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Review Paper On Air Quality Assessment Techniques: Advancements and Applications (2015-2025)
Subject area: Science,Engineering and Technology · Area of research: Environmental Chemistry
Abstract
Air pollution poses a significant global challenge, impacting human health, ecosystems, and climate. Accurate and timely assessment of air quality is crucial for effective policy formulation and mitigation strategies. This review paper provides a comprehensive overview of recent advancements in air quality assessment techniques from 2015 to 2025. It critically examines traditional monitoring methods, highlights the emergence of low-cost sensor networks, explores the increasing role of satellite remote sensing, and discusses the transformative impact of machine learning and artificial intelligence in air quality modeling and prediction. The paper also addresses the challenges and future directions in this evolving field, emphasizing the need for integrated approaches to achieve more precise, spatially resolved, and actionable air quality information.
Keywords
Air quality, assessment techniques, low-cost sensors, satellite remote sensing, machine learning, artificial intelligence, air pollution monitoring.
References
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How to cite this paper
@article{1708663,
author = {Fubara Boma Abiye},
title = {Review Paper On Air Quality Assessment Techniques: Advancements and Applications (2015-2025)},
journal = {Iconic Research And Engineering Journals},
year = {2025},
volume = {8},
number = {11},
pages = {1483-1488},
issn = {2456-8880},
url = {https://www.irejournals.com/formatedpaper/1708663.pdf},
abstract = {Air pollution poses a significant global challenge, impacting human health, ecosystems, and climate. Accurate and timely assessment of air quality is crucial for effective policy formulation and mitigation strategies. This review paper provides a comprehensive overview of recent advancements in air quality assessment techniques from 2015 to 2025. It critically examines traditional monitoring methods, highlights the emergence of low-cost sensor networks, explores the increasing role of satellite remote sensing, and discusses the transformative impact of machine learning and artificial intelligence in air quality modeling and prediction. The paper also addresses the challenges and future directions in this evolving field, emphasizing the need for integrated approaches to achieve more precise, spatially resolved, and actionable air quality information.},
keywords = {Air quality, assessment techniques, low-cost sensors, satellite remote sensing, machine learning, artificial intelligence, air pollution monitoring.},
month = {May},
}