Urban Air Quality, Green Spaces, and Microclimate Analysis

A special issue of Atmosphere (ISSN 2073-4433). This special issue belongs to the section "Biometeorology and Bioclimatology".

Deadline for manuscript submissions: 31 October 2026 | Viewed by 1115

Special Issue Editors


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Guest Editor
Institute of Atmospheric Pollution Research (IIA), National Research Council (CNR), c/o Interateneo Physics Department, Via Amendola 173, 70126 Bari, Italy
Interests: earth observation data processing and fusion; machine learning for atmospheric parameter retrieval; urban environmental monitoring; sustainable development indicators; environmental health applications

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Guest Editor
Sustainable Building Design (SBD) Lab, Department of Urban and Environmental Engineering (UEE), Faculty of Applied Sciences, Université de Liège, 4000 Liège, Belgium
Interests: sustainable building design; climate change adaptation; indoor and outdoor thermal comfort; resilient cooling strategies; building energy performance; life cycle assessment; time-dependent carbon; demand-side climate mitigation; zero carbon buildings; carbon footprint calculation
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Special Issue Information

Dear Colleagues,

Urban environments worldwide face unprecedented challenges from rapid urbanization and climate change, creating complex interactions between atmospheric quality, thermal patterns, and green infrastructure that directly impact human health and environmental sustainability.

For this Special Issue, we welcome the submission of research that advances understanding of these interconnected challenges through a One Health perspective, recognizing the fundamental links between environmental quality, ecosystem health, and human wellbeing. We invite interdisciplinary research that bridges atmospheric science, urban ecology, and public health applications spanning multiple scales—from neighborhoods to metropolitan areas. We particularly encourage investigations that leverage Earth Observation technologies and geospatial analysis, while also considering studies that combine multiple analytical approaches—including satellite observations, microclimate modeling, field measurements, and machine learning techniques—to predict optimal green infrastructure configurations, assess air purification capacity, and quantify cooling effects across diverse urban contexts.

Research addressing global sustainability frameworks, particularly SDG 11 targets focused on reductions in urban resilience and environmental impact, is welcome. This includes efforts to alleviate adverse environmental impacts per capita in cities with attention given to air quality management, as well as initiatives to enhance urban climate resilience and adaptive capacity.

Research contributions may explore machine learning approaches for atmospheric parameter retrieval (particulate matter, trace gases, aerosols, and their precursors); data fusion techniques combining multiple satellite sensors with ground-based observations; high-resolution mapping of pollutant concentrations and exposure assessment; integration of meteorological, topographical, and socioeconomic data; validation methodologies and uncertainty quantification; environmental justice applications; operational tools for public health agencies; and climate-health nexus studies.

Methodological advances utilizing emerging satellite missions and heterogeneous data sources from diverse geographical regions are encouraged. We seek contributions that demonstrate practical applications for urban planning, environmental management, and public health policy development within frameworks that address global sustainability goals and support climate-neutral and resilient smart cities.

Dr. Mariella Aquilino
Prof. Dr. Shady Attia
Guest Editors

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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

  • urban green areas
  • microclimate modeling
  • air quality assessment
  • one health
  • earth observation

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Published Papers (1 paper)

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Research

30 pages, 5633 KB  
Article
High-Resolution NO2, O3, and PMs Estimation in Puglia: Leveraging AI and Explainability Techniques
by Alessandro Fania, Giovanni Lorusso, Roberto Cilli, Nicola Amoroso, Maria Adamo, Mariella Aquilino, Loredana Bellantuono, Marica De Lucia, Antonio Lacalamita, Marianna La Rocca, Tommaso Maggipinto, Angela Morabito, Alessandra Nocioni, Ester Pantaleo, Roberto Primerano, Sabina Tangaro, Roberto Bellotti and Alfonso Monaco
Atmosphere 2026, 17(2), 209; https://doi.org/10.3390/atmos17020209 - 15 Feb 2026
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Abstract
Air pollution remains a major environmental challenge, with severe impacts on human health and ecosystems. Recent advances in satellite technology have transformed air quality monitoring by enabling global, continuous observations of atmospheric pollutants. However, satellite data often lack the precision of ground-based stations. [...] Read more.
Air pollution remains a major environmental challenge, with severe impacts on human health and ecosystems. Recent advances in satellite technology have transformed air quality monitoring by enabling global, continuous observations of atmospheric pollutants. However, satellite data often lack the precision of ground-based stations. This study aims to develop a machine learning model to predict daily surface concentrations of key air pollutants (NO2, O3, PM10, and PM2.5) at high spatial resolution (300 m) in the Apulia region. Using Regional Environmental Protection Agency (ARPA) station data from 2019 to 2022 and meteorological, geographic, land-use, and temporal variables, we trained an XGBoost model on a 300 m grid. Model performance, assessed by repeated cross-validation, showed an average R2 of 0.71, with values of 0.77 for NO2, 0.78 for O3, 0.67 for PM2.5, and 0.64 for PM10. eXplainable AI (XAI) methods confirmed strong alignment with established scientific knowledge, enhancing model reliability and offering insights into pollutant distribution drivers. Full article
(This article belongs to the Special Issue Urban Air Quality, Green Spaces, and Microclimate Analysis)
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