Sensors

Research

Jump to: Review

20 pages, 9151 KB

Open AccessArticle

Detecting Wildfire Smoke Onset from Fixed View Camera Networks

by Shakhnoza Muksimova and Sabina Umirzakova

Sensors 2026, 26(19), 6020; https://doi.org/10.3390/s26196020 - 23 Sep 2026

(1) Background: A wildfire smoke detector’s practical worth is counted in minutes, not percentage points: an alarm raised ten minutes after ignition is worth far less than one raised at two, whatever the two systems’ frame-level scores suggest. Time to detection, however, is [...] Read more.

(1) Background: A wildfire smoke detector’s practical worth is counted in minutes, not percentage points: an alarm raised ten minutes after ignition is worth far less than one raised at two, whatever the two systems’ frame-level scores suggest. Time to detection, however, is almost always computed after training rather than optimized during it. (2) Methods: We treat incipient smoke not as an object to be recognized but as an onset to be caught: a faint, spatially coherent structure that thickens monotonically. At the same time, the rest of the scene continues behaving as it always has. The proposed study learns that habitual behavior from unlabeled fire-free video, surfaces departures from it as a per-tile prediction residual, and reads those residuals through an emergence field of four inspectable cues: residual magnitude, opacity accretion, motion coherence, and temporal persistence. Each common distractor fails a different cue, and detection delay and false alarms directly contribute to the loss. (3) Results: On FIgLib, the proposed study raises its first alarm 1.52 min after ignition while holding 0.21 false alarms per camera-day, and carries over to PyroNear-2025 and SKLFS-WildFire without labels from either. (4) Conclusions: Treating earliness as an optimization target rather than a reporting statistic yields detectors that stay both early and quiet on cameras they never saw in training. Full article

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

► Show Figures

Figure 1

44 pages, 35095 KB

Open AccessArticle

Performance Assessment of the Earthview BluBird Continuous Emission Monitoring System for Oil and Gas Facility Emissions Monitoring

by James Maslanik, Kevin Yoon and Frederick Givhan

Sensors 2026, 26(18), 5946; https://doi.org/10.3390/s26185946 - 20 Sep 2026

Viewed by 168

Abstract

The Earthview BluBird continuous methane emissions monitoring system participated in single-blind controlled-release testing in 2022 and 2024, with the goal of evaluating the leak detection and quantification capabilities of these metal-oxide point sensors under realistic field conditions. The METEC ADED test program consisted [...] Read more.

The Earthview BluBird continuous methane emissions monitoring system participated in single-blind controlled-release testing in 2022 and 2024, with the goal of evaluating the leak detection and quantification capabilities of these metal-oxide point sensors under realistic field conditions. The METEC ADED test program consisted of natural-gas releases (“experiments”) at a simulated gas production facility, with each experiment comprising up to five simultaneous releases from different locations. Here, we analyze the results according to the detection of at least one release per experiment (“per experiment” detection) and the detection of all releases. Using METEC’s standard grading criteria, 91% of ADED 2024 experiments were detected; a substantial improvement compared to the 2022 results. Undetected releases during multi-release experiments, rather than undetected experiments, account for the large majority of missed releases. Detection correlated more strongly with release duration than with release rate. Detection rates and probability of detection improve when alternative classification criteria are applied. Sources were correctly identified at the equipment group level for 75% of single-release experiments. Actual and estimated methane-emission mass summed over daily to monthly intervals correlate significantly, with BluBird underestimating mass by 36% for single-release experiments. This underestimate is dominated by emission rate error rather than release detection capability. Full article

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

► Show Figures

Figure 1

27 pages, 12102 KB

Open AccessArticle

Quantitative Validation of a GNSS Campaign Planning Model for Kinematic Surveys: A Comparison of GPS and GPS/GLONASS Configurations

by Mariusz Specht, Sławomir Figiel and Cezary Specht

Sensors 2026, 26(18), 5864; https://doi.org/10.3390/s26185864 - 16 Sep 2026

Viewed by 134

Abstract

Reliable georeferencing is a fundamental requirement for modern sensor-based environmental monitoring systems employing mobile sensing platforms. This study presents a quantitative validation of a GNSS campaign planning model for kinematic surveys and evaluates how extending a single-constellation GPS configuration to a dual-constellation GPS/GLONASS [...] Read more.

Reliable georeferencing is a fundamental requirement for modern sensor-based environmental monitoring systems employing mobile sensing platforms. This study presents a quantitative validation of a GNSS campaign planning model for kinematic surveys and evaluates how extending a single-constellation GPS configuration to a dual-constellation GPS/GLONASS configuration affects model-observation agreement under real-world conditions. The analysis was based on a kinematic measurement campaign conducted along an 18.4 km route in the Tricity metropolitan area (Gdańsk-Sopot-Gdynia), Poland. Two GNSS receivers operating at 1 Hz were used simultaneously, providing GPS and GPS/GLONASS observations under comparable kinematic and environmental conditions. Model predictions derived from DSM and DTM data were compared with field observations in terms of PDOP, satellite visibility, and model-observation agreement. The results demonstrate that the GPS/GLONASS configuration substantially improved satellite constellation geometry relative to the GPS-only configuration. Mean PDOP values decreased by approximately 30%, while the number of visible satellites increased by 81–86%. More importantly, the GPS/GLONASS configuration improved model-observation agreement. The mean absolute model-observation PDOP difference was reduced by 58.0% for the entire route, 66.7% under favourable observation conditions, and 68.4% under challenging observation conditions. The greatest improvements in model-observation agreement were achieved in dense urban environments affected by signal obstructions. These results demonstrate that constellation configuration influences not only satellite constellation geometry but also the agreement between trajectory-based campaign-planning predictions and real kinematic observations. The proposed methodology may also support the planning of sensor-based environmental monitoring campaigns requiring favourable GNSS observation conditions along measurement trajectories. Full article

