Multi-scale modeling of urban air pollution: development and application of a Street-in-Grid model by coupling MUNICH and Polair3D

Kim, Youngseob; Wu, You; Seigneur, Christian; Roustan, Yelva

doi:10.5194/gmd-2017-189

Cited by 5 publications

(17 citation statements)

References 22 publications

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“…With the increase in environmental management requirements and technology developments, calculation methods are expected to be able to estimate vehicle emissions based on a single road, and to further determine their contributions to the generation of PM 2.5 and ozone (Kim et al 2017). Therefore, real-time road emission characteristics are significant for the presentation of emissions estimates.…”

Section: Introductionmentioning

confidence: 99%

Vehicle emissions calculation for urban roads based on the Macroscopic Fundamental Diagram method and real-time traffic information

Wang

Tong

Cao

et al. 2020

Atmospheric and Oceanic Science Letters

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Vehicle emissions calculation methods mostly use ownership information or annual road monitoring data as the activity level to calculate air pollutant emissions, but it is hard to reflect either the emissions intensity under different conditions or the spatiotemporal characteristics in various sections based on such approaches. This paper presents a method based on the Macroscopic Fundamental Diagram and real-time traffic data to calculate vehicle emissions, which could reflect the operation conditions and emission characteristics of vehicles. Following the 'Technical Guide for the Compiling of Road Vehicle Air Pollutant Emissions Inventories', the emissions of three roads with different lane numbers and road grades in Beijing were estimated and verified using this method. Compared with monitoring data, the average deviations of the traffic flow on the Fifth Expressway, Jingfu National Highway, and Jingzhou Provincial Highway were −25.5%, −26.5%, and −13.4%, respectively, and the average deviations of nitrogen oxides emissions were −27.7%, −12.9%, and −12%, respectively. This method showed good application potentials to construct the emissions inventory applied to the block-scale model and analyze the spatiotemporal distribution characteristics of motor vehicle emissions in urban areas.

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Section: Introductionmentioning

confidence: 99%

Vehicle emissions calculation for urban roads based on the Macroscopic Fundamental Diagram method and real-time traffic information

Wang

Tong

Cao

et al. 2020

Atmospheric and Oceanic Science Letters

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“…Although SIRANE uses a stationary hypothesis for pollutant transport, a new version of SIRANE, named SIRANERISK (Soulhac et al, 2016), removes the steady state hypothesis and simulates dispersion above street canyons using a Gaussian puff model. The Model of Urban Network of Intersecting Canyons and Highways (MUNICH) (Kim et al, 2018) presents a similar box-model parameterization as SIRANE, but it does not employ a Gaussian model to determinate background concentrations.…”

Section: Introductionmentioning

confidence: 99%

“…They may be provided by measurements, as in Kim et al (2018), or regional-scale CTMs, as in our study. This approach allows the implementation of a comprehensive chemical module to better estimate secondary pollutant formation.…”

Section: Introductionmentioning

confidence: 99%

“…In other words, the concentrations calculated in the streets do not influence the background concentrations. The coupling between background and street concentrations is dynamic in the multi-scale Street-In-Grid (SinG) model (Kim et al, 2018), which couples the regional scale model Polair3D (Sartelet et al, 2007) to the street-network model MUNICH, using the Polyphemus platform (Mallet et al, 2007). The street-network model is coupled to the first vertical level of the regional scale model.…”

Section: Introductionmentioning

confidence: 99%

“…Thus, SinG combines dynamically an advanced treatment of atmospheric transport and chemistry at the regional scale with a street-network parametrization formulated for streets with different aspect ratios. Kim et al (2018) validated SinG over a street-network located at a Paris suburb, regarding NO 2 , NO and NO x concentrations. Compared to the street or to the regional model, the SinG multi-scale approach improved NO 2 and NO x simulated concentrations compared to observations.…”

Section: Introductionmentioning

confidence: 99%

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Street-in-Grid modeling of gas-phase pollutants in Paris city

Lugon

Sartelet

Kim

et al. 2019

Preprint

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Abstract. Regional-scale chemistry-transport models have coarse spatial resolution, and thus can only simulate background concentrations. They fail to simulate the high concentrations observed close to roads and in streets, i.e. where a large part of the urban population lives. Local-scale models may be used to simulate concentrations in streets. They often assume that background concentrations are constant and/or use simplified chemistry. Recently developed, the multi-scale model Street-in-Grid (SinG) estimates gaseous pollutant concentrations simultaneously at local and regional scales, coupling them dynamically. This coupling combines the regional-scale chemistry-transport model Polair3D and the street network model MUNICH (Model of Urban Network of Intersecting Canyons and Highway). MUNICH models explicitly street canyons and intersections, and it is coupled to the first vertical level of the chemical-transport model, enabling the transfer of pollutant mass between the street canyon roof and the atmosphere. The original versions of SinG and MUNICH adopt a stationary hypothesis to estimate pollutant concentrations in streets. Although the computation of NOx concentration is numerically stable with the stationary approach, the partitioning between NO and NO2 is highly dependent on the time step of coupling between transport and chemistry processes. In this study, a new non-stationary approach is presented with a fine coupling between transport and chemistry, leading to numerically stable partitioning between NO and NO2. Simulations of NO, NO2 and NOx concentrations over Paris city with SinG, MUNICH and Polair3D are compared to observations at traffic and urban stations to estimate the added value of multi-scale modeling with a dynamical coupling between the regional and local scales. As expected, the regional chemical-transport model underestimates NO and NO2 concentrations in the streets. However, there is a good agreement between the measurements and the concentrations simulated with MUNICH and SinG. The dynamic coupling between the local and regional scales tends to be important for streets with an intermediate aspect ratio and with high traffic emissions.

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Intercomparison of three modeling approaches for traffic-related road dust resuspension using two experimental data sets

Thouron¹,

Seigneur²,

Kim³

et al. 2018

Transportation Research Part D: Transport and Environment

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Multi-scale modeling of urban air pollution: development and application of a Street-in-Grid model by coupling MUNICH and Polair3D

Cited by 5 publications

References 22 publications

Vehicle emissions calculation for urban roads based on the Macroscopic Fundamental Diagram method and real-time traffic information

Vehicle emissions calculation for urban roads based on the Macroscopic Fundamental Diagram method and real-time traffic information

Street-in-Grid modeling of gas-phase pollutants in Paris city

Intercomparison of three modeling approaches for traffic-related road dust resuspension using two experimental data sets

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