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Type of publication: Tezės kituose recenzuojamuose leidiniuose / Theses in other peer-reviewed publications (T1e)
Field of Science: Ekologija ir aplinkotyra / Ecology and environmental sciences (N012)
Author(s): Miškinytė, Auksė;Dėdelė, Audrius
Title: The evaluation of Gaussian dispersion model for the prediction of particulate matter concentrations
Is part of: ITM 2016: 35th international technical meeting on air pollution modelling and its application, 3-7 October 2016, Crete, Greece Bologna : Institute of atmosphere science and climate, 2016
Extent: p. 1-1
Date: 2016
Keywords: Oro tarša;Kietosios dalelės;Matavimų duomenys;Air pollution;Particulate matter;Measurement data
Abstract: Air pollution modelling is necessary and widely used tool for air quality management in urban areas. Atmospheric dispersion models, such as ADMS-Urban, are used to estimate dispersion of air pollutants released from many various sources and are applicable for many specific purposes from environmental impact assessment and air quality management decisions to environmental health studies. However, the high reliability and accuracy of model results is essential that the model could be used as an indicator of air quality impact. One of the most important phases before using the model in actual application is model validation, which involves the comparison of predictions against real data. The aim of this study was to evaluate the performance of ADMS-Urban dispersion model to predict particulate matter smaller than 10 μm (PM10) concentrations in Kaunas city. The data of emissions from road, industrial and domestic household sources as well as meteorology, background concentrations and time varying emission factors were included in the model. To assess the accuracy of ADMS-Urban model, modelled concentrations of PM10 have been compared with measurements conducted at 20 monitoring sites per city. The sampling sites were selected to represent the spatial variation of PM10 in the city. Each site was monitored for 14 days during warm and cold seasons using Harvard impactors, designed to collect particles at a flow rate of 10 l/min. The results showed that ADMS-Urban dispersion model tends to under predict PM10 concentrations compared with measurements and this is most evident when highest values are modelled. The correlation analysis revealed a high positive statistically significant relationship between modelled and measured concentrations of PM10 in warm season (r = 0.74) and in cold season (r = 0.79). The modelling results showed a good agreement with measurement data in both warm and cold seasons
Affiliation(s): Aplinkotyros katedra
Gamtos mokslų fakultetas
Vytauto Didžiojo universitetas
Appears in Collections:Universiteto mokslo publikacijos / University Research Publications

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