A simple model for the dispersion of pollutants from a road tunnel portal

Oettl, Dietmar; Sturm, Peter; Bacher, Michael; Pretterhofer, Gerhard; Almbauer, Raimund

doi:10.1016/s1352-2310(02)00254-6

Cited by 30 publications

(15 citation statements)

References 11 publications

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“…GRAL is run at 10 m horizontal and 2 m vertical resolution on this 17 × 14 km 2 domain. Due to the hilly topography, highways are built through numerous tunnels, creating NO x emission hotspots at ventilation shafts and tunnel portals, which can optionally be treated in GRAL with a specific algorithm, described in Oettl et al (2002), or simply as point sources at the tunnel gates.…”

Section: Model Domainmentioning

confidence: 99%

Evaluation of high-resolution GRAMM–GRAL (v15.12/v14.8) NOx simulations over the city of Zürich, Switzerland

et al. 2017

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Abstract. Hourly NO x concentrations were simulated for the city of Zürich, Switzerland, at 10 m resolution for the years 2013-2014. The simulations were generated with the nested mesoscale meteorology and micro-scale dispersion model system GRAMM-GRAL (versions v15.12 and v14.8) by applying a catalogue-based approach. This approach was specifically designed to enable long-term city-wide buildingresolving simulations with affordable computation costs. It relies on a discrete set of possible weather situations and corresponding steady-state flow and dispersion patterns that are pre-computed and then matched hourly with actual meteorological observations. The modelling system was comprehensively evaluated using eight sites continuously monitoring NO x concentrations and 65 passive samplers measuring NO 2 concentrations on a 2-weekly basis all over the city. The system was demonstrated to fulfil the European Commission standards for air pollution modelling at nearly all sites. The average spatial distribution was very well represented, despite a general tendency to overestimate the observed concentrations, possibly due to a crude representation of trafficinduced turbulence and to underestimated dispersion in the vicinity of buildings. The temporal variability of concentrations explained by varying emissions and weather situations was accurately reproduced on different timescales. The seasonal cycle of concentrations, mostly driven by stronger vertical dispersion in summer than in winter, was very well captured in the 2-year simulation period. Short-term events, such as episodes of particularly high and low concentrations, were detected in most cases by the system, although some unrealistic pollution peaks were occasionally generated, pointing at some limitations of the steady-state approximation.The different patterns of the diurnal cycle of concentrations observed in the city were generally well captured as well. The evaluation confirmed the adequacy of the cataloguebased approach in the context of city-scale air pollution modelling. The ability to reproduce not only the spatial gradients but also the hourly temporal variability over multiple years makes the model system particularly suitable for investigating individualized air pollution exposure in the city.

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Section: Model Domainmentioning

confidence: 99%

Evaluation of high-resolution GRAMM–GRAL (v15.12/v14.8) NOx simulations over the city of Zürich, Switzerland

et al. 2017

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“…Eleven passive sampler sites for NO 2 and SO 2 were available for comparison purposes. The sampling took place over a period of 1 yr (2000 -2001).…”

Section: Air Quality Measurementsmentioning

confidence: 99%

“…The methodology used for the dispersion calculations from tunnel portals is discussed in detail in Oettl et al, 2 and comprehensive validations of the model are described in Oettl et al 6 It should be noted that the most appealing approach for the dispersion calculations for tunnel portals would be the use of RANS models. Generally, such models are able to account for important processes, such as shear stresses along the jet stream from a portal, buoyancy effects, or the inertial forces resulting from the exit velocity.…”

Section: Dispersion Modelingmentioning

confidence: 99%

“…This estimation is based on simple scale considerations but also could be proved by numerical simulations with a RANS model. 2 In the study described here, a very simple NO-NO 2 chemistry model was applied. It links annual mean NO x concentrations to annual mean NO 2 concentrations with an empirically determined relationship derived from numerous observation sites: 34 NO 2 ϭ NO x ⅐ ͭ NO x ϩ 130 ϩ 0.005 ͮ (9) In this way, annual mean NO 2 concentrations were calculated and compared with observations recorded by means of passive samplers and the fixed AQM station.…”

