scholarly journals Empiric Unsupervised Drifts Correction Method of Electrochemical Sensors for in Field Nitrogen Dioxide Monitoring

Sensors ◽  
2021 ◽  
Vol 21 (11) ◽  
pp. 3581
Author(s):  
Rachid Laref ◽  
Etienne Losson ◽  
Alexandre Sava ◽  
Maryam Siadat
Keyword(s):  
Nitrogen Dioxide ◽  
Electrochemical Sensors ◽  
Low Cost ◽  
Correction Method ◽  
Climatic Conditions ◽  
Estimation Accuracy ◽  
Calibration Model ◽  
Monitoring Networks ◽  
Correction Model ◽  
Almost All

This paper investigates the long term drift phenomenon affecting electrochemical sensors used in real environmental conditions to monitor the nitrogen dioxide concentration [NO2]. Electrochemical sensors are low-cost gas sensors able to detect pollutant gas at part per billion level and may be employed to enhance the air quality monitoring networks. However, they suffer from many forms of drift caused by climatic parameter variations, interfering gases and aging. Therefore, they require frequent, expensive and time-consuming calibrations, which constitute the main obstacle to the exploitation of these kinds of sensors. This paper proposes an empirical, linear and unsupervised drift correction model, allowing to extend the time between two successive full calibrations. First, a calibration model is established based on multiple linear regression. The influence of the air temperature and humidity is considered. Then, a correction model is proposed to solve the drift related to age issue. The slope and the intercept of the correction model compensate the change over time of the sensors’ sensitivity and baseline, respectively. The parameters of the correction model are identified using particle swarm optimization (PSO). Data considered in this work are continuously collected onsite close to a highway crossing Metz City (France) during a period of 6 months (July to December 2018) covering almost all the climatic conditions in this region. Experimental results show that the suggested correction model allows maintaining an adequate [NO2] estimation accuracy for at least 3 consecutive months without needing any labeled data for the recalibration.

Field Nitrogen Dioxide and Ozone Monitoring Using Electrochemical Sensors with Partial Least Squares Regression

2021 ◽  
Vol 5 (1) ◽  
pp. 61
Author(s):  
Rachid Laref ◽  
Etienne Losson ◽  
Alexandre Sava ◽  
Maryam Siadat
Keyword(s):  
Nitrogen Dioxide ◽  
Electrochemical Sensors ◽  
Partial Least Square ◽  
Least Square ◽  
Partial Least Square Regression ◽  
Calibration Model ◽  
Least Squares Regression ◽  
Monitoring Networks ◽  
Concentration Estimation ◽  
The Impact

Low-cost gas sensors detect pollutants gas at the parts-per-billion level and may be installed in small devices to densify air quality monitoring networks for the spread analysis of pollutants around an emissive source. However, these sensors suffer from several issues such as the impact of environmental factors and cross-interfering gases. For instance, the ozone (O3) electrochemical sensor senses nitrogen dioxide (NO2) and O3 simultaneously without discrimination. Alphasense proposes the use of a pair of sensors; the first one, NO2-B43F, is equipped with a filter dedicated to measure NO2. The second one, OX-B431, is sensitive to both NO2 and O3. Thus, O3 concentration can be obtained by subtracting the concentration of NO2 from the sum of the two concentrations. This technique is not practical and requires calibrating each sensor individually, leading to biased concentration estimation. In this paper, we propose Partial Least Square regression (PLS) to build a calibration model including both sensors’ responses and also temperature and humidity variations. The results obtained from data collected in the field for two months show that PLS regression provides better gas concentration estimation in terms of accuracy than calibrating each sensor individually.

scholarly journals Development of a general calibration model and long-term performance evaluation of low-cost sensors for air pollutant gas monitoring

2019 ◽  
Vol 12 (2) ◽  
pp. 903-920 ◽  
Author(s):  
Carl Malings ◽  
Rebecca Tanzer ◽  
Aliaksei Hauryliuk ◽  
Sriniwasa P. N. Kumar ◽  
Naomi Zimmerman ◽  
...  
Keyword(s):  
Electrochemical Sensors ◽  
Low Cost ◽  
Air Pollutant ◽  
Calibration Model ◽  
Linear Regression Models ◽  
Quadratic Regression ◽  
Neural Network Models ◽  
Calibration Models ◽  
New Models

