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<p>This study focuses on aerosol properties and their classification in the eastern Indian city of Rourkela, using six years of Microtops II sun photometer data. Aerosol optical depth (AOD) exhibits unique increasing trends from 2017 to 2022, irrespective of seasons. The Ångström Exponent (AE) values indicate the predominance of fine-mode aerosols in winter, pre-monsoon, and post-monsoon months due to high fossil fuel and biomass burning emissions. However, a marginal drop in the AE values is seen during monsoon due to the long-range transport of coarse-mode natural aerosols from the neighboring oceans and arid regions. The single scattering albedo (SSA) values reveal a dominance of absorbing aerosols during winter and post-monsoon months, while indicating a mix of particle types in the pre-monsoon and monsoon periods. The dominance of sea salt aerosols and wet removal of finer absorbing particles during monsoon season result in higher SSA values. A shift in fine particle dominance is found in the inter-annual variabilities, wherein these particles are gradually acquiring scattering characteristics aligning with the regional trend in recent times. Aerosols are classified into urban, biomass-burning, desert, and marine types based on AOD-AE variability. The existence of biomass-burning aerosols is found to dominate over Rourkela, irrespective of seasons. While urban aerosols are usually dominant in winter and post-monsoon due to anthropogenic activities, transported desert dust aerosols show dominance during the pre-monsoon and monsoon seasons. Long-range transport across different atmospheric levels are realized to play important role in modulating aerosol variability. The forecasted values realized through the ‘Linear Regression’ model also indicated a similar trend for the pre-monsoon and monsoon seasons. However, the winter AOD values are expected to increase in the succeeding years. The research sheds light on aerosol properties, their origins, and interactions with the prevailing meteorology, and future projection, providing useful information for urban air quality management.</p>

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Aerosol Characteristics Over an Eastern Indian City Using Sun Photometer Observations and Machine Learning Frameworks

  • 期刊论文

  • 发表日期：

    2025年5月28日

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  • Jagabandhu Panda,
  • Ankan Sarkar,
  • Vaibhav Pandey,
  • Asmita Mukherjee

摘要

This study focuses on aerosol properties and their classification in the eastern Indian city of Rourkela, using six years of Microtops II sun photometer data. Aerosol optical depth (AOD) exhibits unique increasing trends from 2017 to 2022, irrespective of seasons. The Ångström Exponent (AE) values indicate the predominance of fine-mode aerosols in winter, pre-monsoon, and post-monsoon months due to high fossil fuel and biomass burning emissions. However, a marginal drop in the AE values is seen during monsoon due to the long-range transport of coarse-mode natural aerosols from the neighboring oceans and arid regions. The single scattering albedo (SSA) values reveal a dominance of absorbing aerosols during winter and post-monsoon months, while indicating a mix of particle types in the pre-monsoon and monsoon periods. The dominance of sea salt aerosols and wet removal of finer absorbing particles during monsoon season result in higher SSA values. A shift in fine particle dominance is found in the inter-annual variabilities, wherein these particles are gradually acquiring scattering characteristics aligning with the regional trend in recent times. Aerosols are classified into urban, biomass-burning, desert, and marine types based on AOD-AE variability. The existence of biomass-burning aerosols is found to dominate over Rourkela, irrespective of seasons. While urban aerosols are usually dominant in winter and post-monsoon due to anthropogenic activities, transported desert dust aerosols show dominance during the pre-monsoon and monsoon seasons. Long-range transport across different atmospheric levels are realized to play important role in modulating aerosol variability. The forecasted values realized through the ‘Linear Regression’ model also indicated a similar trend for the pre-monsoon and monsoon seasons. However, the winter AOD values are expected to increase in the succeeding years. The research sheds light on aerosol properties, their origins, and interactions with the prevailing meteorology, and future projection, providing useful information for urban air quality management.