Vol. 5 No. 7 (2019) · Articles

Temporal variation and prediction of air pollution: A case study of Ludhiana City

Ashish Gupta
Research Scholar, Civil Engineering Department, Punjab Engineering College (Deemed to be University), Chandigarh-160012, IN

Keywords: ARIMA, Time series, Temporal variation, Air pollution

Abstract

From the past few years more and more emphasis has been laid by the public on day to day air quality and the pollutant levels to which they are exposed. People are becoming more aware and concerned about their health thus a forecasting model is required which can predict the Air Pollution in future, so that we can implement strict rules to decrease the pollutant level. Data of 4 monitoring stations was collected from Central Pollution Control Board (CPCB) and Punjab Pollution Control Board (PPCB) and temporal variations is figured out. Results show that concentration of air pollutants are higher in winters (December, January and February) and post monsoon period (September, October and November) in comparison to summers and monsoons. In order to predict the future air
quality annual average (2001-2018) of RSPM, NOX and SO2 had been examined and prediction of next 7 years (2019- 2025) air quality parameters is carried out. Time series analysis is used to forecast the future trend and it shows that the RSPM level will increase to significant level with maximum concentration going to 296.08 ppm by 2025 which is 5 times the NAAQS limits of 60 ppm. For NOx the concentration will be 42.04 ppm by 2022 thus exceeding the NAAQS limits of 40 ppm. The maximum error in forecasting by 2018 data by ARIMA is 2.06% for RSPM, 6% for NOx and 0.824% for SO2 in comparison to actual results of 2018.

References

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