Articles | Volume 15, issue 19
https://doi.org/10.5194/gmd-15-7371-2022
© Author(s) 2022. 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-15-7371-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
MUNICH v2.0: a street-network model coupled with SSH-aerosol (v1.2) for multi-pollutant modelling
CEREA, École des Ponts, EDF R&D, Marne-la-Vallée, France
Lya Lugon
CEREA, École des Ponts, EDF R&D, Marne-la-Vallée, France
Alice Maison
CEREA, École des Ponts, EDF R&D, Marne-la-Vallée, France
Université Paris-Saclay, INRAE, AgroParisTech, UMR EcoSys, Thiverval-Grignon, France
Thibaud Sarica
CEREA, École des Ponts, EDF R&D, Marne-la-Vallée, France
Yelva Roustan
CEREA, École des Ponts, EDF R&D, Marne-la-Vallée, France
Myrto Valari
Laboratoire de Météorologie Dynamique, Sorbonne Université, École Polytechnique, IPSL, École Normale Supérieure, CNRS, Paris, France
Yang Zhang
Department of Civil and Environmental Engineering, Northeastern University, Boston, MA, USA
Michel André
Department COSYS, Université Gustave Eiffel, Bron, France
CEREA, École des Ponts, EDF R&D, Marne-la-Vallée, France
Related authors
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).
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
Shoma Yamanouchi, Shayamilla Mahagammulla Gamage, Sara Torbatian, Jad Zalzal, Laura Minet, Audrey Smargiassi, Ying Liu, Ling Liu, Forood Azargoshasbi, Jinwoong Kim, Youngseob Kim, Daniel Yazgi, and Marianne Hatzopoulou
Geosci. Model Dev., 17, 3579–3597, https://doi.org/10.5194/gmd-17-3579-2024, https://doi.org/10.5194/gmd-17-3579-2024, 2024
Short summary
Short summary
Air pollution is a major health hazard, and chemical transport models (CTMs) are valuable tools that aid in our understanding of the risks of air pollution at both local and regional scales. In this study, the Polair3D CTM of the Polyphemus air quality modeling platform was set up over Quebec, Canada, to assess the model’s capability in predicting key air pollutant species over the region, at seasonal temporal scales and at regional spatial scales.
Tao Wang, Hang Liu, Jie Li, Shuai Wang, Youngseob Kim, Yele Sun, Wenyi Yang, Huiyun Du, Zhe Wang, and Zifa Wang
Geosci. Model Dev., 16, 5585–5599, https://doi.org/10.5194/gmd-16-5585-2023, https://doi.org/10.5194/gmd-16-5585-2023, 2023
Short summary
Short summary
This paper developed a two-way coupled module in a new version of a regional urban–street network model, IAQMS-street v2.0, in which the mass flux from streets to background is considered. Test cases are defined to evaluate the performance of IAQMS-street v2.0 in Beijing by comparing it with that simulated by IAQMS-street v1.0 and a regional model. The contribution of local emissions and the influence of on-road vehicle control measures on air quality are evaluated by using IAQMS-street v2.0.
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
Short summary
Short summary
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
Short summary
Short summary
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.
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
Short summary
Short summary
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.
Mario Eduardo Gavidia-Calderón, Sergio Ibarra-Espinosa, Youngseob Kim, Yang Zhang, and Maria de Fatima Andrade
Geosci. Model Dev., 14, 3251–3268, https://doi.org/10.5194/gmd-14-3251-2021, https://doi.org/10.5194/gmd-14-3251-2021, 2021
Short summary
Short summary
The MUNICH model was used to calculate pollutant concentrations inside the streets of São Paulo. The VEIN emission model provided the vehicular emissions and the coordinates of the streets. We used information from an air quality station to account for pollutant concentrations over the street rooftops. Results showed that when emissions are calibrated, MUNICH satisfied the performance criteria. MUNICH can be used to evaluate the impact of traffic-related air pollution on public health.
Oscar Jacquot and Karine Sartelet
Geosci. Model Dev., 18, 3965–3984, https://doi.org/10.5194/gmd-18-3965-2025, https://doi.org/10.5194/gmd-18-3965-2025, 2025
Short summary
Short summary
Modelling the size distribution and the number concentration is important to represent ultrafine particles. A new analytic formulation is presented to compute coagulation partition coefficients, allowing us to lower the numerical diffusion associated with the resolution of aerosol dynamics. The significance of this effect is assessed in a 0D box model and over greater Paris with a chemistry transport model, using different size resolutions of the particle distribution.
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).
