Sensors for Air Quality Assessment

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

Deadline for manuscript submissions: closed (30 June 2019) | Viewed by 51521

Special Issue Editors


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Guest Editor
Department of Environmental Science, Aarhus University, 4000 Roskilde, Denmark
Interests: assessment of air pollution exposure; air pollution modelling; field studies using low-cost sensors; integrated monitoring of air pollution using measurements and model calculations in combination

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Guest Editor
Lab for Measurement Technology, Saarland University, 6123 Saarbrücken, Germany.
Interests: sensor system integration; intelligent sensor systems; dynamic operation; advanced signal processing; system calibration and validation; environmental monitoring; indoor air quality
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Guest Editor
Department of Mechanical Engineering, Aristotle University of Thessaloniki, Thessaloniki, Greece
Interests: environmental informatics; computational intelligence oriented data analytics and modelling; urban air quality management and information systems; computational calibration and performance improvement of low-cost environmental sensors; quality of life information services
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Environmental monitoring is, today, based on fixed-site measurement stations using advanced analytical equipment to achieve high data quality. However, such monitoring is associated with high costs for investment in equipment, as well as for quality control and maintenance. Therefore, only a limited number of stations are usually operated in routine monitoring programs, and often these programs only include measurements of pollutants that are directly required for testing compliance with guidelines. Many monitoring programs are supplemented by model calculations in order to better meet the requirements from the local population for obtaining information with personal relevance, i.e., about pollutant levels at their residence or in the streets where they commute. The limited number of monitoring stations means that the models may not be validated for all types of locations. For example, street stations usually include hot spots, i.e., the busiest street canyons, whereas streets with openings in the building face, substantial difference in building heights, or streets with only buildings on one side usually are not represented.

Supplementary networks based on low-cost sensors for gaseous as well as particulate pollutants have been established in many urban areas. Such networks may be fixed site, and/or include mobile measurements on individuals or on buses, trams, etc., in the urban area. Such measurements can supplement conventional measurement stations for mapping local pollution levels in the urban area, as well as for model validation. Moreover, they may also be highly valuable in data fusion or data assimilation where data are merged into model calculations to obtain better concentration surfaces, e.g., over an urban area, or to extend the pollutant spectrum.

In addition, recent developments in Sensor and Internet of Things technologies have led to the introduction of small, portable, low-cost gas and particle sensors into everyday life via smart phones (also with integrated temperature, humidity and pressure sensors), smart air conditioning and air purifying units (combined with temperature, humidity and CO2 sensors), as well as a multiplicity of devices and applications that is growing continuously. This has led to a paradigm shift towards participatory environmental monitoring which has been fueled by citizen science initiatives.

However, in many cases, the data quality from low-cost sensor systems has not been tested before implementation and little or no calibration of the systems was performed. Thus, a lot of data of unknown quality is currently being generated and distributed, e.g., to local authorities, to the population and the media. In some cases, data is very far from describing the real world conditions, but the users cannot judge the quality from what is being reported. There is thus a considerable need for guidelines regarding test, validation and calibration of low-cost sensor based measurement devices, as well as recommendations regarding which type of sensors and systems are applicable for which pollutant, concentration range and location.

The Special Issue will cover a range of topics addressing modern sensor technologies, tests, validation and calibration as well as practical applications including multisensor integration, uses for model validation, data fusion and data assimilation, but also for supporting environmental information services and citizen science goals. The editors target high quality papers on the latest technological developments as well as examples of field studies using low-cost air pollution sensors of various types and for numerous applications in ambient, as well as indoor, environments.

