عنوان مقاله [English]
نویسنده [English]چکیده [English]
Spatial Analysis of PM2.5 Pollutants and its Statistical Correlation with
Meteorological Parameters in Tehran
1*Karimi, S.; 2Sakhaei, M.
1 Assist. Profe. College of Engineering, School of Environment, University of Tehran, Iran
2 M.Sc, Environmental Planning, College of Engineering,
School of Environment, University of Tehran, Iran
(Received: 2016/12/26; Accepted: 2018/10/02)
The objective of this study is the surveying spatial analysis of PM2.5 pollutants condition and the effects of atmospheric factors on it in the metropolis of Tehran. For this, the daily PM2.5 data measured by the controlling air quality and atmospheric parameters measured by Meteorological Organization in Tehran was used. The meteorological parameters used in this study include: temperature (minimum, average and maximum), relative humidity (minimum, average and maximum), wind speed (average and maximum), dew point and atmospheric pressure respectively. To study the spatial concentration of PM2.5, inverse distance weighting interpolation method was used. Inverse distance weighting model results show that in regions 7, 10, 20 and 21 have the highest concentration. Daily average PM2.5 concentrations during the study period showed that the highest concentrations at 18 June and the lowest was in the third April. It also shows the monthly average in January was the highest concentrations, while the lowest concentration is assigned to April. Seasonal Concentration shows the highest concentration of PM2.5 in winter season. Then, the statistical correlation between PM2.5 and atmospheric parameters examined. For this purpose, Pearson correlation and multiple linear regression methods were used. Pearson correlation coefficient analysis shows that, PM2.5 has a direct correlation with air pressure and dew point, While a negative correlation with rainfall and wind speed. The relationship between PM2.5 as the dependent variable and atmospheric parameters as independent variables were investigated by linear regression models (Enter and Stepwise). The correlation coefficient in the equation Enter and Stepwise is 0.427 and 0.346 respectively. Which represents the ability of both models to predict the amount of PM2.5. Test Results of Mean Square Error, shows, Stepwise model to predict PM2.5, is more suitable than other methods.
Keyword: Air pollution, PM2.5, Atmospheric factors, Interpolation, Statistical correlation, Linear regression
*Corresponding author: Email: firstname.lastname@example.org
Afraz, R. 2011. Evaluation of Soil Pollution in Land Scape: A Case Study of Nahavand County. Master's thesis on the environment. Environmental group, Department of natural resources, Isfahan University of Technology. 72 p (in persian).
Ahmadi, H.; Ahmadi, T.; Shahmoradi, B.; Mohammadi, S. & Kohzadi, S. 2015. The effect of climatic parameters on air pollution in Sanandaj, Iran. Journal of Advances in Environmental Health Research, 3(1): 49-61.
Almasi, A.; Moradi, M.; Sharafi, K. & Abbasi, S. 2014. Seasonal Variation in Air Quality of Kermanshah City in Terms of PM10 Concentration over a Four-Year Period (2008-2011). j.health, 5 (2): 149-158 (in persian).
Alvim-Ferraz, M. C. M.; Pereira, M. C.; Ferraz, J. M.; Almeida e Mello, A. M. C. & Martins, F. G. 2005. European directives for air quality: analysis of the new limits in comparison with asthmatic symptoms in children living in the Oporto Metropolitan area, Portugal. Human and Ecological Risk Assessment, 11(3): 607-616.
Basu, R., Woodruff, T. J.; Parker, J. D.; Saulnier, L. & Schoendorf, K. C. 2004. Comparing exposure metrics in the relationship between PM2. 5 and birth weight in California. Journal of Exposure Science and Environmental Epidemiology, 14(5): 391-396.
Cunningham, W. P. C. & Ann, M. 2008. Principles of environmental science: inquiry & applications (No. GE105. C865 2008).
Degobbi, C.; Lopes, F. D.; Carvalho-Oliveira, R.; Muñoz, J. E. & Saldiva, P. H. 2011. Correlation of fungi and endotoxin with PM2. 5 and meteorological parameters in atmosphere of Sao Paulo, Brazil. Atmospheric environment, 45(13): 2277-2283.
Dominick, D.; Latif, M. T.; Juahir, H.; Aris, A. Z. & Zain, S. M. 2012. An assessment of influence of meteorological factors on PM 10 and NO 2 at selected stations in Malaysia. Sustainable Environment Research, 22 (5): 305-315.
