Advances in Air Quality Monitoring and Source Apportionment

Dear Colleagues,

Accurate air quality monitoring and robust source apportionment are fundamental to advancing the scientific understanding of atmospheric pollution and its controlling processes. Recent progress in measurement technologies, high-resolution monitoring networks, and analytical methodologies has enabled more detailed characterizations of particulate and gaseous pollutants and improved the ability to determine their sources across multiple spatial and temporal scales.

This Special Issue, “Advances in Air Quality Monitoring and Source Apportionment,” focuses on methodological and analytical developments in air quality observations and source apportionment techniques. Its scope centers on quantitative approaches for pollutant measurement and source attribution, with particular emphasis on particulate matter (PM_2.5, PM₁₀, and ultrafine particles), trace gases, and chemically resolved datasets.

We welcome original research articles that address advances in the following areas:

• In situ and remote sensing-based air quality measurements, including high-time-resolution and chemically speciated observations.
• Receptor modeling techniques (e.g., PMF, CMB, ME, and related statistical frameworks).
• Source apportionment supported by chemical tracers, isotopic analysis, and marker species.
• The integration of monitoring data with chemical transport models for source attribution.
• Uncertainty quantification, sensitivity analysis, and model evaluation in source apportionment studies.
• The application of low-cost sensor networks and calibration strategies for regulatory air quality monitoring and source apportionment.
• The source apportionment of unintentional emissions from industrial processes and combustion activities.
• Methodological advances for legacy and emerging contaminants in atmospheric monitoring and source identification.

Submissions emphasizing method development, model refinement, and comparative evaluations of source apportionment approaches are particularly encouraged. Case studies should demonstrate clear methodological innovation or provide new insights into source contributions under different atmospheric conditions (e.g., urban environments, pollution episodes, long-range transport).

This Special Issue aims to advance the rigor, reliability, and interpretability of air quality monitoring and source apportionment studies, thereby supporting more robust scientific assessments of emission sources and atmospheric processes.

Topics of Interest

1. Advances in air quality monitoring techniques for particulate matter (PM_2.5, PM₁₀, and ultrafine particles), trace gases and emerging contaminants.
2. High-time-resolution and chemically speciated measurements for source apportionment applications.
3. The development and application of receptor models (e.g., positive matrix factorization, chemical mass balance, multilinear engine).
4. Comparative evaluation and intercomparison of source apportionment methods
5. The use of chemical tracers, marker species, and elemental/organic indicators for source identification.
6. Isotopic approaches (e.g., stable carbon, nitrogen, or lead isotopes) in source apportionment studies.
7. The integration of monitoring observations with chemical transport models for source attribution.
8. Hybrid source apportionment frameworks combining receptor modeling and deterministic modeling approaches.
9. Uncertainty analysis, sensitivity testing, and model validation in source apportionment results.
10. Source apportionment during pollution episodes, extreme events, and high-concentration periods.
11. Urban and regional-scale source apportionment studies with methodological innovation.
12. Assessments of temporal variability (diurnal, seasonal, episodic) in source contributions.
13. An evaluation of long-range transport and regional background contributions using observational data.
14. The application of advanced statistical and data-driven methods (e.g., machine learning) in source apportionment, when directly linked to observations.
15. Quality assurance, calibration, and data reliability issues in air quality monitoring for source apportionment.
16. The performance evaluation and calibration of low-cost sensor networks for air quality monitoring and source attribution.
17. The source apportionment of unintentional emissions from industrial processes and combustion activities.
18. Methodological advances for legacy and emerging contaminants in atmospheric monitoring and source identification.

Dr. Yetkin Dumanoğlu
Guest Editor

Manuscript Submission Information

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