Abstract
Abstract. For detection of benzene, a gas sensor system with metal oxide semiconductor (MOS) gas sensors using temperature-cycled operation (TCO) is presented. The system has been tested in two different laboratories at the concentration range from 0.5 up to 10 ppb. The system is equipped with three gas sensors and advanced temperature control and read-out electronics for the extraction of features from the TCO signals. A sensor model is used to describe the sensor response in dependence on the gas concentration. It is based on a linear differential surface reduction (DSR) at a low temperature phase, which is linked to an exponential growth of the sensor conductance. To compensate for cross interference to other gases, the DSR is measured at three different temperatures (200, 250, 300 ∘C) and the calculated features are put into a multilinear regression (partial least square regression – PLSR) for the quantification of benzene at both laboratories. In the tests with the first set-up, benzene was supplied in defined gas profiles in a continuous gas flow with variation of humidity and various interferents, e.g. toluene and carbon monoxide (CO). Depending on the gas background and interferents, the quantification accuracy is between ±0.2 and ±2 ppb. The second gas mixing system is based on a circulation of the carrier gas stream in a closed-loop control for the benzene concentration and other test gases based on continuously available reference measurements for benzene and other organic and inorganic compounds. In this system, a similar accuracy was achieved for low background contaminations and constant humidity; the benzene level could be quantified with an error of less than 0.5 ppb. The transfer of regression models for one laboratory to the other has been tested successfully.
Highlights
Air quality is an important pre-requisite for public health
The benzene concentrations predicted by the PLSR model for the JRC data at 60 %RH still show a very small error of below 200 ppt with respect to the concentration measured by the gas chromatography (GC)-proportional– integral–derivative (PID) 955
Within the measured sensor signals all tested benzene concentrations were in good agreement with the prediction of the differential surface reduction (DSR) model
Summary
Air quality is an important pre-requisite for public health. The pollution of the air with gaseous compounds contributes relevantly to the burden of disease in industrial and developing countries (Bernstein et al, 2008). The result of one prototype using metal oxide semiconductor (MOS) gas sensors with temperature cycle operation (TCO) is reported in this paper. This approach has previously been studied for the selective detection of volatile organic compounds (VOCs), e.g. benzene in indoor air (Leidinger et al, 2014; Schütze et al, 2017). It is dynamic operation (Nakata et al, 1998a, b) and in this sense it enables sensor properties that cannot be found in a sensor at any constant temperature Following this line, some of us could prove in the last few years that an optimized TCO can increase the sensitivity (Baur et al, 2015) and the stability (Schultealbert et al, 2017) of the sensor signal as well. We could show that the benzene concentration in the range from 500 ppt to 10 ppb air can be quantified very accurately in a purified air background, whereby compensation of the ubiquitous gas background and interfering gas reduces the accuracy of detection (Leidinger et al, 2017)
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