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Special Issue "Sensors for Environmental Monitoring 2016"

A special issue of Sensors (ISSN 1424-8220).

Deadline for manuscript submissions: closed (15 November 2016)

Special Issue Editor

Guest Editor
Prof. Dr. Russell Binions

School of Engineering and Materials Science, Queen Mary University of London, Mile End Road, London E1 4NS, UK
Website | E-Mail
Interests: chemical vapour deposition; functional metal oxide films; metal oxide semiconductor; gas sensors; chromogenic materials; photocatalysis; nanocomposite thin films

Special Issue Information

Dear Colleagues,

The ability to sense chemical vapours is of increasing importance in a highly technological world. Sensing in environmental monitoring is particularly important as the effects of climate change become more apparent. As such there is an increasing push for more sensitive, selective and stable sensors, particularly those that can work in remote, isolated, and sometimes-harsh conditions. This Special Issue on environmental monitoring seeks to bring together industrialists and academics working in this area to publish the latest and highest impact results.

Manuscripts from all areas of environmental sensing technology are welcome, including, but not limited to:

  • Optical sensors
  • electrochemical sensors
  • metal oxide semiconductor sensors
  • carbon materials based sensors
  • sensor networks
  • data processing and visualisation

All aspects of environmental sensing are to be included from novel materials synthesis, sensor device preparation and processing, and chemical sensor device performance, data processing and visualisation.

Dr. Russell Binions
Guest Editor

Manuscript Submission Information

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Keywords

  • Chemical Sensors
  • Environmental Monitoring

Published Papers (15 papers)