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
Jerry Jose, Auguste Gires, Yelva Roustan, Ernani Schnorenberger, Ioulia Tchiguirinskaia, and Daniel Schertzer
Nonlin. Processes Geophys., 31, 587–602, https://doi.org/10.5194/npg-31-587-2024, https://doi.org/10.5194/npg-31-587-2024, 2024
Short summary
Short summary
Wind energy exhibits extreme variability in space and time. However, it also shows scaling properties (properties that remain similar across different times and spaces of measurement). This can be quantified using appropriate statistical tools. In this way, the scaling properties of power from a wind farm are analysed here. Since every turbine is manufactured by design for a rated power, this acts as an upper limit on the data. This bias is identified here using data and numerical simulations.
Jerry Jose, Auguste Gires, Ernani Schnorenberger, Yelva Roustan, Daniel Schertzer, and Ioulia Tchiguirinskaia
Nonlin. Processes Geophys., 31, 603–624, https://doi.org/10.5194/npg-31-603-2024, https://doi.org/10.5194/npg-31-603-2024, 2024
Short summary
Short summary
To understand the influence of rainfall on wind power production, turbine power and rainfall were measured simultaneously on an operational wind farm and analysed. The correlation between wind, wind power, air density, and other fields was obtained on various temporal scales under rainy and dry conditions. An increase in the correlation was observed with an increase in the rain; rain also influenced the correspondence between actual and expected values of power at various velocities.
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
Short summary
Short summary
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
Short summary
Short summary
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.
Marc Bocquet, Pierre J. Vanderbecken, Alban Farchi, Joffrey Dumont Le Brazidec, and Yelva Roustan
Nonlin. Processes Geophys., 31, 335–357, https://doi.org/10.5194/npg-31-335-2024, https://doi.org/10.5194/npg-31-335-2024, 2024
Short summary
Short summary
A novel approach, optimal transport data assimilation (OTDA), is introduced to merge DA and OT concepts. By leveraging OT's displacement interpolation in space, it minimises mislocation errors within DA applied to physical fields, such as water vapour, hydrometeors, and chemical species. Its richness and flexibility are showcased through one- and two-dimensional illustrations.
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
Short summary
Short summary
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.
Shoma Yamanouchi, Shayamilla Mahagammulla Gamage, Sara Torbatian, Jad Zalzal, Laura Minet, Audrey Smargiassi, Ying Liu, Ling Liu, Forood Azargoshasbi, Jinwoong Kim, Youngseob Kim, Daniel Yazgi, and Marianne Hatzopoulou
Geosci. Model Dev., 17, 3579–3597, https://doi.org/10.5194/gmd-17-3579-2024, https://doi.org/10.5194/gmd-17-3579-2024, 2024
Short summary
Short summary
Air pollution is a major health hazard, and chemical transport models (CTMs) are valuable tools that aid in our understanding of the risks of air pollution at both local and regional scales. In this study, the Polair3D CTM of the Polyphemus air quality modeling platform was set up over Quebec, Canada, to assess the model’s capability in predicting key air pollutant species over the region, at seasonal temporal scales and at regional spatial scales.
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
Short summary
Short summary
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
Short summary
Short summary
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.
Calvin Howes, Pablo E. Saide, Hugh Coe, Amie Dobracki, Steffen Freitag, Jim M. Haywood, Steven G. Howell, Siddhant Gupta, Janek Uin, Mary Kacarab, Chongai Kuang, L. Ruby Leung, Athanasios Nenes, Greg M. McFarquhar, James Podolske, Jens Redemann, Arthur J. Sedlacek, Kenneth L. Thornhill, Jenny P. S. Wong, Robert Wood, Huihui Wu, Yang Zhang, Jianhao Zhang, and Paquita Zuidema
Atmos. Chem. Phys., 23, 13911–13940, https://doi.org/10.5194/acp-23-13911-2023, https://doi.org/10.5194/acp-23-13911-2023, 2023
Short summary
Short summary
To better understand smoke properties and its interactions with clouds, we compare the WRF-CAM5 model with observations from ORACLES, CLARIFY, and LASIC field campaigns in the southeastern Atlantic in August 2017. The model transports and mixes smoke well but does not fully capture some important processes. These include smoke chemical and physical aging over 4–12 days, smoke removal by rain, sulfate particle formation, aerosol activation into cloud droplets, and boundary layer turbulence.
Tao Wang, Hang Liu, Jie Li, Shuai Wang, Youngseob Kim, Yele Sun, Wenyi Yang, Huiyun Du, Zhe Wang, and Zifa Wang
Geosci. Model Dev., 16, 5585–5599, https://doi.org/10.5194/gmd-16-5585-2023, https://doi.org/10.5194/gmd-16-5585-2023, 2023
Short summary
Short summary
This paper developed a two-way coupled module in a new version of a regional urban–street network model, IAQMS-street v2.0, in which the mass flux from streets to background is considered. Test cases are defined to evaluate the performance of IAQMS-street v2.0 in Beijing by comparing it with that simulated by IAQMS-street v1.0 and a regional model. The contribution of local emissions and the influence of on-road vehicle control measures on air quality are evaluated by using IAQMS-street v2.0.
