STATISTICAL TIME SERIES AND PREDICTABILITY ANALYSIS OF NITROGEN DIOXIDE
By
Rashmi Bhardwaj, Dimple Pruthi
Non Linear Dynamics Lab, University School of Basic and Applied Sciences
Guru Gobind Singh Indraprastha University, Delhi, India
Email: *rashmib22@gmail.com
(Received : November 24, 2017 ; Revised: September 06, 2018)
Abstract
Main component of deadly smog is ground-level ozone. Ozone pollution is triggering pulmonary disorders and respiratory infections at high rate. The chemical reaction of oxides of nitrogen with volatile organic compound in sunlight leads to the formation of ozone. Ozone is a complex pollutant to be controlled due to its formation process. The primary source in the formation of ozone is nitrogen dioxide. According to CPCB, the NO2 level has increased by 1.8 times from 36μg=m3 in 2000 to 65μg=m3 in 2016. Alarming ozone concentration has been found in the residential area RK Puram, Delhi. To control ozone level, nitrogen dioxide has to be considered. The predictability index of nitrogen dioxide not close to zero indicates NO2 concentration is predictable. In order to raise alarm for increasing ozone level, nitrogen dioxide can be predicted. The presen study attempts to predict the daily future concentration of nitrogen dioxide using developed autoregressive integrated moving average model.This will assist regulatory bodies to warn about poor air quality and carry out preventive measures.
Keywords and phrases: ARIMA, Predictability Index, Ground level ozone, Nitrogen Dioxide, Air Pollutant.
2010 Mathematics Subject Classification: 62P12