sampling lines – a Bayesian inversion approach with SLIC v1.0
Top-down CO emission estimates using TROPOMI CO data in the TM5-4DVAR (r1258) inverse modeling suit
The Multi-Compartment Hg Modeling and Analysis Project (MCHgMAP): mercury modeling to support international environmental policy
Similarity-based analysis of atmospheric organic compounds for machine learning applications
Porting the Meso-NH atmospheric model on different GPU architectures for the next generation of supercomputers (version MESONH-v55-OpenACC)
Estimation of aerosol and cloud radiative heating rate in the tropical stratosphere using a radiative kernel method
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
Modelling extensive green roof CO2 exchanges in the TEB urban canopy model
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
A dynamical process-based model for quantifying global agricultural ammonia emissions – AMmonia–CLIMate v1.0 (AMCLIM v1.0) – Part 2: livestock farming
Least travel time ray tracer, version Two (LTT v2) adapted to the grid geometry of the OpenIFS atmospheric model
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
Development of the CMA-GFS-AERO 4D-Var assimilation system v1.0 – Part 1: System description
The third Met Office Unified Model-JULES Regional Atmosphere and Land Configuration, RAL3
Tyler P. Janoski, Ivan Mitevski, Ryan J. Kramer, Michael Previdi, and Lorenzo M. Polvani
Geosci. Model Dev., 18, 3065–3079, https://doi.org/10.5194/gmd-18-3065-2025, https://doi.org/10.5194/gmd-18-3065-2025, 2025
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We developed ClimKern, a Python package and radiative kernel repository, to simplify calculating radiative feedbacks and make climate sensitivity studies more reproducible. Testing of ClimKern with sample climate model data reveals that radiative kernel choice may be more important than previously thought, especially in polar regions. Our work highlights the need for kernel sensitivity analyses to be included in future studies.
Matti Niskanen, Aku Seppänen, Henri Oikarinen, Miska Olin, Panu Karjalainen, Santtu Mikkonen, and Kari Lehtinen
Geosci. Model Dev., 18, 2983–3001, https://doi.org/10.5194/gmd-18-2983-2025, https://doi.org/10.5194/gmd-18-2983-2025, 2025
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Particle size is a key factor determining the properties of aerosol particles which have a major influence on the climate and on human health. When measuring the particle sizes, however, sometimes the sampling lines that transfer the aerosol to the measurement device distort the size distribution, making the measurement unreliable. We propose a method to correct for the distortions and estimate the true particle sizes, improving measurement accuracy.
Johann Rasmus Nüß, Nikos Daskalakis, Fabian Günther Piwowarczyk, Angelos Gkouvousis, Oliver Schneising, Michael Buchwitz, Maria Kanakidou, Maarten C. Krol, and Mihalis Vrekoussis
Geosci. Model Dev., 18, 2861–2890, https://doi.org/10.5194/gmd-18-2861-2025, https://doi.org/10.5194/gmd-18-2861-2025, 2025
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We estimate carbon monoxide emissions through inverse modeling, an approach where measurements of tracers in the atmosphere are fed to a model to calculate backwards in time (inverse) where the tracers came from. We introduce measurements from a new satellite instrument and show that, in most places globally, these on their own sufficiently constrain the emissions. This alleviates the need for additional datasets, which could shorten the delay for future carbon monoxide source estimates.
Ashu Dastoor, Hélène Angot, Johannes Bieser, Flora Brocza, Brock Edwards, Aryeh Feinberg, Xinbin Feng, Benjamin Geyman, Charikleia Gournia, Yipeng He, Ian M. Hedgecock, Ilia Ilyin, Jane Kirk, Che-Jen Lin, Igor Lehnherr, Robert Mason, David McLagan, Marilena Muntean, Peter Rafaj, Eric M. Roy, Andrei Ryjkov, Noelle E. Selin, Francesco De Simone, Anne L. Soerensen, Frits Steenhuisen, Oleg Travnikov, Shuxiao Wang, Xun Wang, Simon Wilson, Rosa Wu, Qingru Wu, Yanxu Zhang, Jun Zhou, Wei Zhu, and Scott Zolkos
Geosci. Model Dev., 18, 2747–2860, https://doi.org/10.5194/gmd-18-2747-2025, https://doi.org/10.5194/gmd-18-2747-2025, 2025
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This paper introduces the Multi-Compartment Mercury (Hg) Modeling and Analysis Project (MCHgMAP) aimed at informing the effectiveness evaluations of two multilateral environmental agreements: the Minamata Convention on Mercury and the Convention on Long-Range Transboundary Air Pollution. The experimental design exploits a variety of models (atmospheric, land, oceanic ,and multimedia mass balance models) to assess the short- and long-term influences of anthropogenic Hg releases into the environment.