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Research

Open AccessArticle Integrating Statistical Machine Learning in a Semantic Sensor Web for Proactive Monitoring and Control
Sensors 2017, 17(4), 807; doi:10.3390/s17040807
Received: 1 November 2016 / Revised: 11 January 2017 / Accepted: 24 January 2017 / Published: 9 April 2017
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Abstract
Proactive monitoring and control of our natural and built environments is important in various application scenarios. Semantic Sensor Web technologies have been well researched and used for environmental monitoring applications to expose sensor data for analysis in order to provide responsive actions in
[...] Read more.
Proactive monitoring and control of our natural and built environments is important in various application scenarios. Semantic Sensor Web technologies have been well researched and used for environmental monitoring applications to expose sensor data for analysis in order to provide responsive actions in situations of interest. While these applications provide quick response to situations, to minimize their unwanted effects, research efforts are still necessary to provide techniques that can anticipate the future to support proactive control, such that unwanted situations can be averted altogether. This study integrates a statistical machine learning based predictive model in a Semantic Sensor Web using stream reasoning. The approach is evaluated in an indoor air quality monitoring case study. A sliding window approach that employs the Multilayer Perceptron model to predict short term PM 2 . 5 pollution situations is integrated into the proactive monitoring and control framework. Results show that the proposed approach can effectively predict short term PM 2 . 5 pollution situations: precision of up to 0.86 and sensitivity of up to 0.85 is achieved over half hour prediction horizons, making it possible for the system to warn occupants or even to autonomously avert the predicted pollution situations within the context of Semantic Sensor Web. Full article
(This article belongs to the Special Issue Sensors for Environmental Monitoring 2016)
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Open AccessArticle A Networked Sensor System for the Analysis of Plot-Scale Hydrology
Sensors 2017, 17(3), 636; doi:10.3390/s17030636
Received: 18 November 2016 / Revised: 6 March 2017 / Accepted: 10 March 2017 / Published: 20 March 2017
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Abstract
This study presents the latest updates to the Audubon Society of Western Pennsylvania (ASWP) testbed, a $50,000 USD, 104-node outdoor multi-hop wireless sensor network (WSN). The network collects environmental data from over 240 sensors, including the EC-5, MPS-1 and MPS-2 soil moisture and
[...] Read more.
This study presents the latest updates to the Audubon Society of Western Pennsylvania (ASWP) testbed, a $50,000 USD, 104-node outdoor multi-hop wireless sensor network (WSN). The network collects environmental data from over 240 sensors, including the EC-5, MPS-1 and MPS-2 soil moisture and soil water potential sensors and self-made sap flow sensors, across a heterogeneous deployment comprised of MICAz, IRIS and TelosB wireless motes. A low-cost sensor board and software driver was developed for communicating with the analog and digital sensors. Innovative techniques (e.g., balanced energy efficient routing and heterogeneous over-the-air mote reprogramming) maintained high success rates (>96%) and enabled effective software updating, throughout the large-scale heterogeneous WSN. The edaphic properties monitored by the network showed strong agreement with data logger measurements and were fitted to pedotransfer functions for estimating local soil hydraulic properties. Furthermore, sap flow measurements, scaled to tree stand transpiration, were found to be at or below potential evapotranspiration estimates. While outdoor WSNs still present numerous challenges, the ASWP testbed proves to be an effective and (relatively) low-cost environmental monitoring solution and represents a step towards developing a platform for monitoring and quantifying statistically relevant environmental parameters from large-scale network deployments. Full article
(This article belongs to the Special Issue Sensors for Environmental Monitoring 2016)
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Open AccessArticle Online Classification of Contaminants Based on Multi-Classification Support Vector Machine Using Conventional Water Quality Sensors
Sensors 2017, 17(3), 581; doi:10.3390/s17030581
Received: 9 December 2016 / Revised: 14 February 2017 / Accepted: 9 March 2017 / Published: 13 March 2017
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Abstract
Water quality early warning system is mainly used to detect deliberate or accidental water pollution events in water distribution systems. Identifying the types of pollutants is necessary after detecting the presence of pollutants to provide warning information about pollutant characteristics and emergency solutions.
[...] Read more.
