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Analyzing and forecasting ambient air quality of Chennai city in India

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Regardless of the existing governmental and public preventive actions for surveillance and controlling the air quality in several regions of the Chennai city in India, the air quality does not meet the desired standard. In this regard, this study employs an ARMA/ARIMA modelling approach for forecasting Respirable Suspended Particulate Matter (RSPM), Sulphur dioxide (SO2) and Nitrogen dioxide (NO2) concentration for three most polluted sites in Chennai city. A total of nine univariate linear stochastic models have been developed, three for each of the stations which includes one for each of the specific pollutants in order to forecasts the concentration of each pollutant. The evaluation of the model statistics R2 values and index of agreement values evince that a significant level of real-time forecasting of the pollutants can be achieved by employing the developed ARMA/ARIMA models. Moreover, the comparisons of actual air pollutant concentration have been carried out with the permissible limit as prescribed by the National ambient air quality standards (NAAQS) of India for assessing the level of pollution of all three locations.

About the Authors

Imran Nadeem
B.S Abdur Rahman Crescent Institute of Science and Technology

Department of Mathematics

GST Road Vandalur 600048, Chennai

Ashiq M. Ilyas
B.S Abdur Rahman Crescent Institute of Science and Technology

Department of Mathematics

GST Road Vandalur 600048, Chennai

P.S. Sheik Uduman
B.S Abdur Rahman Crescent Institute of Science and Technology

Department of Mathematics

GST Road Vandalur 600048, Chennai


1. Adebiyi A.A., Adewumi A.O. and Ayo C.K. (2014). Comparison of ARIMA and artificial neural networks models for stock price prediction. Journal of Applied Mathematics, 2(1), 1-7, DOI: 10.1155/2014/614342.

2. Box GEP and Jenkins G.M. (1976). Time series analysis, forecasting and control, revised ed. Holden-Day, San Francisco.

3. Box GEP. Jenkins GM. and Reinsel, GC. (1994). Time series analysis: Forecasting and control (3rd ed.). Englewood Cliffs, New Jersey: Prentice Hall.

4. Benson P. E. & Pinkerman, K.O. (1984). CALINE4, a dispersion model for predicting air pollution concentration near roadways. State of California, Department of Transportation, Division of Engineering Services, Office of Transportation Laboratory.

5. Brockwell J.B. and Davis R.A. (2002). Introduction to time series and forecasting. New York: Springer.

6. Burnham K.P. and Anderson D.R. (2004). Multimodel inference: understanding AIC and BIC in Model Selection. Sociological Methods & Research, 33, 261-304, DOI: 10.1177/0049124104268644.

7. Cats G.J. and Holtslag A.A.M. (1980). Prediction of air pollution frequency distribution, The lognormal distribution. Atmospheric Environment, 14, 255-258.

8. Chubarova N.E., Androsova E.E., Kirsanov A.A., Vogel B., Vogel H., Popovicheva O.B. and Rivin G.S. (2019). Aerosol And Its Radiative Effects During The Aeroradcity 2018 Moscow Experiment. Geography, Environment, Sustainability, 12(4), 114-131, DOI: 10.24057/2071-9388-2019-72.

9. Duenas C., Fernandez M.C., Canete S., Carretero J. and Liger E. (2005). Stochastic model to forecast ground-level ozone concentration at urban and rural areas. Chemosphere. 61(10), 1379-1389.

10. Dhyani R., Sharma N. and Maity A.K. (2017). Prediction of PM2.5 along urban highway corridor under mixed traffic conditions using CALINE4 model. Journal of Environmental Management, 198, 24-32.

11. Guttikunda S.K., Goel R., Mohan D., Tiwari G. and Gadepalli R. (2015). Particulate and gaseous emissions in two coastal cities – Chennai and Vishakhapatnam, India. Air Quality, Atmosphere & Health, 8(6), 559-572.

12. Guttikunda S.K., Nishadh K.A. and Jawahar P. (2019). Air pollution knowledge assessments (APnA) for 20 Indian cities. Urban Climate, 27, 124-141.

13. Jakeman A.J., Simpson R.W. and Taylor J.A. (1988). Modelling distributions of air pollutant concentrations — III. The hybrid deterministicstatistical distribution approach. Atmospheric Environment, 22, 163-174.

14. Jian L., Zhao Y., Zhang M.B. and Bertolatti D. (2012). An application of ARIMA model to predict submicron particle concentrations from meteorological factors at a busy roadside in Hangzhou, China. Science of the Total Environment, 426, 336-345.

15. Juda K. (1989). Air pollution modelling. In P. N. Cheremisinoff (Ed.), Encyclopedia of environmental control technology, air pollution control, USA: Gulf Publishing Company 2, 83-134.

16. Kaushik G., Chel A., Patil S. and Chaturvedi S. (2019). Status of Particulate Matter Pollution in India: A Review. Handbook of Environmental Materials Management, 167-193.

17. Khandelwal I., Adhikari R. and Verma G. (2015). Time series forecasting using hybrid Arima and ANN models based on dwt decomposition. Procedia Computer Science, 48, 173-179.

18. Koppen climate classification | climatology. Encyclopedia Britannica. Archived from the original on 2020-02-19. Retrieved 2020-02-19.

19. Kumar K., Yadav A.K., Singh M.P., Hassan H. and Jain VK. (2004). Forecasting daily maximum surface ozone concentrations in Brunei Darussalam – An ARIMA modelling approach. Journal of Air Waste management Association, 84, 809-814.

20. Kumar U. and Jain V.K. (2010). ARIMA forecasting of ambient air pollutants ( , NO, and CO). Stochastic Environmental Research and Risk Assessment, 24, 751-760.