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
Short summary
Short summary
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.
Pierre J. Vanderbecken, Joffrey Dumont Le Brazidec, Alban Farchi, Marc Bocquet, Yelva Roustan, Élise Potier, and Grégoire Broquet
Atmos. Meas. Tech., 16, 1745–1766, https://doi.org/10.5194/amt-16-1745-2023, https://doi.org/10.5194/amt-16-1745-2023, 2023
Short summary
Short summary
Instruments dedicated to monitoring atmospheric gaseous compounds from space will provide images of urban-scale plumes. We discuss here the use of new metrics to compare observed plumes with model predictions that will be less sensitive to meteorology uncertainties. We have evaluated our metrics on diverse plumes and shown that by eliminating some aspects of the discrepancies, they are indeed less sensitive to meteorological variations.
Joffrey Dumont Le Brazidec, Marc Bocquet, Olivier Saunier, and Yelva Roustan
Geosci. Model Dev., 16, 1039–1052, https://doi.org/10.5194/gmd-16-1039-2023, https://doi.org/10.5194/gmd-16-1039-2023, 2023
Short summary
Short summary
When radionuclides are released into the atmosphere, the assessment of the consequences depends on the evaluation of the magnitude and temporal evolution of the release, which can be highly variable as in the case of Fukushima Daiichi.
Here, we propose Bayesian inverse modelling methods and the reversible-jump Markov chain Monte Carlo technique, which allows one to evaluate the temporal variability of the release and to integrate different types of information in the source reconstruction.
Chandan Sarangi, Yun Qian, L. Ruby Leung, Yang Zhang, Yufei Zou, and Yuhang Wang
Atmos. Chem. Phys., 23, 1769–1783, https://doi.org/10.5194/acp-23-1769-2023, https://doi.org/10.5194/acp-23-1769-2023, 2023
Short summary
Short summary
We show that for air quality, the densely populated eastern US may see even larger impacts of wildfires due to long-distance smoke transport and associated positive climatic impacts, partially compensating the improvements from regulations on anthropogenic emissions. This study highlights the tension between natural and anthropogenic contributions and the non-local nature of air pollution that complicate regulatory strategies for improving future regional air quality for human health.
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
Short summary
Short summary
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
Short summary
Short summary
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 %.
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
Short summary
Short summary
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
Short summary
Short summary
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.
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.
Sally S.-C. Wang, Yun Qian, L. Ruby Leung, and Yang Zhang
Atmos. Chem. Phys., 22, 3445–3468, https://doi.org/10.5194/acp-22-3445-2022, https://doi.org/10.5194/acp-22-3445-2022, 2022
Short summary
Short summary
This study develops an interpretable machine learning (ML) model predicting monthly PM2.5 fire emission over the contiguous US at 0.25° resolution and compares the prediction skills of the ML and process-based models. The comparison facilitates attributions of model biases and better understanding of the strengths and uncertainties in the two types of models at regional scales, for informing future model development and their applications in fire emission projection.
Ruili Wu, Christopher W. Tessum, Yang Zhang, Chaopeng Hong, Yixuan Zheng, Xinyin Qin, Shigan Liu, and Qiang Zhang
Geosci. Model Dev., 14, 7621–7638, https://doi.org/10.5194/gmd-14-7621-2021, https://doi.org/10.5194/gmd-14-7621-2021, 2021
Short summary
Short summary
Reduced-complexity air quality models are less computationally intensive and easier to use. We developed a reduced-complexity air quality Intervention Model for Air Pollution over China (InMAP-China) to rapidly predict the air quality and estimate the health impacts of emission sources in China. We believe that this work will be of great interest to a broad audience, including environmentalists in China and scientists in relevant fields at both national and local institutes.
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
Short summary
Short summary
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.
Kai Wang, Yang Zhang, Shaocai Yu, David C. Wong, Jonathan Pleim, Rohit Mathur, James T. Kelly, and Michelle Bell
Geosci. Model Dev., 14, 7189–7221, https://doi.org/10.5194/gmd-14-7189-2021, https://doi.org/10.5194/gmd-14-7189-2021, 2021
Short summary
Short summary
The two-way coupled WRF-CMAQ model accounting for complex chemistry–meteorology feedbacks has been applied to the long-term predictions of regional meteorology and air quality over the US. The model results show superior performance and importance of chemistry–meteorology feedbacks when compared to the offline coupled WRF and CMAQ simulations, which suggests that feedbacks should be considered along with other factors in developing future model applications to inform policy making.
