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Advances in Integrated Air Quality Management: Emissions, Monitoring, Modelling (4th...
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Advances in Integrated Air Quality Management: Emissions, Monitoring, Modelling (4th Edition)

A special issue of Atmosphere (ISSN 2073-4433). This special issue belongs to the section "Air Quality".

Deadline for manuscript submissions: 31 January 2026 | Viewed by 1061

Special Issue Editors

Dr. Kyriaki-Maria Fameli

E-Mail Website
Guest Editor
Institute for Environmental Research & Sustainable Development, National Observatory of Athens, GR-15236 Athens, Greece
Interests: emission inventory development (classical pollutants and GHGs); air and particulate pollution over urban areas; GIS; air quality modeling; low-cost sensor monitoring; raising climate change awareness
Special Issues, Collections and Topics in MDPI journals
Dr. Vasiliki Assimakopoulos

E-Mail Website
Guest Editor
Institute for Environmental Research & Sustainable Development, National Observatory of Athens, GR-15236 Athens, Greece
Interests: emission inventory development; chemical transport modeling; urban air quality; air pollution mitigation strategies
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This Special Issue is a follow-up to the Special Issue entitled “Advances in Integrated Air Quality Management: Emissions, Monitoring, Modelling (3rd Edition)” (https://www.mdpi.com/journal/atmosphere/special_issues/808841P0HU) published in Atmosphere, and it covers all aspects of air quality management issues.

Air pollution has become an increasingly important environmental issue on a global scale since the sources that contribute to poor air quality and climate change are becoming increasingly widespread. Both natural and anthropogenic components of air pollution have been long recognized and are continuously being investigated to identify their links with local and regional air quality, the impact on the climate, health and ecosystems, and new sources and pollutants, as well as links between emissions and air pollution management. In this respect, climate change effects exacerbate the increase in critical air pollutants such as ozone, and air pollution contributes to climate change (e.g., black carbon from the combustion of fossil fuels).

Air quality is monitored at the surface through ground-based monitors, official networks, low-cost sensors and, recently, cheap and easy-to-use sensors used by regular citizens. Additional data are derived from satellite and remote observations, contributing to the temporal and spatial study of air pollution. Monitoring aims to identify and quantify the pollution sources, air quality, compliance with ambient air quality standards, and the impact of exposure to other parameters (meteorology, topography, accidental release, etc.). In order for air quality to be managed, the continuous application and updating of modeling tools, emissions inventories, and advanced statistical methodologies to produce solutions and assess policies is a prerequisite.

This Special Issue aims to gather research papers focused on the interactions between air pollution and climate change, assessing the implementation of policies and measures, novel methodologies for emission inventories, remote and in situ experimental observations, meteorological parameters, the application of chemical transport and/or development of statistical models for forecasting air pollution levels, and assisting the monitoring and mapping of air pollution close to major sources or areas across large areas.

Dr. Kyriaki-Maria Fameli
Dr. Vasiliki Assimakopoulos
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 250 words) can be sent to the Editorial Office for assessment.

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

  • emission inventory
  • air pollution monitoring
  • air pollution assessment
  • exposure
  • climate change and air pollution
  • PM2.5
  • PM10
  • ozone
  • aerosols
  • statistical forecasting models
  • chemical transport models
  • urban air pollution
  • remote sensing

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Published Papers (2 papers)

