Dispersion modelling of air pollution caused by road traffic using a Markov Chain–Monte Carlo model |
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Authors: | D Oettl R A Almbauer P J Sturm G Pretterhofer |
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Institution: | (1) Institute for Internal Combustion Engines and Thermodynamics, Graz University of Technology, Inffeldgasse 25, 8010 Graz, Austria e-mail: oettl@vkmb.tu-graz.ac.at, AT |
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Abstract: | Although the strict legislation regarding vehicle emissions in Europe (EURO 4, EURO 5) will lead to a remarkable reduction
of emissions in the near future, traffic related air pollution still can be problematic due to a large increase of traffic
in certain areas. Many dispersion models for line-sources have been developed to assess the impact of traffic on the air pollution
levels near roads, which are in most cases based on the Gaussian equation. Previous studies gave evidence, that such kind
of models tend to overestimate concentrations in low wind speed conditions or when the wind direction is almost parallel to
the street orientation. This is of particular interest, since such conditions lead generally to the highest observed concentrations
in the vicinity of streets. As many air quality directives impose limits on high percentiles of concentrations, it is important
to have good estimates of these quantities in environmental assessment studies. The objective of this study is to evaluate
a methodology for the computation of especially those high percentiles required by e.g. the EU daughter directive 99/30/EC
(for instance the 99.8 percentile for NO2). The model used in this investigation is a Markov Chain – Monte Carlo model to predict pollutant concentrations, which performs
well in low wind conditions as is shown here. While usual Lagrangian models use deterministic time steps for the calculation
of the turbulent velocities, the model presented here, uses random time steps from a Monte Carlo simulation and a Markov Chain
simulation for the sequence of the turbulent velocities. This results in a physically better approach when modelling the dispersion
in low wind speed conditions. When Lagrangian dispersion models are used for regulatory purposes, a meteorological pre-processor
is necessary to obtain required input quantities like Monin-Obukhov length and friction velocity from routinely observed data.
The model and the meteorological pre-processor applied here, were tested against field data taken near a major motorway south
of Vienna. The methodology used is based on input parameters, which are also available in usual environmental assessment studies.
Results reveal that the approach examined is useful and leads to reasonable concentration levels near motorways compared to
observations.
We wish to thank Andreas Schopper (Styrian Government) for providing air quality values, M. Kalina for providing the raw
data of the air quality stations near the motorway and J. Kukkonen for providing the road site data set from the Finish Meteorological
Institute (FMI). The study was partly funded by the Austrian science fund under the project P14075-TEC. |
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Keywords: | : Lagrangian dispersion model Traffic Air pollution Low wind speed Environmental assessment studies |
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