Dataset Information

Development and Evaluation of A Novel and Cost-Effective Approach for Low-Cost NO? Sensor Drift Correction.

ABSTRACT: Emerging low-cost gas sensor technologies have received increasing attention in recent years for air quality measurements due to their small size and convenient deployment. However, in the diverse applications these sensors face many technological challenges, including sensor drift over long-term deployment that cannot be easily addressed using mathematical correction algorithms or machine learning methods. This study aims to develop a novel approach to auto-correct the drift of commonly used electrochemical nitrogen dioxide (NO?) sensor with comprehensive evaluation of its application. The impact of environmental factors on the NO? electrochemical sensor in low-ppb concentration level measurement was evaluated in laboratory and the temperature and relative humidity correction algorithm was evaluated. An automated zeroing protocol was developed and assessed using a chemical absorbent to remove NO? as a means to perform zero correction in varying ambient conditions. The sensor system was operated in three different environments in which data were compared to a reference NO? analyzer. The results showed that the zero-calibration protocol effectively corrected the observed drift of the sensor output. This technique offers the ability to enhance the performance of low-cost sensor based systems and these findings suggest extension of the approach to improve data quality from sensors measuring other gaseous pollutants in urban air.

SUBMITTER: Sun L

PROVIDER: S-EPMC5580082 | biostudies-other | 2017 Aug

REPOSITORIES: biostudies-other

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Publications

Development and Evaluation of A Novel and Cost-Effective Approach for Low-Cost NO₂ Sensor Drift Correction.

Sun Li L Westerdahl Dane D Ning Zhi Z

Sensors (Basel, Switzerland) 20170819 8

Emerging low-cost gas sensor technologies have received increasing attention in recent years for air quality measurements due to their small size and convenient deployment. However, in the diverse applications these sensors face many technological challenges, including sensor drift over long-term deployment that cannot be easily addressed using mathematical correction algorithms or machine learning methods. This study aims to develop a novel approach to auto-correct the drift of commonly used el ...[more]

PMID: 28825633

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Project description:ObjectiveFinely resolved PM2.5 exposure measurements at the level of individual participants or over a targeted geographic area can be challenging due to the cost, size and weight of the monitoring equipment. We propose re-purposing the low-cost, portable and lightweight Shinyei PPD42NS particle counter as a particle counting device. Previous field deployment of this sensor suggests that it captures trends in ambient PM2.5 concentrations, but important characteristics of the sensor response have yet to be determined. Laboratory testing was undertaken in order to characterize performance.MethodsThe Shinyei sensors, in-line with a TSI Aerosol Particle Sizer (APS) model 3321, tracked particle decay within an aerosol exposure chamber. Test atmospheres were composed of monodisperse polystyrene spheres with diameters of 0.75, 1, 2 3 and 6 um as well as a polydisperse atmosphere of ASHRAE test dust #1.ResultsTwo-minute block averages of the sensor response provide a measurement with low random error, within sensor, for particles in the 0.75-6?m range with a limit of detection of 1 ?g/m3. The response slope of the sensors is idiomatic, and each sensor requires a unique response curve. A linear model captures the sensor response for concentrations below 50 ?g/m3 and for concentrations above 50 ?g/m3 a non-linear function captures the response and saturates at 800 ?g/m3. The Limit of Detection (LOD) is 1 ?g/m3. The response time is on the order of minutes, making it appropriate for tracking short-term changes in concentration.ConclusionsWhen paired with prior evaluation, these sensors are appropriate for use as ambient particle counters for low and medium concentrations of respirable particles (< 100 ug/m3). Multiple sensors deployed over a spatial grid would provide valuable spatio-temporal variability in PM2.5 and could be used to validate exposure models. When paired with GPS tracking, these devices have the potential to provide time and space resolved exposure measurements for a large number of participants, thus increasing the power of a study.

Dataset Information

Development and Evaluation of A Novel and Cost-Effective Approach for Low-Cost NO? Sensor Drift Correction.

Publications

Development and Evaluation of A Novel and Cost-Effective Approach for Low-Cost NO₂ Sensor Drift Correction.

Similar Datasets

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