MUNICH v2.0: a street-network model coupled with SSH-aerosol (v1.2) for multi-pollutant modelling

Kim, Youngseob; Lugon, Lya; Maison, Alice; Sarica, Thibaud; Roustan, Yelva; Valari, Myrto; Zhang, Yang; Meynier, André; Sartelet, Karine

doi:10.5194/gmd-15-7371-2022

Cited by 14 publications

(30 citation statements)

References 45 publications

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“…1). As detailed in Kim et al (2022), emissions are estimated from the fleet composition and the number of vehicles in the street using COPERT's emission factors (COmputer Program to calculate Emissions from Road Transport, version 2019, EMEP/EEA, 2019). After the speciation of NO x , volatile organic compounds (VOCs), PM 2.5 , and PM 10 into model species, emissions are set for 16 gaseous model species and 3 particle model species: dust and unspecified matter (dust), black carbon (BC), and primary organic aerosol of low volatility (POAlP).…”

Section: Simulation Setupmentioning

confidence: 99%

Modeling of street-scale pollutant dispersion by coupled simulation of chemical reaction, aerosol dynamics, and CFD

et al. 2023

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Abstract. In the urban environment, gas and particles impose adverse impacts on the health of pedestrians. The conventional computational fluid dynamics (CFD) methods that regard pollutants as passive scalars cannot reproduce the formation of secondary pollutants and lead to uncertain prediction. In this study, SSH-aerosol, a modular box model that simulates the evolution of gas, primary and secondary aerosols, is coupled with the CFD software, OpenFOAM and Code_Saturne. The transient dispersion of pollutants emitted from traffic in a street canyon is simulated using the unsteady Reynolds-averaged Navier–Stokes equations (RANS) model. The simulated concentrations of NO2, PM10, and black carbon (BC) are compared with field measurements on a street of Greater Paris. The simulated NO2 and PM10 concentrations based on the coupled model achieved better agreement with measurement data than the conventional CFD simulation. Meanwhile, the black carbon concentration is underestimated, probably partly because of the underestimation of non-exhaust emissions (tire and road wear). Aerosol dynamics lead to a large increase of ammonium nitrate and anthropogenic organic compounds from precursor gas emitted in the street canyon.

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Section: Simulation Setupmentioning

confidence: 99%

Modeling of street-scale pollutant dispersion by coupled simulation of chemical reaction, aerosol dynamics, and CFD

et al. 2023

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“…Chemical transformations are then applied to the resulting concentrations. As deposition and resuspension processes have minor effects compared to transport and chemistry (Lugon et al, 2021b;Kim et al, 2022), they are omitted in the rest of this study.…”

Section: Model Descriptionmentioning

confidence: 99%

“…Three parameterizations are implemented in MUNICH to determine the vertical transfer coefficient, q vert , between the street and the overlying atmosphere (Maison et al, 2022). However, currently only the parameterization adapted from Wang (2014) 95 is designed to provide vertical profiles for both wind speed and mixing length within the street.…”

Section: Vertical Transfer Coefficient For Turbulent Fluxmentioning

confidence: 99%

“…For many years, various modelling approaches have been developed to contribute to the understanding of the phenomena of NO 2 and CO, and to concentrations simulated by OSPM are discussed in Section 3. MUNICH is applied in Section 4 to the street network near Paris, France, used to validate MUNICH v2.0 (Kim et al, 2022), and the impacts of the heterogeneous version on concentrations of NO 2 and particles are studied. To estimate the impact of the modelling hypothesis on the transport of pollutants between streets in the new version of MUNICH, a sensitivity analysis to the presence of a street network is performed in Section 5.…”

Section: Introductionmentioning

confidence: 99%

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Modelling concentration heterogeneities in streets using the street-network model MUNICH

Sarica

Maison

Roustan

et al. 2023

Preprint

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Abstract. Populations in urban areas are exposed to high local concentrations of pollutants, such as nitrogen dioxide and particulate matter, because of unfavorable dispersion conditions and the proximity to traffic. To simulate these concentrations over cities, models like the street-network model MUNICH (Model of Urban Network of Intersecting Canyons and Highways) rely on parameterizations to represent the air flow and the concentrations of pollutants in streets. In the current version MUNICH v2.0, concentrations are assumed to be homogeneous in each street segment. A new version of MUNICH where the street volume is discretized is developed to represent the street gradients and better estimate people exposure. Three vertical levels are defined in each street segment. A horizontal discretization is also introduced under specific conditions by considering two zones with a parameterization taken from the Operational Street Pollution Model (OSPM). Simulations are performed over two districts of Copenhagen, Denmark, and one district of Greater Paris, France. Results show an improvement of the comparison to observations with higher concentrations at the bottom of the street, closer to traffic, of pollutants emitted by traffic (NOx, black carbon, organic matter). Finally, a sensitivity analysis to the influence of the street network highlights the importance to use the model MUNICH with a network rather than with a single street.