Giri, D.; Murthy, V. K. & Adhikary, P. R. 2007. The influence of meteorological conditions on PM10 concentrations in Kathmandu Valley. Int. J. Environ. Res, 2 (1): 49-60
Habashi, H.; Hoseini, S.; Shetaei, H. & Mohammadi, J. 2006. Evaluation of the accuracy and accuracy of in-line methods for estimating the total nitrogen content using GIS. Third Space Information System Conference, pp. 71-76 (in persian).
Javanbakht Amiri, S. & Khatami, H. 2012. Investigation of the relationship between pollutants of air quality index and meteorological parameters in Tehran with regression analysis method in 2005. Journal of Human and Environment, 10 (1):15-28 (in persian).
Mansouri, N.; Vaezi, M.; Darvish, N.; Ghanadi, A. & Tabatabaei, R. 2011. Statistical analysis of the distribution of CO and PM10 pollutants with wind speed changes in a five-year period in Tehran. Natural Environment Journal. 64 (4):443-455 (in persian).
McKendry, I. G. 2000. PM10 levels in the Lower Fraser Valley, British Columbia, Canada: an overview of spatiotemporal variations and meteorological controls. Journal of the Air & Waste Management Association, 50 (3): 443-452.
Miri, M.; Ghaneian, M. T.; Gholizadeh, A.; Yazdani Avval, M. & Nikoonahad, A. 2016. Assessment of Spatial Analysis Methods in Mapping of Air Pollution in Mashhad. jehe. 3 (2):143-154 (in persian).
Najafpoor, A.; Jonidi Jafari, A. & Doosti, S. 2015. Analysis of the trend of changes in the concentration of five pollutants of air quality index in Tehran metropolis and their relationship with meteorological data during the years of 2001-2009. Health Journal of Shaheed Beheshti, University of Medical Sciences, Faculty of Health. 3 (2):17-26 (in persian).
Nazari, Z.; Khorasani, N.; Feyznia, S. & Karami, M. 2013. Investigation of changes in the concentration of PM10 and the effect of meteorological parameters on it during the years 2005-2010. Natural Environment Journal. 66 (1):101-11 (in persian).
Nourpoor, A. & Feyz, A. 2014. Determination of spatial and temporal variations of sulfur dioxide, nitrogen dioxide and various suspended particles by using GIS techniques in Tehran. Journal of Environmental Studies. 40 (3):723-738 (in persian).
Rahimi, M.; Yazdani, M.; Asadi, M. & Heydari, M. 2015. Investigation of Sanandaj air pollution with emphasis on time variation of PM10 concentration. Two letters of research on urban ecology, 6 (1):99-116 (in persian).
Rezaei, A.; Sayadi, M. & Rezaei, M. 2013. Quantitative and qualitative study of air pollution and its relation with climate factors of Birjand city in 2012. Short report of community health. 7 (4):62-65 (in persian).
Sahsavani, A.; Yarahmadi, M.; Mesdaghinia, A.; Younesyan, M.; Jaafarzadeh, N. A.; Naeemabadi, A. & Nadafi, K. 2012. Analysis of dust storms entering Iran with emphasis on Khuzestan Province. Hakim Research. 3:192-202.
Shareipoor, Z. & Akbari Bidokhti, A. 2014. The study of spatial distribution of air pollutants in Tehran during the cold months of 2011-2013. Environmental science and technology. 16 (1):149-166 (in persian).
Shareipoor, Z. 2009. Study seasonal and daily changes of air pollutants and their relation with meteorological parameters. Journal of Earth and Space Physics. 35 (2):119-137 (in persian).
Sousa, S. I. V.; Martins, F. G.; Pereira, M. C.; Alvim-Ferraz, M. C. M.; Ribeiro, H.; Oliveira, M. & Abreu, I. 2008. Influence of atmospheric ozone, PM 10 and meteorological factors on the concentration of airborne pollen and fungal spores. Atmospheric Environment, 42(32): 7452-7464.
Tecer, L. H.; Süren, P.; Alagha, O.; Karaca, F. & Tuncel, G. 2008. Effect of meteorological parameters on fine and coarse particulate matter mass concentration in a coal-mining area in Zonguldak, Turkey. Journal of the Air & Waste Management Association, 58(4): 543-552.
Zhang, A.; Qi, Q.; Jiang, L.; Zhou, F. & Wang, J. 2013. Population exposure to PM 2.5 in the urban area of Beijing. PloS one, 8(5): e63486.