Daily air pollution time series analysis of Isfahan City

Different time series analysis of daily air pollution of Isfahan city were performed in this study. Descriptive analysis showed different long-term variation of daily air pollution. High persistence in daily air pollution time series were identified using autocorrelation function except for SO2 which seemed to be short memory. Standardized air pollution index (SAPI) time series were also calculated to compare fluctuation of different time series with different levels. SAPI time series indicated that NO and NO2, CH4 and non-CH4 have similar time fluctuations. The effects of weather condition and vehicle accumulation in Isfahan city in cold and warm seasons are also distinguished in SAPI plots.

[1]  J H Seinfeld,et al.  On frequency distributions of air pollutant concentrations. , 1976, Atmospheric environment.

[2]  E. Ziegel.  Forecasting and Time Series: An Applied Approach , 2000 .

[3]  D. J. Mckee,et al.  Health effects associated with ozone and nitrogen dioxide exposure , 1993 .

[4]  J. Schwartz,et al.  Mortality and air pollution in London: a time series analysis. , 1990, American journal of epidemiology.

[5]  Chung-Kung Lee,et al.  Multifractal Characteristics in Air Pollutant Concentration Time Series , 2002 .

[6]  David R. Maidment,et al.  Handbook of Hydrology , 1993 .

[7]  Joel Schwartz,et al.  Analysis of health outcome time series data in epidemiological studies , 2004 .

[8]  Phaedon C. Kyriakidis,et al.  Stochastic modeling of atmospheric pollution: a spatial time-series framework. Part II: application to monitoring monthly sulfate deposition over Europe , 2001 .

[9]  Nelson Gouveia,et al.  Time series analysis of air pollution and mortality: effects by cause, age and socioeconomic status , 2000, Journal of epidemiology and community health.

[10]  Ralf Toumi,et al.  SCALING AND PERSISTENCE OF UK POLLUTION , 2001 .

[11]  Kasım Koçak,et al.  Nonlinear time series prediction of O3 concentration in Istanbul , 2000 .

[12]  R. Treffeisen,et al.  Spectral analysis of air pollutants. Part 1: elemental carbon time series , 2000 .

[13]  H. Lange,et al.  Trends of air pollution in the Fichtelgebirge Mountains, Bavaria , 1999, Environmental science and pollution research international.

[14]  Eugene Yee,et al.  A simple model for the probability density function of concentration fluctuations in atmospheric plumes , 1997 .

[15]  P. Young,et al.  Time series analysis, forecasting and control , 1972, IEEE Transactions on Automatic Control.

[16]  Romualdo Salcedo,et al.  Time-series analysis of air pollution data , 1999 .

[17]  K. Hipel,et al.  Time series modelling of water resources and environmental systems , 1994 .

[18]  Panos G. Georgopoulos,et al.  Statistical distributions of air pollutant concentrations , 1982 .

[19]  Agnes M. Herzberg,et al.  Can public policy be influenced? , 2003 .

[20]  Chung-Kung Lee,et al.  Simple multifractal cascade model for air pollutant concentration (APC) time series , 2003 .

[21]  Rainer Brüggemann,et al.  Data analysis of environmental air pollutant monitoring systems in Europe , 2004 .

[22]  Gwilym M. Jenkins,et al.  Time series analysis, forecasting and control , 1972 .

[23]  Panos G. Georgopoulos,et al.  Statistical distributions of air pollutant concentrations. , 1982, Environmental science & technology.

[24]  S. Roberts,et al.  Combining data from multiple monitors in air pollution mortality time series studies , 2003 .

[25]  B L Bowerman,et al.  FORECASTING AND TIME SERIES, AN APPLIED APPROACH, DUXBURY , 1993 .