Hilda Sandström and Patrick Rinke
Geosci. Model Dev., 18, 2701–2724, https://doi.org/10.5194/gmd-18-2701-2025, https://doi.org/10.5194/gmd-18-2701-2025, 2025
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Machine learning has the potential to aid the identification of organic molecules involved in aerosol formation. Yet, progress is stalled by a lack of curated atmospheric molecular datasets. Here, we compared atmospheric compounds with large molecular datasets used in machine learning and found minimal overlap with similarity algorithms. Our result underlines the need for collaborative efforts to curate atmospheric molecular data to facilitate machine learning models in atmospheric sciences.
Juan Escobar, Philippe Wautelet, Joris Pianezze, Florian Pantillon, Thibaut Dauhut, Christelle Barthe, and Jean-Pierre Chaboureau
Geosci. Model Dev., 18, 2679–2700, https://doi.org/10.5194/gmd-18-2679-2025, https://doi.org/10.5194/gmd-18-2679-2025, 2025
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The Meso-NH weather research code is adapted for GPUs using OpenACC, leading to significant performance and energy efficiency improvements. Called MESONH-v55-OpenACC, it includes enhanced memory management, communication optimizations and a new solver. On the AMD MI250X Adastra platform, it achieved up to 6× speedup and 2.3× energy efficiency gain compared to CPUs. Storm simulations at 100 m resolution show positive results, positioning the code for future use on exascale supercomputers.
Jie Gao, Yi Huang, Jonathon S. Wright, Ke Li, Tao Geng, and Qiurun Yu
Geosci. Model Dev., 18, 2569–2586, https://doi.org/10.5194/gmd-18-2569-2025, https://doi.org/10.5194/gmd-18-2569-2025, 2025
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The aerosol in the upper troposphere and stratosphere is highly variable, and its radiative effect is poorly understood. To estimate this effect, the radiative kernel is constructed and applied. The results show that the kernels can reproduce aerosol radiative effects and are expected to simulate stratospheric aerosol radiative effects. This approach reduces computational expense, is consistent with radiative model calculations, and can be applied to atmospheric models with speed requirements.
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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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.
Aurélien Mirebeau, Cécile de Munck, Bertrand Bonan, Christine Delire, Aude Lemonsu, Valéry Masson, and Stephan Weber
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-233, https://doi.org/10.5194/gmd-2024-233, 2025
Revised manuscript accepted for GMD
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The greening of cities is recommended to limit the effects of climate change. In particular, green roofs can provide numerous environmental benefits, such as urban cooling, water retention and carbon sequestration. The aim of this research is to develop a new module for calculating green roof CO2 fluxes within a model that can already simulate hydrological and thermal processes of such roofs. The calibration and evaluation of this module take advantage of long term experimental data.
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
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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
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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
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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
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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.
Jize Jiang, David S. Stevenson, Aimable Uwizeye, Giuseppe Tempio, Alessandra Falcucci, Flavia Casu, and Mark A. Sutton
EGUsphere, https://doi.org/10.5194/egusphere-2024-3803, https://doi.org/10.5194/egusphere-2024-3803, 2024
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A special model called AMmonia–CLIMate (AMCLIM) has been developed to understand and calculate NH3 emissions from livestock farming. It is estimated that about 30 % of excreted N from livestock was lost due to NH3 emissions from housing, manure management and land application of manure. High NH3 volatilization often occurred in hot regions, while poor management practices also result in significant N losses through NH3 emissions.