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“…In addition, the CFD model does not usually consider complex chemical reactions; this introduces limitations to the simulation of secondary pollutants, such as O3 (Fellini et al, 2019;Thouron et al, 2019;Ashie and Kono, 2011). Street-scale network models, such as the Model of Urban Network of Intersecting Canyons and Highways (MUNICH), operational urban dispersion model (SIRANE), and the Operational Street Pollution Model (OSPM) (Kakosimos et al, 2010;Soulhac et al, 2011;Kim et al, 2018;Kim et al, 2022) can simulate the distribution of pollutants at the street scale with a lower computational cost. MUNICH has been widely used for investigating the air quality at the street scale (Gavidia-Calderón et al, 2021;Lugon et al, 2020;Kim et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

IAQMS-street v2.0: a two-way coupled regional-urban–street-network model system for Beijing, China

Wang

Liu

et al. 2023

Preprint

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Abstract. Owing to the substantial traffic emissions in urban areas, especially near road areas, the concentrations of pollutants, such as ozone (O3) and its precursors, have a large gap with the regional averages and their distributions cannot be captured accurately by traditional single-scale air-quality models. In this study, a new version of a regional-urban-street-network model (IAQMS-street v2.0) is presented. An upscaling module is implemented in IAQMS-street v2.0 to calculate the impact of mass transfer to regional scale from street network. The influence of pollutants in street network is considered in the concentration calculation on regional scale, which is not considered in a previous version (IAQMS-street v1.0). In this study, the simulated results in Beijing during August 2021 by using IAQMS-street v2.0, IAQMS-street v1.0, and the regional model (NAQPMS) are compared. On-road traffic emissions in Beijing, as the key model-input data, were established using intelligent image-recognition technology and real-time traffic big data from navigation applications. The simulated results showed that the O3 and nitrogen oxides (NOx) concentrations in Beijing were reproduced by using IAQMS-street v2.0 both on regional scale and street scale. The prediction fractions within a factor of two (FAC2s) between simulations and observations of NO and NO2 increased from 0.11 and 0.34 in NAQPMS to 0.78 and 1.00 in IAQMS-street v2.0, respectively. The normalized mean biases (NMBs) of NO and NO2 decreased from 2.67 and 1.33 to -0.25 and 0.08. the concentration of NOx at street scale is higher than that at the regional scale, and the simulated distribution of pollutants on regional scale was improved in IAQMS-street v2.0 compared with that in IAQMS-street v1.0. We further used the IAQMS-street v2.0 to quantify the contribution of local on-road traffic emissions to the O3 and NOx emissions and analyze the effect of traffic-regulation policies in Beijing. Results showed that heavy-duty trucks are the major source of on-road traffic emissions of NOx. The relative contributions of local traffic emissions to NO2, NO, and O3 emissions were 53.41, 57.45, and 8.49 %, respectively. We found that traffic-regulation policies in Beijing largely decreased the concentrations of NOx and hydrocarbons (HC); however, the O3 concentration near the road increased due to the decrease consumption of O3 by NO. To decrease the O3 concentration in urban areas, controlling the local emissions of HC and NOx from other sources requires consideration.

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MUNICH v2.0: a street-network model coupled with SSH-aerosol (v1.2) for multi-pollutant modelling

Cited by 14 publications

References 45 publications

Modeling of street-scale pollutant dispersion by coupled simulation of chemical reaction, aerosol dynamics, and CFD

Modeling of street-scale pollutant dispersion by coupled simulation of chemical reaction, aerosol dynamics, and CFD

Modelling concentration heterogeneities in streets using the street-network model MUNICH

IAQMS-street v2.0: a two-way coupled regional-urban–street-network model system for Beijing, China

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