Air Quality Modelling in Jaipur: A SARIMA Approach to Forecasting PM2.5 and PM10 Levels

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IJEP 45(10): 931-938 : Vol. 45 Issue. 10 (October 2025)

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Karishma Chauhan1, Abhyudaya Singh2, Anil Dutt Vyas1* and Meena Kumari Sharma1

1. Manipal University, Department of Civil Engineering, Jaipur – 313 001, Rajasthan, India
2. Malaviya National Institute of Technology Jaipur (MNIT), Department of Civil Engineering, Jaipur – 302 017, Rajasthan, India

Abstract

Air pollution is a significant issue in urban areas, poses serious health and environmental risks. This research examines the seasonal and temporal fluctuations of particulate matter (PM2.5 and PM10) concentrations in Jaipur, India from 2018 to 2023, employing SARIMA models for trend analysis and forecasting. Analysis of data from the Central Pollution Control Board (CPCB) indicated that particulate concentrations often surpassed WHO safety thresholds, with maximum levels occurring in winter and autumn as a result of stable atmospheric conditions and anthropogenic activities. The SARIMA models specifically SARIMA (3,1,0) (0,0,0,12) for PM2.5 and SARIMA (1,1,1) (1,0,0,12) for PM10, exhibited robust predictive performance, characterized by low Akaike information criterion (AIC), Bayesian information criterion (BIC) and Hannan-Quinn information criterion (HQIC) values, alongside favourable Ljung-Box test outcomes. The 2023 forecasts validated the model’s reliability, highlighting its capability for air quality monitoring. The results underscore the immediate necessity for mitigation strategies, encompassing more stringent industrial emissions regulations, enhanced transportation initiatives and efficient management of construction dust. This research highlights the importance of statistical modelling in comprehending pollution dynamics and assisting policymakers in formulating effective strategies to address air quality issues in Jaipur.

Keywords

Air quality, Multiple pollutants, ARIMA, SARIMA, PM, NOx

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