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2007 | 16 | 4 |

Tytuł artykułu

Prediction of SO2 and PM concentrations in a coastal mining area [Zonguldak, Turkey] using an artificial neural network

Autorzy

Warianty tytułu

Języki publikacji

EN

Abstrakty

EN
In this study, artificial neural networks are proposed to predict the concentrations of S02 and PM at two different stations in Zonguldak city, a major coastal mining area in Turkey. The established artificial neural network models involve meteorological parameters and historical data on observed S02, PM as input variables. The models are based on a three-layer neural network trained by a back-propagation algorithm. The models accurately measure the trend of SO2 and PM concentrations. The results obtained through the proposed models show that artificial neural networks can efficiently be used in the analysis and prediction of air quality.

Wydawca

-

Rocznik

Tom

16

Numer

4

Opis fizyczny

p.633-638,fig.,ref.

Twórcy

autor
  • Balikesir University, 10100 Balikesir, Turkey

Bibliografia

  • 1. WONG, G.W.K., KO, F.W.S., LAU, T.S., LI, S.T., HUI, D., PANGI, S.W., LEUNG, R., FOK, T.F., LAI, C.K.W. Tem­poral relationship between air pollution and hospital admis­sions for asthmatic children in Hong Kong, Clinical and Ex­perimental allergy, 31, 565, 2001.
  • 2. BALLESTER, F., SAEZ, M., HOYOS, S.P., INIQUEZ, C., GANDARILLAS, A., TOBIAS, A., BELLIDO, J., TARA- CIDO, M., ARRIBAS, F., DAPONTE, A., ALANSO, E., CANADA, A., GRIMA, F.G., CIRERA, L., BOILLOS, M.J.P., SAURINA, C., GOMEZ, F., TENIAS, J.M. The EMECAM project: a multicentre study on air pollution and mortality in spain: combined results for particulates and for sulfur dioxide, Occup. Environ. Med., 59, 300, 2002.
  • 3. TIMONEN, K.L., PEKKANEN, J., TIITTANEN, P., SA- LONEN, R.O., Effects of air pollution on changes in lung function induced by exercise in children with chronic respiratory symptoms, Occup. Environ. Med., 59, 129, 2002
  • 4. LIFPERT, F.W., MORRIS, S.C. Temporal and spatial rela­tions between age specific mortality and ambient air quality in the United States: regression results for counties, 1960­97, Occup. Environ. Med., 59, 156, 2002
  • 5. MAIER, H.R., DANDY, G.C. Neural network based mod­elling of environmental variables: A systematic approach, Math. and Computer Modelling 33, 669, 2001
  • 6. NISKA, H., HILTUNEN, T., KARPPINEN, A., RUUS- KANEN, J., KOLEHMAINEN, T. Evolving the neurah network model for forecasting air pollution time series, Engineering Applications of Artificial Intelligence, 17, 159, 2004.
  • 7. NISKA, H., RANTAMAKI, M., HILTUNEN, T., KARP­PINEN, A., HUKKONEN, J., RUUSKANEN, J., KOLEH­MAINEN, M. Evaluation of an integrated modelling system containing a multi-layer perceptron model and the numeri­cal weather prediction model HURLEM for the forecasting of urban airborne pollutant concentrations. atmospheric en­vironment 39, 6524, 2005.
  • 8. CHELANI, H.R., RAO, C.V.C., PHADKE, K.M., HASAN, M.Z. Prediction of sulphur dioxide concentration using arti­ficial neural networks. Environmental Modelling and Soft­ware, 17, 161, 2002.
  • 9. PEREZ, P., REYES, T. Integrated neural network model for PM10 forecasting. Atmospheric Environment, 40, 2845, 2006.
  • 10. GRIVAS, G., CHALAULAKOU, A. Artificial neural net­work models for prediction of PM10 hourly concentrations, in the Greater Area of Athens, Greece. Atmospheric Envi­ronment, 40, 1216, 2006
  • 11. WANG, W., LU, W., WANG, X., LEUNG A.Y.T. Prediction of maximum daily ozone level using combined neural net­work and statistical characteristics, Environmental Interna­tional, 29, 555, 2003.
  • 12. BASURKO, E.A., BERASTEGI, G.I., MADARIAGA, I. Regression and multilayer perceptron-based models to fore­cast hourly O3 and NO2 levels in the Bilbao area, Environ­mental Modelling and Software, 21, 430, 2006.
  • 13. LU, H.C., HSIEH, J.C., CHANG, T.S. Prediction of daily maximum ozone concentrations form meteorological con­ditions using a two-stage neural network. Atmospheric Re­search, 81, 124-139, 2006.
  • 14. BOZNAR M., LESJAK M., AND MLAKAR P. A Neural Net­work Based Method for Short Term Predictions of Ambient SO2 Concentrations in Highly Polluted Industrial Areas of Complex Terrain, Atmospheric Environment, 27B, 2,.221-230, 1993.
  • 15. Zonguldak Local Agenda 21, http://www.iula-emme.org/ la21/cities/Zonguldak
  • 16. GHOSE, M.K., MAJEE, S.R. Air pollution caused by open­cast mining and its abetement measures in India. J. Environ­mental Management, 63, 193, 2001.
  • 17. TOMAQ N., ACUN C., DEMIREL F., ERMI§ B., AYOGLU F.N. Zonguldak ilinde astim ve diger allerjik hastaliklarin preva- lansi ve bazi risk faktorlerinin ara^tirilmasi. X. UlusalAllerji ve Klinik Immunoloji Kongresi,, Adana, Turkey, 24-27 Eylul 2002
  • 18. GARDNER, M.W., DORLING, S.R. Artificial neural net­works (the multilayer perceptron) - a review of applications in the atmospheric sciences. Atm. Environment, 32(14/15), 2627, 1998.

Typ dokumentu

Bibliografia

Identyfikatory

Identyfikator YADDA

bwmeta1.element.agro-article-aae2d62d-df62-4ac8-812d-117ae7e07feb
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