Advanced Electrochemical Sensors for Environmental Monitoring
A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Chemical Sensors".
Deadline for manuscript submissions: 20 October 2026 | Viewed by 12
Special Issue Editor
Special Issue Information
Dear Colleagues,
Electrochemical sensors are rapidly evolving into important tools for environmental monitoring, driven by advances in materials science and, more recently, artificial intelligence. Current research focuses on developing sensors with greater sensitivity, selectivity, stability, and the possibility of miniaturisation for the detection of trace levels of contaminants such as heavy metals, pesticides, pharmaceuticals, and microplastics in complex environmental matrices. The field is rapidly progressing toward more robust, green, and intelligent sensing systems that can provide comprehensive, real-time insights into environmental quality. The integration of nanomaterials—including graphene, carbon nanotubes, and metal nanoparticles—has significantly enhanced electron transfer and surface reactivity, improving analytical performance.
This Special Issue welcomes contributions that explore novel sensing materials such as RuO2-based electrodes and nanostructured composites, alongside machine learning techniques for signal processing. Emphasis will be placed on systems capable of real-time and in situ monitoring, autonomous calibration, and integration with wireless networks or IoT platforms. By bridging electrochemistry, environmental science, and computational intelligence, this issue aims to showcase how smart sensing technologies can improve detection accuracy and support data-driven environmental decision-making. Applications in water and air quality, soil contamination, and climate-related metrics will be central to this collection, offering a comprehensive view of the future of intelligent environmental sensing.
Dr. Magdalena Wajrak
Guest Editor
Manuscript Submission Information
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Keywords
- electrochemical sensors
- environmental monitoring
- smart sensing
- solid-state electrodes
- artificial intelligence
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