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Mann–Kendall trend of pollutants, temperature and humidity over an urban station of India with forecast verification using different ARIMA models

Abstract

The purpose of the present research is to identify the trends in the concentrations of few atmospheric pollutants and meteorological parameters over an urban station Kolkata (22° 32′ N; 88° 20′ E), India, during the period from 2002 to 2011 and subsequently develop models for precise forecast of the concentration of the pollutants and the meteorological parameters over the station Kolkata. The pollutants considered in this study are sulphur dioxide (SO2), nitrogen dioxide (NO2), particulates of size 10-μm diameters (PM10), carbon monoxide (CO) and tropospheric ozone (O3). The meteorological parameters considered are the surface temperature and relative humidity. The Mann–Kendall, non-parametric statistical analysis is implemented to observe the trends in the data series of the selected parameters. A time series approach with autoregressive integrated moving average (ARIMA) modelling is used to provide daily forecast of the parameters with precision. ARIMA models of different categories; ARIMA (1, 1, 1), ARIMA (0, 2, 2) and ARIMA (2, 1, 2) are considered and the skill of each model is estimated and compared in forecasting the concentration of the atmospheric pollutants and meteorological parameters. The results of the study reveal that the ARIMA (0, 2, 2) is the best statistical model for forecasting the daily concentration of pollutants as well as the meteorological parameters over Kolkata. The result is validated with the observation of 2012.

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Acknowledgments

The authors thank the IMD and WBPCB for providing the data for research and Department of Science and Technology (DST) for financial assistance under PURSE and INSPIRE programme. The MoES, Government of India supported Air Quality Monitoring Network (MAPAN) is acknowledged for the MOU with DAS-CU.

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Correspondence to Sutapa Chaudhuri.

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Chaudhuri, S., Dutta, D. Mann–Kendall trend of pollutants, temperature and humidity over an urban station of India with forecast verification using different ARIMA models. Environ Monit Assess 186, 4719–4742 (2014). https://doi.org/10.1007/s10661-014-3733-6

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  • DOI: https://doi.org/10.1007/s10661-014-3733-6

Keywords

  • Mann–Kendall trend
  • ARIMA
  • Pollutants
  • Meteorological parameters