Lya Lugon, Jérémy Vigneron, Christophe Debert, Olivier Chrétien, and Karine Sartelet
Geosci. Model Dev., 14, 7001–7019, https://doi.org/10.5194/gmd-14-7001-2021, https://doi.org/10.5194/gmd-14-7001-2021, 2021
Short summary
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.
Laurent Menut, Bertrand Bessagnet, Régis Briant, Arineh Cholakian, Florian Couvidat, Sylvain Mailler, Romain Pennel, Guillaume Siour, Paolo Tuccella, Solène Turquety, and Myrto Valari
Geosci. Model Dev., 14, 6781–6811, https://doi.org/10.5194/gmd-14-6781-2021, https://doi.org/10.5194/gmd-14-6781-2021, 2021
Short summary
Short summary
The CHIMERE chemistry-transport model is presented in its new version, V2020r1. Many changes are proposed compared to the previous version. These include online modeling, new parameterizations for aerosols, new emissions schemes, a new parameter file format, the subgrid-scale variability of urban concentrations and new transport schemes.
Syuichi Itahashi, Rohit Mathur, Christian Hogrefe, Sergey L. Napelenok, and Yang Zhang
Geosci. Model Dev., 14, 5751–5768, https://doi.org/10.5194/gmd-14-5751-2021, https://doi.org/10.5194/gmd-14-5751-2021, 2021
Short summary
Short summary
The Community Multiscale Air Quality (CMAQ) modeling system extended for hemispheric-scale applications (H-CMAQ) incorporated the satellite-constrained degassing SO2 emissions from 50 volcanos across the Northern Hemisphere. The impact on tropospheric sulfate aerosol (SO42−) is assessed for 2010. Although the considered volcanic emissions occurred at or below the middle of free troposphere (500 hPa), SO42− enhancements of more than 10 % were detected up to the top of free troposphere (250 hPa).
Joffrey Dumont Le Brazidec, Marc Bocquet, Olivier Saunier, and Yelva Roustan
Atmos. Chem. Phys., 21, 13247–13267, https://doi.org/10.5194/acp-21-13247-2021, https://doi.org/10.5194/acp-21-13247-2021, 2021
Short summary
Short summary
The assessment of the environmental consequences of a radionuclide release depends on the estimation of its source. This paper aims to develop inverse Bayesian methods which combine transport models with measurements, in order to reconstruct the ensemble of possible sources.
Three methods to quantify uncertainties based on the definition of probability distributions and the physical models are proposed and evaluated for the case of 106Ru releases over Europe in 2017.
Xiaoyang Chen, Yang Zhang, Kai Wang, Daniel Tong, Pius Lee, Youhua Tang, Jianping Huang, Patrick C. Campbell, Jeff Mcqueen, Havala O. T. Pye, Benjamin N. Murphy, and Daiwen Kang
Geosci. Model Dev., 14, 3969–3993, https://doi.org/10.5194/gmd-14-3969-2021, https://doi.org/10.5194/gmd-14-3969-2021, 2021
Short summary
Short summary
The continuously updated National Air Quality Forecast Capability (NAQFC) provides air quality forecasts. To support the development of the next-generation NAQFC, we evaluate a prototype of GFSv15-CMAQv5.0.2. The performance and the potential improvements for the system are discussed. This study can provide a scientific basis for further development of NAQFC and help it to provide more accurate air quality forecasts to the public over the contiguous United States.
Mario Eduardo Gavidia-Calderón, Sergio Ibarra-Espinosa, Youngseob Kim, Yang Zhang, and Maria de Fatima Andrade
Geosci. Model Dev., 14, 3251–3268, https://doi.org/10.5194/gmd-14-3251-2021, https://doi.org/10.5194/gmd-14-3251-2021, 2021
Short summary
Short summary
The MUNICH model was used to calculate pollutant concentrations inside the streets of São Paulo. The VEIN emission model provided the vehicular emissions and the coordinates of the streets. We used information from an air quality station to account for pollutant concentrations over the street rooftops. Results showed that when emissions are calibrated, MUNICH satisfied the performance criteria. MUNICH can be used to evaluate the impact of traffic-related air pollution on public health.
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
Short summary
Short summary
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.
Evangelia Kostenidou, Alvaro Martinez-Valiente, Badr R'Mili, Baptiste Marques, Brice Temime-Roussel, Amandine Durand, Michel André, Yao Liu, Cédric Louis, Boris Vansevenant, Daniel Ferry, Carine Laffon, Philippe Parent, and Barbara D'Anna
Atmos. Chem. Phys., 21, 4779–4796, https://doi.org/10.5194/acp-21-4779-2021, https://doi.org/10.5194/acp-21-4779-2021, 2021
Short summary
Short summary
Passenger vehicle emissions can be a significant source of particulate matter in urban areas. In this study the particle-phase emissions of seven Euro 5 passenger vehicles were characterized. Changes in engine technologies and after-treatment devices can alter the chemical composition and the size of the emitted particulate matter. The condition of the diesel particle filter (DPF) plays an important role in the emitted pollutants.