Water quality early warning system is mainly used to detect deliberate or accidental water pollution events in water distribution systems. Identifying the types of pollutants is necessary after detecting the presence of pollutants to provide warning information about pollutant characteristics and emergency solutions. Thus, a real-time contaminant classification methodology, which uses the multi-classification support vector machine (SVM), is proposed in this study to obtain the probability for contaminants belonging to a category. The SVM-based model selected samples with indistinct feature, which were mostly low-concentration samples as the support vectors, thereby reducing the influence of the concentration of contaminants in the building process of a pattern library. The new sample points were classified into corresponding regions after constructing the classification boundaries with the support vector. Experimental results show that the multi-classification SVM-based approach is less affected by the concentration of contaminants when establishing a pattern library compared with the cosine distance classification method. Moreover, the proposed approach avoids making a single decision when classification features are unclear in the initial phase of injecting contaminants. Full article
(This article belongs to the Special Issue Sensors for Environmental Monitoring 2016)
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Open AccessArticle PHYLIS: A Low-Cost Portable Visible Range Spectrometer for Soil and Plants
Sensors 2017, 17(1), 99; doi:10.3390/s17010099
Received: 12 November 2016 / Revised: 30 December 2016 / Accepted: 4 January 2017 / Published: 7 January 2017
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Abstract
Monitoring soil and crop condition is vital for the sustainable management of agricultural systems. Often, land management decision-making requires rapid assessment of conditions, which is difficult if samples need to be taken and sent elsewhere for analysis. In recent years, advances in field-based
[...] Read more.
Monitoring soil and crop condition is vital for the sustainable management of agricultural systems. Often, land management decision-making requires rapid assessment of conditions, which is difficult if samples need to be taken and sent elsewhere for analysis. In recent years, advances in field-based spectroscopy have led to improvements in real-time monitoring; however, the cost of equipment and user training still makes it inaccessible for most land managers. At the James Hutton Institute, we have developed a low-cost visible wavelength hyperspectral device intended to provide rapid field-based assessment of soil and plant conditions. This device has been tested at the Institute’s research farm at Balruddery, linking field observations with existing sample analysis and crop type information. We show that it is possible to rapidly and easily acquire spectral information that enables site characteristics to be estimated. Improvements to the sensor and its potential uses are discussed. Full article
(This article belongs to the Special Issue Sensors for Environmental Monitoring 2016)
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Open AccessArticle Development and Application of a Synthetically-Derived Lead Biosensor Construct for Use in Gram-Negative Bacteria
Sensors 2016, 16(12), 2174; doi:10.3390/s16122174
Received: 10 November 2016 / Revised: 9 December 2016 / Accepted: 13 December 2016 / Published: 18 December 2016
Cited by 2 | PDF Full-text (2213 KB) | HTML Full-text | XML Full-text
Abstract
The use of lead in manufacturing has decreased significantly over the last few decades. However, previous widespread use of lead-containing products and their incorrect disposal has resulted in environmental contamination. Accumulation of harmful quantities of lead pose a threat to all living organisms,
[...] Read more.
The use of lead in manufacturing has decreased significantly over the last few decades. However, previous widespread use of lead-containing products and their incorrect disposal has resulted in environmental contamination. Accumulation of harmful quantities of lead pose a threat to all living organisms, through inhalation, ingestion, or direct contact, resulting in lead poisoning. This study utilized synthetic biology principles to develop plasmid-based whole-cell bacterial biosensors for detection of lead. The genetic element of the lead biosensor construct consists of pbrR, which encodes the regulatory protein, together with its divergent promoter region and a promoterless gfp. GFP expression is controlled by PbrR in response to the presence of lead. The lead biosensor genetic element was cloned onto a low-copy number broad host range plasmid, which can stably exist in a range of laboratory and environmental isolates, including Pseudomonas, Shewanella, and Enterobacter. The biosensors constructed were found to be sensitive, rapid, and specific and could, as such, serve as monitoring tools for lead-contaminated water. Full article
(This article belongs to the Special Issue Sensors for Environmental Monitoring 2016)
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Open AccessArticle Comparing ∆Tmax Determination Approaches for Granier-Based Sapflow Estimations
