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Abstract <p>Air pollution, caused by both natural events and human activities, poses serious threats to human health and ecosystems. Remote sensing involves measuring electromagnetic radiation reflected, emitted, or scattered by a target object or area. This comprehensive review explores the latest advances in remote sensing technologies, specifically ground-based, aerial, and satellite systems, and their applications for monitoring various natural and human-made pollution sources. These sources include volcanic eruptions, wildfires, transportation, industrial emissions, agricultural activities, and landfills. The review systematically categorizes these pollution sources and compares how different system setups, operational methods, and effectiveness vary across air quality monitoring techniques. A key focus is on the rapid progress in sensor technology, driven by the growing need for accurate, real-time, and scalable air quality monitoring solutions. Modern sensing platforms, such as high-resolution satellite imagers, multispectral and hyperspectral sensors, and advanced data fusion techniques, are recognized for their transformative impact. However, the field faces significant challenges, including sensor calibration, standardizing data across platforms, and integrating diverse datasets. Limitations in spatial and temporal resolution, especially in satellite-based monitoring, highlight the importance of hybrid systems that combine multiple sensing methods. The review concludes by emphasizing the need for ongoing innovation, interdisciplinary collaboration, and the integration of advanced sensing technologies into national and global regulatory frameworks. These efforts are crucial for improving environmental management, protecting public health, and strengthening climate resilience.</p> Graphical Abstract <p>This figure illustrates the various remote sensing platforms used to monitor air pollution from both natural and&#xa0;human sources. Ground-based, airborne, and satellite sensors, including specialized instruments such as photometers, RADAR, LIDAR, and&#xa0;TEMPO, collect data on pollutants. To ensure accuracy, these sensors undergo pre-flight and cross-sensor calibration. The collected data is then&#xa0;processed and analyzed using different methods, helping interpret complex pollution patterns. The framework identifies major pollution sources,&#xa0;including natural sources like volcanic eruptions that release gases (CO2, SO2, H2S, CO) and wildfires that emit particulates (PM2.5, PM10). Humanmade&#xa0;sources include transportation (CO, NOx, PM2.5), industrial activities (SO2, NOx), agriculture (PM2.5, PM10), and landfills (CH). Together,&#xa0;these platforms and methods form a comprehensive system for tracking and understanding pollution dynamics across various environments.</p>

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Remote-sensing technologies for air pollution monitoring in the USA: a comprehensive review

  • 期刊论文

  • 发表日期：

    2026年5月26日

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  • Santosh Sapkota,
  • Gamal El Afandi,
  • Chastity Bradford,
  • Muhammad Irfan,
  • Salem Ibrahim,
  • Amira Moustafa,
  • Reda Algendy

摘要

Abstract

Air pollution, caused by both natural events and human activities, poses serious threats to human health and ecosystems. Remote sensing involves measuring electromagnetic radiation reflected, emitted, or scattered by a target object or area. This comprehensive review explores the latest advances in remote sensing technologies, specifically ground-based, aerial, and satellite systems, and their applications for monitoring various natural and human-made pollution sources. These sources include volcanic eruptions, wildfires, transportation, industrial emissions, agricultural activities, and landfills. The review systematically categorizes these pollution sources and compares how different system setups, operational methods, and effectiveness vary across air quality monitoring techniques. A key focus is on the rapid progress in sensor technology, driven by the growing need for accurate, real-time, and scalable air quality monitoring solutions. Modern sensing platforms, such as high-resolution satellite imagers, multispectral and hyperspectral sensors, and advanced data fusion techniques, are recognized for their transformative impact. However, the field faces significant challenges, including sensor calibration, standardizing data across platforms, and integrating diverse datasets. Limitations in spatial and temporal resolution, especially in satellite-based monitoring, highlight the importance of hybrid systems that combine multiple sensing methods. The review concludes by emphasizing the need for ongoing innovation, interdisciplinary collaboration, and the integration of advanced sensing technologies into national and global regulatory frameworks. These efforts are crucial for improving environmental management, protecting public health, and strengthening climate resilience.

Graphical Abstract

This figure illustrates the various remote sensing platforms used to monitor air pollution from both natural and human sources. Ground-based, airborne, and satellite sensors, including specialized instruments such as photometers, RADAR, LIDAR, and TEMPO, collect data on pollutants. To ensure accuracy, these sensors undergo pre-flight and cross-sensor calibration. The collected data is then processed and analyzed using different methods, helping interpret complex pollution patterns. The framework identifies major pollution sources, including natural sources like volcanic eruptions that release gases (CO2, SO2, H2S, CO) and wildfires that emit particulates (PM2.5, PM10). Humanmade sources include transportation (CO, NOx, PM2.5), industrial activities (SO2, NOx), agriculture (PM2.5, PM10), and landfills (CH). Together, these platforms and methods form a comprehensive system for tracking and understanding pollution dynamics across various environments.