CHADETRIK ROUT, GAURAV SHUKLA, VIKAS BENIWAL, SURENDRA PAL SINGH AND RAHUL GROVER*
Department of Civil Engineering, Maharishi Markandeshwar (Deemed to be University), Mullana, Ambala-133 207
*(e-mail : firstname.lastname@example.org; Mobile : 96710 20303)
(Received : January 4, 2022; Accepted : March, 10, 2022)
Time series is a time-oriented or chronological sequence of observations on a variable of interest. AutoRegressive Integrated Moving Average (ARIMA) model approach was used in this study for time series analysis of NO2 concentration in Punjab region, India. Kriging Spatial Interpolation method was also used. This study integrated the satellite observed data with statistical methods. The predicted NO2 concentration was used for spatial distribution and estimation of NO2. OMI satellite data for tropospheric NO2 from the year 2012 to 2019 were used to make a forecast of NO2 concentrations for the year 2020. The R2 value showed good agreement between the observed and predicted concentrations of NO2 in both the approaches.
Key words : : Tropospheric NO2, ARIMA, Kriging interpolation, time series modelling, spatial distribution