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Modeling Earth Systems and Environment

, Volume 4, Issue 4, pp 1435–1444 | Cite as

Autoregressive integrated moving average time series model for forecasting air pollution in Nanded city, Maharashtra, India

  • Govind Eknath Kulkarni
  • Aniket Avinash Muley
  • Nilesh Kailas Deshmukh
  • Parag Upendra Bhalchandra
Original Article
  • 102 Downloads

Abstract

The present study assesses the time series data of air pollution in Nanded city since 2011 and is collected from source of Central Pollution Control Board, Government of India. In this study, autoregressive integrated moving average (ARIMA) time series forecasting approach is used for prediction of air pollution in Nanded city with two main locations. The main aim of this study is to forecast the air pollution for next 5 years by using ARIMA model with the air pollutants NOx, SO2, RSPM and SPM. The time series analysis is the predictive analytic technique gives us better results and this analysis is performed through free and open source software R. The prediction results obtained through ARIMA model highlight the increasing level of air pollution in Nanded city. In future, this study may be helpful to maintain the air pollutant within the permissible limit and in the development of smart city.

Keywords

Air pollution ARIMA Time series Forecasting Nanded 

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Govind Eknath Kulkarni
    • 1
  • Aniket Avinash Muley
    • 2
  • Nilesh Kailas Deshmukh
    • 1
  • Parag Upendra Bhalchandra
    • 1
  1. 1.School of Computational SciencesSwami Ramanand Teerth Marathwada UniversityNandedIndia
  2. 2.School of Mathematical SciencesSwami Ramanand Teerth Marathwada UniversityNandedIndia

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