Tableau Air Quality Exploratory Analysis of India

Abstract

Air pollution is a pressing environmental and public health issue, particularly in rapidly urbanizing countries like India. With growing industrialization, vehicular emissions, and urban development, Indian cities have seen a significant decline in air quality over the past few decades. This research focuses on an exploratory analysis of air quality across different regions of India using data visualization techniques in Tableau. The primary dataset, collected from Kaggle, comprises over 430,000 records detailing air pollutant levels—including SO₂, NO₂, RSPM, SPM, and PM2.5—collected across various Indian states from different locations and monitoring stations.

The aim of this study is to uncover spatial and temporal trends in air pollution, identify critically polluted regions, and provide actionable insights through interactive dashboards. The dataset includes parameters such as station codes, sampling dates, pollutant concentrations, location types (residential, industrial, etc.), and agency information, which are leveraged to perform in-depth visual analytics. Tableau’s powerful capabilities are utilized to generate state-wise pollution heatmaps, pollutant trend graphs over years, and comparisons between residential and industrial zones.

The findings reveal seasonal fluctuations in pollutant levels, with urban and industrial locations exhibiting higher concentrations of harmful gases. States such as Delhi, Uttar Pradesh, Maharashtra, and West Bengal consistently report elevated levels of pollutants, raising concerns about air quality regulation and the need for sustainable development practices. Additionally, the analysis shows that PM2.5 data is relatively sparse, indicating challenges in monitoring finer particulate matter.

This study serves as a foundational tool for policymakers, environmentalists, and researchers to understand air quality dynamics in India and to advocate for data-driven environmental interventions. The integration of Tableau not only facilitates clearer comprehension but also empowers stakeholders with interactive tools for monitoring and planning.

Country : India

1 Imaan Junaid2 Abdul Raheem Khan3 Sai Kiran4 Dr. Diana Moses

  1. Student, Department of Artificial Intelligence and Data Science, Methodist College of Engineering And Technology, Hyderabad, India
  2. Student, Department of Artificial Intelligence and Data Science, Methodist College of Engineering And Technology, Hyderabad, India
  3. Student, Department of Artificial Intelligence and Data Science, Methodist College of Engineering And Technology, Hyderabad, India
  4. Associate Professor, Department of Computer Science and Engineering, Methodist College of Engineering and Technology, Hyderabad, India

IRJIET, Volume 9, Issue 6, June 2025 pp. 29-34

doi.org/10.47001/IRJIET/2025.906005

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