Section: Dispersion Modelingmentioning

confidence: 99%

“…Neither could prognostic Eulerian models (e.g., Reynolds averaged Navier-Stokes models [RANS]) be used for the dispersion simulation, owing to (1) the excessive demand on computer capacity (large area, high resolution), and (2) problems inherent in such models in the treatment of turbulence processes in the vicinity of tunnel portals. 2 The choice was, therefore, to use a modeling system consisting of a combined Lagrangian model for the dispersion 2-6 and a RANS model [7][8][9] for the wind field calculations. Coupling of Lagrangian dispersion models with wind field models has already been done by different authors mainly for scientific purposes or for smaller time-and length-scales.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Lagrangian Dispersion Modeling of Vehicular Emissions from a Highway in Complex Terrain

Oettl

Sturm

Pretterhofer

et al. 2003

Journal of the Air & Waste Management Association

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Transit traffic through the Austrian Alps is of major concern in government policy. Pollutant burdens resulting from such traffic are discussed widely in Austrian politics and have already led to measures to restrict traffic on transit routes. In the course of an environmental assessment study, comprehensive measurements were performed. These included air quality observations using passive samplers, a differential optical absorption spectroscopy system, a mobile and a fixed air quality monitoring station, and meteorological observations. As was evident from several previous studies, dispersion modeling in such areas of complex terrain and, moreover, with frequent calm wind conditions, is difficult to handle. Further, in the case presented here, different pollutant sources had to be treated simultaneously (e.g., road networks, exhaust chimneys from road tunnels, and road tunnel portals). No appropriate system for modeling all these factors has so far appeared in the literature. A prognostic wind field model coupled with a Lagrangian dispersion model is thus presented here and is designed to treat all these factors. A comparison of the modeling system with results from passive samplers and from a fixed air quality monitoring station proved the ability of the model to provide reasonable figures for concentration distributions along the A10.

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Computational Simulation of the Flow Field of a Filter System inside Self-Ventilated Road Tunnels due to Heavy Vehicle Traffic

Iser¹,

Almbauer

The Aerodynamics of Heavy Vehicles II: Trucks, Buses, and Trains

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A simple model for the dispersion of pollutants from a road tunnel portal

Cited by 30 publications

References 11 publications

Evaluation of high-resolution GRAMM–GRAL (v15.12/v14.8) NO<sub><i>x</i></sub> simulations over the city of Zürich, Switzerland

Evaluation of high-resolution GRAMM–GRAL (v15.12/v14.8) NO<sub><i>x</i></sub> simulations over the city of Zürich, Switzerland

Lagrangian Dispersion Modeling of Vehicular Emissions from a Highway in Complex Terrain

Computational Simulation of the Flow Field of a Filter System inside Self-Ventilated Road Tunnels due to Heavy Vehicle Traffic

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A simple model for the dispersion of pollutants from a road tunnel portal

Cited by 30 publications

References 11 publications

Evaluation of high-resolution GRAMM–GRAL (v15.12/v14.8) NO&lt;sub&gt;&lt;i&gt;x&lt;/i&gt;&lt;/sub&gt; simulations over the city of Zürich, Switzerland

Evaluation of high-resolution GRAMM–GRAL (v15.12/v14.8) NO&lt;sub&gt;&lt;i&gt;x&lt;/i&gt;&lt;/sub&gt; simulations over the city of Zürich, Switzerland

Lagrangian Dispersion Modeling of Vehicular Emissions from a Highway in Complex Terrain

Computational Simulation of the Flow Field of a Filter System inside Self-Ventilated Road Tunnels due to Heavy Vehicle Traffic

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Evaluation of high-resolution GRAMM–GRAL (v15.12/v14.8) NO<sub><i>x</i></sub> simulations over the city of Zürich, Switzerland

Evaluation of high-resolution GRAMM–GRAL (v15.12/v14.8) NO<sub><i>x</i></sub> simulations over the city of Zürich, Switzerland