Sensors 2016, 16(12), 2042; doi:10.3390/s16122042
Received: 19 October 2016 / Revised: 22 November 2016 / Accepted: 28 November 2016 / Published: 1 December 2016
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Abstract
Granier-type thermal dissipation probes are common instruments for quantifying tree water use in forest hydrological studies. Estimating sapflow using Granier-type sapflow sensors requires determining the maximum temperature gradient (∆Tmax) between the heated probe and the reference probe below. ∆Tmax represents
[...] Read more.
Granier-type thermal dissipation probes are common instruments for quantifying tree water use in forest hydrological studies. Estimating sapflow using Granier-type sapflow sensors requires determining the maximum temperature gradient (∆Tmax) between the heated probe and the reference probe below. ∆Tmax represents a state of zero sap flux, which was originally assumed to occur each night leading to a ∆Tmax determination on a daily basis. However, researchers have proven that, under certain conditions, sapflow may continue throughout the night. Therefore alternative approaches to determining ∆Tmax have been developed. Multiple ∆Tmax approaches are now in use; however, sapflow estimates remain imprecise because the empirical equation that transfers the raw temperature signal (∆T) to sap flux density (Fd) is strongly sensitive to ∆Tmax. In this study, we analyze the effects of different ∆Tmax determination approaches on sub-daily, daily and (intra-)seasonal Fd estimations. On this basis, we quantify the uncertainty of sapflow calculations, which is related to the raw signal processing. We show that the ∆Tmax determination procedure has a major influence on absolute ∆Tmax values and the respective sap flux density computations. Consequently, the choice of the ∆Tmax determination approach may be a significant source of uncertainty in sapflow estimations. Full article
(This article belongs to the Special Issue Sensors for Environmental Monitoring 2016)
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Open AccessArticle Quencher-Free Fluorescence Method for the Detection of Mercury(II) Based on Polymerase-Aided Photoinduced Electron Transfer Strategy
Sensors 2016, 16(11), 1945; doi:10.3390/s16111945
Received: 16 October 2016 / Revised: 10 November 2016 / Accepted: 15 November 2016 / Published: 18 November 2016
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Abstract
A new quencher-free Hg2+ ion assay method was developed based on polymerase-assisted photoinduced electron transfer (PIET). In this approach, a probe is designed with a mercury ion recognition sequence (MRS) that is composed of two T-rich functional areas separated by a spacer
[...] Read more.
A new quencher-free Hg2+ ion assay method was developed based on polymerase-assisted photoinduced electron transfer (PIET). In this approach, a probe is designed with a mercury ion recognition sequence (MRS) that is composed of two T-rich functional areas separated by a spacer of random bases at the 3′-end, and a sequence of stacked cytosines at the 5′-end, to which a fluorescein (FAM) is attached. Upon addition of Hg2+ ions into this sensing system, the MRS folds into a hairpin structure at the 3′-end with Hg2+-mediated base pairs. In the presence of DNA polymerase, it will catalyze the extension reaction, resulting in the formation of stacked guanines, which will instantly quench the fluorescence of FAM through PIET. Under optimal conditions, the limit of detection for Hg2+ ions was estimated to be 5 nM which is higher than the US Environmental Protection Agency (EPA) standard limit. In addition, no labeling with a quencher was requiring, and the present method is fairly simple, fast and low cost. It is expected that this cost-effective fluorescence method might hold considerable potential in the detection of Hg2+ ions in real biological and environmental samples. Full article
(This article belongs to the Special Issue Sensors for Environmental Monitoring 2016)
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Open AccessArticle In-Field, In Situ, and In Vivo 3-Dimensional Elemental Mapping for Plant Tissue and Soil Analysis Using Laser-Induced Breakdown Spectroscopy
Sensors 2016, 16(10), 1764; doi:10.3390/s16101764
Received: 28 July 2016 / Revised: 14 October 2016 / Accepted: 19 October 2016 / Published: 22 October 2016
PDF Full-text (3634 KB) | HTML Full-text | XML Full-text
Abstract
Sensing and mapping element distributions in plant tissues and its growth environment has great significance for understanding the uptake, transport, and accumulation of nutrients and harmful elements in plants, as well as for understanding interactions between plants and the environment. In this study,
[...] Read more.