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Research

12 pages, 1198 KB  
Article
Regional and Whole-Body Dermal Emission Rates of Volatile Sulfur Compounds and Potential Impact on Indoor Air Odour
by Tomomi Osaka, Daisuke Sato, Akihiro Hosomi, Mizuki Fukui and Yoshika Sekine
Atmosphere 2025, 16(12), 1331; https://doi.org/10.3390/atmos16121331 - 25 Nov 2025
Viewed by 247
Abstract
Volatile sulfur compounds (VSCs) are known to cause characteristic—and sometimes unpleasant—body odour. Human presence may influence the odour of indoor air; however, the contribution of skin-derived VSCs has not been thoroughly evaluated. This study aimed to elucidate the regional and whole-body dermal emission [...] Read more.
Volatile sulfur compounds (VSCs) are known to cause characteristic—and sometimes unpleasant—body odour. Human presence may influence the odour of indoor air; however, the contribution of skin-derived VSCs has not been thoroughly evaluated. This study aimed to elucidate the regional and whole-body dermal emission rates of VSCs—diallyl disulfide (DADS), allyl methyl sulfide (AMS), ethyl mercaptan (EMT), allyl mercaptan (AMT) and dimethyl trisulfide (DMTS)—by conducting simultaneous and multi-point measurements of dermal emissions from the human skin surface to assess their potential impact on indoor air quality. Dermal emission fluxes of VSCs were measured at 14 anatomical regions of 12 healthy young subjects using a passive flux sampler coupled with gas chromatography/mass spectrometry. These fluxes were converted to emission rates using regional body surface area, and the whole-body emission rates were subsequently used to estimate indoor air concentrations for comparison with the odour thresholds of each VSC. The results showed that although some regional differences in emission rates were observed among subjects, the large inter-individual variability ultimately led to no significant differences in whole-body emission rates of VSCs between males and females. Using the average whole-body emission rates across 12 subjects, the estimated indoor air concentrations of VSCs followed the descending order: EMT > AMT >> DMTS > AMS > DADS. The odour quotient was used to evaluate the impact of skin-derived VSCs on indoor air quality and indicated that EMT consistently contributes to indoor odour. Full article
(This article belongs to the Special Issue Advances in Integrated Air Quality Management: Emissions, Monitoring, Modelling (4th Edition))
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28 pages, 2424 KB  
Article
A Novel Application of Choquet Integral for Multi-Model Fusion in Urban PM10 Forecasting
by Houria Bouzghiba, Amine Ajdour, Najiya Omar, Abderrahmane Mendyl and Gábor Géczi
Atmosphere 2025, 16(11), 1274; https://doi.org/10.3390/atmos16111274 - 10 Nov 2025
Viewed by 517
Abstract
Air pollution forecasting remains a critical challenge for urban public health management, with traditional approaches struggling to balance accuracy and interpretability. This study introduces a novel PM10 forecasting framework combining physics-informed feature engineering with interpretable ensemble fusion using the Choquet integral, the [...] Read more.
Air pollution forecasting remains a critical challenge for urban public health management, with traditional approaches struggling to balance accuracy and interpretability. This study introduces a novel PM10 forecasting framework combining physics-informed feature engineering with interpretable ensemble fusion using the Choquet integral, the first application of this non-linear aggregation operator for air quality forecasting. Using hourly data from 11 monitoring stations in Budapest (2021–2023), we developed four specialized feature sets capturing distinct atmospheric processes: short-term dynamics, long-term patterns, meteorological drivers, and anomaly detection. We evaluated machine learning models including Random Forest variants (RF), Gradient Boosting (GBR), Support Vector Regression (SVR), K-Nearest Neighbors (KNN), and Long Short-Term Memory (LSTM) architectures across six identified pollution regimes. Results revealed the critical importance of feature engineering over architectural complexity. While sophisticated models failed when trained on raw data, the KNN model with 5-dimensional anomaly features achieved exceptional performance, representing an 86.7% improvement over direct meteorological input models. Regime-specific modeling proved essential, with GBR-Regime outperforming GBR-Stable by a remarkable effect size. For ensemble fusion, we compared the novel Choquet integral approach against conventional methods (mean, median, Bayesian Model Averaging, stacking). The Choquet integral achieved near-equivalent performance to state-of-the-art stacking while providing complete mathematical interpretability through interaction coefficients. Analysis revealed predominantly redundant interactions among models, demonstrating that sophisticated fusion must prevent information over-counting rather than merely combining predictions. Station-specific interaction patterns showed selective synergy exploitation at complex urban locations while maintaining redundancy management at simpler sites. This work establishes that combining domain-informed feature engineering with interpretable Choquet integral aggregation can match black-box ensemble performance while maintaining the transparency essential for operational deployment and regulatory compliance in air quality management systems. Full article
(This article belongs to the Special Issue Advances in Integrated Air Quality Management: Emissions, Monitoring, Modelling (4th Edition))
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