Abstract. Assessing the intracity spatial distribution and temporal variability in air quality can be facilitated by a dense network of monitoring stations. However, the cost of implementing such a network can be prohibitive if traditional high-quality, expensive monitoring systems are used. To this end, the Real-time Affordable Multi-Pollutant (RAMP) monitor has been developed, which can measure up to five gases including the criteria pollutant gases carbon monoxide (CO), nitrogen dioxide (NO2), and ozone (O3), along with temperature and relative humidity. This study compares various algorithms to calibrate the RAMP measurements including linear and quadratic regression, clustering, neural networks, Gaussian processes, and hybrid random forest–linear regression models. Using data collected by almost 70 RAMP monitors over periods ranging up to 18 months, we recommend the use of limited quadratic regression calibration models for CO, neural network models for NO, and hybrid models for NO2 and O3 for any low-cost monitor using electrochemical sensors similar to those of the RAMP. Furthermore, generalized calibration models may be used instead of individual models with only a small reduction in overall performance. Generalized models also transfer better when the RAMP is deployed to other locations. For long-term deployments, it is recommended that model performance be re-evaluated and new models developed periodically, due to the noticeable change in performance over periods of a year or more. This makes generalized calibration models even more useful since only a subset of deployed monitors are needed to build these new models. These results will help guide future efforts in the calibration and use of low-cost sensor systems worldwide.

scholarly journals Long-term behavior and stability of calibration models for NO and NO<sub>2</sub> low cost sensors

2022 ◽  
Author(s):  
Horim Kim ◽  
Michael Müller ◽  
Stephan Henne ◽  
Christoph Hüglin
Keyword(s):  
Electrochemical Sensors ◽  
Low Cost ◽  
Air Pollutant ◽  
Coefficient Of Determination ◽  
Monitoring Networks ◽  
Pollution Levels ◽  
Pollutant Concentrations ◽  
Air Quality Measurements ◽  
One Year

Abstract. Low-cost sensors are considered as exhibiting great potential to complement classical air quality measurements in existing monitoring networks. However, the use of low-cost sensors poses some challenges. In this study, the behavior and performance of electrochemical sensors for NO and NO2 were determined over a longer operating period in a real-world deployment. After careful calibration of the sensors, based on co-location with reference instruments at a rural traffic site during six months and by using robust linear regression and random forest regression, the coefficient of determination of both types of sensors were high (R2 > 0.9) and the root mean square error (RMSE) of NO and NO2 sensors were about 6.8 ppb and 3.5 ppb, respectively, for 10-minute mean concentrations. The RMSE of the NO2 sensors, however, more than doubled, when the sensors were deployed without re-calibration for a one-year period at other site types (including urban background locations), where the range and the variability of air pollutant concentrations differed from the calibration site. This indicates a significant effect of the re-location of the sensors on the quality of their data. During deployment, we found that the NO2 sensors are capable of distinguishing general pollution levels, but they proved unsuitable for accurate measurements, mainly due to significant biases. In order to investigate the long-term stability of the original calibration, the sensors were re-installed at the calibration site after deployment. Surprisingly, the coefficient of determination and the RMSE of the NO sensor remained almost unchanged after more than one year of operation. In contrast, the performance of the NO2 sensors clearly deteriorated as indicated by a higher RMSE (about 7.5 ppb, 10-minute mean concentrations) and a lower coefficient of determination (R2 = 0.59).

scholarly journals Deployment, Calibration, and Cross-Validation of Low-Cost Electrochemical Sensors for Carbon Monoxide, Nitrogen Oxides, and Ozone for an Epidemiological Study

Sensors ◽  
2021 ◽  
Vol 21 (12) ◽  
pp. 4214
Author(s):  
Christopher Zuidema ◽  
Cooper S. Schumacher ◽  
Elena Austin ◽  
Graeme Carvlin ◽  
Timothy V. Larson ◽  
...  
Keyword(s):  
Carbon Monoxide ◽  
Exposure Assessment ◽  
Epidemiological Study ◽  
Electrochemical Sensors ◽  
Low Cost ◽  
Puget Sound ◽  
Ambient Air ◽  
Ambient Air Pollution ◽  
Calibration Models ◽  
Study Participants

