Non-dispersive Infrared Detector Research Articles

Real Time Factory Smokes Monitoring System Using Android Smartphone

Owing to widespread deforestation and the rapid growth of modern plants, we can see and experience a lot of air that is no longer what it once was. Carbon Monoxide (CO), which is generated by residual combustion in industrial plants and emitted through factory chimneys, is one of the factors that contribute to air pollution. This study was designed to help the government monitor Carbon Monoxide (CO) levels more efficiently because it can be done at any time in real time using an Android smartphone's media. Furthermore, this research is being conducted to develop simple technology that can be used by parties who need or have an interest in monitoring Carbon Monoxide (CO) levels as well as reducing the number of emissions in the local area. The results showed that the MQ-7 sensor on the monitoring tool could detect carbon monoxide levels accurately and had a 0.72 percent error rate when retrieving data several times. The CO meter's sensitivity is equivalent to that of an NDIR (Non-Dispersive Infrared Detector) Analyzer, which is commonly used for measuring and detecting carbon monoxide levels in the air. These findings suggest that this instrument can be used to better monitor carbon monoxide (CO) levels in the air.

Identifying and quantifying geogenic organic carbon in soils – the case of graphite

Abstract. A widely overlooked source of carbon (C) in the soil environment is organic carbon (OC) of geogenic origin, e.g. graphite, occurring mostly in metamorphic rocks. Appropriate methods are not available to quantify graphite and to differentiate it from other organic and inorganic C sources in soils. This methodological shortcoming also complicates studies on OC in soils formed on graphite-containing bedrock because of the unknown contribution of a very different soil OC source. In this study, we examined Fourier-transform infrared (FTIR) spectroscopy, thermogravimetric analysis (TGA) and the smart combustion method for their ability to identify and quantify graphitic C in soils. For this purpose, several artificial soil samples with graphite, CaCO3 and plant litter as the usual C components were created. A graphitic standard was mixed with pure quartz and a natural soil for calibration and validation of the methods over a graphitic C range of 0.1 % to 4 %. Furthermore, rock and soil material from a graphite-bearing schist and a schist without natural graphite were used for method validation. FTIR. As specific signal intensities of distinct graphite absorption bands were missing, calibration could only be performed on general effects of graphite contents on the energy transmitted through the samples. The use of samples from different mineral origins yielded significant matrix effects and hampered the prediction of geogenic graphite contents in soils. TGA. Thermogravimetric analysis, based on changes in mass loss due to differences in thermal stabilities, is suggested as a useful method for graphite identification, although (calcium) carbonate and graphitic C have a similar thermal stability. However, the quantitative estimation of the graphite contents was challenging as dehydroxylation (mass loss) of a wide range of soil minerals occurs in a similar temperature range. Smart combustion. The method is based on measuring the release of C during a combustion program, quantified by a non-dispersive infrared detector (NDIR) as part of a commercial elemental analyser, whereby carbonates and graphitic C could be separated by switching between oxic and anoxic conditions during thermal decomposition. Samples were heated to 400 ∘C under oxygen-rich conditions, after which further heating was done under anoxic conditions till 900 ∘C. The residual oxidizable carbon (ROC), hypothesized to be graphitic C, was measured by switching back to oxygenic conditions at 900 ∘C. Test samples showed promising results for quantifying graphitic C in soils. For the purpose of quantifying graphitic C content in soil samples, smart combustion was the most promising method of those which have been examined in this study. However, caution should be taken with carbonate-rich soils as increasing amounts of carbonate resulted in an underestimation of graphitic C content.

Assessment of the final metrological characteristics of a MOEMS-based NDIR spectrometer through system modeling and data processing

A model of a miniaturized non-dispersive infrared (NDIR) gas analysis system, aiming to predict the final system specifications, is presented. It comprises the different elements of the NDIR detector, including a surface micromachined Fabry-Perot tunable filter. These models have been used to estimate the response of the NDIR system to different gas mixtures. Multivariate regression methods like partial least squares allow recovering the true sample composition from the IR absorption spectra measured with the NDIR system, despite the limited selectivity of the filter. Combining model and data processing permits to predict the effect on the final system specification of design parameters. Here, we compare the effect of the technology used for the filter on the system errors.