Dr. Ole Hertel
Dr. Andreas Schütze
Dr. Kostas Karatzas
Guest Editors

Manuscript Submission Information

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Keywords

  • Low-cost sensors
  • System integration
  • Data analysis
  • Air pollution measurements
  • Ambient air quality
  • Exposure assessment
  • Data fusion and data assimilation
  • Air pollution mapping
  • Environmental information services
  • Citizen science

Published Papers (4 papers)

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Research

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20 pages, 5640 KiB  
Article
Development and Implementation of a Platform for Public Information on Air Quality, Sensor Measurements, and Citizen Science
by Joost Wesseling, Henri de Ruiter, Christa Blokhuis, Derko Drukker, Ernie Weijers, Hester Volten, Jan Vonk, Lou Gast, Marita Voogt, Peter Zandveld, Sjoerd van Ratingen and Erik Tielemans
Atmosphere 2019, 10(8), 445; https://doi.org/10.3390/atmos10080445 - 1 Aug 2019
Cited by 44 | Viewed by 8248
Abstract
The use of low-cost sensors for air quality measurements is expanding rapidly, with an associated rise in the number of citizens measuring air quality themselves. This has major implications for traditional air quality monitoring as performed by Environmental Protection Agencies. Here we reflect [...] Read more.
The use of low-cost sensors for air quality measurements is expanding rapidly, with an associated rise in the number of citizens measuring air quality themselves. This has major implications for traditional air quality monitoring as performed by Environmental Protection Agencies. Here we reflect on the experiences of the Dutch Institute for Public Health and the Environment (RIVM) with the use of low-cost sensors, particularly NO2 and PM10/PM2.5-sensors, and related citizen science, over the last few years. Specifically, we discuss the Dutch Innovation Program for Environmental Monitoring, which comprises the development of a knowledge portal and sensor data portal, new calibration approaches for sensors, and modelling and assimilation techniques for incorporating these uncertain sensor data into air pollution models. Finally, we highlight some of the challenges that come with the use of low-cost sensors for air quality monitoring, and give some specific use-case examples. Our results show that low-cost sensors can be a valuable addition to traditional air quality monitoring, but so far, their use in official monitoring has been limited. More research is needed to establish robust calibration methods while ongoing work is also aimed at a better understanding of the public’s needs for air quality information to optimize the use of low-cost sensors. Full article
(This article belongs to the Special Issue Sensors for Air Quality Assessment)
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13 pages, 1120 KiB  
Article
Using Medium-Cost Sensors to Estimate Air Quality in Remote Locations. Case Study of Niedzica, Southern Poland
by Ewa Adamiec, Jacek Dajda, Agnieszka Gruszecka-Kosowska, Edeltrauda Helios-Rybicka, Marek Kisiel-Dorohinicki, Radosław Klimek, Dariusz Pałka and Jarosław Wąs
Atmosphere 2019, 10(7), 393; https://doi.org/10.3390/atmos10070393 - 13 Jul 2019
Cited by 13 | Viewed by 3649
Abstract
The aim of this study was to assess air quality by using medium-cost sensors in recreational areas that are not covered by permanent monitoring. Concentrations of air pollutants PM2.5, PM10, PM1, CO, O 3 , NO 2 in the Niedzica recreational area in [...] Read more.
The aim of this study was to assess air quality by using medium-cost sensors in recreational areas that are not covered by permanent monitoring. Concentrations of air pollutants PM2.5, PM10, PM1, CO, O 3 , NO 2 in the Niedzica recreational area in southern Poland were obtained. The research revealed that in cold weather, particulate matter concentrations significantly exceeded acceptable levels determined for PM2.5 and PM10. The most important factor that affects air quality within the studied area seems to be the combustion of poor quality fuels for heating purposes. The information obtained by the research presented could be a useful tool for local authorities to make environmental decisions, based on the potential health impacts of poor air quality levels on the population. Full article
(This article belongs to the Special Issue Sensors for Air Quality Assessment)
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18 pages, 7880 KiB  
Article
Performance Assessment of a Low-Cost PM2.5 Sensor for a near Four-Month Period in Oslo, Norway
by Hai-Ying Liu, Philipp Schneider, Rolf Haugen and Matthias Vogt
Atmosphere 2019, 10(2), 41; https://doi.org/10.3390/atmos10020041 - 22 Jan 2019
Cited by 144 | Viewed by 14390
Abstract
The very low-cost Nova particulate matter (PM) sensor SDS011 has recently drawn attention for its use for measuring PM mass concentration, which is frequently used as an indicator of air quality. However, this sensor has not been thoroughly evaluated in real-world conditions and [...] Read more.
The very low-cost Nova particulate matter (PM) sensor SDS011 has recently drawn attention for its use for measuring PM mass concentration, which is frequently used as an indicator of air quality. However, this sensor has not been thoroughly evaluated in real-world conditions and its data quality is not well documented. In this study, three SDS011 sensors were evaluated by co-locating them at an official, air quality monitoring station equipped with reference-equivalent instrumentation in Oslo, Norway. The sensors’ measurement results for PM2.5 were compared with data generated from the air quality monitoring station over almost a four-month period. Five performance aspects of the sensors were examined: operational data coverage, linearity of response and accuracy, inter-sensor variability, dependence on relative humidity (RH) and temperature (T), and potential improvement of sensor accuracy, by data calibration using a machine-learning method. The results of the study are: (i) the three sensors provide quite similar results, with inter-sensor correlations exhibiting R values higher than 0.97; (ii) all three sensors demonstrate quite high linearity against officially measured concentrations of PM2.5, with R2 values ranging from 0.55 to 0.71; (iii) high RH (over 80%) negatively affected the sensor response; (iv) data calibration using only the RH and T recorded directly at the three sensors increased the R2 value from 0.71 to 0.80, 068 to 0.79, and 0.55 to 0.76. The results demonstrate the general feasibility of using these low cost SDS011 sensors for indicative PM2.5 monitoring under certain environmental conditions. Within these constraints, they further indicate that there is potential for deploying large networks of such devices, due to the sensors’ relative accuracy, size and cost. This opens up a wide variety of applications, such as high-resolution air quality mapping and personalized air quality information services. However, it should be noted that the sensors exhibit often very high relative errors for hourly values and that there is a high potential of abusing these types of sensors if they are applied outside the manufacturer-provided specifications particularly regarding relative humidity. Furthermore, our analysis covers only a relatively short time period and it is desirable to carry out longer-term studies covering a wider range of meteorological conditions. Full article
(This article belongs to the Special Issue Sensors for Air Quality Assessment)
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Review

