scholarly journals Mid-IR evanescent-field fiber sensor with enhanced sensitivity for volatile organic compounds

RSC Advances ◽  
2019 ◽  
Vol 9 (37) ◽  
pp. 21186-21191 ◽  
Author(s):  
Farah Alimagham ◽  
Max Platkov ◽  
Joshua Prestage ◽  
Svetlana Basov ◽  
Gregory Izakson ◽  
...  
Keyword(s):  
Organic Compound ◽  
Gas Phase ◽  
Organic Compounds ◽  
Volatile Organic Compound ◽  
Evanescent Field ◽  
Fiber Sensor ◽  
Porous Coating ◽  
Enhanced Sensitivity ◽  
Volatile Organic ◽  
Increased Sensitivity

Increased sensitivity of mid-IR evanescent field sensing for gas-phase volatile organic compound detection using a nano-porous coating of an optical-fibre.

scholarly journals A MEMS µ-Preconcentrator Employing a Carbon Molecular Sieve Membrane for Highly Volatile Organic Compound Sampling

Chemosensors ◽  
2021 ◽  
Vol 9 (5) ◽  
pp. 104
Author(s):  
Hung-Yang Kuo ◽  
Wei-Riu Cheng ◽  
Tzu-Heng Wu ◽  
Horn-Jiunn Sheen ◽  
Chih-Chia Wang ◽  
...  
Keyword(s):  
Organic Compound ◽  
Organic Compounds ◽  
Volatile Organic Compound ◽  
Molecular Sieve ◽  
Amplification Factor ◽  
Microfluidic Channel ◽  
Carbon Molecular Sieve ◽  
Volatile Organic ◽  
Chromatographic Peaks ◽  
Gaseous Toluene

This paper presents the synthesis and evaluation of a carbon molecular sieve membrane (CMSM) grown inside a MEMS-fabricated μ-preconcentrator for sampling highly volatile organic compounds. An array of µ-pillars measuring 100 µm in diameter and 250 µm in height were fabricated inside a microfluidic channel to increase the attaching surface for the CMSM. The surface area of the CMSM was measured as high as 899 m2/g. A GC peak amplification factor >2 × 104 was demonstrated with gaseous ethyl acetate. Up to 1.4 L of gaseous ethanol at the 100 ppb level could be concentrated without exceeding the capacity of this microchip device. Sharp desorption chromatographic peaks (<3.5 s) were obtained while using this device directly as a GC injector. Less volatile compounds such as gaseous toluene, m-xylene, and mesitylene appeared to be adsorbed strongly on CMSM, showing a memory effect. Sampling parameters such as sample volatilities, sampling capacities, and compound residual issues were empirically determined and discussed.

scholarly journals Volatile organic compound signature from co-culture of lung epithelial cell line with Pseudomonas aeruginosa

The Analyst ◽  
2018 ◽  
Vol 143 (13) ◽  
pp. 3148-3155 ◽  
Author(s):  
Oluwasola Lawal ◽  
Hugo Knobel ◽  
Hans Weda ◽  
Lieuwe D. Bos ◽  
Tamara M. E. Nijsen ◽  
...  
Keyword(s):  
Pseudomonas Aeruginosa ◽  
Volatile Organic Compounds ◽  
Organic Compound ◽  
Epithelial Cell ◽  
Organic Compounds ◽  
Volatile Organic Compound ◽  
Epithelial Cell Line ◽  
Diagnostic Biomarkers ◽  
Lung Epithelial ◽  
Volatile Organic

Bacterial volatile organic compounds have the potential to be utilised as diagnostic biomarkers for infections.

Review of Distribution Characteristics and Sources of Volatile Organic Compound in Atmosphere

2013 ◽  
Vol 726-731 ◽  
pp. 944-949
Author(s):  
Zhen Hua Xiong ◽  
Feng Qian ◽  
Xue Feng ◽  
Rong Rong Su ◽  
Yu Zeng
Keyword(s):  
Volatile Organic Compounds ◽  
Organic Compound ◽  
Human Health ◽  
Organic Compounds ◽  
Volatile Organic Compound ◽  
Distribution Characteristics ◽  
Sources Apportionment ◽  
Secondary Pollutants ◽  
Volatile Organic ◽  
Many Sources

Volatile Organic Compounds (VOCs) have many sources, and they have effects on ecology and human health, which has aroused extensive attentions of many researchers. The Chinese and other countries studies in VOCs in atmosphere focused on detecting concentrations and compositions, sources apportionment, secondary pollutants transformation, health effects and other aspects. In the present paper, VOCs level in atmosphere, distribution characteristics and sources apportionment of VOCs in atmosphere were reviewed, the current studies results of VOCs in atmosphere were summarized.

