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Objectives: Air pollution has become a serious problem in India. Seven out of top ten most polluted cities in the World in 2018 are Indian Cities (World Air Quality Ranking report). PM2.5 stands for Particulate Matter measuring 2.5 microns or less in diameter suspended in air. PM2.5 can cause significant negative health impacts such as Ischemic Heart Disease (IHD), and Lung cancer. The objective of this study is to estimate trends and patterns of Particulate Matter 2.5 Concentration levels in Indian cities.

Methods: We consider an Auto Regressive Integrated Moving Average (ARIMA) model to explain the variability of particulate matter (PM2.5) levels across six different cities in India, using the daily observation data provided by the Central Pollution Control Board of India.

Findings: Results from our model indicate that statistically significant differences exist in pollutant levels between Bangalore, Delhi, Chennai, Hyderabad, Vijayawada, and Vishakhapatnam. Seasonality in pollutant levels is also significant. Mean levels of pollutants are generally higher during winter months and lower around the monsoon season for all the south Indian cities.

Applications: Results from our model could be useful for understanding and predicting the air pollutant trends and patterns of south Indian cities.


Keywords

Air Pollution in India, ARIMA Model, Trends and Patterns of PM2.5 Levels.
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