Hourly Air Quality Index Dynamics in Visakhapatnam: Diurnal Patterns,  Pollutant Interactions, and Ensemble Machine Learning Prediction

P. Srivyshnavi, Sreenivasulu T  ,P Shankaraiah , M Darshan Teja

Hourly Air Quality Index Dynamics in Visakhapatnam: Diurnal Patterns, Pollutant Interactions, and Ensemble Machine Learning Prediction

Authors

P. Srivyshnavi, Sreenivasulu T ,P Shankaraiah , M Darshan Teja

Keywords:

Air Quality Index; AQI prediction; Visakhapatnam; hourly air quality; diurnal pattern; Random Forest

Abstract

This study presents a comprehensive analysis of hourly Air Quality Index (AQI) dynamics inVisakhapatnam a rapidly industrialising coastal city on India's eastern seaboard using a nearcomplete dataset of 24,576 hourly observations spanning January 2022 to October 2024. Unlike the preponderance of daily-resolution air quality studies

References

Balakrishnan, K., Dey, S., Gupta, T., Dhaliwal, R. S., Brauer, M., Cohen, A. J., Stanaway, J. D., Beig, G., Joshi, T. K., Aggarwal, A. N., Sabde, Y., Sadhu, H., Frostad, J., Causey, K., Bhattacharya, S., Forouzanfar, M. H., & Collaborators, I.-I. (2019). The impact of air pollution on deaths, disease burden, and life expectancy across the states of India: The Global Burden of Disease Study 2017. The Lancet Planetary Health, 3(1), e26–e39.

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Published

2025-02-20

How to Cite

P. Srivyshnavi, Sreenivasulu T ,P Shankaraiah , M Darshan Teja. (2025). Hourly Air Quality Index Dynamics in Visakhapatnam: Diurnal Patterns, Pollutant Interactions, and Ensemble Machine Learning Prediction. Journal of Computational Analysis and Applications (JoCAAA), 34(2), 282–296. Retrieved from https://www.eudoxuspress.com/index.php/pub/article/view/5527