Abstract
Sensor technology has enabled the development of portable low-cost monitoring kits that might supplement many applications in conventional monitoring stations. Despite the sensitivity of electrochemical gas sensors to environmental change, they are increasingly important in monitoring polluted microenvironments. The performance of a compact diffusion-based Personal Exposure Kit (PEK) was assessed for real-time gaseous pollutant measurement (CO, O3, and NO2) under typical environmental conditions encountered in the subtropical city of Hong Kong. A dynamic baseline tracking method and a range of calibration protocols to address system performance were explored under practical scenarios to assess the performance of the PEK in reducing the impact of rapid changes in the ambient environment in personal exposure assessment applications. The results show that the accuracy and stability of the ppb level gas measurement is enhanced even in heterogeneous environments, thus avoiding the need for data post-processing with mathematical algorithms, such as multi-linear regression. This establishes the potential for use in personal exposure monitoring, which has been difficult in the past, and for reporting more accurate and reliable data in real-time to support personal exposure assessment and portable air quality monitoring applications.
Highlights
Assessments of exposure to air pollutants have often depended heavily on measurements from stationary reference instruments, but these may poorly represent individual exposure linked to the pattern of human activity
Require considerable care in housing and maintenance and are not moved. They fail to provide data that reflect the high degree of spatial and temporal variation that contributes to personal exposure in urban microenvironments [1,2,3]
It is not practical to improve exposure assessment by adding conventional sites, so this study will evaluate the accuracy of a sensor-based portable monitoring unit, which includes a novel dynamic baseline tracking approach to deal with the effects of humidity and temperature on the observations made in assessing real world exposure
Summary
Assessments of exposure to air pollutants have often depended heavily on measurements from stationary reference instruments, but these may poorly represent individual exposure linked to the pattern of human activity. It is not practical to improve exposure assessment by adding conventional sites, so this study will evaluate the accuracy of a sensor-based portable monitoring unit, which includes a novel dynamic baseline tracking approach to deal with the effects of humidity and temperature on the observations made in assessing real world exposure. Mathematical algorithms to compensate for sensor response to environmental variation have used multi-linear regression [14,15] and artificial neural networks (ANN) [16] Another approach is to apply baseline correction methods, where a baseline is extracted by determining the minimum measurement within a specific time interval with ambient temperature and humidity and allowing these to serve as explanatory variables over a range of meteorological conditions [11,17]. The kit has sufficient battery capacity to run for three days, it can be powered and recharged using a 12-volt supply
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