Sensing and mapping element distributions in plant tissues and its growth environment has great significance for understanding the uptake, transport, and accumulation of nutrients and harmful elements in plants, as well as for understanding interactions between plants and the environment. In this study, we developed a 3-dimensional elemental mapping system based on laser-induced breakdown spectroscopy that can be deployed in- field to directly measure the distribution of multiple elements in living plants as well as in the soil. Mapping is performed by a fast scanning laser, which ablates a micro volume of a sample to form a plasma. The presence and concentration of specific elements are calculated using the atomic, ionic, and molecular spectral characteristics of the plasma emission spectra. Furthermore, we mapped the pesticide residues in maize leaves after spraying to demonstrate the capacity of this method for trace elemental mapping. We also used the system to quantitatively detect the element concentrations in soil, which can be used to further understand the element transport between plants and soil. We demonstrate that this method has great potential for elemental mapping in plant tissues and soil with the advantages of 3-dimensional and multi-elemental mapping, in situ and in vivo measurement, flexible use, and low cost. Full article
(This article belongs to the Special Issue Sensors for Environmental Monitoring 2016)
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Open AccessArticle Methodological Comparison between a Novel Automatic Sampling System for Gas Chromatography versus Photoacoustic Spectroscopy for Measuring Greenhouse Gas Emissions under Field Conditions
Sensors 2016, 16(10), 1638; doi:10.3390/s16101638
Received: 18 August 2016 / Accepted: 29 September 2016 / Published: 3 October 2016
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Abstract
Trace gases such as nitrous oxide (N2O), methane (CH4), and carbon dioxide (CO2) are climate-related gases, and their emissions from agricultural livestock barns are not negligible. Conventional measurement systems in the field (Fourier transform infrared spectroscopy (FTIR); photoacoustic system (PAS)) are not sufficiently
[...] Read more.
Trace gases such as nitrous oxide (N2O), methane (CH4), and carbon dioxide (CO2) are climate-related gases, and their emissions from agricultural livestock barns are not negligible. Conventional measurement systems in the field (Fourier transform infrared spectroscopy (FTIR); photoacoustic system (PAS)) are not sufficiently sensitive to N2O. Laser-based measurement systems are highly accurate, but they are very expensive to purchase and maintain. One cost-effective alternative is gas chromatography (GC) with electron capture detection (ECD), but this is not suitable for field applications due to radiation. Measuring samples collected automatically under field conditions in the laboratory at a subsequent time presents many challenges. This study presents a sampling designed to promote laboratory analysis of N2O concentrations sampled under field conditions. Analyses were carried out using PAS in the field (online system) and GC in the laboratory (offline system). Both measurement systems showed a good correlation for CH4 and CO2 concentrations. Measured N2O concentrations were near the detection limit for PAS. GC achieved more reliable results for N2O in very low concentration ranges. Full article
(This article belongs to the Special Issue Sensors for Environmental Monitoring 2016)
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Open AccessArticle Optimization of Stripping Voltammetric Sensor by a Back Propagation Artificial Neural Network for the Accurate Determination of Pb(II) in the Presence of Cd(II)
Sensors 2016, 16(9), 1540; doi:10.3390/s16091540
Received: 29 July 2016 / Revised: 29 August 2016 / Accepted: 7 September 2016 / Published: 21 September 2016
Cited by 1 | PDF Full-text (3411 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
An easy, but effective, method has been proposed to detect and quantify the Pb(II) in the presence of Cd(II) based on a Bi/glassy carbon electrode (Bi/GCE) with the combination of a back propagation artificial neural network (BP-ANN) and square wave anodic stripping voltammetry
[...] Read more.
An easy, but effective, method has been proposed to detect and quantify the Pb(II) in the presence of Cd(II) based on a Bi/glassy carbon electrode (Bi/GCE) with the combination of a back propagation artificial neural network (BP-ANN) and square wave anodic stripping voltammetry (SWASV) without further electrode modification. The effects of Cd(II) in different concentrations on stripping responses of Pb(II) was studied. The results indicate that the presence of Cd(II) will reduce the prediction precision of a direct calibration model. Therefore, a two-input and one-output BP-ANN was built for the optimization of a stripping voltammetric sensor, which considering the combined effects of Cd(II) and Pb(II) on the SWASV detection of Pb(II) and establishing the nonlinear relationship between the stripping peak currents of Pb(II) and Cd(II) and the concentration of Pb(II). The key parameters of the BP-ANN and the factors affecting the SWASV detection of Pb(II) were optimized. The prediction performance of direct calibration model and BP-ANN model were tested with regard to the mean absolute error (MAE), root mean square error (RMSE), average relative error (ARE), and correlation coefficient. The results proved that the BP-ANN model exhibited higher prediction accuracy than the direct calibration model. Finally, a real samples analysis was performed to determine trace Pb(II) in some soil specimens with satisfactory results. Full article
