Sulfur dioxide dispersion and source contribution to receptors of downtown Patras, Greece |
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Authors: | Panayotis C Yannopoulos |
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Institution: | (1) Environmental Engineering Laboratory, Civil Engineering Department, University of Patras, 265 00 Patras, Greece |
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Abstract: | Background The development of the city of Patras, including harbour relocation, in conjunction with the protection of the regional ecosystems,
requires air quality assessment and management. For this reason, a model applicable in the Patras area is necessary and valuable.
The goal of this study was to validate a model suitable for predicting the dispersion of sulfur dioxide (SO2), based on particular activity, topography and weather conditions.
Methods We used the US-EPA ISCLT3 integral dispersion model to predict SO2 concentrations for Patras, Greece. We assumed that the major contribution to Patras air pollution came from central heating,
harbour and traffic. We calculated traffic emissions using COPERTIII.
Results and Discussion Assigning suitable values of the mixing height, the model predicted the local and spatial distribution of the mean monthly
SO2 concentrations in downtown Patras, as well computed the contribution of the SO2 emissions originating from each particular source at each receptor location on a seasonal and annual basis. The comparison
between predictions and measurements shows that the model performance for estimating the SO2 concentrations and period pattern is satisfactory.
Conclusion The mixing height was the critical parameter for calibrating the model. Model validation promises satisfactory predictions
for SO2 pollution levels on monthly basis.
Recommendations and Outlook The model could be used in predicting SO2 concentrations and source contribution for several downtown Patras receptors using pertinent meteorological and emission
information. It could be also extended to predict the dispersion of other primary air pollutants. The calibrated model predictions
could be used to fill gaps in monitoring data, saving money and time, and help in assess and manage air quality as Patras
develops. |
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Keywords: | Air quality management dispersion model long-term prediction model validation primary air pollutants sulfur dioxide |
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