SIRANERISK: Modelling dispersion of steady and unsteady pollutant releases in the urban canopy

Soulhac, Lionel; Lamaison, Guillevic; Cierco, François-Xavier; Salem, Nabil Ben; Salizzoni, Pietro; Méjean, P.; Armand, Patrick; Patryl, Luc

doi:10.1016/j.atmosenv.2016.04.027

Cited by 21 publications

(8 citation statements)

References 28 publications

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“…Like Gaussian dispersion models, street-network models require only few flow specifications, which can be either imported from an external flow simulation or obtained through suitable parametrisations. The only street-network models currently used operationally are the SIRANE [71,72] model and its unsteady version SIRANERISK [69], which both contain built-in flow parametrisations.…”

Section: Options For Fast Urban Dispersion Modellingmentioning

confidence: 99%

Evaluation of fast atmospheric dispersion models in a regular street network

et al. 2018

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The need to balance computational speed and simulation accuracy is a key challenge in designing atmospheric dispersion models that can be used in scenarios where near real-time hazard predictions are needed. This challenge is aggravated in cities, where models need to have some degree of building-awareness, alongside the ability to capture effects of dominant urban flow processes. We use a combination of high-resolution large-eddy simulation (LES) and wind-tunnel data of flow and dispersion in an idealised, equal-height urban canopy to highlight important dispersion processes and evaluate how these are reproduced by representatives of the most prevalent modelling approaches: (i) a Gaussian plume model, (ii) a Lagrangian stochastic model and (iii) street-network dispersion models. Concentration data from the LES, validated against the wind-tunnel data, were averaged over the volumes of streets in order to provide a high-fidelity reference suitable for evaluating the different models on the same footing. For the particular combination of forcing wind

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Section: Options For Fast Urban Dispersion Modellingmentioning

confidence: 99%

Evaluation of fast atmospheric dispersion models in a regular street network

et al. 2018

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“…However, estimating background concentrations above streets with a Gaussian plume model inhibits a comprehensive atmospheric chemistry treatment, impacting the modeling of secondary pollutant concentrations, such as O 3 , and the secondary formation of NO 2 concentrations. 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), developed by Kim et al (2018), presents a similar box-model parameterization as SIRANE, but it does not employ a Gaussian model to determine background concentrations.…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2020

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Abstract. Regional-scale chemistry-transport models have coarse spatial resolution (coarser than 1 km ×1 km) and can thus only simulate background concentrations. They fail to simulate the high concentrations observed close to roads and in streets, 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 by coupling them dynamically. This coupling combines the regional-scale chemistry-transport model Polair3D and a street-network model, the Model of Urban Network of Intersecting Canyons and Highway (MUNICH), with a two-way feedback. MUNICH explicitly models 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 the 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 nonstationary 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 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 two-way 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 good agreement between the measurements and the concentrations simulated with MUNICH and SinG. The two-way 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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“…On one side they allow for an investigation of the phenomena that are responsible of the pollutant transfer, depending on the geometrical characteristics of the domain [ 9 , 20 – 22 ]. On the other, they provide data sets that can be subsequently used to evaluate the accuracy of the dispersion models in prediction time-averaged concentrations [ 23 – 25 ].…”

Section: Introductionmentioning

confidence: 99%

Physical and Numerical Models of Atmospheric Urban Dispersion of Pollutants

Toscano¹,

Marro²,

Mele³

et al. 2020

Computational Science and Its Applications – ICCSA 2020

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In this paper the application of numerical and physical models for the simulation of airborne pollutants in urban areas are presented. The assessment of the impact of cruise ships during the hoteling phase in the port of Naples is considered as case study. A physical model of the urban area of Naples has been realized (scale 1:500) and tested in the wind tunnel facility of the Ecole Central de Lyon. Results of wind tunnel tests are compared with CALPUFF and CFD simulations with the aim to validate the performances of the models. The results obtained give useful information for an optimized use of dispersion models.

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SIRANERISK: Modelling dispersion of steady and unsteady pollutant releases in the urban canopy

Cited by 21 publications

References 28 publications

Evaluation of fast atmospheric dispersion models in a regular street network

Evaluation of fast atmospheric dispersion models in a regular street network

Nonstationary modeling of NO<sub>2</sub>, NO and NO<sub><i>x</i></sub> in Paris using the Street-in-Grid model: coupling local and regional scales with a two-way dynamic approach

Physical and Numerical Models of Atmospheric Urban Dispersion of Pollutants

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SIRANERISK: Modelling dispersion of steady and unsteady pollutant releases in the urban canopy

Cited by 21 publications

References 28 publications

Evaluation of fast atmospheric dispersion models in a regular street network

Evaluation of fast atmospheric dispersion models in a regular street network

Nonstationary modeling of NO&lt;sub&gt;2&lt;/sub&gt;, NO and NO&lt;sub&gt;&lt;i&gt;x&lt;/i&gt;&lt;/sub&gt; in Paris using the Street-in-Grid model: coupling local and regional scales with a two-way dynamic approach

Physical and Numerical Models of Atmospheric Urban Dispersion of Pollutants

Contact Info

Product

Resources

About

Nonstationary modeling of NO<sub>2</sub>, NO and NO<sub><i>x</i></sub> in Paris using the Street-in-Grid model: coupling local and regional scales with a two-way dynamic approach