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Evaluation of the Street Pollution Model OSPM for Measurements at 12 Streets Stations Using a Newly Developed and Freely Available Evaluation Tool

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Evaluation of the Street Pollution Model OSPM for Measurements at 12 Streets Stations Using a Newly Developed and Freely Available Evaluation Tool

The Operational Street Pollution Model (OSPM) has been evaluated in comparison with continuous half-hourly measurements over a multi-year period for five permanent street monitor stations that constitute part of the Danish Air Quality Monitoring Programme as well as with passive measurements with long averaging times at nine locations in Copenhagen as part of a specific project. Results are discussed in relation to the quality objective within the EU Air Quality Directive and general uncertainties in model parameters and model input data. It is demonstrated that OSPM reproduces the observed basic dependencies of concentrations on meteorological parameters–most notably wind direction and wind speed. However, in some cases the modelled annual trends in NOx and NO2 are slightly different from what is found in the measured concentrations. For NOx the OSPM reproduces the observations well, especially for the most recent years, while for NO2 the model over-predicts in two cases. The explanation for this over-prediction is believed to be uncertainties in the traffic or emission input data, but also in model parameters, and the representativeness of the urban background data may play an important role. The newly developed evaluation tool is used for exploratory data analysis of the large amount of data, and is free available for the research community. The evaluation tool is complementary to the ‘Delta Tool’ that has been developed in the framework of FAIRMODE by JRC Ispra. OSPM calculations for nine streets with passive sampler measurements were conducted as ‘blind test’ i.e. without knowing the measured values. OSPM calculations were in good agreement with the measurements for seven out of nine street sections. Refinements of the input data lead to a significant improvement of the agreement between model results and measurements at the two remaining locations. Recommendations could be derived for an improved quality assurance of the input data and for minor adjustments in the OSPM.  Read more..

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