Maksym Vasiuta, Angel Navarro Trastoy, Sanam Motlaghzadeh, Lauri Tuppi, Torsten Mayer-Gürr, and Heikki Järvinen
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-136, https://doi.org/10.5194/gmd-2024-136, 2024
Revised manuscript accepted for GMD
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Propagation of electromagnetic signals in the Earth's neutral atmosphere inflicts errors in space geodetic observations. To model these errors as accurately as possible, it is necessary to use a signal ray tracing algorithm which is informed of the state of the atmosphere. We developed such algorithm and tested it by modelling errors in GNSS network observations. Our algorithm's main advantage is loss-less utilization of atmospheric information provided by numerical weather prediction models.
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
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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
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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
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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
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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
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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
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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.
Yongzhu Liu, Xiaoye Zhang, Wei Han, Chao Wang, Wenxing Jia, Deying Wang, Zhaorong Zhuang, and Xueshun Shen
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-148, https://doi.org/10.5194/gmd-2024-148, 2024
Revised manuscript accepted for GMD
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In order to investigate the feedbacks of chemical data assimilation on meteorological forecasts, we developed a strongly coupled chemistry meteorology four-dimensional variational (4D-Var) assimilation system, CMA-GFS-AERO 4D-Var, based on the framework of the incremental analysis scheme of the CMA-GFS operational global numerical weather model. The results show that assimilating BC observations can generate analysis increments not only for BC but also for atmospheric variables.
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
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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.
Cited articles
Abu-Allaban, M., Gillies, J. A., Gertler, A. W., Clayton, R., and Proffitt, D.: Tailpipe, resuspended road dust, and brake-wear emission factors from on-road vehicles, Atmos. Environ., 37, 5283–5293, https://doi.org/10.1016/j.atmosenv.2003.05.005, 2003. a, b
Amato, F., Pandolfi, M., Viana, M., Querol, X., Alastuey, A., and Moreno, T.: Spatial and chemical patterns of PM10 in road dust deposited in urban
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Awad, Y. A., Koutrakis, P., Coull, B. A., and Schwartz, J.: A spatio-temporal prediction model based on support vector machine regression: ambient black carbon in three New England states, Environ. Res., 159, 427–434, https://doi.org/10.1016/j.envres.2017.08.039, 2017. a
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Beji, A., Deboudt, K., Khardi, S., Muresan, B., Flament, P., Fourmentin, M., and Lumière, L.: Non-exhaust particle emissions under various driving conditions: Implications for sustainable mobility, Transport. Res. D-Tr. E., 81, 102290, https://doi.org/10.1016/j.trd.2020.102290, 2020. a, b, c
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Boniardi, L., Dons, E., Campo, L., Van Poppel, M., Panis, L. I., and Fustinoni, S.: Annual, seasonal, and morning rush hour land use regression models for black carbon in a school catchment area of Milan, Italy, Environ. Res., 176, 108520, https://doi.org/10.1016/j.envres.2019.06.001, 2019. a
Boutahar, J., Lacour, S., Mallet, V., Quélo, D., Roustan, Y., and Sportisse, B.: Development and validation of a fully modular platform for numerical modelling of air pollution: POLAIR, Int. J. Environ. Pollut., 22, 17–28, https://doi.org/10.1504/IJEP.2004.005474, 2004. a
