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<p>Air pollution (AP) poses a significant public health risk, particularly in developing countries, where it contributes to a growing prevalence of health issues. This study investigates seasonal variations in key air pollutants, including particulate matter, nitrogen dioxide (NO<sub>2</sub>), sulfur dioxide (SO<sub>2</sub>), carbon monoxide (CO), and ozone (O<sub>3</sub>), in New Delhi during 2024. Utilizing Sentinel-5 satellite data processed through the Google earth engine (GEE), a cloud-based geospatial analysis platform, the study evaluates pollutant dynamics during pre-monsoon and post-monsoon seasons. The methodology involved programming in JavaScript to extract pollution parameters, applying cloud filters to eliminate contaminated data, and generating average pollution maps at monthly, seasonal, and annual intervals. The results revealed distinct seasonal pollution patterns. Pre-monsoon root mean square error (RMSE) values for CO, NO<sub>2</sub>, SO<sub>2</sub>, and O<sub>3</sub> were 0.13, 2.58, 4.62, and 2.36, respectively, while post-monsoon values were 0.17, 2.41, 4.31, and 4.60. Winter months exhibited the highest pollution levels due to increased emissions from biomass burning, vehicular activity, and industrial operations, coupled with atmospheric inversions. Conversely, monsoon months saw a substantial reduction in pollutant levels due to wet deposition and improved dispersion driven by stronger winds. Additionally, post-monsoon crop residue burning emerged as a major episodic pollution source. This study underscores the utility of Sentinel-5 products in monitoring urban air pollution and provides valuable insights for policymakers to develop targeted mitigation strategies, particularly for urban megacities like Delhi, where seasonal and source-specific interventions are crucial for reducing air pollution and its associated health risks.</p>

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Seasonal patterns of air pollution in Delhi: interplay between meteorological conditions and emission sources

  • 期刊论文

  • 发表日期：

    2025年4月16日

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  • Najib Ansari,
  • Preeti Kumari,
  • Rahul Kumar,
  • Pavan Kumar,
  • Aquib Shamshad,
  • Saddam Hossain,
  • Ashutosh Sharma,
  • Yogeshwar Singh,
  • Maya Kumari,
  • Varun Narayan Mishra,
  • Rukhsana,
  • Akram Javed

摘要

Air pollution (AP) poses a significant public health risk, particularly in developing countries, where it contributes to a growing prevalence of health issues. This study investigates seasonal variations in key air pollutants, including particulate matter, nitrogen dioxide (NO2), sulfur dioxide (SO2), carbon monoxide (CO), and ozone (O3), in New Delhi during 2024. Utilizing Sentinel-5 satellite data processed through the Google earth engine (GEE), a cloud-based geospatial analysis platform, the study evaluates pollutant dynamics during pre-monsoon and post-monsoon seasons. The methodology involved programming in JavaScript to extract pollution parameters, applying cloud filters to eliminate contaminated data, and generating average pollution maps at monthly, seasonal, and annual intervals. The results revealed distinct seasonal pollution patterns. Pre-monsoon root mean square error (RMSE) values for CO, NO2, SO2, and O3 were 0.13, 2.58, 4.62, and 2.36, respectively, while post-monsoon values were 0.17, 2.41, 4.31, and 4.60. Winter months exhibited the highest pollution levels due to increased emissions from biomass burning, vehicular activity, and industrial operations, coupled with atmospheric inversions. Conversely, monsoon months saw a substantial reduction in pollutant levels due to wet deposition and improved dispersion driven by stronger winds. Additionally, post-monsoon crop residue burning emerged as a major episodic pollution source. This study underscores the utility of Sentinel-5 products in monitoring urban air pollution and provides valuable insights for policymakers to develop targeted mitigation strategies, particularly for urban megacities like Delhi, where seasonal and source-specific interventions are crucial for reducing air pollution and its associated health risks.