(This article belongs to the Special Issue Sensors for Environmental Monitoring 2016)
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Open AccessArticle Diurnal Variability in Chlorophyll-a, Carotenoids, CDOM and SO42− Intensity of Offshore Seawater Detected by an Underwater Fluorescence-Raman Spectral System
Sensors 2016, 16(7), 1082; doi:10.3390/s16071082
Received: 29 April 2016 / Revised: 15 June 2016 / Accepted: 30 June 2016 / Published: 13 July 2016
Cited by 1 | PDF Full-text (2331 KB) | HTML Full-text | XML Full-text
Abstract
A newly developed integrated fluorescence-Raman spectral system (λex = 532 nm) for detecting Chlorophyll-a (chl-a), Chromophoric Dissolved Organic Matter (CDOM), carotenoids and SO42− in situ was used to successfully investigate the diurnal variability of all above. Simultaneously using the integration
[...] Read more.
A newly developed integrated fluorescence-Raman spectral system (λex = 532 nm) for detecting Chlorophyll-a (chl-a), Chromophoric Dissolved Organic Matter (CDOM), carotenoids and SO42− in situ was used to successfully investigate the diurnal variability of all above. Simultaneously using the integration of fluorescence spectroscopy and Raman spectroscopy techniques provided comprehensive marine information due to the complementarity between the different excitation mechanisms and different selection rules. The investigation took place in offshore seawater of the Yellow Sea (36°05′40′′ N, 120°31′32′′ E) in October 2014. To detect chl-a, CDOM, carotenoids and SO42−, the fluorescence-Raman spectral system was deployed. It was found that troughs of chl-a and CDOM fluorescence signal intensity were observed during high tides, while the signal intensity showed high values with larger fluctuations during ebb-tide. Chl-a and carotenoids were influenced by solar radiation within a day cycle by different detection techniques, as well as displaying similar and synchronous tendency. CDOM fluorescence cause interference to the measurement of SO42−. To avoid such interference, the backup Raman spectroscopy system with λex = 785 nm was employed to detect SO42− concentration on the following day. The results demonstrated that the fluorescence-Raman spectral system has great potential in detection of chl-a, carotenoids, CDOM and SO42− in the ocean. Full article
(This article belongs to the Special Issue Sensors for Environmental Monitoring 2016)
Open AccessArticle Methods and Best Practice to Intercompare Dissolved Oxygen Sensors and Fluorometers/Turbidimeters for Oceanographic Applications
Sensors 2016, 16(5), 702; doi:10.3390/s16050702
Received: 1 March 2016 / Revised: 23 April 2016 / Accepted: 6 May 2016 / Published: 17 May 2016
PDF Full-text (7781 KB) | HTML Full-text | XML Full-text
Abstract
In European seas, ocean monitoring strategies in terms of key parameters, space and time scale vary widely for a range of technical and economic reasons. Nonetheless, the growing interest in the ocean interior promotes the investigation of processes such as oxygen consumption, primary
[...] Read more.
In European seas, ocean monitoring strategies in terms of key parameters, space and time scale vary widely for a range of technical and economic reasons. Nonetheless, the growing interest in the ocean interior promotes the investigation of processes such as oxygen consumption, primary productivity and ocean acidity requiring that close attention is paid to the instruments in terms of measurement setup, configuration, calibration, maintenance procedures and quality assessment. To this aim, two separate hardware and software tools were developed in order to test and simultaneously intercompare several oxygen probes and fluorometers/turbidimeters, respectively in the same environmental conditions, with a configuration as close as possible to real in-situ deployment. The chamber designed to perform chlorophyll-a and turbidity tests allowed for the simultaneous acquisition of analogue and digital signals of several sensors at the same time, so it was sufficiently compact to be used in both laboratory and onboard vessels. Methodologies and best practice committed to the intercomparison of dissolved oxygen sensors and fluorometers/turbidimeters have been used, which aid in the promotion of interoperability to access key infrastructures, such as ocean observatories and calibration facilities. Results from laboratory tests as well as field tests in the Mediterranean Sea are presented. Full article
(This article belongs to the Special Issue Sensors for Environmental Monitoring 2016)
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Open AccessArticle A Mobile and Low-Cost System for Environmental Monitoring: A Case Study
Sensors 2016, 16(5), 710; doi:10.3390/s16050710
Received: 8 February 2016 / Revised: 9 May 2016 / Accepted: 10 May 2016 / Published: 17 May 2016
Cited by 3 | PDF Full-text (15406 KB) | HTML Full-text | XML Full-text
Abstract