Yohei Shinozuka, Pablo E. Saide, Gonzalo A. Ferrada, Sharon P. Burton, Richard Ferrare, Sarah J. Doherty, Hamish Gordon, Karla Longo, Marc Mallet, Yan Feng, Qiaoqiao Wang, Yafang Cheng, Amie Dobracki, Steffen Freitag, Steven G. Howell, Samuel LeBlanc, Connor Flynn, Michal Segal-Rosenhaimer, Kristina Pistone, James R. Podolske, Eric J. Stith, Joseph Ryan Bennett, Gregory R. Carmichael, Arlindo da Silva, Ravi Govindaraju, Ruby Leung, Yang Zhang, Leonhard Pfister, Ju-Mee Ryoo, Jens Redemann, Robert Wood, and Paquita Zuidema
Atmos. Chem. Phys., 20, 11491–11526, https://doi.org/10.5194/acp-20-11491-2020, https://doi.org/10.5194/acp-20-11491-2020, 2020
Short summary
Short summary
In the southeast Atlantic, well-defined smoke plumes from Africa advect over marine boundary layer cloud decks; both are most extensive around September, when most of the smoke resides in the free troposphere. A framework is put forth for evaluating the performance of a range of global and regional atmospheric composition models against observations made during the NASA ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS) airborne mission in September 2016.
Cited articles
Airparif: Source apportionment of airbone particles in the Île-de-France
region – Final report (INIS-FR–20-1041), https://inis.iaea.org/search/search.aspx?orig_q=RN:51070022 (last access: 15
February 2022), 2011. a
André, M., Sartelet, K., Moukhtar, S., André, J.-M., and Redaelli, M.:
Diesel, petrol or electric vehicles: What choices to improve urban air
quality in the Ile-de-France region? A simulation platform and case study,
Atmos. Environ., 241, 117752, https://doi.org/10.1016/j.atmosenv.2020.117752, 2020. a, b
André, M. et al.: Particules de l'air extérieur – Impact sur la pollution
atmosphérique des technologies et de la composition du parc de véhicules
automobiles circulant en France, 2014-SA-0156, ANSES,
https://www.anses.fr/fr/system/files/AIR2014SA0156Ra-Emission.pdf (last
access: 7 December 2021), 2019. a
Benson, P. E.: A review of the development and application of the CALINE3 and 4
models, Atmos. Environ., 26, 379–390, https://doi.org/10.1016/0957-1272(92)90013-I,
1992. a
Berkowicz, R.: OSPM – a parameterised street pollution model, Environ. Monit.
Assess., 65, 323–331, https://doi.org/10.1023/A:1006448321977, 2000. a
Briant, R., Seigneur, C., Gadrat, M., and Bugajny, C.: Evaluation of roadway Gaussian plume models with large-scale measurement campaigns, Geosci. Model Dev., 6, 445–456, https://doi.org/10.5194/gmd-6-445-2013, 2013. 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
Chrit, M., Sartelet, K., Sciare, J., Pey, J., Marchand, N., Couvidat, F., Sellegri, K., and Beekmann, M.: Modelling organic aerosol concentrations and properties during ChArMEx summer campaigns of 2012 and 2013 in the western Mediterranean region, Atmos. Chem. Phys., 17, 12509–12531, https://doi.org/10.5194/acp-17-12509-2017, 2017. a
Cyrys, J., Eeftens, M., Heinrich, J., Ampe, C., Armengaud, A., Beelen, R.,
Bellander, T., Beregszaszi, T., Birk, M., Cesaroni, G., Cirach, M., de
Hoogh, K., De Nazelle, A., de Vocht, F., Declercq, C., Dėdelė, A.,
Dimakopoulou, K., Eriksen, K., Galassi, C., Grąulevičienė, R., Grivas, G.,
Gruzieva, O., Gustafsson, A. H., Hoffmann, B., Iakovides, M., Ineichen, A.,
Krämer, U., Lanki, T., Lozano, P., Madsen, C., Meliefste, K., Modig, L.,
Mölter, A., Mosler, G., Nieuwenhuijsen, M., Nonnemacher, M., Oldenwening,
M., Peters, A., Pontet, S., Probst-Hensch, N., Quass, U., Raaschou-Nielsen,
O., Ranzi, A., Sugiri, D., Stephanou, E. G., Taimisto, P., Tsai, M.-Y., Éva
Vaskövi, Villani, S., Wang, M., Brunekreef, B., and Hoek, G.: Variation of
NO2 and NOx concentrations between and within 36 European study areas:
Results from the ESCAPE study, Atmos. Environ., 62, 374–390,
https://doi.org/10.1016/j.atmosenv.2012.07.080, 2012. a
