Approximation of mission level at air monitoring stations by means of autonomous neural models

• Autorzy: Hoffman S
• Języki publikacji: EN

Abstrakty

EN

Long-term collection of data, recorded at several air monitoring stations located in Central Poland, was analyzed. The main objective of the analysis was to choose optimum modelling methods for concentration of specified air pollutants. For this purpose accuracies of various groups of autonomous models were compared. Prediction of any air pollutants was performed using three different modelling methods. The modelled value was instantaneous concentration of specified pollutant. The models varied in the number and type of the explanatory variables and the modelling technique. It was presumed that there is a need for modelling the measurement gap, comprising a selected extract of the time series of a chosen pollutant. For successive cases in the gap, prediction errors of various methods of modelling were compared.

Słowa kluczowe

EN

air pollution; environmental engineering; waste management; air monitoring stations; air pollutants

PL

zanieczyszczenie powietrza; inżynieria środowiska; gospodarowanie odpadami; stacje monitoringu powietrza; zanieczyszczenia powietrza

• Wydawca: Oficyna Wydawnicza Politechniki Wrocławskiej
• Czasopismo: Environment Protection Engineering
• Rocznik: 2012
• Tom: Vol. 38, nr 2
• Strony: 109--119
• Opis fizyczny: Bibliogr. 7 poz., tab., rys.

Twórcy

autor

Hoffman S

• Częstochowa University of Technology, Department of Chemistry, Water and Wastewater Technology, ul. Dąbrowskiego 69, 42-200 Częstochowa

Bibliografia

• [1] PLAIA A.,BONDI A.L., Atmos. Environ., 2006, 40 (38), 7316.
• [2] GENTILI S.,MAGNATERRA L., PASSERINI G., An introduction to the statistical filling of environmental data time series, [In:] Handling Missing Data: Applications to Environmental Analysis, G. Latini, G. Passerini (Eds.), Wit Press, Southampton, 2006, 1–27.
• [3] Regulation of Ministry of Environment of 17 December 2008, On the evaluation of levels of substances in the air, Journal of Laws of the Republic of Poland, 2009, No 5, item 31.
• [4] HOFFMAN S., Treating missing data at air monitoring stations, [In:] Environmental Engineering, L. Pawłowski, M.R. Dudzińska, A. Pawłowski (Eds.),Taylor and Francis Group, London, 2007, 349–353.
• [5] HOFFMAN S.,Environ. Eng. Sci., 2006, 23 (4), 603.
• [6] HOFFMAN S., Application of Neural Networks to Regression Modeling of Air Pollutants Concentrations, Wydawnictwa Politechniki Częstochowskiej, Częstochowa, 2004 (in Polish).
• [7] HOFFMAN S., JASIŃSKI R., Missing Data Imputation into the Data Sets of Air Quality Monitoring Systems, Wydawnictwo Politechniki Częstochowskiej, Częstochowa, 2009 (in Polish).