21. Liu P.W.G. (2009). Simulation of the daily average concentrations at Ta-Liao with Box–Jenkins time series models and multivariate analysis. Atmospheric Environment, 43, 2104-2113.

22. Meyler A., Kenny G. and Quinn T. (1998). Forecasting Irish inflation using ARIMA models, 1-48.

23. Mills T.C. (1991). Time series techniques for economists. Cambridge: Cambridge University Press.

24. National Ambient Air Quality Monitoring NAAQMS/……/2014-2015, Retrieved 19 November, 2018. [online] Available at: Status_ Trend_Report_2012.pdf. [Accessed 20 May 2020].

25. Naveen V. and Anu N. (2017). Time Series Analysis to Forecast Air Quality Indices in Thiruvananthapuram District, Kerala, India. International Journal of Engineering Research and Application, 7(6), 66-84.

26. Pankratz A. (1983). Forecasting with Univariate Box–Jenkins models: concepts and cases. Wiley, New York, DOI: 10.1002/9780470316566.

27. Pant P., Lal R.M., Guttikunda S.K., Russell A.G., Nagpure A.S., Ramaswami A. and Peltier R.E. (2019). Monitoring particulate matter in India Recent trends and future outlook. Air Quality, Atmosphere & Health, 12(1), 45-58.

28. Petersen W.B. (1980). User’s guide for HIWAY-2: A highway air pollution model.US Environmental Protection Agency.

29. Raimondi P.M., Rando F., Vitale M.C. and Calcara A.M.V. (1997). Short-time fuzzy DAP predictor for air pollution due to vehicular traffic. WIT Transactions on Ecology and the Environment, 19.

30. Rajamanickam R. and Nagan S. (2018). Assessment of air quality index for cities and major towns in Tamil Nadu, India. Journal of Civil and Environmental Engineering, 8(2).

31. Rao S.T., Sistla G., Petersen W.B., Irwin J.S. and Turner D.B. (1985). Evaluation of the performance of RAM with the regional air pollution study database. Atmospheric Environment, 19, 229-245.

32. Road Statistics of India. [online] Available at: [Accessed 20 June 2019].

33. Schwarz G. (1978). Estimating the dimension of a model. The Annals of Statistics 6(2), 461-464.

34. Sivaramasundaram K. and Muthusubramanian P. (2010). A preliminary assessment of and TSP concentrations in Tuticorin India. Air Quality, Atmosphere and Health, 3(2), 95-102.

35. Slini Th., Karatzas K., Moussiopoulos N. (2002). Statistical analysis of environmental data as the basis of forecasting: an air quality application. Science of the Total Environment, 288(3), 227-237.

36. Sharma P., Chandra A. and Kaushik S.C. (2009). Forecasts using Box–Jenkins models for the ambient air quality data of Delhi City. Environmental Monitering and Assessment, 157(1-4), 105-112.

37. Sharma R. Kumar R. Sharma DK. Priyadarshini I. Pham BT. Bui DT. and Rai S. (2019). Inferring air pollution from air quality index by different geographical areas: case study in India. Air Quality, Atmosphere & Health, 1-11.

38. Shumway R.H., Stoffer D.S. (2006). Time series analysis and its applications – with R examples. Springer Science, Business Media, LLC.

39. Srimuruganandam B. and Nagendra SMS. (2011). Characteristics of particulate matter and heterogeneous traffic in the urban area of India. Atmospheric Environment, 45(18), 3091-3102.

40. Srimuruganandam B. and Nagendra S.M.S. (2012a). Source characterization of and mass using a chemical mass balance model at urban roadside. Science of the Total Environment, 433, 8-19.

41. Tabachnik B.G. and Fidell L.S. (2005). Using multivariate statistics, 5th edition. Pearson Int. Edition, Boston.

42. Urban Infrastructure: Twelfth Five Year Plan (2012–2017). [online] Available at: [Accessed 27 August 2017].

43. Venkataraman C., Brauer M., Tibrewal K., Sadavarte P., Ma Q., Cohen A., Chaliyakunnel S., Frostad J., Klimont Z.,Martin R.V., Millet D.B., Phillip S., Walker K. and Wang S. (2018). Source influence on emission pathways and ambient PM2.5 pollution over India (2015–2050). Atmospheric Chemistry and Physics Discussions, 18, 8017-8039.

44. Willmott C.J. and Wicks D.E. (1980). An empirical method for the spatial interpolation of monthly precipitation within California. Physical Geography, 1, 59-73.

45. Willmott C.J. (1981). On the validation of models. Physical geography, 2(2), 184-194.

46. Willmott C.J., Ackleson S.G., Davis R.E., Feddema J.J., Klink K.M. and Legates D.R. (1985). Statistics for the evaluation and comparison of models. Journal of Geophysical Research, 90, 8995-9005.

47. World Health Organization. (2014). Seven million premature deaths annually linked to air pollution, World Health Organization, 25 March 2014, viewed on 15 Jan 2016. [online] Available at: [Accessed 20 May 2020].

48. Zannetti P. (1989). Simulating short-term, short-range air quality dispersion phenomena. In Encyclopedia of environmental control technology, Gulf Publishing Company Houston.

For citation:

Nadeem I., Ilyas A.M., Uduman P.S. Analyzing and forecasting ambient air quality of Chennai city in India. GEOGRAPHY, ENVIRONMENT, SUSTAINABILITY. 2020;13(3):13-21.

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ISSN 2071-9388 (Print)
ISSN 2542-1565 (Online)