Please use this identifier to cite or link to this item:https://hdl.handle.net/20.500.12259/52869
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): Dėdelė, Audrius;Miškinytė, Auksė;Vilkaitė, Milda
Title: Forecasting of daily carbon monoxide concentrations in Klaipėda
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;Anglies monoksidas;ARIMA;Air pollution;Carbon monoxide;ARIMA
Abstract: Many people in urban areas are affected by high levels of air pollution, which can cause harmful effects on human health. Local air pollution forecasting plays an important role in air quality management system providing relevant information not only for public authorities, but also for the community, and allows taking actions to prevent or to avoid episodes of high pollution. Carbon monoxide is one of the main air pollutants, which emissions are produced from the combustion of fossil fuels, in Lithuania mostly from energy use and road transport. The exposure to CO can lead to acute and chronic diseases, especially in vulnerable populations. The study aim was to develop forecasting model for predicting daily concentrations of carbon monoxide (CO) in Klaipėda, the third largest city in Lithuania. Hourly time series of CO concentrations and meteorological parameters were obtained from the city monitoring stations. To assess the significance (p<0.05) between meteorological parameters and CO concentrations, correlation analysis was made. Autoregressive integrated moving average (ARIMA) model was used for CO concentration forecasting. Meteorological variables that had the highest positive correlation coefficients were selected for the modelling. The evaluation of model performance was made through statistical parameters such as root mean square error (RMSE), the correlation coefficient and the coefficient of determination. The daily average CO concentration forecasted by ARIMA model and observed by air quality monitoring station was 0.247 mg/m3 and 0.252 mg/m3 . The RMSE between observed and model‘s forecasted CO concentrations was 0.0541. The correlation coefficient and the coefficient of determination were 0.725 and 0.526. The results of this study indicated that predicted CO concentrations by ARIMA model agreed well with observed concentrations
Internet: http://flashnews.gr/storage/files/uploads/diethnes-sinedrio.pdf
Affiliation(s): Aplinkotyros katedra
Gamtos mokslų fakultetas
Vytauto Didžiojo universitetas
Appears in Collections:Universiteto mokslo publikacijos / University Research Publications

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