We designed and built a network of monitors for ambient air pollution equipped with low-cost gas sensors to be used to supplement regulatory agency monitoring for exposure assessment within a large epidemiological study. This paper describes the development of a series of hourly and daily field calibration models for Alphasense sensors for carbon monoxide (CO; CO-B4), nitric oxide (NO; NO-B4), nitrogen dioxide (NO2; NO2-B43F), and oxidizing gases (OX-B431)—which refers to ozone (O3) and NO2. The monitor network was deployed in the Puget Sound region of Washington, USA, from May 2017 to March 2019. Monitors were rotated throughout the region, including at two Puget Sound Clean Air Agency monitoring sites for calibration purposes, and over 100 residences, including the homes of epidemiological study participants, with the goal of improving long-term pollutant exposure predictions at participant locations. Calibration models improved when accounting for individual sensor performance, ambient temperature and humidity, and concentrations of co-pollutants as measured by other low-cost sensors in the monitors. Predictions from the final daily models for CO and NO performed the best considering agreement with regulatory monitors in cross-validated root-mean-square error (RMSE) and R2 measures (CO: RMSE = 18 ppb, R2 = 0.97; NO: RMSE = 2 ppb, R2 = 0.97). Performance measures for NO2 and O3 were somewhat lower (NO2: RMSE = 3 ppb, R2 = 0.79; O3: RMSE = 4 ppb, R2 = 0.81). These high levels of calibration performance add confidence that low-cost sensor measurements collected at the homes of epidemiological study participants can be integrated into spatiotemporal models of pollutant concentrations, improving exposure assessment for epidemiological inference.

scholarly journals Nanocomposite Materials Based on Electrochemically Synthesized Graphene Polymers: Molecular Architecture Strategies for Sensor Applications

Chemosensors ◽  
2021 ◽  
Vol 9 (6) ◽  
pp. 149
Author(s):  
André Olean-Oliveira ◽  
Gilberto A. Oliveira Brito ◽  
Celso Xavier Cardoso ◽  
Marcos F. S. Teixeira
Keyword(s):  
Conducting Polymers ◽  
Specific Surface ◽  
Surface Area ◽  
Specific Surface Area ◽  
Electrochemical Sensors ◽  
Structural Characteristics ◽  
Low Cost ◽  
Large Specific Surface Area ◽  
Molecular Architecture ◽  
Sensor Applications

The use of graphene and its derivatives in the development of electrochemical sensors has been growing in recent decades. Part of this success is due to the excellent characteristics of such materials, such as good electrical and mechanical properties and a large specific surface area. The formation of composites and nanocomposites with these two materials leads to better sensing performance compared to pure graphene and conductive polymers. The increased large specific surface area of the nanocomposites and the synergistic effect between graphene and conducting polymers is responsible for this interesting result. The most widely used methodologies for the synthesis of these materials are still based on chemical routes. However, electrochemical routes have emerged and are gaining space, affording advantages such as low cost and the promising possibility of modulation of the structural characteristics of composites. As a result, application in sensor devices can lead to increased sensitivity and decreased analysis cost. Thus, this review presents the main aspects for the construction of nanomaterials based on graphene oxide and conducting polymers, as well as the recent efforts made to apply this methodology in the development of sensors and biosensors.

scholarly journals Experiments on Energy-Efficient Evaporative Cooling Systems for Poultry Farm Application in Multan (Pakistan)

2021 ◽  
Vol 13 (5) ◽  
pp. 2836
Author(s):  
Khawar Shahzad ◽  
Muhammad Sultan ◽  
Muhammad Bilal ◽  
Hadeed Ashraf ◽  
Muhammad Farooq ◽  
...  
Keyword(s):  
Heat Stress ◽  
Low Cost ◽  
Evaporative Cooling ◽  
Thermal Exposure ◽  
Climatic Conditions ◽  
The Body ◽  
Dew Point ◽  
Sweat Glands ◽  
Cooling Systems ◽  
Humidity Index

