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This study conducted between May and November 2024 analyzed air pollution in Puebla, Mexico, aiming to identify patterns and forecast pollutant concentrations using time series models. Historical data (2020–2024) from monitoring stations in several neighborhoods were analyzed, covering ozone (O₃), nitrogen dioxide (NO₂), carbon monoxide (CO), sulfur dioxide (SO₂) all measured in ppm, and particulate matter (PM10 and PM2.5, both measured in µg/m3). Using RStudio, ARIMA and TBATS models were implemented to identify trends and forecast pollutant levels. An interactive web application was developed using Shiny to visualize dynamic graphics, heat maps, and 24-h forecasts. Results include analysis of seasonal patterns and projections, significantly contributing to air quality management strategies.

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A Study for Air Quality Analysis in the City of Puebla

  • 会议论文

  • 发表日期：

    2025年

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  • T. Romero,
  • A. Sánchez,
  • J. Badillo

摘要

This study conducted between May and November 2024 analyzed air pollution in Puebla, Mexico, aiming to identify patterns and forecast pollutant concentrations using time series models. Historical data (2020–2024) from monitoring stations in several neighborhoods were analyzed, covering ozone (O₃), nitrogen dioxide (NO₂), carbon monoxide (CO), sulfur dioxide (SO₂) all measured in ppm, and particulate matter (PM10 and PM2.5, both measured in µg/m3). Using RStudio, ARIMA and TBATS models were implemented to identify trends and forecast pollutant levels. An interactive web application was developed using Shiny to visualize dynamic graphics, heat maps, and 24-h forecasts. Results include analysis of seasonal patterns and projections, significantly contributing to air quality management strategies.