Brasseur, O., Declerck, P., Heene, B., and Vanderstraeten, P.: Modelling Black Carbon concentrations in two busy street canyons in Brussels using CANSBC, Atmos. Environ., 101, 72–81, https://doi.org/10.1016/j.atmosenv.2014.10.049, 2015. a, b
Chen, Y., Schleicher, N., Fricker, M., Cen, K., Liu, X.-l., Kaminski, U., Yu, Y., Wu, X.-f., and Norra, S.: Long-term variation of black carbon and PM2.5 in Beijing, China with respect to meteorological conditions and governmental measures, Environ. Pollut., 212, 269–278, https://doi.org/10.1016/j.envpol.2016.01.008, 2016. a
Cherin, N., Roustan, Y., Musson-Genon, L., and Seigneur, C.: Modelling atmospheric dry deposition in urban areas using an urban canopy approach, Geosci. Model Dev., 8, 893–910, https://doi.org/10.5194/gmd-8-893-2015, 2015. a, b
Chung, S. H. and Seinfeld, J. H.: Climate response of direct radiative forcing of anthropogenic black carbon, J. Geophys. Res., 110, D11102, https://doi.org/10.1029/2004JD005441, 2005. a
Councell, T. B., Duckenfield, K. U., Landa, E. R., and Callender, E.: Tire-wear particles as a source of zinc to the environment, Environ. Sci. Technol., 38, 4206–4214, https://doi.org/10.1021/es034631f, 2004. a
de Miranda, R. M., Perez-Martinez, P. J., de Fatima Andrade, M., and Ribeiro, F. N. D.: Relationship between black carbon (BC) and heavy traffic in São Paulo, Brazil, Transport. Res. D-Tr. E., 68, 84–98, https://doi.org/10.1016/j.trd.2017.09.002, 2019. a
Denby, B. R., Sundvor, I., Johansson, C., Pirjola, L., Ketzel, M., Norman, M., Kupiainen, K., Gustafsson, M., Blomqvist, G., and Omstedt, G.: A coupled road dust and surface moisture model to predict non-exhaust road traffic induced particle emissions (NORTRIP). Part 1: Road dust loading and suspension modelling, Atmos. Environ., 77, 283–300, https://doi.org/10.1016/j.atmosenv.2013.04.069, 2013a. a, b, c, d, e, f, g, h, i, j, k, l, m, n
Denby, B. R., Sundvor, I., Johansson, C., Pirjola, L., Ketzel, M., Norman, M., Kupiainen, K., Gustafsson, M., Blomqvist, G., and Omstedt, G.: A coupled road dust and surface moisture model to predict non-exhaust road traffic induced particle emissions (NORTRIP). Part 2: Surface moisture and salt impact modelling, Atmos. Environ., 81, 485–503, https://doi.org/10.1016/j.atmosenv.2013.09.003, 2013b. a, b, c, d, e
Dons, E., Panis, L. I., Van Poppel, M., Theunis, J., and Wets, G.: Personal exposure to black carbon in transport microenvironments, Atmos. Environ., 55, 392–398, https://doi.org/10.1016/j.atmosenv.2012.03.020, 2012. a
Dore, C. J., Goodwin, J. W. L., Watterson, J. D., Murrells, T. P., Passant, N. R., Hobson, M. M., Haigh, K. E., Baggott, S. L., Pye, S. T., Coleman, P. J., and King, K. R.: UK emissions of air pollutants 1970 to 2001, National Atmospheric Emissions Inventory, 2003. a
Grigoratos, T. and Martini, G.: Brake wear particle emissions: a review, Environ. Sci. Pollut. R., 22, 2491–2504, https://doi.org/10.1007/s11356-014-3696-8, 2015. a
Guevara, M., Tena, C., Porquet, M., Jorba, O., and Pérez García-Pando, C.: HERMESv3, a stand-alone multi-scale atmospheric emission modelling framework – Part 2: The bottom–up module, Geosci. Model Dev., 13, 873–903, https://doi.org/10.5194/gmd-13-873-2020, 2020. a, b, c
Hanna, S. and Chang, J.: Acceptance criteria for urban dispersion model evaluation, Meteorol. Atmos. Phys., 116, 133–146, https://doi.org/10.1007/s00703-011-0177-1, 2012. a, b
Harrison, R. M., Yin, J., Mark, D., Stedman, J., Appleby, R. S., Booker, J., and Moorcroft, S.: Studies of the coarse particle (2.5–10 µm) component in UK urban atmospheres, Atmos. Environ., 35, 3667–3679, https://doi.org/10.1016/S1352-2310(00)00526-4, 2001. a
Herring, S. and Huq, P.: A review of methodology for evaluating the performance of atmospheric transport and dispersion models and suggested protocol for providing more informative results, Fluids, 3, 20, https://doi.org/10.3390/fluids3010020, 2018. a, b
