Status and preparation of prediction models for ozone as an air pollutant in Shiraz, Iran

Document Type : Original Research Paper

Authors

Department of Natural Resources and Environment, Shiraz University, Shiraz, Iran

10.7508/pj.2016.04.002

Abstract

In the present study, air quality analyses for ozone (O3) were conducted in Shiraz, a city in the south of Iran. The measurements were taken from 2011 through 2012 in two different locations to prepare average data in the city. The average concentrations were calculated for every 24 hours, each month and each season. Results showed that the highest concentration of ozone occurs generally in the afternoon while the least concentration was found in the morning and at midnight. Monthly concentrations of ozone showed the highest value in August and June while the least value was in December. The seasonal concentrations showed the least amounts in autumn while the highest amounts were in spring. Relations between the air pollutant and some meteorological parameters were calculated statistically using the daily average data. The wind data (velocity, direction), relative humidity, temperature, sunshine periods, evaporation, dew point, and rainfall were considered as independent variables. The relationships between concentration of pollutant and meteorological parameters were expressed by multiple linear regression equations for both annual and seasonal conditions using SPSS software. Root mean square error (RMSE) test showed that among different prediction models, stepwise model is the best option. 

Keywords

References

Abdul-Wahab, S.A. and Al-Alawi, S.M. (2002). Assessment and prediction of tropospheric ozone concentration levels using artificial neural networks. Environ. Modell. Softw., 17(3), 219–228.
Abdul-Wahab, S.A., Bakheit, C.S. and Al-Alawi, S.M. (2005). Principal component and multiple regression analysis in modelling of ground-level ozone and factors affecting its concentrations. Environ. Modell. Softw., 20 (10), 1263–1271.
Asrari, E., Sen, P.N. and Masoudi, M. (2007). Status of carbon mono oxide in Tehran City- Iran. Pollut. Res., 26 (4), 531-535.
Bernhard, G., Booth, C.R. and Ehramjian, J.C. (2010). Climatology of ultraviolet radiation at high latitudes derived from measurements of the National Science Foundation’s ultraviolet spectral irradiance monitoring network. Springer-Verlag and Tsinghua University Press.
Camalier, L., Cox, W. and Dolwick, P. (2007). The effects of meteorology on ozone in urban areas and their use in assessing ozone trends. Atmos. Environ., 41,127-137.
Chelani, A.B. et al. (2001). Statistical modeling of ambient air pollutants in Delhi. Water Air Soil Pollut., 1326, 315-331.
Cuhadaroglu, B. and Demirci, E. (1997). Influence of some meteorological factors on air pollution in Trabzon city. Energ. Buildings,  25 (3), 179–184.
Cunningham, W.P., and Cunningham, M.A. (2002). Principles of environmental science inquiry and applications. MxGraw Hill Company.
Elminir, H.K. (2005). Dependence of urban air pollutants on meteorology. Sci. Total. Environ., 350, 225–237.
Fabian, P. and Martin, D. (2014). Ozone in atomespher. Springer_ Verlay Barlin Hei delbery.
Gerami, S. (2014). Study of air pollution and its relationship with meteorological parameters in Esfahan city. Project of B.Sc, Shiraz University.
Guinness World Records (2013). Page 036 (Hardcover edition). ISBN 9781904994879.
Jacob, D., Logan, J.A., Yevich, R.M., Gardner, G.M., Spivakovsky, C.M. et al. (1993). Simulation of summertime ozone over North America. J. Geophys. Res., 98, 14797-14816.
Ho, L.C. and Lin, W.Y. (1994). Semi-statistical model for evaluating the effects of source emissions and meteorological effects on daily average NOx concentrations in South Taiwan. Atmos. Environ., 37, 2051-2059.
