Electrochemical sensors for environmental gas analysis

Williams, David E.

doi:10.1016/j.coelec.2020.06.006

Cited by 53 publications

(33 citation statements)

References 69 publications

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“…E lectrochemical sensors for environmental gas analysis, 1 widely used for many years for industrial health and safety monitoring, 2 have proven to be reliable and robust for measurement at concentrations that approach a short-term hazard to human healthscale parts-per-million (1:10 6 ) by volume (ppm). In recent years, the same devices have been explored and then marketed for the measurement of critical pollutant gases at concentrations found in the open atmosphere, typically in urban environments.…”

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confidence: 99%

“…6 There are two particular effects that strongly influence the reliability of atmospheric pollutant concentration data derived from electrochemical gas sensors. 1 The first is a largeamplitude noise that is observed on exposure in the atmosphere, with a frequency greater than about 0.01 Hz. This noise signal (±10−20 ppb equivalent) is significant in comparison with the desired pollutant concentration signal (see Figure 2).…”

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confidence: 99%

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Understanding and Correcting Unwanted Influences on the Signal from Electrochemical Gas Sensors

Farquhar¹,

Henshaw²,

Williams

2021

ACS Sens.

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Humidity- and temperature-dependent errors in concentrations reported by electrochemical sensors for atmospheric nitrogen dioxide significantly limit the reliability of the data. A basic understanding of the source of these errors has been missing. Empirical, software-based corrections are of limited reliability. The sensors feature a 40 wt % (≈4 molal) sulfuric acid electrolyte, and carbon working and quasi-reference (QRE) electrodes. We show that the sensor behaves as a truncated transmission line with resistance and capacitance elements varying with humidity. High-amplitude current fluctuations are due to humidity fluctuations, and are charging currents in response to fluctuations in interfacial capacitance. Baseline currents are due to very small differences in the open-circuit electrode potential between working and reference electrodes. We deduce that acid concentration changes in the meniscus within the porous electrode structure, in response to changes in the ambient temperature and humidity, cause both the capacitance fluctuations and the baseline changes. The open-circuit potential differences driving the baseline current variations are in part due to a difference in the liquid junction potential between the QRE and working electrode, dependent on humidity and temperature and caused by a gradient of acid concentration, and in part due to temperature- and acid-concentration-dependent variations in the rate of the potential-determining reactions. Based on the understanding obtained, we demonstrate a simple hardware change that corrects these unwanted errors.

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Understanding and Correcting Unwanted Influences on the Signal from Electrochemical Gas Sensors

Farquhar¹,

Henshaw²,

Williams

2021

ACS Sens.

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“…Unfortunately, these approaches have been shown not to perform well in the assessment of LCS measurement errors, due to the presence of multiple, potentially unknown, sensor interferences from other atmospheric constituents (Thompson & Ellison, 2005). These significant sensitivities to constituents such as water vapour and other gases mean laboratory-based calibrations of LCS become exceedingly complex, and expensive, as they attempt to simulate the true atmospheric complexity, often resulting in observed errors being very different to real-world sampling (Rai et al, 2017;Williams, 2020). This has resulted in colocation calibration becoming the accepted method for characterizing LCS measurement uncertainties (De Vito et al, 2020;Masson et al, 2015;Mead et al, 2013;Popoola et al, 2016;Sun et al, 2017), where sensor devices are run alongside traditional reference measurement systems for a period of time, and statistical corrections derived to minimise the error between the two.…”

Section: Dealing With Errors: Established Techniques Vs Low-cost Sensorsmentioning

confidence: 99%

Air pollution measurement errors: Is your data fit for purpose?

Diez

Lacy

Bannan

et al. 2022

Preprint

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Abstract. When making measurements of air quality, having a reliable estimate of the measurement uncertainty is key to assessing the information content that an instrument is capable of providing, and thus its usefulness in a particular application. This is especially important given the widespread emergence of Low Cost Sensors (LCS) to measure air quality. To do this, end users need to clearly identify the data requirements a priori and design quantifiable success criteria by which to judge the data. All measurements suffer from errors, with the degree to which these impact the accuracy of the final data often determined by our ability to identify and correct for them. The advent of LCS has provided a challenge in that many error sources show high spatial and temporal variability, making laboratory derived corrections difficult. Characterizing LCS performance thus currently depends primarily on colocation studies with reference instruments, which are very expensive and do not offer a definitive solution but rather a glimpse of LCS performance in specific conditions over a limited period of time. Despite the limitations, colocation studies do provide useful information on measurement device error structure, but the results are non-trivial to interpret and often difficult to extrapolate to future device performance. A problem that obscures much of the information content of these colocation performance assessments is the exacerbated use of global performance metrics (R2, RMSE, MAE, etc.). Colocation studies are complex and time-consuming, and it is easy to fall into the temptation to only use these metrics when trying to define the most appropriate sensor technology to subsequently use. But the use of these metrics can be limited, and even misleading, restricting our understanding of the error structure and therefore the measurements’ information content. In this work, the nature of common air pollution measurement errors is investigated, and the implications these have on traditional metrics and other empirical, potentially more insightful, approaches to assess measurement performance. With this insight we demonstrate the impact these errors can have on measurements, using a selection of LCS deployed alongside reference measurements as part of the QUANT project, and discuss the implications this has on device end-use.

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“…In the case of electrochemical biosensors, the biocomponent recognizes its complementary analyte resulting in a catalytic or binding event that ultimately produces an electrical signal that is proportional to the analyte concentration and that can be monitored by the transducer [ 52 ]. Numerous applications have been tested for electrochemical sensors and biosensors in biomedical [ 53 , 54 , 55 ], environmental [ 55 , 56 , 57 ], industrial [ 55 ], and agricultural [ 58 ] applications. The sensitivity of the electrochemical sensors and biosensors can be greatly improved by using different nanomaterials such as graphene [ 59 ], carbon nanotubes, MXenes and metal nanoparticles [ 60 ].…”

Section: Sensors For Wound Infection Biomarkersmentioning

confidence: 99%

Wearable Sensors for the Detection of Biomarkers for Wound Infection

et al. 2021

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Infection represents a major complication that can affect wound healing in any type of wound, especially in chronic ones. There are currently certain limitations to the methods that are used for establishing a clinical diagnosis of wound infection. Thus, new, rapid and easy-to-use strategies for wound infection diagnosis need to be developed. To this aim, wearable sensors for infection diagnosis have been recently developed. These sensors are incorporated into the wound dressings that are used to treat and protect the wound, and are able to detect certain biomarkers that can be correlated with the presence of wound infection. Among these biomarkers, the most commonly used ones are pH and uric acid, but a plethora of others (lactic acid, oxygenation, inflammatory mediators, bacteria metabolites or bacteria) have also been detected using wearable sensors. In this work, an overview of the main types of wearable sensors for wound infection detection will be provided. These sensors will be divided into electrochemical, colorimetric and fluorimetric sensors and the examples will be presented and discussed comparatively.

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Electrochemical sensors for environmental gas analysis

Cited by 53 publications

References 69 publications

Understanding and Correcting Unwanted Influences on the Signal from Electrochemical Gas Sensors

Understanding and Correcting Unwanted Influences on the Signal from Electrochemical Gas Sensors

Air pollution measurement errors: Is your data fit for purpose?

Wearable Sensors for the Detection of Biomarkers for Wound Infection

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