Highwood, E. J. and Kinnersley, R. P.: When smoke gets in our eyes: The multiple impacts of atmospheric black carbon on climate, air quality and health, Environ. Int., 32, 560–566, https://doi.org/10.1016/j.envint.2005.12.003, 2006. a
Hong, Y., Bonhomme, C., Le, M.-H., and Chebbo, G.: New insights into the urban washoff process with detailed physical modelling, Sci. Total Environ., 573, 924–936, https://doi.org/10.1016/j.scitotenv.2016.08.193, 2016b. a, b
Invernizzi, G., Ruprecht, A., Mazza, R., De Marco, C., Močnik, G., Sioutas, C., and Westerdahl, D.: Measurement of black carbon concentration as an indicator of air quality benefits of traffic restriction policies within the ecopass zone in Milan, Italy, Atmos. Environ., 45, 3522–3527, https://doi.org/10.1016/j.atmosenv.2011.04.008, 2011. a
Jacobson, M. Z.: Strong radiative heating due to the mixing state of black carbon in atmospheric aerosols, Nature, 409, 695–697, https://doi.org/10.1038/35055518, 2001. a
Jansen, K. L., Larson, T. V., Koenig, J. Q., Mar, T. F., Fields, C., Stewart, J., and Lippmann, M.: Associations between health effects and particulate matter and black carbon in subjects with respiratory disease, Environ. Health Persp., 113, 1741–1746, https://doi.org/10.1289/ehp.8153, 2005. a
Janssen, N. A. H., Hoek, G., Simic-Lawson, M., Fischer, P., Van Bree, L., Ten Brink, H., Keuken, M., Atkinson, R. W., Anderson, H. R., Brunekreef, B., and Casse, F. R.: Black carbon as an additional indicator of the adverse health effects of airborne particles compared with PM10 and PM2.5, Environ. Health Persp., 119, 1691–1699, https://doi.org/10.1289/ehp.1003369, 2011. a
Jones, R. R., Hoek, G., Fisher, J. A., Hasheminassab, S., Wang, D., Ward, M. H., Sioutas, C., Vermeulen, R., and Silverman, D. T.: Land use regression models for ultrafine particles, fine particles, and black carbon in southern California, Sci. Total Environ., 699, 134234, https://doi.org/10.1016/j.scitotenv.2019.134234, 2020. a
Khare, P., Machesky, J., Soto, R., He, M., Presto, A. A., and Gentner, D. R.: Asphalt-related emissions are a major missing nontraditional source of secondary organic aerosol precursors, Sci. Adv., 6, eabb9785, https://doi.org/10.1126/sciadv.abb9785, 2020. a
Kim, Y., Wu, Y., Seigneur, C., and Roustan, Y.: Multi-scale modeling of urban air pollution: development and application of a Street-in-Grid model (v1.0) by coupling MUNICH (v1.0) and Polair3D (v1.8.1), Geosci. Model Dev., 11, 611–629, https://doi.org/10.5194/gmd-11-611-2018, 2018. a, b, c, d, e, f, g, h
Kreider, M. L., Panko, J. M., McAtee, B. L., Sweet, L. I., and Finley, B. L.: Physical and chemical characterization of tire-related particles: Comparison of particles generated using different methodologies, Sci. Total Environ., 408, 652–659, 2010. a
Lawrence, S., Sokhi, R., and Ravindra, K.: Quantification of vehicle fleet PM10 particulate matter emission factors from exhaust and non-exhaust sources using tunnel measurement techniques, Environ. Pollut., 210, 419–428, https://doi.org/10.1016/j.envpol.2016.01.011, 2016. a, b
Lequy, E., Siemiatycki, J., de Hoogh, K., Vienneau, D., Dupuy, J.-F., Garès, V., Hertel, O., Christensen, J. H., Zhivin, S., Goldberg, M., et al.: Contribution of Long-Term Exposure to Outdoor Black Carbon to the Carcinogenicity of Air Pollution: Evidence regarding Risk of Cancer in the Gazel Cohort, Environ. Health Persp., 129, 037005, https://doi.org/10.1289/EHP8719, 2021. a
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Short summary
The multiscale Street-in-Grid model is used to simulate black carbon (BC) concentrations in streets. To respect street-surface mass balance, particle resuspension is estimated with a new approach based on deposited mass. The contribution of resuspension is low, but non-exhaust emissions from tyre wear may largely contribute to BC concentrations. The impact of the two-way dynamic coupling between scales on BC concentrations varies depending on the street geometry and traffic emission intensity.
The multiscale Street-in-Grid model is used to simulate black carbon (BC) concentrations in...
