Long-Term Dust Transport

Dear Colleagues,

Dust is one of the most significant air pollutants due to its ability to transport over long distances and wide ranges, and thus it has crucial impacts on human health and the environment. It also plays a role in influencing Earth's energy balance and global climate patterns. Consequently, detecting, monitoring, and analyzing dust is vital for protecting both human and natural ecosystems.

Recent advancements in remote sensing technologies, big data analytics, and computational resources have enabled researchers to study dust with enhanced spatial, temporal, and spectral resolutions, as well as extended temporal coverage. However, challenges remain in terms of parameter sensitivity, adaptability across various regions, and the long-term reliability of these methods. These issues can challenge the accuracies of dust transport studies, such as those focusing on transatlantic dust movement.

To overcome these challenges, innovative methods are needed to investigate dust transport patterns, leveraging increasing computational power, artificial intelligence techniques, and big data frameworks. This Special Issue aims to highlight the latest advancements in the detection, tracking, and analysis of long-term dust transport, exploring how new technologies, datasets, and algorithms can advance this field. Submissions related to dust applications or reviews summarizing current research are also encouraged.

Potential topics include, but are not limited to:

• Detection and monitoring of long-term dust transport characteristics and patterns (e.g., transatlantic dust);
• Simulation and prediction of dust trajectories and events;
• Interactions between airborne dust, clouds, precipitation, and other pollutants;
• Applications of artificial intelligence-based approaches for dust tracking, detection, monitoring, and analysis.

Dr. Qian Liu
Guest Editor

Manuscript Submission Information

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