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<p>Ozone (O₃) is a short-lived climate pollutant of growing concern due to its dual role as a greenhouse gas and a secondary air pollutant adversely affecting human health, ecosystems, and agricultural productivity. This study investigated the vertical dynamics of atmospheric O₃ over 28 Indian states during 2003–2024 using Atmospheric Infra-red Sounder (AIRS)-derived O₃, methane (CH₄), and air temperature, land surface temperature (LST), and solar radiation data. Results revealed a pronounced vertical and regional heterogeneity. Tropospheric O₃ exhibited strong seasonality, with monsoon minima and pre-monsoon maxima, while stratospheric layers showed a coherent bimodal pattern. Significant long-term increases were detected in both upper-stratospheric (1–20&#xa0;hPa) and lower-tropospheric (300–1000&#xa0;hPa) layers, whereas mid-stratospheric levels (30–150&#xa0;hPa) displayed widespread declines, particularly during monsoon months. Correlation analyses highlighted that CH₄ and O₃ were negatively associated in the upper atmosphere but strongly positively associated near the surface, whereas LST and solar radiation showed consistent positive relationships with O₃ across states. Threat assessment indicated that several northern and eastern states frequently exceeded the 40 ppbv crop-damage threshold, posing substantial agricultural risk. Multi- Layer Perceptron (MLP) - based neural network models resulted in high accuracy as indicated by the Root Mean Square Error values. Overall, the study provides the first vertically resolved, multi-decadal ozone assessment for India, offering critical insights into climate–chemistry interactions, agricultural vulnerability, and the utility of machine learning for atmospheric prediction. The findings underscore the need for integrated mitigation strategies targeting O₃ precursors under a rapidly warming climate.</p>

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Vertical profiling of ozone concentrations over India in response to the atmospheric parameters using integrated geospatial- machine learning technique

  • 期刊论文

  • 发表日期：

    2026年5月16日

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  • Arnab Mandal,
  • Argha Ghosh,
  • Akhilesh Kumar Gupta,
  • Udhayanithi Malayalan,
  • Bishakha Priyadarshini,
  • Sudipta Manna,
  • Bishwajit Sinha,
  • Araya Kumar Biswamohan Mohapatra

摘要

Ozone (O₃) is a short-lived climate pollutant of growing concern due to its dual role as a greenhouse gas and a secondary air pollutant adversely affecting human health, ecosystems, and agricultural productivity. This study investigated the vertical dynamics of atmospheric O₃ over 28 Indian states during 2003–2024 using Atmospheric Infra-red Sounder (AIRS)-derived O₃, methane (CH₄), and air temperature, land surface temperature (LST), and solar radiation data. Results revealed a pronounced vertical and regional heterogeneity. Tropospheric O₃ exhibited strong seasonality, with monsoon minima and pre-monsoon maxima, while stratospheric layers showed a coherent bimodal pattern. Significant long-term increases were detected in both upper-stratospheric (1–20 hPa) and lower-tropospheric (300–1000 hPa) layers, whereas mid-stratospheric levels (30–150 hPa) displayed widespread declines, particularly during monsoon months. Correlation analyses highlighted that CH₄ and O₃ were negatively associated in the upper atmosphere but strongly positively associated near the surface, whereas LST and solar radiation showed consistent positive relationships with O₃ across states. Threat assessment indicated that several northern and eastern states frequently exceeded the 40 ppbv crop-damage threshold, posing substantial agricultural risk. Multi- Layer Perceptron (MLP) - based neural network models resulted in high accuracy as indicated by the Root Mean Square Error values. Overall, the study provides the first vertically resolved, multi-decadal ozone assessment for India, offering critical insights into climate–chemistry interactions, agricultural vulnerability, and the utility of machine learning for atmospheric prediction. The findings underscore the need for integrated mitigation strategies targeting O₃ precursors under a rapidly warming climate.