The Estimate of Dust Concentration Using of Weather Variable (A Case study: Ahvaz City) | ||
| نشریه محیط زیست طبیعی | ||
| Article 8, Volume 71, Issue 3, December 2018, Pages 385-397 PDF (1.1 M) | ||
| Document Type: Research Paper | ||
| DOI: 10.22059/jne.2018.221268.1280 | ||
| Authors | ||
| Sajad Alimahmoodi Sarab1; Shaban Shataee Jouybari2; Alireza Rashki3 | ||
| 1PhD Student / Gorgan University of Agriculture and Natural Resources | ||
| 2Faculty Member / Gorgan University of Agricultural Sciences and Natural Resources | ||
| 3Faculty Member / Ferdowsi University of Mashhad | ||
| Abstract | ||
| The amount of dust and other air pollutants have increased during recent years. The PM10 is one of the most important variables that is used for monitoring and assessment of dust pollution. To predict PM10, different studies have used various statistical methods. In this study, two aims were pursuit: 1) Using of Spearman analysis to determine the relation between PM10 and weather variables such as temperature (maximum, average, minimum), relative Humid (maximum, average, minimum), rain, wind (speed and direction), and visibility, and 2) prediction of PM10 with using of Random Forest model on daily data (in a period study: 2008 to 2011). The results of Spearman analysis were shown that PM10 had most relation with visibility and minimum temperature and least relation with rain, -0.376, +0.349, and -0.077, respectively. In addition, Random Forest analysis was shown that for prediction of PM10, visibility and minimum temperature were very important. Fitting curve between observed and prediction data was shown a medium correlation with Y=0.1686x +183.49 and R2=47/0, sig=0.99. Final sequence of trees of random forest was shown that of all data, just maximum and minimum of relative humid and minimum of temperature were able to classification with 396 (>0.205 %), 389(>0.305 %), and 387 (>5.5 oC) data for each variable, respectively. | ||
| Keywords | ||
| Air pollution; weather variables; estimate of dust concentration; Random Forest regression | ||
| References | ||
|
Afzali, A., Rashid, M., Sabariah, B., Ramli, M., 2014. PM10 Pollution: Its Prediction and Meteorological Influence in PasirGudang, Johor. 8th International Symposium of the Digital Earth (ISDE8). IOP Conf. Series: Earth and Environmental Science 18: 012100. Akbari, A., Fakheri, M., Poorgholamhossin, A., Akbari, Z., 2016. Monthly Zoning of the Air Pollution and Surveying its Relationship with Climatic Factors (Case Study: Mashhad City). Journal of Natural Environment. 68(4): 533- 547. (in Persian) Aldrin, M., Haff, I., 2005. Generalised Additive Modelling of Air Pollution, Traffic Volume and Meteorology. Atmos. Environ. 39: 2145–2155. Alyari, M., Teshnelab, M., Sedigh, A. KH., 2008. Predict air pollution data by using Multi-Layer Percepteron, Time Delay Line, Gamma and ANFIS by gradient free learning methods. Journal - management control 2(1): 1- 19. (in Persian) Asgari, M. M., DuBois. A., Asgari, M., 1998. Association of ambient air quality with children's lung functions in urban and rural Iran. Arch Environ Health; 53-222. (in Persian) Berastegi, G., Elias, A., Barona, A., Saenz, J., Ezcurra, A., Argandona, D., 2008. From diagnosis to prognosis for forecasting air pollution using neural networks: Air pollution monitoring in Bilbao. Environmental Modelling & Software 23, 662-637. Bihamta M. R., Zare Chahouki M. A., 2008. Principles of Statistics for the Natural Resources Science, Tehran, University of Tehran Press. (in Persian) Bodaghpor, S., Charkhestani, A., 2011. Predictaion of GAS pollution concentration by means of Artificial neural network in Tehran urban. Journal of environmental science and technology: Spring 2011, Volume 13, Number 1 (48), Page 1 To 10 . (in Persian) Breiman, Leo., 2001. Random forests. Machine learning. 45.1: 5-32. Brunelli, U., Piazza, V., Pignato, L., Sorbello, F., Vitabile, S., 2007. Two-days ahead prediction of daily maximum concentrations of So2, O3, Pm10, No2, Co in the urban area of Palermo, Italy. Atmospheric Environment 41, 2967-2995. Camalier, L., Cox, W., Dolwick, P., 2007. The effects of meteorology on ozone in urban areas and their use in assessing ozone trends. Atmos. Environ. 