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

Deadline for manuscript submissions: 31 January 2027 | Viewed by 9514

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Editors

Prof. Dr. Bartolomeo Montrucchio

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Guest Editor

Department of Control and Computer Engineering, Politecnico di Torino, 10129 Turin, Italy
Interests: sensor networks; radio-frequency identifications (RFIDs); quantum computing
Special Issues, Collections and Topics in MDPI journals

Dr. Jacopo Sini

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Guest Editor

Department of Control and Computer Engineering, Politecnico di Torino, 10129 Turin, Italy
Interests: functional safety; edge computing; human physiological parameters analysis
Special Issues, Collections and Topics in MDPI journals

Dr. Antonio Costantino Marceddu

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Guest Editor

Department of Control and Computer Engineering, Politecnico di Torino, 10129 Turin, Italy
Interests: machine learning; computer vision; data fusion; data visualization

Special Issue Information

Dear Colleagues,

We are witnessing a continuous increase in the human population, which has led to a growth in agriculture, breeding, industrial activities, and, ultimately, energy consumption. This growth is strongly related to far-reaching issues such as the reduction of air, water, and soil quality. These areas are essential to ensuring good health for humans and all living beings. Other issues of rising importance, which mainly affect large cities, are noise and light pollution. Among their harmful effects are mood disorders and their impact on human and animal circadian rhythms, which regulate the alternation of sleep and wakefulness. These issues have made it vital to develop advanced monitoring applications and devices that ensure compliance with regulations and laws and mitigate the risks of harmful effects on the environment and living beings.

This Special Issue focuses on techniques that allow us to obtain information about the environment and the living beings immersed in it to carry out appropriate assessments and, where necessary, take adequate countermeasures. Using sensors with secure networks and protocols is essential in order to obtain and transfer these sorts of data for storage and analysis. This analysis can be performed manually by humans, through graphs and screens, or automatically through systems that use artificial intelligence or ad hoc algorithms, which are eventually run at the edge or are, in general, suitable for the concept of the computing continuum, which is targeted, among others, by European Commission KDT JU- and Chips JU-funded projects.

Potential topics for this Special Issue include, but are not limited to, the following:

Biomedical monitoring;
Edge-AI computing;
Embedded systems;
Environmental monitoring;
Signal processing.

Prof. Dr. Bartolomeo Montrucchio
Dr. Jacopo Sini
Dr. Antonio Costantino Marceddu
Guest Editors

Manuscript Submission Information

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Keywords

biomedical monitoring
edge-ai computing
embedded systems
environmental monitoring
signal processing

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Published Papers (9 papers)

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Research

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22 pages, 12282 KB

Open AccessArticle

Micro-PEMS Based on OBD and MOX Sensors

by Jordy Alexander Hernández and José Ignacio Huertas

Sensors 2026, 26(14), 4333; https://doi.org/10.3390/s26144333 - 8 Jul 2026

Viewed by 325

Abstract

In response to the EURO 7 regulation, which mandates near-continuous monitoring of pollutant gas emissions from every vehicle during real driving conditions, this research reports the development of a micro portable emissions monitoring system (µPEMS) for monitoring tailpipe mass emissions of NO_x, CO, and CO₂. It consists of low-cost MOX sensors installed in the exhaust pipe to detect pollutant concentrations, complemented with engine operation data from the vehicle’s On-Board Diagnostics (OBD) system. Issues of sensor drift, cross-sensitivity, and varying sampling frequency were addressed. Readings from this µPEMS prototype exhibited high correlation (R² > 0.87) with experimental data obtained under real driving conditions using a well-accepted PEMS for the cases of three vehicles (gasoline, diesel, and hybrid). This innovation enables new alternatives to regulate vehicular emissions. It also provides valuable real-time data for improving ecodriving, vehicle technology, and national emission inventories. Full article

(This article belongs to the Special Issue Sensor-Based Systems for Environmental Monitoring and Assessment)

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15 pages, 6951 KB

Open AccessArticle

Study of the Impact of Radioactivity Detection on the Water Distribution Network Versus the Installation of an Early Warning Network

by Natalia Alegría, Igor Peñalva, Charles Pinto and Adriana Merello

Sensors 2026, 26(12), 3859; https://doi.org/10.3390/s26123859 - 17 Jun 2026

Viewed by 260

Abstract

This study investigates the radiological characteristics of drinking water sources managed by the Bilbao Bizkaia Water Consortium (CABB). To this end, the radiological monitoring parameters established by current regulations, as well as those applied by other international organizations, are reviewed and analyzed. In addition, commercially available continuous monitoring equipment is assessed in terms of its suitability for drinking water applications. To identify optimal deployment locations, a comprehensive evaluation of CABB water infrastructure is conducted, with the aim of ensuring radiological safety across the Bizkaia region. Furthermore, an economic assessment is carried out to estimate the potential cost of water supply under abnormal contamination scenarios. Full article