Poultry are one of the most vulnerable species of its kind once the temperature-humidity nexus is explored. This is so because the broilers lack sweat glands as compared to humans and undergo panting process to mitigate their latent heat (moisture produced in the body) in the air. As a result, moisture production inside poultry house needs to be maintained to avoid any serious health and welfare complications. Several strategies such as compressor-based air-conditioning systems have been implemented worldwide to attenuate the heat stress in poultry, but these are not economical. Therefore, this study focuses on the development of low-cost and environmentally friendly improved evaporative cooling systems (DEC, IEC, MEC) from the viewpoint of heat stress in poultry houses. Thermodynamic analysis of these systems was carried out for the climatic conditions of Multan, Pakistan. The results appreciably controlled the environmental conditions which showed that for the months of April, May, and June, the decrease in temperature by direct evaporative cooling (DEC), indirect evaporative cooling (IEC), and Maisotsenko-Cycle evaporative cooling (MEC) systems is 7–10 °C, 5–6.5 °C, and 9.5–12 °C, respectively. In case of July, August, and September, the decrease in temperature by DEC, IEC, and MEC systems is 5.5–7 °C, 3.5–4.5 °C, and 7–7.5 °C, respectively. In addition, drop in temperature-humidity index (THI) values by DEC, IEC, and MEC is 3.5–9 °C, 3–7 °C, and 5.5–10 °C, respectively for all months. Optimum temperature and relative humidity conditions are determined for poultry birds and thereby, systems’ performance is thermodynamically evaluated for poultry farms from the viewpoint of THI, temperature-humidity-velocity index (THVI), and thermal exposure time (ET). From the analysis, it is concluded that MEC system performed relatively better than others due to its ability of dew-point cooling and achieved THI threshold limit with reasonable temperature and humidity indexes.

scholarly journals Molecularly Imprinted Polymers Combined with Electrochemical Sensors for Food Contaminants Analysis

Molecules ◽  
2021 ◽  
Vol 26 (15) ◽  
pp. 4607
Author(s):  
Dounia Elfadil ◽  
Abderrahman Lamaoui ◽  
Flavio Della Pelle ◽  
Aziz Amine ◽  
Dario Compagnone
Keyword(s):  
Food Safety ◽  
Molecularly Imprinted Polymers ◽  
Electrochemical Sensors ◽  
Low Cost ◽  
Electrochemical Analysis ◽  
Ease Of Use ◽  
Electrochemical Sensing ◽  
Food Contaminants ◽  
Molecularly Imprinted ◽  
Imprinted Polymers

Detection of relevant contaminants using screening approaches is a key issue to ensure food safety and respect for the regulatory limits established. Electrochemical sensors present several advantages such as rapidity; ease of use; possibility of on-site analysis and low cost. The lack of selectivity for electrochemical sensors working in complex samples as food may be overcome by coupling them with molecularly imprinted polymers (MIPs). MIPs are synthetic materials that mimic biological receptors and are produced by the polymerization of functional monomers in presence of a target analyte. This paper critically reviews and discusses the recent progress in MIP-based electrochemical sensors for food safety. A brief introduction on MIPs and electrochemical sensors is given; followed by a discussion of the recent achievements for various MIPs-based electrochemical sensors for food contaminants analysis. Both electropolymerization and chemical synthesis of MIP-based electrochemical sensing are discussed as well as the relevant applications of MIPs used in sample preparation and then coupled to electrochemical analysis. Future perspectives and challenges have been eventually given.

scholarly journals Carbon nanomaterial hybrids via laser writing for high-performance non-enzymatic electrochemical sensors: a critical review

2021 ◽  
Author(s):  
Marcel Simsek ◽  
Nongnoot Wongkaew
Keyword(s):  
Noble Metal ◽  
Critical Review ◽  
High Performance ◽  
Carbon Nanomaterials ◽  
Electrochemical Sensors ◽  
Low Cost ◽  
Three Dimensional ◽  
Laser Writing ◽  
Enzyme Mimicking ◽  
Natural Enzyme