IPCC (2007). Climate Change 2007: Synthesis Report, Contribution of Working Groups I, II and III to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. IPCC, Geneva, Switzerland, 104.
Lam, G.C.K., Leong, D.Y.C. et al. (1997). Street level concentration of NOX and suspended particulate matter in Hong Kong. Atmos. Environ. 93, 1-11.
Li, L., Qian, J., Ou, C.Q., Zhou, Y.X., Guo, C., and Guo, Y. (2014). Spatial and temporal analysis of Air Pollution Index and its timescale-dependent relationship with meteorological factors in Guangzhou, China, 2001–2011. Environ. Pollut., 190, 75-81.
Kalabokas, P.D., Adamopoulos, A.D. and Viras L.G. (2012). Seasonal variation characteristics of PM10 particles, nitrogen oxides and ozone in the Mediterranean urban areas of Athens and Thessaloniki, Greece. Fresen. Environ. Bull., 21 (11), 3168-3176.
Kinnear, P.R. (2002). SPSS for windows made simple release 10. (Psychology press).
Lacis, A.A., Wuebbles, D.J. and Logan, J.A. (1990). Radiative forcing of climate by changes in the vertical distribution of ozone. J. Geophys. Res., 95, 9971-9981.
Mandal, S. (2000). Progressive decrease of air pollution level from west to east at Calcutta', Indian. Indian Eval. Clin. Pract., 20, 6-10.
Masoudi, M. and Asadifard, E. (2015). Status and prediction of Nitrogen Dioxide as an air pollutant in Ahvaz City, Iran. Pollut. Atmos., 225, 1-10.
Masoudi, M., Asadifard, E. and Rastegar, M. (2014a). Status and prediction of ozone as an air pollutant in Ahvaz City, Iran. Caspian J. Environ. Sci., 12, 215-224.
Masoudi, M., Behzadi, F. and Sakhaei, M. (2014b). Status and prediction of Ozone as an air pollutant in Tehran, Iran. Ecol., Environ. Conserv., 20 (2), 771-776.
Masoudi, M., Sakhaei, M., Behzadi, F. and Jokar, P. (2016). Status of PM10 as an air pollutant and its prediction using meteorological parameters in Tehran, Iran. Fresen. Environ. Bull., 25(4), under publication.
Mulumba, J.P., Venkataraman, S. and Afullo, T.J.O. (2015). Modeling Tropospheric Ozone Climatology over Irene (South Africa) Using Retrieved Remote Sensing and Ground-Based Measurement Data. J. Remote Sensing & GIS, 4(3): 1-11.
Rasmussen, D.J., Fiore, A.M., Naik, V., Horowitz, L.W. and McGinnis, S.J. (2012). Surface ozone- temperature relationships in the eastern US: A monthly climatology for evaluating chemistry-climate models. Atmos. Environ., 47, 142-153.
Ryan, W.F., Doddridge, B.G., Dickerson, R.R., Morales, R.M., Hallock, K.A. et al. (2007). Assessment of the performance of ECC-ozonesondes under quasi- flight conditions in the environmental simulation chamber: Insights from the Juelich Ozone Sonde Intercomparison Experiment (JOSIE). J. Geophys. Res., 112, D19306.
Sabah, A., Al-Rubiei, R. and Al-Shamsi, A. (2003). A statistical model for predicting carbon monoxide levels. Int. J. Environ. Pollut., 19, 209-224.
Sánchez-Ccoyllo, O.R. and Andrade, M.F. (2002). The influence of meteorological conditions on the behavior of pollutants concentrations in São Paulo, Brazil. Environ. Pollut., 116 (2), 257–263.
Sharma, B.K. (2001). An Introduction to environmental pollution. Krishna prakashan media (p) ltd.
Wang, S.M., Yu, H., Song, L., Xie, Y. and Zhu, Q. (2015). Air quality in a mountainous city: A case study in Chongqing, China. Fresen. Environ. Bull., 24(9), 2699-2706.
Yoo, J.M., Lee, Y.R., Kim, D., Jeong, M.J., Stockwell, W.R., Kundu, P.K., Oh, S.M., Shin, D.B. and Lee, S.J. (2014). New indices for wet scavenging of air pollutants (O3, CO, NO2, SO2, and PM10) by summertime rain. Atmos. Environ., 82, 226-237.
Pollution
Volume 2, Issue 4
October 2016
Pages 387-397

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