(This article belongs to the Special Issue Sensor-Based Systems for Environmental Monitoring and Assessment)

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32 pages, 2439 KB

Open AccessArticle

Dual-Signal Direct Time-of-Flight Method for Long-Range Groundwater Level Monitoring in Observation Wells

by Abror Shavkatovich Buriboev, Farkhat Rajabov, Jamoljon Djumanov, Khudoyorkhon Jamolov, Akmal Abduvaitov, Temur Azamov, Ilhom Rahmatullayev and Cheolwon Lee

Sensors 2026, 26(12), 3672; https://doi.org/10.3390/s26123672 - 9 Jun 2026

Viewed by 401

Abstract

Accurate and reliable groundwater-level monitoring in deep observation wells remains difficult for conventional non-contact ultrasonic systems because narrow tubular geometries intensify multipath reflections, signal attenuation, and echo ambiguity. This study proposes a dual-signal direct time-of-flight (ToF) method that combines radiofrequency (RF) synchronization with one-way airborne ultrasonic propagation to a floating receiver located at the groundwater surface. In the proposed architecture, the RF signal provides a near-instantaneous time reference, whereas the ultrasonic signal defines the propagation delay, thereby eliminating dependence on echo-based ranging. The system integrates a wellhead surface unit for synchronized transmission and control, a floating unit for ToF acquisition and embedded processing, and an optional reference channel for in situ estimation of the effective sound speed. A duty-cycled power architecture is used to support low-power long-term deployment, while a multi-shot acquisition strategy with a median-like estimator improves robustness against startup transients, timing jitters, and false detections. Field validation was conducted over a 12-month period under actual groundwater-monitoring conditions, during which the groundwater depth varied between 14 m and 30 m below the wellhead datum. Within this field-validation interval, the proposed system achieved a mean absolute error of 0.048 m, a maximum absolute error of 0.050 m, and an overall valid detection rate of 99.4% over 358 valid cycles out of 360 scheduled cycles. In addition, a separate range-dependent confined-tubular propagation test was conducted to evaluate the extended detection capability of the RF-synchronized one-way ultrasonic ToF architecture. This test demonstrated stable acoustic-link ToF detection up to 300 m inside the tested 170 mm confined plastic pipeline. Therefore, the 300 m result should be interpreted as a range-dependent valid-detection result rather than as a 12-month groundwater-depth validation over the full 300 m interval. These results demonstrate that the proposed direct-ToF method provides an RF-synchronized one-way ultrasonic ToF framework with a floating receiver for groundwater-level monitoring in deep observation wells, while remaining compatible with low-power and IoT-based environmental monitoring systems. Full article

(This article belongs to the Special Issue Sensor-Based Systems for Environmental Monitoring and Assessment)

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20 pages, 2924 KB

Open AccessArticle

Fabrication and Enhancement of the Gas Sensing Characteristics of Silicon Micropillar NH₃ Sensors Based on MOF-808/rGO Nanocomposites at Room Temperature

by Haoyue Wang, Shaolun Feng, Zhiqiang Fan and Sai Chen

Sensors 2026, 26(10), 3216; https://doi.org/10.3390/s26103216 - 19 May 2026

Viewed by 596

Abstract

This study develops high-performance ammonia sensors based on composites of metal-organic frameworks (MOF-808 and MOF-818) with reduced graphene oxide (rGO). Two sensor architectures were fabricated: interdigital electrodes and silicon micropillar arrays. The MOF-808/rGO composite demonstrated superior sensing performance for 40 ppm NH₃ at room temperature, with faster response kinetics and higher sensitivity compared to pristine rGO and MOF-818/rGO. Silicon micropillar array sensors showed enhanced performance through optimized periodic arrangements, while oxygen plasma surface modification improved both sensor types. Comprehensive testing confirmed that the MOF-808/rGO sensor maintains reliable NH₃ detection at concentrations as low as 5 ppm under high humidity conditions, exhibiting excellent stability and selectivity. These findings provide valuable insights for developing advanced gas sensors for environmental monitoring applications. Full article

(This article belongs to the Special Issue Sensor-Based Systems for Environmental Monitoring and Assessment)

