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Journals
Atmosphere
Special Issues
Emerging Technologies for Observation of Air Pollution
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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: 2 August 2024 | Viewed by 4447

Special Issue Editors

Prof. Dr. Klaus Schäfer

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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

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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. Denise Böhnke

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Guest Editor
Division 4 - Natural and Built Environment, Karlsruhe Institute of Technology, 76131 Karlsruhe, Germany
Interests: micro-meteorology; urban climate; urban heat island; measurement-based research
Dr. Georgios Tsegas

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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 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

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

Published Papers (3 papers)

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Research

17 pages, 3323 KiB  
Article
Concentration Gradients of Ammonia, Methane, and Carbon Dioxide at the Outlet of a Naturally Ventilated Dairy Building
by Harsh Sahu, Sabrina Hempel, Thomas Amon, Jürgen Zentek, Anke Römer and David Janke
Atmosphere 2023, 14(9), 1465; https://doi.org/10.3390/atmos14091465 - 21 Sep 2023
Cited by 1 | Viewed by 839
Abstract
In natural ventilation system-enabled dairy buildings (NVDB), achieving accurate gas emission values is highly complicated. The external weather affects measurements of the gas concentration of pollutants (cP) and volume flow rate (Q) due to the open-sided design. Previous [...] Read more.
In natural ventilation system-enabled dairy buildings (NVDB), achieving accurate gas emission values is highly complicated. The external weather affects measurements of the gas concentration of pollutants (cP) and volume flow rate (Q) due to the open-sided design. Previous research shows that increasing the number of sensors at the side opening is not cost-effective. However, accurate measurements can be achieved with fewer sensors if an optimal sampling position is identified. Therefore, this study attempted to calibrate the outlet of an NVDB for the direct emission measurement method. Our objective was to investigate the cP gradients, in particular, for ammonia (cNH3), carbon dioxide (cCO2), and methane (cCH4) considering the wind speed (v) and their mixing ratios ([cCH4/cNH3¯]) at the outlet, and assess the effect of sampling height (H). The deviations in each cP at six vertical sampling points were recorded using a Fourier-transform infrared (FTIR) spectrometer. Additionally, wind direction and speed were recorded at the gable height (10 m) by an ultrasonic anemometer. The results indicated that, at varied heights, the average cNH3 (p < 0.001), cCO2 (p < 0.001), and (p < 0.001) were significantly different and mostly concentrated at the top (H = 2.7). Wind flow speed information revealed drastic deviations in cP, for example up to +105.1% higher cNH3 at the top (H = 2.7) compared to the baseline (H = 0.6), especially during low wind speed (v < 3 m s−1) events. Furthermore, [cCH4/cNH3¯] exhibited significant variation with height, demonstrating instability below 1.5 m, which aligns with the average height of a cow. In conclusion, the average cCO2, cCH4, and cNH3 measured at the barn’s outlet are spatially dispersed vertically which indicates a possibility of systematic error due to the sensor positioning effect. The outcomes of this study will be advantageous to locate a representative gas sampling position when measurements are limited to one constant height, for example using open-path lasers or low-cost devices. Full article
(This article belongs to the Special Issue Emerging Technologies for Observation of Air Pollution)
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21 pages, 5470 KiB  
Article
Design, Modelling, and Experimental Validation of a Glass U-Tube Mass Sensing Cantilever for Particulate Direct-on-Line Emissions Measurement
by Daniel Nicklin and Hamidreza Gohari Darabkhani
Atmosphere 2023, 14(6), 915; https://doi.org/10.3390/atmos14060915 - 24 May 2023
Viewed by 1053
Abstract
The requirement to monitor and control industrial processes has increased over recent years, therefore innovative techniques are required to meet the demand for alternative methods of particulate measurement. Resonant mass sensors are now strong candidates for accurate mass measurement and are frequently used [...] Read more.
The requirement to monitor and control industrial processes has increased over recent years, therefore innovative techniques are required to meet the demand for alternative methods of particulate measurement. Resonant mass sensors are now strong candidates for accurate mass measurement and are frequently used in many diverse fields of science and engineering. This paper presents the design, modelling, and optimal geometry selection for sensitivity improvement of a U-shaped glass tube as a resonant mass sensing cantilever with a view to becoming a component of particulate measurement equipment. Finite Element Analysis (FEA) was used to develop the system which was validated experimentally using a physical model. This paper focuses on both the proof of concept and the geometry selection of the sensor using analysis of the system sensitivity for best selection. Modal and harmonic analysis were undertaken across a range of commercially available glass tube sizes from 6 mm to 10 mm diameter, to determine the optimal geometry selection, validated with practical experimental data. Results show a consistent difference of 3–5% between the simulation and experimental results, showing strong correlation. This research provides a methodology on the development of using a U-shaped glass tube for accurate mass measurement with a view to exploring the design as a component of particulate emissions equipment. The experimental and simulation results confirm that the highest sensitivity is achieved when the geometry dimensions, and therefore the vacant mass of the tube, is reduced. The 6 mm diameter tube with the smallest bend radius was the most suitable design to meet the design criteria. The calibration curve was plotted to allow an unknown mass to be calculated, which gave an R2 value of 0.9984. All experimental work was repeated three times with results giving an average of 0.44% between the minimum and maximum showing strong linearity and suggesting the potential for implementation of the methodology in its intended application. The design provides possible solutions to some of the issues currently seen with particulate measurement from stationary sources. Full article
(This article belongs to the Special Issue Emerging Technologies for Observation of Air Pollution)
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27 pages, 16039 KiB  
Article
Deployment and Evaluation of a Network of Open Low-Cost Air Quality Sensor Systems
by Philipp Schneider, Matthias Vogt, Rolf Haugen, Amirhossein Hassani, Nuria Castell, Franck R. Dauge and Alena Bartonova
Atmosphere 2023, 14(3), 540; https://doi.org/10.3390/atmos14030540 - 11 Mar 2023
Viewed by 1760
Abstract
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 m−3). 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 m−3). 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 m−3), 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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