41, 7,127–7,137. Cox, W.M., Chu, S.-H., 1995. Assessment of interannual ozone variation in urban areas from a climatological perspective. Atmos. Environ. 30, 2615–2625. Daniel, J, Jacob., Darrell, A, Winner., 2009. Effect of climate change on air quality. Atmospheric Environment. 43: 51–63. Escudero, M., Querol, X., Ávila, A., Cuevas, E., 2007. Origin of the exceedances of the European daily PM limit value in regional background areas of Spain. Atmospheric Environment. 41(4):730-44. Forster, C., et al., 2001. Forster, C., Wandinger, U., Wotawa, G., James, P., Mattis, I., Althausen, D., Simmonds, P., O'Doherty, S., Gerard Jennings, S., Kleefeld, C., Schneider, J., Trickl, T., Kreipl, S., Jäger, H., Stohl, A., Transport of boreal forest fire emissions from Canada to Europe. J. Geophys. Res. 106, 22,887–22,906. François-Xavier, J., Jean-Michel, P., Bruno, P., 2009. Three Non-Linear Statistical Methods for Analyzing PM10 Pollution in Rouen Area. CS-BIGS 3(1): 1-17. Gauderman, W., 2004. The effect of air pollution on lung development from 10 to 18 years of age”. N. Engl. J. Med. 351,11,1057-1067. Heald, C. L., Jacob, D.J., Park, R.J., Alexander, B., Fairlie, T.D., Yantosca, R.M., Chu, D.A., 2006. Transpacific transport of Asian anthropogenic aerosols and its impact on surface air quality in the United States. J. Geophys. Res. 111, D14310. Javanbakht Amiri, S., Khatemi, H., 2012. The relationship between pollution index air quality and meteorological parameters in Tehran regression analysis approach. Islamic Azad University - Science and Research Branch of Tehran. 10(1): 15- 28. (in Persian) Oliveira, S., Oehler, F., San-Miguel-Ayanz, J., Camia, A., Pereira, Joss M.C., 2012. Modeling spatial patterns of fire occurrence in Mediterranean Europe using multiple regression and random forest. Forest Ecology and Management 275(1):117-129. Ordonez, C., Mathis, H., Furger, M., Henne, S., Hoglin, C., Staehelin, J., Prevot, A.S.H., 2005. Changes of daily surface ozone maxima in Switzerland in all seasons from 1992 to 2002 and discussion of summer 2003. Atmos. Chem. Phys. 5, 1187– 1203. Pearson, R.L., 2000. Distance-weighted traffic density in proximity to a home is a risk factor for leukemia and other childhood cancers. J. Air Waste Manag. Assoc, 50(2):175-80. Perez, P., Reyes, J., 2006. An integrated neural network model for PM10 forecasting. Atmospheric Environment 40, 2845-2851. Prospero, J.M., 1999. Long-term measurements of the transport of African mineral dust to the southeastern United States: implications for regional air quality. J. Geophys. Res. 104, 15917–15927. Sabetghadam, S., Ahmadi-Givi, F., Golestani, Y., Aliakbari-Bidokhti, A. A., 2013. The impact of urban air pollutants on atmospheric visibility in Tehran, 2008. Journal of the Earth and Space Physics. ISSN 8647-1025. (in Persian) Sabouri, R., Akhmi, M., Zarasvandi, A., Khodadi, M., 2010. To determine the influence of Karun River water quality parameters in terms of the phenomena in the form of dust prediction model (Case study: Ahvaz city). Journal of Wetland eclogy. 2(7): 47- 56. (in Persian) Sadeghi, H., khaksar, S., 2015. Neural Network Model for Short Term Prediction of PM10 Pollution in Ahvaz City. Environmental researches. 5(9): 177- 186. (in Persian) Sayegh, Arwa S. Munir, Said. Turki Habeebullah, M. 2014. Comparing the Performance of Statistical Models for Predicting PM10 Concentrations. Aerosol and Air Quality Research, 14: 653–665. United Nations Economic Comission for Europe, 2007. Hemispheric Transport of Air Pollution 2007. Air Pollution Studies No. 16. United Nations, New York and Geneva. Wise, E, K., Comrie, A.C., 2005. Meteorologically adjusted urban air quality trends in the Southwestern United States. Atmos. Environ. 39, 2969–2980. You, W., Zang, Z., Pan, X., Zhang, L., Chen, D., 2015. Estimating PM2.5 in Xi'an, China using aerosol optical depth: A comparison between the MODIS and MISR retrieval models. Science of the Total Environment. 505: 1156- 1165. Yunesian, M., Malek, Afzali, H., 2002. Air pollution mortality in elderly in Tehran, Iran. Payesh, Journal of the Iranian Institute for Health Sciences Research 1: 19-24. (in Persian) | ||
|
Statistics Article View: 766 PDF Download: 838 |
||