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29 pages, 10271 KB

Open AccessArticle

A Spatiotemporally Coupled Carbon Flux Monitoring System for Salt Marsh Wetlands Based on Integrated Land–Air Collaborative Intelligence

by Yichen Zha, Zeyan Wang and Jianping Shi

Sensors 2026, 26(10), 2966; https://doi.org/10.3390/s26102966 - 8 May 2026

Viewed by 749

Abstract

Against the backdrop of intensifying global climate change, reducing carbon emissions has become a shared global objective. Blue carbon, as a significant carbon sink type, still lacks a mature assessment framework. Monitoring carbon fluxes in marine salt marsh wetlands is a core technology for accurately evaluating blue carbon potential. In response, this study independently developed a spatiotemporally coupled carbon flux monitoring system for marine salt marsh wetlands. The system consists of real-time monitoring equipment, a cloud-based intelligent storage and visualization analysis platform, and a terminal assessment system. It enables the real-time monitoring of carbon fluxes across multiple spatial scales and integrates time-series patterns to assess carbon sequestration potential from multiple dimensions. To address the bottleneck of sensor accuracy, a multi-algorithm fusion technology was innovatively developed, significantly enhancing the accuracy of monitoring data. A modular integrated design was employed to construct a land–air integrated monitoring architecture, which is adaptable to the complex environments of salt marsh wetlands. This facilitates long-term automated monitoring while reducing the need for manual intervention. The terminal assessment system processes spatial-scale data using the DeNitrification-DeComposition model (DNDC 9.5) and integrates time-series carbon flux patterns, enabling precise quantification of marine carbon sink potential through spatiotemporal comprehensive analysis. The system first completed performance verification during the experimental phase, acquiring a total of 5760 sets of valid monitoring data, with a data qualification rate of 99.72%. The proposed multi-algorithm fusion method kept monitoring data fluctuations within 0.5%, and the relative error of the spatiotemporal integrated prediction was as low as 0.31%, thereby ensuring the stability and accuracy of long-term in situ monitoring. Based on this, a one-year field validation was conducted in a 100-hectare coastal salt marsh wetland in Dafeng, Yancheng. Using a spatiotemporal coupling assessment, the annual total carbon sequestration of this area was estimated at 1498.4 tons of carbon, with an assessment error of only 5.1%, achieving precise quantification of the blue carbon sink in the salt marsh wetland. This study provides reliable technical support for evaluating the carbon sequestration capacity of coastal salt marsh wetlands, contributing to the implementation of carbon emission reduction strategies. It also offers a scientific basis for global carbon cycle research and carbon sink management decision-making. Full article

(This article belongs to the Special Issue Sensor-Based Systems for Environmental Monitoring and Assessment)

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24 pages, 15270 KB

Open AccessArticle

The Analysis of Urban Nighttime Light Spatial Heterogeneity and Driving Factors Based on SDGSAT-1 Data

by Jinke Liu, Yiran Zhang, Yifei Zhu, Xuesheng Zhao and Wei Guo

Sensors 2026, 26(7), 2094; https://doi.org/10.3390/s26072094 - 27 Mar 2026

Viewed by 722

Abstract

Artificial light at night (ALAN) data is widely used in urban function analysis and socio-economic activity monitoring, but its application at the micro-scale of cities still faces challenges. This study utilizes high spatial resolution SDGSAT-1 nighttime light data to explore the spatial heterogeneity of ALAN at the street scale in two representative Chinese cities—Beijing and Guangzhou. By integrating multi-source data (such as building vector data, road networks, and point of interest data), a multi-dimensional indicator system covering urban morphology, functional structure, and transportation accessibility is constructed. Based on this, the study employs a Geographically Weighted Random Forest (GWRF) model combined with the Shapley Additive Explanations (SHAP) method to deeply analyze the non-linear relationships between ALAN intensity and multiple driving factors, as well as their spatial variability. Results demonstrate the superiority of the GWRF model over global models in capturing spatial non-stationarity, with R² values of 0.67 for Beijing and 0.74 for Guangzhou, compared to 0.62 and 0.71 for the random forest models, respectively. Road density is the dominant factor influencing nighttime light intensity in both Beijing and Guangzhou. However, the relationship between ALAN and its driving factors varies across these cities. In Beijing, a balanced multi-factor model is observed, whereas in Guangzhou, ALAN intensity is primarily driven by road density, with secondary influences from other factors like sky view factor. This study validates SDGSAT-1 for micro-scale analysis, offering a scientific basis for differentiated urban lighting planning. Full article

(This article belongs to the Special Issue Sensor-Based Systems for Environmental Monitoring and Assessment)

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27 pages, 8315 KB

Open AccessArticle

Calibration and Validation of an Autonomous, Novel, Low-Cost, Dynamic Flux Chamber for Measuring Landfill Methane Emissions

by Avery G. Brown, Nikona G. Rousseau, Dylan Doskocil, Cullen T. O’Neill, Seth G. VanMatre, Justin J. Kane, Joanna G. Casey, Michael P. Hannigan and Evan R. Coffey

