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Editorial Board Members’ Collection Series: Sensors for Monitoring Environmental Pollution

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Environmental Sensing".

Deadline for manuscript submissions: closed (25 February 2024) | Viewed by 1798

Special Issue Editors


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Guest Editor
1. Osservatorio Vesuviano-Sez, Napoli Istituto Nazionale di Geofisica e Vulcanologia, Via Diocleziano, 328-80124 Napoli, Italy
2. IRISS-Istituto di Ricerca su Innovazione e Servizi per lo Sviluppo, Via Guglielmo Sanfelice, 8-80134 Napoli, Italy
3. ISMAR—Istituto di Scienze Marine Calata Porta Di Massa—Porto Di Napoli, 80-80133 Napoli, Italy
Interests: geochemistry; medical geology; geothermal energy; isotopes; environmental geochemistry; volcanology; natural disasters; public health; sensors
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Research Institute for the Integrated Management of Coastal Zones (IGIC), Polytechnic University of Valencia, 46022 València, Spain
Interests: aquaculture; environmental monitoring; precision agriculture; water quality; wireless sensor networks; chemical sensors; physical sensors; pollution monitoring
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Pollution due to human activity affects the atmosphere, water, and soil. In some particular geological areas, it is also difficult to discriminate between anthropogenic and natural pollution. The continuous monitoring of pollutant levels and their impact on the environment is crucial for studying the effects and measures for controlling pollution. Sensors are one of the most useful tools for environmental pollution monitoring, allowing for real-time, remote, and precise monitoring, with the most critical aspects of their use being accuracy, specificity, and robustness. Sometimes, the environment in which sensors must be deployed is harsh, and they must be isolated and resistant to water, dust, and corrosive elements. In other cases, the accuracy attained using existing sensors is not enough if only low concentrations of environmental pollutants are present. Finally, specificity becomes a challenge when specific compounds must be identified and quantified in complex matrixes with hundreds of compounds, some of them similar to the target.

This Special Issue intends to collect the most relevant publications in environmental pollution sensing, welcoming critical reviews and original works from the fields of engineering, chemistry, environmental and earth sciences, and health. Topics of interest for this collection include, but are not limited to:

  • Acoustic sensors;
  • Biosensors;
  • Chemical sensors;
  • Magnetic sensors;
  • Optical sensors;
  • Water pollution;
  • Atmospheric pollution;
  • Soil pollution;
  • Environmental impact;
  • Case studies;
  • Sensor deployment.

Dr. Renato Somma
Dr. Lorena Parra
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. Sensors is an international peer-reviewed open access semimonthly 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 2600 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.

Published Papers (2 papers)

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Research

23 pages, 19263 KiB  
Article
Indication Variability of the Particulate Matter Sensors Dependent on Their Location
by Alicja Wiora, Józef Wiora and Jerzy Kasprzyk
Sensors 2024, 24(5), 1683; https://0-doi-org.brum.beds.ac.uk/10.3390/s24051683 - 05 Mar 2024
Viewed by 533
Abstract
Particulate matter (PM) suspended in the air significantly impacts human health. Those of anthropogenic origin are particularly hazardous. Poland is one of the countries where the air quality during the heating season is the worst in Europe. Air quality in small towns and [...] Read more.
Particulate matter (PM) suspended in the air significantly impacts human health. Those of anthropogenic origin are particularly hazardous. Poland is one of the countries where the air quality during the heating season is the worst in Europe. Air quality in small towns and villages far from state monitoring stations is often much worse than in larger cities where they are located. Their residents inhale the air containing smoke produced mainly by coal-fired stoves. In the frame of this project, an air quality monitoring network was built. It comprises low-cost PMS7003 PM sensors and ESP8266 microcontrollers with integrated Wi-Fi communication modules. This article presents research results on the influence of the PM sensor location on their indications. It has been shown that the indications from sensors several dozen meters away from each other can differ by up to tenfold, depending on weather conditions and the source of smoke. Therefore, measurements performed by a network of sensors, even of worse quality, are much more representative than those conducted in one spot. The results also indicated the method of detecting a sudden increase in air pollutants. In the case of smokiness, the difference between the mean and median indications of the PM sensor increases even up to 400 µg/m3 over a 5 min time window. Information from this comparison suggests a sudden deterioration in air quality and can allow for quick intervention to protect people’s health. This method can be used in protection systems where fast detection of anomalies is necessary. Full article
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15 pages, 1798 KiB  
Article
From Local Issues to Global Impacts: Evidence of Air Pollution for Romania and Turkey
by Tugce Pekdogan, Mihaela Tinca Udriștioiu, Hasan Yildizhan and Arman Ameen
Sensors 2024, 24(4), 1320; https://0-doi-org.brum.beds.ac.uk/10.3390/s24041320 - 18 Feb 2024
Cited by 1 | Viewed by 664
Abstract
Air pollution significantly threatens human health and natural ecosystems and requires urgent attention from decision makers. The fight against air pollution begins with the rigorous monitoring of its levels, followed by intelligent statistical analysis and the application of advanced machine learning algorithms. To [...] Read more.
Air pollution significantly threatens human health and natural ecosystems and requires urgent attention from decision makers. The fight against air pollution begins with the rigorous monitoring of its levels, followed by intelligent statistical analysis and the application of advanced machine learning algorithms. To effectively reduce air pollution, decision makers must focus on reducing primary sources such as industrial plants and obsolete vehicles, as well as policies that encourage the adoption of clean energy sources. In this study, data analysis was performed for the first time to evaluate air pollution based on the SPSS program. Correlation coefficients between meteorological parameters and particulate matter concentrations (PM1, PM2.5, PM10) were calculated in two urban regions of Romania (Craiova and Drobeta-Turnu Severin) and Turkey (Adana). This study establishes strong relationships between PM concentrations and meteorological parameters with correlation coefficients ranging from −0.617 (between temperature and relative humidity) to 0.998 (between PMs). It shows negative correlations between temperature and particulate matter (−0.241 in Romania and −0.173 in Turkey) and the effects of humidity ranging from moderately positive correlations with PMs (up to 0.360 in Turkey), highlighting the valuable insights offered by independent PM sensor networks in assessing and improving air quality. Full article
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