Recent Advances in Low-Cost Chemical Sensor Technologies for Environmental Monitoring Applications

A special issue of Chemosensors (ISSN 2227-9040). This special issue belongs to the section "Applied Chemical Sensors".

Deadline for manuscript submissions: 31 December 2025 | Viewed by 2287

Special Issue Editor


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Guest Editor
ENEA, Italian National Agency for New Technologies, Energy and Sustainable Economic Development, Department for Sustainability, Division of Sustainable Materials, Laboratory Functional Materials and Technologies for Sustainable Applications, Brindisi Research Center, km 706, Strada Statale 7, Appia, I-72100 Brindisi, Italy
Interests: sensor materials; functional materials; gas sensors; air quality sensor systems; sensor technology development; environmental measurements; urban air quality sensor networks; smart cities applications; environmental sustainability
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Special Issue Information

Dear Colleagues,

Global warming and climate change are serious environmental threats at global level. Air pollution due to the rapid urbanization is one of the major reasons of environmental deterioration. The emission of air-pollutants and toxic gases such as nitrogen oxides (NOx), ozone (O3), carbon monoxide (CO), sulfur dioxide (SO2), including Volatile Organic Compounds (VOCs) are extremely dangerous for ecosystems and human beings. Particulate matter (PM10, PM2.5, PM1.0 and Ultrafine Particles) is highly nocive for public health and environment. Greenhouse gases (GHG), including carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O) are the main drivers of global warming. Thus, their continuous monitoring at high spatial-temporal resolution is crucial to prevent environmental disasters.

Air quality monitoring based on low-cost sensor technologies is very popular for several emerging applications such as citizen science, community sensing, public health protection, environmental information, smart city planning, environmental monitoring and sustainability.

Current sensor technologies include several types of transducers and system configurations, evolving quickly with different open questions and considerable challenges in terms of sensitivity, selectivity, stability, limit of detection, accuracy, calibration, repeatability, and so on. The evolution of sensor performance for air quality monitoring by networked low-cost sensor-systems equipped by artificial intelligence (AI) is crucial for future applications in real scenario.

This Special Issue will focus on chemical sensor technology, gas sensors, particulate matter sensors/detectors, greenhouse gas devices, sensor-nodes, hardware and software innovations, data communication, system integration, sensor evaluation, processing/correction algorithms, Machine Learning, new environmental solutions, and applications for air pollution monitoring. Proper calibration techniques are necessary, both in the laboratory and in field applications of single sensors and networked sensor-systems for environmental monitoring. Wireless sensor networks combined with modelling and chemical weather forecasting will be considered for smart city applications, including case-studies of air quality experimental campaigns and environmental measurements in urban hot spots.

In this Special Issue, we invite front-line researchers and authors to submit original researches and review articles on exploring Recent Advances in Low-Cost Chemical Sensor Technologies for Environmental Monitoring Applications.

The areas of particular interest to this Special Issue include but are not limited to:

  • Low-cost air quality sensors (gas, VOCs, PM);
  • Chemical sensors;
  • GHG sensors;
  • Chemical sensor-nodes and system development;
  • Chemical sensor calibration;
  • Machine Learning and Artificial Intelligence for chemical sensors;
  • Wireless sensor networks for chemical sensing;
  • Urban air pollution monitoring by chemical sensors;
  • Chemical sensors for environmental measurements;
  • Chemical sensors for smart cities IoT applications;
  • Chemical sensors for case-studies in experimental campaigns;
  • New concepts and trends in air quality sensors.

Prof. Dr. Michele Penza
Guest Editor

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Keywords

  • low-cost air quality sensors (gas, VOCs, PM)
  • GHG sensors
  • chemical sensor-nodes
  • chemical sensor calibration
  • machine learning
  • artificial intelligence for chemical sensors
  • wireless sensor networks for chemical sensing
  • urban air pollution monitoring by chemical sensors
  • chemical sensors for environmental measurements and case-studies
  • chemical sensors for smart cities
  • IoT applications
  • new concepts and trends in air quality sensors

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Published Papers (2 papers)

