Meerut City Air Quality Index forecasting and future prediction using the ARIMA time series model

One of the most important parts of the survival of life on Earth is air. Air pollution continuously rises due to weather, traffic, non-renewable energy use, and industrial reasons. These elements have an impact on the well-being and success of all species on Earth, thus it is necessary to regularly assess the state of the air quality in our surroundings. The Air Quality Index (AQI), which measures the quality of the air, is affected by several different factors, including the growth of Nitrogen Dioxide (NO2), Sulfur Dioxide (SO2), Particulate Matter (PM2.5, and PM10). The present study uses an Autoregressive Integrated Moving Average (ARIMA) model for the forecasting and future prediction of monthly AQI, several individual factors such as the accumulation of NO2, SO2, PM2.5, and PM10 in Meerut City

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-03-07
DOI
https://doi.org/10.5281/zenodo.14988226
Primary Topic
Air Quality Monitoring and Forecasting
Type
article
Field-Weighted Citation Impact
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article

Meerut City Air Quality Index forecasting and future prediction using the ARIMA time series model

Zenodo (CERN European Organization for Nuclear Research)
Air Quality Monitoring and Forecasting
article

Meerut City Air Quality Index forecasting and future prediction using the ARIMA time series model

article en

Abstract

One of the most important parts of the survival of life on Earth is air. Air pollution continuously rises due to weather, traffic, non-renewable energy use, and industrial reasons. These elements have an impact on the well-being and success of all species on Earth, thus it is necessary to regularly assess the state of the air quality in our surroundings. The Air Quality Index (AQI), which measures the quality of the air, is affected by several different factors, including the growth of Nitrogen Dioxide (NO2), Sulfur Dioxide (SO2), Particulate Matter (PM2.5, and PM10). The present study uses an Autoregressive Integrated Moving Average (ARIMA) model for the forecasting and future prediction of monthly AQI, several individual factors such as the accumulation of NO2, SO2, PM2.5, and PM10 in Meerut City

Zenodo (CERN European Organization for Nuclear Research)
Sustainable cities and communities
Openalex Percentile: Top 58%
Air Quality Monitoring and Forecasting
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