Northern Italy has one of the highest air pollution levels in the European Union. This paper describes a mobile wireless sensor network system intended to complement the already existing official air quality monitoring systems of the metropolitan town of Torino. The system is
[...] Read more.
Northern Italy has one of the highest air pollution levels in the European Union. This paper describes a mobile wireless sensor network system intended to complement the already existing official air quality monitoring systems of the metropolitan town of Torino. The system is characterized by a high portability and low cost, in both acquisition and maintenance. The high portability of the system aims to improve the spatial distribution and resolution of the measurements from the official static monitoring stations. Commercial PM 10 and O 3 sensors were incorporated into the system and were subsequently tested in a controlled environment and in the field. The test in the field, performed in collaboration with the local environmental agency, revealed that the sensors can provide accurate data if properly calibrated and maintained. Further tests were carried out by mounting the system on bicycles in order to increase their mobility. Full article
(This article belongs to the Special Issue Sensors for Environmental Monitoring 2016)
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Open AccessArticle In Situ Representation of Soil/Sediment Conductivity Using Electrochemical Impedance Spectroscopy
Sensors 2016, 16(5), 625; doi:10.3390/s16050625
Received: 14 February 2016 / Revised: 26 March 2016 / Accepted: 9 April 2016 / Published: 30 April 2016
Cited by 1 | PDF Full-text (1265 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
The electrical conductivity (EC) of soil is generally measured after soil extraction, so this method cannot represent the in situ EC of soil (e.g., EC of soils with different moisture contents) and therefore lacks comparability in some cases. Using a resistance measurement apparatus
[...] Read more.
The electrical conductivity (EC) of soil is generally measured after soil extraction, so this method cannot represent the in situ EC of soil (e.g., EC of soils with different moisture contents) and therefore lacks comparability in some cases. Using a resistance measurement apparatus converted from a configuration of soil microbial fuel cell, the in situ soil EC was evaluated according to the Ohmic resistance (Rs) measured using electrochemical impedance spectroscopy. The EC of soils with moisture content from 9.1% to 37.5% was calculated according to Rs. A significant positive correlation (R2 = 0.896, p < 0.01) between the soil EC and the moisture content was observed, which demonstrated the feasibility of the approach. This new method can not only represent the actual soil EC, but also does not need any pretreatment. Thus it may be used widely in the measurement of the EC for soils and sediments. Full article
(This article belongs to the Special Issue Sensors for Environmental Monitoring 2016)
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Open AccessArticle Poly(3-Methylthiophene) Thin Films Deposited Electrochemically on QCMs for the Sensing of Volatile Organic Compounds
Sensors 2016, 16(4), 423; doi:10.3390/s16040423
Received: 8 February 2016 / Revised: 16 March 2016 / Accepted: 18 March 2016 / Published: 23 March 2016
Cited by 4 | PDF Full-text (5313 KB) | HTML Full-text | XML Full-text
Abstract
Poly(3-methylthiophene) (PMeT) thin films were electrochemically deposited on quartz crystal microbalance QCM transducers to investigate their volatile organic compound (VOC) sensing properties depending on ambient conditions. Twelve different VOCs including alcohols, ketones, chlorinated compounds, amines, and the organosphosphate dimethyl methylphosphonate (DMMP) were used
[...] Read more.
Poly(3-methylthiophene) (PMeT) thin films were electrochemically deposited on quartz crystal microbalance QCM transducers to investigate their volatile organic compound (VOC) sensing properties depending on ambient conditions. Twelve different VOCs including alcohols, ketones, chlorinated compounds, amines, and the organosphosphate dimethyl methylphosphonate (DMMP) were used as analytes. The responses of the chemical sensors against DMMP were the highest among the tested analytes; thus, fabricated chemical sensors based on PMeT can be evaluated as potential candidates for selectively detecting DMMP. Generally, detection limits in the low ppm range could be achieved. The gas sensing measurements were recorded at various humid air conditions to investigate the effects of the humidity on the gas sensing properties. The sensing performance of the chemical sensors was slightly reduced in the presence of humidity in ambient conditions. While a decrease in sensitivity was observed for humidity levels up to 50% r.h., the sensitivity was nearly unaffected for higher humidity levels and a reliable detection of the VOCs and DMMP was possible with detection limits in the low ppm range. Full article
(This article belongs to the Special Issue Sensors for Environmental Monitoring 2016)

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