Special Issue "Emerging Technologies for Observation of Air Pollution"

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

Deadline for manuscript submissions: closed (31 March 2023) | Viewed by 746

Special Issue Editors

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
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
Division 4 - Natural and Built Environment, Karlsruhe Institute of Technology, 76131 Karlsruhe, Germany
Interests: micro-meteorology; urban climate; urban heat island; measurement-based research
Sustainability Engineering Laboratory, Aristotle University Thessaloniki, 541 24 Thessaloniki, Greece
Interests: air quality; atmospheric pollution modelling; urban meteorology; data assimilation; numerical methods

Special Issue Information

Dear Colleagues,

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. Denise Böhnke
Dr. Georgios Tsegas
Guest Editors

Manuscript Submission Information

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

Published Papers (1 paper)

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Deployment and Evaluation of a Network of Open Low-Cost Air Quality Sensor Systems
Atmosphere 2023, 14(3), 540; https://doi.org/10.3390/atmos14030540 - 11 Mar 2023
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Low-cost air quality sensors have the potential to complement the regulatory network of air quality monitoring stations, with respect to increased spatial density of observations, however, their data quality continues to be of concern. Here we report on our experience with a small [...] Read more.
Low-cost air quality sensors have the potential to complement the regulatory network of air quality monitoring stations, with respect to increased spatial density of observations, however, their data quality continues to be of concern. Here we report on our experience with a small network of open low-cost sensor systems for air quality, which was deployed in the region of Stavanger, Norway, under Nordic winter conditions. The network consisted of AirSensEUR sensor systems, equipped with sensors for, among others, nitrogen dioxide and fine particulate matter. The systems were co-located at an air quality monitoring station, for a period of approximately six weeks. A subset of the systems was subsequently deployed at various roadside locations for half a year, and finally co-located at the same air quality monitoring station again, for a post-deployment evaluation. For fine particulate matter, the co-location results indicate a good inter-unit consistency, but poor average out-of-the-box performance (R2 = 0.25, RMSE = 9.6 μg m3). While Köhler correction did not significantly improve the accuracy in our study, filtering for high relative humidity conditions improved the results (R2 = 0.63, RMSE = 7.09 μg m3). For nitrogen dioxide, the inter-unit consistency was found to be excellent, and calibration models were developed which showed good performance during the testing period (on average R2 = 0.98, RMSE = 5.73 μg m3), however, due to the short training period, the calibration models are likely not able to capture the full annual variability in environmental conditions. A post-deployment co-location showed, respectively, a slight and significant decrease in inter-sensor consistency for fine particulate matter and nitrogen dioxide. We further demonstrate, how observations from even such a small network can be exploited by assimilation in a high-resolution air quality model, thus adding value to both the observations and the model, and ultimately providing a more comprehensive perspective of air quality than is possible from either of the two input datasets alone. Our study provides valuable insights on the operation and performance of an open sensor system for air quality, particularly under challenging Nordic environmental conditions. Full article
(This article belongs to the Special Issue Emerging Technologies for Observation of Air Pollution)
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