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

► Show Figures

Figure 1

32 pages, 53918 KB

Open AccessArticle

MANNA-VISW: A Low-Cost Multimodal Autonomous Platform for Environmental and Ecosystem Recovery Monitoring in Disconnected Post-Disaster Scenarios

by André B. Verona, Hani C. Yehia, Geraldo Wilson Fernandes, Yumi Oki and Linnyer B. R. Aylon

Sensors 2026, 26(17), 5522; https://doi.org/10.3390/s26175522 - 31 Aug 2026

Viewed by 301

Abstract

Monitoring environmental degradation requires robust solutions capable of capturing the complex dynamics of ecosystems. This study presents VISW (Verona Image, Sound, and Weather), a low-cost autonomous platform designed for long-term operation in remote areas, developed with support from the MANNA and LEEB research [...] Read more.

Monitoring environmental degradation requires robust solutions capable of capturing the complex dynamics of ecosystems. This study presents VISW (Verona Image, Sound, and Weather), a low-cost autonomous platform designed for long-term operation in remote areas, developed with support from the MANNA and LEEB research groups. The system employs a multimodal sensing approach, integrating weather data acquisition, multispectral imaging, and environmental acoustic monitoring. VISW was engineered for continuous autonomous operation, incorporating dedicated energy management, data acquisition, and storage subsystems suitable for adverse field conditions. This work was developed in the context of the Fundão dam collapse (2015), one of the largest environmental disasters in Brazil’s history. To monitor biodiversity recovery in the impacted areas, nine VISW Station units were deployed throughout the Doce River basin (Minas Gerais, Brazil). Data collection has been continuously carried out since September 2024, creating a valuable multimodal dataset composed of environmental sounds, multispectral images, and meteorological data from the affected regions. This dataset enables the investigation of complex relationships among vegetation dynamics, climatic patterns, and local soundscapes, providing a comprehensive understanding of ecological processes in areas impacted by disasters. Finally, field tests validated the VISW as a robust, scalable, and cost-effective solution for long-term environmental monitoring. Full article

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

► Show Figures

Figure 1

16 pages, 13257 KB

Open AccessArticle

Calculation of the Increase in Dose Rate Due to Precipitation at the Bilbao Radiological Station of the Basque Country Radiological Surveillance Network

by Natalia Alegría, Miguel Ángel Hernández-Ceballos, Igor Peñalva and Fernando Legarda

Sensors 2026, 26(14), 4560; https://doi.org/10.3390/s26144560 - 18 Jul 2026

Viewed by 387

Abstract

The Radiological Surveillance Network of the Autonomous Community of the Basque Country continuously monitors environmental dose rate levels to detect potential radiological anomalies. However, during rainfall events, increases in dose rate that occasionally exceed predefined alarm thresholds have been observed, despite the absence [...] Read more.

The Radiological Surveillance Network of the Autonomous Community of the Basque Country continuously monitors environmental dose rate levels to detect potential radiological anomalies. However, during rainfall events, increases in dose rate that occasionally exceed predefined alarm thresholds have been observed, despite the absence of radiological incidents. This study presents a predictive model to estimate the increase in dose rate caused by precipitation events at the Bilbao monitoring station. The model accounts for the atmospheric scavenging of radon progeny by raindrops and their subsequent deposition on horizontal surfaces surrounding the detector. Atmospheric transport, radioactive decay, washout processes, and rainwater accumulation dynamics are incorporated into the formulation. The model is implemented numerically using a finite-difference scheme and validated against experimental measurements from the monitoring station. The results (correlation coefficient, BIAS, RMSE) show good agreement between calculated and measured dose rate increases during precipitation episodes, indicating that the observed variations are mainly attributable to the deposition of short-lived radon progeny. Full article

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

► Show Figures

Figure 1

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 780

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 [...] Read more.

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)

► Show Figures

Figure 1

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 373

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 [...] Read more.

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)

► Show Figures

Figure 1

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 582

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 [...] Read more.

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)

► Show Figures

Figure 1

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 817

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 [...] Read more.

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)

► Show Figures

Figure 1

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 880

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 [...] Read more.

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)

► Show Figures

Figure 1

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

Cited by 1 | Viewed by 923

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 [...] Read more.

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)

► Show Figures

Figure 1

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 2302

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 [...] Read more.

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)

► Show Figures

Figure 1

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 1582

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. [...] Read more.

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)

► Show Figures

Figure 1

Review

Jump to: Research

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 3 | Viewed by 1620

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 [...] Read more.

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)

► Show Figures

Figure 1

Journal Menu

Journal Browser

Sensor-Based Systems for Environmental Monitoring and Assessment

Share This Special Issue

Editors

Special Issue Information

Keywords

Benefits of Publishing in a Special Issue

Published Papers (14 papers)

Research

Review

Further Information

Guidelines

MDPI Initiatives

Follow MDPI