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41 pages, 10090 KiB  
Review
Review of the Performance of Low-Cost Sensors for Air Quality Monitoring
by Federico Karagulian, Maurizio Barbiere, Alexander Kotsev, Laurent Spinelle, Michel Gerboles, Friedrich Lagler, Nathalie Redon, Sabine Crunaire and Annette Borowiak
Atmosphere 2019, 10(9), 506; https://doi.org/10.3390/atmos10090506 - 29 Aug 2019
Cited by 247 | Viewed by 23578
Abstract
A growing number of companies have started commercializing low-cost sensors (LCS) that are said to be able to monitor air pollution in outdoor air. The benefit of the use of LCS is the increased spatial coverage when monitoring air quality in cities and [...] Read more.
A growing number of companies have started commercializing low-cost sensors (LCS) that are said to be able to monitor air pollution in outdoor air. The benefit of the use of LCS is the increased spatial coverage when monitoring air quality in cities and remote locations. Today, there are hundreds of LCS commercially available on the market with costs ranging from several hundred to several thousand euro. At the same time, the scientific literature currently reports independent evaluation of the performance of LCS against reference measurements for about 110 LCS. These studies report that LCS are unstable and often affected by atmospheric conditions—cross-sensitivities from interfering compounds that may change LCS performance depending on site location. In this work, quantitative data regarding the performance of LCS against reference measurement are presented. This information was gathered from published reports and relevant testing laboratories. Other information was drawn from peer-reviewed journals that tested different types of LCS in research studies. Relevant metrics about the comparison of LCS systems against reference systems highlighted the most cost-effective LCS that could be used to monitor air quality pollutants with a good level of agreement represented by a coefficient of determination R2 > 0.75 and slope close to 1.0. This review highlights the possibility to have versatile LCS able to operate with multiple pollutants and preferably with transparent LCS data treatment. Full article
(This article belongs to the Special Issue Sensors for Air Quality Assessment)
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