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Research

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30 pages, 12475 KiB  
Article
Optimizing Sputtered SnO2:Dy Thin Films for NO2 Gas Detection
by Marwen Mezyen, Nabila Bitri, Ibtissem Riahi, Fatma Chaabouni and Eduard Llobet
Chemosensors 2025, 13(4), 121; https://doi.org/10.3390/chemosensors13040121 - 1 Apr 2025
Viewed by 781
Abstract
Notwithstanding the success of SnO2 as a fundamental material for gas sensing, it has often been criticized for its cross-sensitivity and high operational temperatures. Therefore, in this study, RF-sputtered SnO2 thin films were subjected to a modification process through doping with [...] Read more.
Notwithstanding the success of SnO2 as a fundamental material for gas sensing, it has often been criticized for its cross-sensitivity and high operational temperatures. Therefore, in this study, RF-sputtered SnO2 thin films were subjected to a modification process through doping with a rare earth element, dysprosium (Dy), and subsequently deposited onto two different types of substrates: alumina and glass substrates. All thin films underwent a comprehensive series of characterizations aimed at ensuring their suitability as NO2 sensors. The dysprosium doping levels ranged from 1 to 7 wt.% in increments of 2% (wt.%). X-ray patterns showed that all deposited films exhibited the tetragonal rutile structure of SnO2. The optical band gap energy (Eg) increased with Dy doping, while the Urbach energy decreased with Dy doping. Field emission scanning electron microscopy (FESEM) revealed highly compacted grainy surfaces with high roughness for alumina substrate thin films, which also exhibited higher resistivity that increased with the levels of Dy doping. Energy-dispersive X-ray spectroscopy (EDX) analyses confirmed the stoichiometry of both types of thin films. Gas sensing tests were conducted at different operating temperatures, where the highest response to nitrogen dioxide, over 42%, was recorded for the higher dopant level at 250 °C. Moreover, the sensor’s selectivity toward nitrogen dioxide traces was evaluated by introducing interfering gases at higher concentrations. However, the sensors showed also significant responses when operated at room temperature. Also, we have demonstrated that higher stability is related to the temperature of the sensors and Dy ratio. Hence, a detailed discussion of the gas-sensing mechanisms was undertaken to gain a deeper insight into the NO2 sensitivity exhibited by the Dy-doped SnO2 layer. Full article
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Review

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29 pages, 8644 KiB  
Review
Recent Advances in Resistive Gas Sensors: Fundamentals, Material and Device Design, and Intelligent Applications
by Peiqingfeng Wang, Shusheng Xu, Xuerong Shi, Jiaqing Zhu, Haichao Xiong and Huimin Wen
Chemosensors 2025, 13(7), 224; https://doi.org/10.3390/chemosensors13070224 - 21 Jun 2025
Viewed by 236
Abstract
Resistive gas sensors have attracted significant attention due to their simple architecture, low cost, and ease of integration, with widespread applications in environmental monitoring, industrial safety, and healthcare diagnostics. This review provides a comprehensive overview of recent advances in resistive gas sensors, focusing [...] Read more.
Resistive gas sensors have attracted significant attention due to their simple architecture, low cost, and ease of integration, with widespread applications in environmental monitoring, industrial safety, and healthcare diagnostics. This review provides a comprehensive overview of recent advances in resistive gas sensors, focusing on their fundamental working mechanisms, sensing material design, device architecture optimization, and intelligent system integration. These sensors primarily operate based on changes in electrical resistance induced by interactions between gas molecules and sensing materials, including physical adsorption, charge transfer, and surface redox reactions. In terms of materials, metal oxide semiconductors, conductive polymers, carbon-based nanomaterials, and their composites have demonstrated enhanced sensitivity and selectivity through strategies such as doping, surface functionalization, and heterojunction engineering, while also enabling reduced operating temperatures. Device-level innovations—such as microheater integration, self-heated nanowires, and multi-sensor arrays—have further improved response speed and energy efficiency. Moreover, the incorporation of artificial intelligence (AI) and Internet of Things (IoT) technologies has significantly advanced signal processing, pattern recognition, and long-term operational stability. Machine learning (ML) algorithms have enabled intelligent design of novel sensing materials, optimized multi-gas identification, and enhanced data reliability in complex environments. These synergistic developments are driving resistive gas sensors toward low-power, highly integrated, and multifunctional platforms, particularly in emerging applications such as wearable electronics, breath diagnostics, and smart city infrastructure. This review concludes with a perspective on future research directions, emphasizing the importance of improving material stability, interference resistance, standardized fabrication, and intelligent system integration for large-scale practical deployment. Full article
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