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Atmosphere
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Emerging Technologies for Observation of Air Pollution (2nd Edition)
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Emerging Technologies for Observation of Air Pollution (2nd Edition)

A special issue of Atmosphere (ISSN 2073-4433). This special issue belongs to the section "Atmospheric Techniques, Instruments, and Modeling".

Deadline for manuscript submissions: 15 August 2025 | Viewed by 849

Special Issue Editors

Prof. Dr. Klaus Schäfer

E-Mail Website
Guest Editor
Atmospheric Physics Consultant, 82467 Garmisch-Partenkirchen, Germany
Interests: air quality; air pollutants; measurement techniques; meteorological influences; atmospheric data analyses
Special Issues, Collections and Topics in MDPI journals
Dr. Nuria Castell

E-Mail Website
Guest Editor
Urban Environment and Industry Department, NILU—Norwegian Institution for Air Research, 2027 Kjeller, Norway
Interests: environmental monitoring; urban sustainability; citizen science; low-cost sensor technology; co-creation; urban living labs; transdisciplinary research
Special Issues, Collections and Topics in MDPI journals
Dr. Georgios Tsegas

E-Mail Website
Guest Editor
Sustainability Engineering Laboratory, Aristotle University Thessaloniki, 541 24 Thessaloniki, Greece
Interests: air quality; atmospheric pollution modelling; urban meteorology; data assimilation; numerical methods
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This Special Issue is the second volume in a series of publications dedicated to “Emerging Technologies for Observation of Air Pollution” (https://www.mdpi.com/journal/atmosphere/special_issues/EQ5K6Z2085).

The problem of poor air quality still influences inhabitant’s life in all cities of the globe. During growing urbanization scientific research shows origin of air pollution from local scales and from regional and global scales including interactions with climate protection measures. Additionally, the public awareness is growing to improve management and assessment strategies and effective control policies for reducing the health impact of air pollution.

The focus of this Special Issue is on new research contributions on developments in observation techniques and data operation algorithms which enable personal air pollution exposure determination, as well as new conclusions about sources of air pollutants and emission reduction measures.  New research results about spatially complete information on air pollutants, about urban air quality observations by smart air quality networks, as well as corresponding near-real time numerical simulations at the small scale are ideal contributions to this Special Issue.

We can offer substantial discounts for high-quality papers.

Prof. Dr. Klaus Schäfer
Dr. Nuria Castell
Dr. Georgios Tsegas
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

  • atmospheric observations
  • urban air quality
  • sensors and measurements
  • crowd sourcing
  • numerical simulations and modeling

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Published Papers (1 paper)

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Research

17 pages, 7826 KiB  
Article
Evaluating the Spatial Coverage of Air Quality Monitoring Stations Using Computational Fluid Dynamics
by Giannis Ioannidis, Paul Tremper, Chaofan Li, Till Riedel, Nikolaos Rapkos, Christos Boikos and Leonidas Ntziachristos
Atmosphere 2025, 16(3), 326; https://doi.org/10.3390/atmos16030326 - 12 Mar 2025
Viewed by 623
Abstract
Densely populated urban areas often experience poor air quality due to high levels of anthropogenic emissions. The population is frequently exposed to harmful gaseous and particulate pollutants, which are directly linked to various health issues, including respiratory diseases. Accurately assessing and predicting pollutant [...] Read more.
Densely populated urban areas often experience poor air quality due to high levels of anthropogenic emissions. The population is frequently exposed to harmful gaseous and particulate pollutants, which are directly linked to various health issues, including respiratory diseases. Accurately assessing and predicting pollutant concentrations within urban areas is therefore crucial. This study developed a computational fluid dynamic (CFD) model designed to capture turbulence effects that influence pollutant dispersion in urban environments. The focus was on key pollutants commonly associated with vehicular emissions, such as carbon monoxide (CO), nitrogen oxides (NOx), volatile organic compounds (VOCs), and particulate matter (PM). The model was applied to the city of Augsburg, Germany, to simulate pollutant behavior at a microscale level. The primary objectives were twofold: first, to accurately predict local pollutant concentrations and validate these predictions against measurement data; second, to evaluate the representativeness of air quality monitoring stations in reflecting the broader pollutant distribution in their vicinity. The approach presented here has demonstrated that when focusing on an area within a specific radius of an air quality station, the representativeness ranges between 10% and 16%. On the other hand, when assessing the representativeness across the street of deployment, the spatial coverage of the sensor ranges between 23% and 80%. This analysis highlights that air quality stations primarily capture pollution levels from high-activity areas directly across their deployment site, rather than reflecting conditions in nearby lower-activity zones. This approach ensures a more comprehensive understanding of urban air pollution dynamics and assesses the reliability of air quality (AQ) monitoring stations. Full article
(This article belongs to the Special Issue Emerging Technologies for Observation of Air Pollution (2nd Edition))
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