EMEP/EEA: EMEP/EEA air pollutant emission inventory guidebook 2019, EEA
Report No 13/2019, European Environment Agency,
https://www.eea.europa.eu/publications/emep-eea-guidebook-2019 (last
access 7 December 2021), 2019. a
Giardina, M. and Buffa, P.: A new approach for modeling dry deposition velocity
of particles, Atmos. Environ., 180, 11–22,
https://doi.org/10.1016/j.atmosenv.2018.02.038, 2018. a
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
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
Janhäll, S.: Review on urban vegetation and particle air pollution –
Deposition and dispersion, Atmos. Environ., 105, 130–137,
https://doi.org/10.1016/j.atmosenv.2015.01.052, 2015. a
Jeanjean, A., Hinchliffe, G., McMullan, W., Monks, P., and Leigh, R.: A CFD
study on the effectiveness of trees to disperse road traffic emissions at a
city scale, Atmos. Environ., 120, 1–14,
https://doi.org/10.1016/j.atmosenv.2015.08.003, 2015. a
Kim, Y., Couvidat, F., Sartelet, K., and Seigneur, C.: Comparison of different
gas-phase mechanisms and aerosol modules for simulating particulate matter
formation, J. Air Waste Manage. Assoc., 61, 1–9,
https://doi.org/10.1080/10473289.2011.603999, 2011. 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, i, j, k, l
Kim, Y., Sartelet, K., Lugon, L., Roustan, Y., Sarica, T., Maison, A., Valari, M., Zhang, Y., and André, M.: The Model of Urban Network
of Intersecting Canyons and Highways (MUNICH) v2.0,
Zenodo [code], https://doi.org/10.5281/zenodo.6167477, 2022. a, b
Krzyzanowski, M., Apte, J., Bonjour, S., Brauer, M., Cohen, A., and
Prüss-Ustun, A.: Air pollution in the mega-cities, Curr. Environ. Health
Rep., 1, 185–191, https://doi.org/10.1007/s40572-014-0019-7, 2014. a
Kusaka, H., Kondo, H., Kikegawa, Y., and Kimura, F.: A simple single-layer
urban canopy model for atmospheric models: comparison with multi-layer and
slab models, Bound.-Lay. Meteorol., 101, 329–358,
https://doi.org/10.1023/A:1019207923078, 2001. a
Leclercq, L., Laval, J. A., and Chevallier, E.: The Lagrangian coordinates and
what it means for first order traffic flow models, Proceedings of the 17th
international symposium on transportation and traffic theory,
edited by: Allsop, R. E., Bell, M. G. H., and Heydecker, B. G., Elsevier, London, 735–753, https://www.researchgate.net/publication/285761378_The_Lagrangian_coordinates_and_what_it_means_for_first_order_traffic_flow_models (last access: 27 September 2022), 2007. a, b
Lemonsu, A., Grimmond, C. S. B., and Masson, V.: Modeling the surface
energy balance of the core of an old Mediterranean city: Marseille, J.
Appl. Meteorol., 43, 312–327,
https://doi.org/10.1175/1520-0450(2004)043<0312:MTSEBO>2.0.CO;2, 2004. a, b
Lugon, L., Sartelet, K., Kim, Y., Vigneron, J., and Chrétien, O.: Nonstationary modeling of NO2, NO and NOx in Paris using the Street-in-Grid model: coupling local and regional scales with a two-way dynamic approach, Atmos. Chem. Phys., 20, 7717–7740, https://doi.org/10.5194/acp-20-7717-2020, 2020. a, b, c, d, e, f, g, h, i, j, k
Lugon, L., Vigneron, J., Debert, C., Chrétien, O., and Sartelet, K.: 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), Geosci. Model Dev., 14, 7001–7019, https://doi.org/10.5194/gmd-14-7001-2021, 2021b. a, b, c, d, e, f, g, h, i, j
Macdonald, R., Griffiths, R., and Hall, D.: An improved method for the
estimation of surface roughness of obstacle arrays, Atmos. Environ., 32,
1857–1864, https://doi.org/10.1016/S1352-2310(97)00403-2, 1998. a, b, c, d
Maison, A., Flageul, C., Carissimo, B., Tuzet, A., and Sartelet, K.:
Parametrization of Horizontal and Vertical Transfers for the Street-Network
Model MUNICH Using the CFD Model Code_Saturne, Atmosphere, 13, 527,
https://doi.org/10.3390/atmos13040527, 2022. a, b, c
McHugh, C., Carruthers, D., and Edmunds, H.: ADMS–Urban: an air quality
management system for traffic, domestic and industrial pollution, Int. J.