Sensors 2025, 25(21), 6613; https://doi.org/10.3390/s25216613 - 28 Oct 2025

Viewed by 2038

Abstract

A low-cost, dynamic flux chamber optimized for landfill emissions measurement was designed, fabricated, calibrated, and validated for measurements of methane flux ranging from 0 to 150 g/m²-day. A centrifugal blower fan and a flow meter were plumbed in series to draw a bypass flow through the flux chamber. Both ambient and chamber methane concentrations were measured using the arrays of four low-cost metal oxide sensors. Leveraging the sensors’ overlapping sensitivity to changes in methane concentration, temperature, and humidity, multiple linear regressions were trained on laboratory data and combined into a piecewise methane calibration function. An algorithm was developed to select the most useful interaction terms among all sensor responses to optimize the predictors in each model. The piecewise regions for methane measurement were 0–100 ppm, 100–1500 ppm, and 1500–12,000 ppm. The root mean squared errors for each piecewise region were 3.1 ppm, 21 ppm, and 307 ppm, respectively. Controlled quantities of methane were delivered to the flux chamber in a laboratory setting for validation. Measurements yielded good agreement with an RMSE and MBE of 7.3 g m⁻² d⁻¹ and 2.2 g m⁻² d⁻¹, respectively. The flux chamber was tested at a closed landfill to validate its ability to autonomously and continuously operate in the field. Full article

(This article belongs to the Special Issue Sensor-Based Systems for Environmental Monitoring and Assessment)

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14 pages, 7774 KB

Open AccessArticle

Temperature Differences Between Rooftop and Urban Canyon Sensors: Diurnal Dynamics, Drivers, and Implications

by Lorenzo Marinelli, Andrea Cecilia, Giampietro Casasanta, Alessandro Conidi, Igor Petenko and Stefania Argentini

Sensors 2025, 25(13), 4121; https://doi.org/10.3390/s25134121 - 2 Jul 2025

Cited by 2 | Viewed by 1417

Abstract

Understanding temperature variations within the complex urban canopy layer (UCL) is challenging due to limitations and discrepancies between temperature measurements taken in urban canyons and on rooftops. The key question is how much these measurements differ and what factors contribute to these differences. According to the guidance by the World Meteorological Organization (WMO), rooftop observations are not encouraged for urban monitoring, due to potentially anomalous microclimatic conditions, whereas measurements within urban canyons are recommended. This is particularly relevant given the increasing number of rooftop sensors deployed through citizen science, raising questions about the representativeness of such data. This study aimed to address this knowledge gap by comparing temperatures within the UCL using two sensors: one located on a rooftop, and the other positioned within the canyon. The temperature difference between these two nearby locations followed a clear diurnal cycle, peaking at over 1 °C between 12:00 and 16:00 local time, with the canyon warmer than the rooftop. This daytime warming was primarily driven by solar radiation and, to a lesser extent, by wind speed, but only under clear-sky conditions. During the rest of the day, the temperature difference remained negligible. Full article

(This article belongs to the Special Issue Sensor-Based Systems for Environmental Monitoring and Assessment)

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Review

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30 pages, 3739 KB

Open AccessReview

Molecular Imprinting Polymer-Based Sensing of Neonicotinoids

by Jelena Golijanin, Diane Hyewoo Lee, Riley Y. Li and Soha Ahmadi

Sensors 2025, 25(23), 7251; https://doi.org/10.3390/s25237251 - 27 Nov 2025

Cited by 2 | Viewed by 1425

Abstract

Neonicotinoids are a novel class of insecticides that exhibit environmental persistence and off-target effects on both humans and ecosystems. Therefore, there is a need for sensitive and selective sensors to monitor concentrations of neonicotinoids in environmental water and soil systems. Molecularly imprinted polymer (MIP)-based sensors are an emerging technology with strong potential for reliable, sensitive, and selective detection of neonicotinoids. Moreover, MIPs are versatile and compatible with a wide range of analytical techniques, which can further enhance measurement capabilities in the development of practical and robust sensors. Despite this promise, many routes remain underexplored for neonicotinoid detection. This review reports on the current state of neonicotinoid chemical sensors and detection methods using MIPs and highlights potential applications of MIP-based approaches as cost-effective and easy-to-operate solutions for monitoring neonicotinoids. Recent sensors incorporating MIPs and electrochemical or optical techniques for neonicotinoid detection are described and compared. Approaches employing magnetic solid-phase extraction and quartz crystal microbalance are also discussed. Additionally, the influence of monomer choice for MIP synthesis, as well as the use of additives and nanomaterials for sensor construction and analyte detection, is reviewed. These methods may promote sustainability, reusability, ratiometric or simultaneous detection of neonicotinoids, and sensor portability for on-site monitoring. Full article

(This article belongs to the Special Issue Sensor-Based Systems for Environmental Monitoring and Assessment)

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