10.57647/j.jtap.2025.1904.36

Radiative transfer model application with satellite imagery for methane emission analysis

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  • Kamala Aghayeva1,
  • German Krauklit*1,
  1. Space Research Institute of Natural Resources, Azerbaijan National Aerospace Agency, Azerbaijan

Received: 2025-03-17

Revised: 2025-07-28

Accepted: 2025-08-12

Published in Issue 2025-08-31

Copyright (c) 2025 Kamala Aghayeva, German Krauklit (Author)

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This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

1.
Aghayeva K, Krauklit G. Radiative transfer model application with satellite imagery for methane emission analysis. J Theor Appl phys. 2025 Aug. 31;19(4). Available from: https://oiccpress.com/jtap/article/view/17649
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Abstract

The purpose of this study was to develop and implement a radiative transfer model for the analysis of methane emissions using satellite imagery. A methodology has been developed that defines the steps and processes for radiative transfer, an important process in atmospheric sciences that explains how electromagnetic radiation, such as light or infrared radiation, interacts with the atmosphere and its components, such as clouds, aerosols, and gases. As a result of the study, a detailed radiative transfer modelling scheme was developed and refined. This scheme is essential for quantifying methane emissions from satellite data and plays a critical role in improving our understanding of the Earth’s energy balance, climate change dynamics, and atmospheric radiative processes. Radiative transfer, essential in atmospheric science, involves the emission, absorption, and scattering of radiation by atmospheric particles and gases. This study applies radiative transfer models to analyse methane emissions using Sentinel-2 satellite data, which includes bands sensitive to methane absorption. By comparing fractional radiance levels from model simulations with satellite data, authors accurately retrieve methane concentrations. The methodology’s adaptability to other satellites with similar spectral bands enhances its potential for global methane monitoring.

Keywords

  • Atmospheric physics,
  • Remote sensing,
  • Sentinel-2,
  • Radiation,
  • Global monitoring
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