Environ. Pollut., 8, 666–674, https://www.inderscienceonline.com/doi/abs/10.1504/IJEP.1997.028218 (last access: 27 September 2022), 1997. a
Milliez, M. and Carissimo, B.: Numerical simulations of pollutant dispersion in
an idealized urban area, for different meteorological conditions,
Bound.-Lay. Meteorol., 122, 321–342,
https://doi.org/10.1007/s10546-006-9110-4, 2007. a
Muyshondt, A., Anand, N. K., and McFarland, A. R.: Turbulent deposition of
aerosol particles in large transport tubes, Aerosol Sci. Tech., 24,
107–116, https://doi.org/10.1080/02786829608965356, 1996. a
Namdeo, A. and Colls, J.: Development and evaluation of SBLINE, a suite of
models for the prediction of pollution concentrations from vehicles in urban
areas, Sci. Total Environ., 189-190, 311–320,
https://doi.org/10.1016/0048-9697(96)05224-2, 1996. a
Putaud, J.-P., Van Dingenen, R., Alastuey, A., Bauer, H., Birmili, W., Cyrys,
J., Flentje, H., Fuzzi, S., Gehrig, R., Hansson, H., Harrison, R., Herrmann,
H., Hitzenberger, R., Hüglin, C., Jones, A., Kasper-Giebl, A., Kiss, G.,
Kousa, A., Kuhlbusch, T., Löschau, G., Maenhaut, W., Molnar, A., Moreno,
T., Pekkanen, J., Perrino, C., Pitz, M., Puxbaum, H., Querol, X., Rodriguez,
S., Salma, I., Schwarz, J., Smolik, J., Schneider, J., Spindler, G., ten
Brink, H., Tursic, J., Viana, M., Wiedensohler, A., and Raes, F.: A
European aerosol phenomenology – 3: Physical and chemical characteristics of
particulate matter from 60 rural, urban, and kerbside sites across Europe,
Atmos. Environ., 44, 1308–1320, https://doi.org/10.1016/j.atmosenv.2009.12.011, 2010. a, b
Ritchie, H. and Roser, M.: Urbanization, Our world in data,
https://ourworldindata.org/urbanization (last access 8 December 2021),
2018. a
Roustan, Y., Sartelet, K., Tombette, M., Debry, É., and Sportisse, B.:
Simulation of aerosols and gas-phase species over Europe with the Polyphemus
system. Part II: Model sensitivity analysis for 2001, Atmos. Environ., 44,
4219–4229, https://doi.org/10.1016/j.atmosenv.2010.07.005, 2010. a, b
Salizzoni, P., Soulhac, L., and Mejean, P.: Street canyon ventilation and
atmospheric turbulence, Atmos. Environ., 43, 5056–5067,
https://doi.org/10.1016/j.atmosenv.2009.06.045, 2009. a
Santiago, J.-L., Rivas, E., Sanchez, B., Buccolieri, R., and Martin, F.: The
impact of planting trees on NOx concentrations: the case of the Plaza de la
Cruz neighborhood in Pamplona (Spain), Atmosphere, 8, 131,
https://doi.org/10.3390/atmos8070131, 2017. a
Sarica, T.: Pollemission: computational tool for air pollutant
emission factors from traffic (2.0), Zenodo [code],
https://doi.org/10.5281/zenodo.5721253, 2021. a
Sartelet, K., Zhu, S., Moukhtar, S., André, M., André, J.-M., Gros, V.,
Favez, O., Brasseur, A., and Redaelli, M.: Emission of intermediate, semi and
low volatile organic compounds from traffic and their impact on secondary
organic aerosol concentrations over Greater Paris, Atmos. Environ., 180,
126–137, https://doi.org/10.1016/j.atmosenv.2018.02.031, 2018. a, b
Sartelet, K., Couvidat, F., Wang, Z., Flageul, C., and Kim, Y.: SSH-Aerosol
v1.1: a modular box model to simulate the evolution of primary and secondary
aerosols, Atmosphere, 11, 525, https://doi.org/10.3390/atmos11050525, 2020. a, b, c, d
Sartelet, K. N., Debry, É., Fahey, K., Roustan, Y., Tombette, M., and
Sportisse, B.: Simulation of aerosols and gas-phase species over Europe
with the Polyphemus system: Part I–Model-to-data comparison for
2001, Atmos. Environ., 41, 6116–6131, https://doi.org/10.1016/j.atmosenv.2007.04.024,
2007. a
Schulte, N., Tan, S., and Venkatram, A.: The ratio of effective building height
to street width governs dispersion of local vehicle emissions, Atmos.