AbstractNon-enzymatic electrochemical sensors possess superior stability and affordability in comparison to natural enzyme-based counterparts. A large variety of nanomaterials have been introduced as enzyme mimicking with appreciable sensitivity and detection limit for various analytes of which glucose and H2O2 have been mostly investigated. The nanomaterials made from noble metal, non-noble metal, and metal composites, as well as carbon and their derivatives in various architectures, have been extensively proposed over the past years. Three-dimensional (3D) transducers especially realized from the hybrids of carbon nanomaterials either with metal-based nanocatalysts or heteroatom dopants are favorable owing to low cost, good electrical conductivity, and stability. In this critical review, we evaluate the current strategies to create such nanomaterials to serve as non-enzymatic transducers. Laser writing has emerged as a powerful tool for the next generation of devices owing to their low cost and resultant remarkable performance that are highly attractive to non-enzymatic transducers. So far, only few works have been reported, but in the coming years, more and more research on this topic is foreseeable. Graphical abstract

scholarly journals Contribution of Nanomaterials to the Development of Electrochemical Aptasensors for the Detection of Antimicrobial Residues in Food Products

Chemosensors ◽  
2021 ◽  
Vol 9 (4) ◽  
pp. 69
Author(s):  
Valérie Gaudin
Keyword(s):  
Signal Amplification ◽  
Electrochemical Sensors ◽  
Low Cost ◽  
Food Products ◽  
Animal Origin ◽  
Screening Methods ◽  
Chemical Methods ◽  
Portable Instrumentation ◽  
Physico Chemical ◽  
Antimicrobial Residues

The detection of antimicrobial residues in food products of animal origin is of utmost importance. Indeed antimicrobial residues could be present in animal derived food products because of animal treatments for curative purposes or from illegal use. The usual screening methods to detect antimicrobial residues in food are microbiological, immunological or physico-chemical methods. The development of biosensors to propose sensitive, cheap and quick alternatives to classical methods is constantly increasing. Aptasensors are one of the major trends proposed in the literature, in parallel with the development of immunosensors based on antibodies. The characteristics of electrochemical sensors (i.e., low cost, miniaturization, and portable instrumentation) make them very good candidates to develop screening methods for antimicrobial residues in food products. This review will focus on the recent advances in the development of electrochemical aptasensors for the detection of antimicrobial residues in food products. The contribution of nanomaterials to improve the performance characteristics of electrochemical aptasensors (e.g., Sensitivity, easiness, stability) in the last ten years, as well as signal amplification techniques will be highlighted.

scholarly journals Improving Air Pollutant Metal Oxide Sensor Quantification Practices through: An Exploration of Sensor Signal Normalization, Multi-Sensor and Universal Calibration Model Generation, and Physical Factors Such as Co-Location Duration and Sensor Age

Atmosphere ◽  
2021 ◽  
Vol 12 (5) ◽  
pp. 645
Author(s):  
Kristen Okorn ◽  
Michael Hannigan
Keyword(s):  
Metal Oxide ◽  
Low Cost ◽  
Air Pollutant ◽  
Sensor System ◽  
Physical Factors ◽  
Time Averaging ◽  
Calibration Model ◽  
Sensor Signal ◽  
Metal Oxide Sensors ◽  
Signal Normalization

As low-cost sensors have become ubiquitous in air quality measurements, there is a need for more efficient calibration and quantification practices. Here, we deploy stationary low-cost monitors in Colorado and Southern California near oil and gas facilities, focusing our analysis on methane and ozone concentration measurement using metal oxide sensors. In comparing different sensor signal normalization techniques, we propose a z-scoring standardization approach to normalize all sensor signals, making our calibration results more easily transferable among sensor packages. We also attempt several different physical co-location schemes, and explore several calibration models in which only one sensor system needs to be co-located with a reference instrument, and can be used to calibrate the rest of the fleet of sensor systems. This approach greatly reduces the time and effort involved in field normalization without compromising goodness of fit of the calibration model to a significant extent. We also explore other factors affecting the performance of the sensor system quantification method, including the use of different reference instruments, duration of co-location, time averaging, transferability between different physical environments, and the age of metal oxide sensors. Our focus on methane and stationary monitors, in addition to the z-scoring standardization approach, has broad applications in low-cost sensor calibration and utility.

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