Advanced Technologies in Air Pollution Monitoring and Control
This special issue belongs to the section "Environmental Sciences".
Special Issue Information
Dear Colleagues,
Air pollution remains a critical challenge in environmental science. The continuous advancement, integration, and application of emerging technologies are increasingly recognized as core drivers of future breakthroughs in air pollution monitoring and control. The rapid pace of innovation in materials science, data and information technology, large AI models, and engineering control has created a unique opportunity to accelerate technological innovation for air quality management.
We invite you to submit original research articles and up-to-date reviews to our upcoming Special Issue. This Special Issue aims to showcase high-impact work that leverages cutting-edge methodologies to address both atmospheric and indoor air pollution.
Topics of interest include, but are not limited to, the following:
- Novel detection and sensing technologies for air pollutants in ambient and indoor environments, covering particulate matter (PM), volatile organic compounds, odor, emerging contaminants, biological pollutants (e.g., airborne viruses, bacteria, pollen), and indoor radioactive pollutants such as radon.
- Novel approaches integrating technologies such as source control, process management, and digitalized operation and maintenance (O&M) to establish whole-process control of air pollution.
- Intelligent strategies that fuse advanced sensors, machine learning, digital twins, and AI models to achieve integrated monitoring, assessment, decision-making, and dynamic control of air quality. We particularly encourage interdisciplinary contributions that bridge physical sciences, biological sciences, computational science, and engineering to deliver practical and scalable solutions.
We look forward to receiving your contributions and building a collection that will shape the next generation of air pollution research.
Dr. Rui Chen
Dr. Peng Zhao
Guest Editors
Manuscript Submission Information
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Keywords
- PM2.5
- fine and ultrafine particles
- bioaerosol
- volatile organic compounds
- air pollution
- indoor air pollution
- MEMS sensors
- digital twin
- certified reference materials (CRMs)
- sensor calibration
- online monitoring
- machine learning (ML)
- nanoparticles and nanomaterials
- metals and heavy metals
- pollution prevention and control
- analytical techniques
- microfluidic chip
- AI
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