Employing Artificial Intelligence and Geographic Information Systems to Monitor Greenhouse Gases in Iraq Using the TROPOMI-5P Sensor for 2024
DOI:
https://doi.org/10.31185/eduj.Vol59.Iss1.4317Keywords:
Greenhouse Gases, Geographic Information Systems, Artificial IntelligenceAbstract
Artificial intelligence (AI) and Geographic Information Systems (GIS) contribute to the accurate and efficient monitoring and tracking of greenhouse gases by analyzing environmental data and tracing emission sources. AI relies on advanced algorithms to analyze gas levels under various weather conditions, aiding in the precise prediction of climate changes. GIS helps create interactive maps reflecting the spatial distribution of greenhouse gas emissions, providing insights into the impact of industrial activities on the environment. This integration supports the development of sustainable strategies to reduce emissions and mitigate the effects of climate change through precise scientific analyses. This study aims to monitor greenhouse gases in Iraq during the winter and summer seasons of 2024 using Sentinel-5P satellite algorithms, focusing on gases such as carbon dioxide (CO₂), nitrogen dioxide (NO₂), sulfur dioxide (SO₂), and aerosol index (AER AI).
The study concluded that the integration of AI and GIS technologies enables accurate monitoring of greenhouse gases through fast data processing and geographic visualization. In winter, the very low concentration of aerosols dominates, covering 100%, while in summer, the concentration drops to 77.58%, with increased levels in medium and high categories. For NO₂ and CO gases, higher concentrations are observed in both winter and summer due to human activity and higher temperatures. As for SO₂, low concentration dominates in winter, while the very low concentration increases in summer due to drought and heat.
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