Advances in Air Pollution Data Analysis: From Classical Geostatistics to Big Data and Artificial Intelligence
A special issue of Atmosphere (ISSN 2073-4433). This special issue belongs to the section "Air Pollution Control".
Deadline for manuscript submissions: 31 December 2025 | Viewed by 19
Special Issue Editors
Interests: air pollution measurements; air quality monitoring; artificial intelligence, anthropogenic emission; spatio-temporal geostatistics; geophysics; smart cities
Interests: geostatistics; spatial data analysis; machine learning; air pollution measurements; air quality monitoring; geophysics
Interests: atmospheric chemistry; reactive nitrogen; ammonia; isotopic analysis; haze; secondary aerosol formation
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
We invite researchers and practitioners to contribute to this Special Issue focusing on the evolving landscape of air pollution data analysis, bridging traditional geostatistics with groundbreaking advancements in big data and artificial intelligence (AI). This Special Issue aims to capture the latest innovations and foster interdisciplinary dialog on leveraging advanced analytical techniques to address air quality challenges. Air pollution, a critical environmental and public health concern, demands increasingly sophisticated tools to handle the complexity and scale of modern data. From satellite imagery and ground-based sensors to citizen science and IoT networks, the availability of vast, high-resolution datasets opens new frontiers for exploration. However, extracting actionable insights from these data sources requires a fusion of traditional methods and emerging technologies.
This Special Issue seeks contributions across a broad spectrum of topics, including, but not limited to, the following:
- Applications of geostatistics for spatial and temporal modeling of air quality;
- Big data techniques for managing and analyzing large-scale pollution datasets;
- AI and machine learning models for predictive analysis, anomaly detection, and source apportionment;
- Integrating heterogeneous data sources (satellite, sensor, and citizen science) for comprehensive air quality assessments;
- Uncertainty quantification, explainable AI, and ethical considerations in air pollution analysis;
- Real-time applications in pollution forecasting, urban planning, and policymaking.
By submitting to this Special Issue, you will showcase your research at the forefront of this dynamic field, contributing to innovative solutions for global air quality management. Together, let us push the boundaries of air pollution science and technology.
Dr. Mateusz Zareba
Dr. Elżbieta Węglińska
Prof. Dr. Yunhua Chang
Guest Editors
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Atmosphere is an international peer-reviewed open access monthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- air pollution
- air quality monitoring
- machine learning
- big data
- spatial analysis
- artificial intelligence
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