Environ., 112, 54–63, https://doi.org/10.1016/j.atmosenv.2015.03.061, 2015. a
Skamarock, W. C., Klemp, J. B., Dudhia, J., Gill, D. O., Barker,
D. M., Duda, M. G., Huang, X.-Y., Wang, W., and Powers, J. G.:
A description of the Advanced Research WRF version 3, (No.
NCAR/TN-475+STR), University Corporation for Atmospheric
Research, [code], https://doi.org/10.5065/D68S4MVH, 2008. a
Soulhac, L., Garbero, V., Salizzoni, P., Mejean, P., and Perkins, R.: Flow and
dispersion in street intersections, Atmos. Environ., 43, 2981 – 2996,
https://doi.org/10.1016/j.atmosenv.2009.02.061, 2009. a
Soulhac, L., Salizzoni, P., Cierco, F.-X., and Perkins, R.: The model SIRANE
for atmospheric urban pollutant dispersion; part I, presentation of the
model, Atmos. Environ., 45, 7379–7395,
https://doi.org/10.1016/j.atmosenv.2011.07.008, 2011. a, b, c, d
Thouron, L., Kim, Y., Seigneur, C., and Bruge, B.: Intercomparison of two
modeling approaches for traffic air pollution in street canyons, Urban Clim.,
27, 163–178, https://doi.org/10.1016/j.uclim.2018.11.006, 2019. a
Vardoulakis, S., Fisher, B. E., Pericleous, K., and Gonzalez-Flesca, N.:
Modelling air quality in street canyons: a review, Atmos. Environ., 37,
155–182, https://doi.org/10.1016/S1352-2310(02)00857-9, 2003. a
Venkatram, A. and Pleim, J.: The electrical analogy does not apply to modeling
dry deposition of particles, Atmos. Environ., 33, 3075–3076,
https://doi.org/10.1016/S1352-2310(99)00094-1, 1999.
https://doi.org/10.5194/acp-18-10199-2018, 2018.
a
Vivanco, M. G., Theobald, M. R., García-Gómez, H., Garrido, J. L., Prank, M., Aas, W., Adani, M., Alyuz, U., Andersson, C., Bellasio, R., Bessagnet, B., Bianconi, R., Bieser, J., Brandt, J., Briganti, G., Cappelletti, A., Curci, G., Christensen, J. H., Colette, A., Couvidat, F., Cuvelier, C., D'Isidoro, M., Flemming, J., Fraser, A., Geels, C., Hansen, K. M., Hogrefe, C., Im, U., Jorba, O., Kitwiroon, N., Manders, A., Mircea, M., Otero, N., Pay, M.-T., Pozzoli, L., Solazzo, E., Tsyro, S., Unal, A., Wind, P., and Galmarini, S.: Modeled deposition of nitrogen and sulfur in Europe estimated by 14 air quality model systems: evaluation, effects of changes in emissions and implications for habitat protection, Atmos. Chem. Phys., 18, 10199–10218, a, b
Wolf, T., Pettersson, L. H., and Esau, I.: A very high-resolution assessment and modelling of urban air quality, Atmos. Chem. Phys., 20, 625–647, https://doi.org/10.5194/acp-20-625-2020, 2020. a
Wu, L., Hang, J., Wang, X., Shao, M., and Gong, C.: APFoam 1.0: integrated computational fluid dynamics simulation of O3–NOx–volatile organic compound chemistry and pollutant dispersion in a typical street canyon, Geosci. Model Dev., 14, 4655–4681, https://doi.org/10.5194/gmd-14-4655-2021, 2021. a
Yarwood, G., Rao, S., Yocke, M., and Whitten, G.: Updates to the carbon bond
chemical mechanism: CB05, Rep. RT-0400675,
https://camx-wp.azurewebsites.net/Files/CB05_Final_Report_120805.pdf
(last access: 8 December 2021), 2005. a
Zhang, L., Gong, S., Padro, J., and Barrie, L.: A size-segregated particle dry
deposition scheme for an atmospheric aerosol module, Atmos. Environ., 35,
549–560, https://doi.org/10.1016/S1352-2310(00)00326-5, 2001. a
Zhang, Y., Ye, X., Wang, S., He, X., Dong, L., Zhang, N., Wang, H., Wang, Z., Ma, Y., Wang, L., Chi, X., Ding, A., Yao, M., Li, Y., Li, Q., Zhang, L., and Xiao, Y.: Large-eddy simulation of traffic-related air pollution at a very high resolution in a mega-city: evaluation against mobile sensors and insights for influencing factors, Atmos. Chem. Phys., 21, 2917–2929, https://doi.org/10.5194/acp-21-2917-2021, 2021. a
Short summary
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.
This paper presents the latest version of the street-network model MUNICH, v2.0. The description...