Selective adsorption of chlorinated volatile organic compound vapours by microcrystalline 1D coordination polymers

2016 ◽  
Vol 45 (47) ◽  
pp. 18832-18837 ◽  
Author(s):  
Massimo Cametti ◽  
Javier Martí-Rujas
Keyword(s):  
Organic Compound ◽  
Organic Compounds ◽  
Coordination Polymers ◽  
Volatile Organic Compound ◽  
Selective Adsorption ◽  
X Ray Diffraction ◽  
X Ray ◽  
Chlorinated Volatile Organic Compounds ◽  
H Nmr ◽  
Volatile Organic

Microcrystalline 1D coordination polymers 1–3Pwd are able to adsorb vapours of chlorinated volatile organic compounds (Cl-VOCs), displaying interesting selectivity patterns, as demonstrated by 1H-NMR and X-ray diffraction analyses.

The effect of anthropogenic volatile organic compound sources on ozone in Boise, Idaho

2014 ◽  
Vol 11 (4) ◽  
pp. 445 ◽  
Author(s):  
Victor Vargas ◽  
Marie-Cecile Chalbot ◽  
Robert O'Brien ◽  
George Nikolich ◽  
David W. Dubois ◽  
...  
Keyword(s):  
Volatile Organic Compounds ◽  
Organic Compound ◽  
Organic Compounds ◽  
Volatile Organic Compound ◽  
Fugitive Emissions ◽  
Wildfire Smoke ◽  
Volatile Organic ◽  
The Mean ◽  
Photochemical Processing ◽  
Ozone Levels

Environmental context Volatile organic compounds are precursors of ozone, a pollutant with adverse environmental effects. It is important to determine the associations between the various sources of volatile organic compounds and ozone levels because emission controls are based on sources. We estimated the contributions of specific sources of volatile organic compounds on ozone levels using both measurements and statistical models, and found that traffic is the largest source even in events when wildfire smoke is present. Abstract Here, we present the application of a tiered approach to apportion the contributions of volatile organic compound (VOC) sources on ozone (O3) concentrations. VOCs from acetylene to n-propylbenzene were measured at two sites at Boise, Idaho, using an online pneumatically focussed gas chromatography system. The mean 24-h concentrations of individual VOCs varied from 0.4ppbC (parts per billion carbon) for 1-butene to 23.2ppbC for m- and p-xylene. The VOC sources at the two monitoring sites were determined by positive matrix factorisation. They were attributed to: (i) liquefied petroleum and natural gas (LPG/NG) emissions; (ii) fugitive emissions of olefins from fuel and solvents; (iii) fugitive emissions of aromatic VOCs from area sources and (iv) vehicular emissions. Vehicle exhausts accounted for 36 to 45% of VOCs followed by LPG/NG and fugitive emissions of aromatic VOCs. Evaluation of photochemical changes showed that the four separate VOC sources were identified by PMF rather than different stages of photochemical processing of fresh emissions. The contributions of VOC sources on daily 8-h maximum O3 concentrations measured at seven locations in the metropolitan urban area were identified by regression analysis. The four VOC sources added, on average, 6.4 to 16.5 parts per billion by volume (ppbv) O3, whereas the unexplained (i.e. intercept) O3 was comparable to non-wildfire policy-relevant background O3 levels in the absence of all anthropogenic emissions of VOC precursors in North America for the region. Traffic was the most significant source influencing O3 levels contributing up to 32ppbv for days with O3 concentrations higher than 75ppbv.

scholarly journals High-Performance VOC Quantification for IAQ Monitoring Using Advanced Sensor Systems and Deep Learning

Atmosphere ◽  
2021 ◽  
Vol 12 (11) ◽  
pp. 1487
Author(s):  
Yannick Robin ◽  
Johannes Amann ◽  
Tobias Baur ◽  
Payman Goodarzi ◽  
Caroline Schultealbert ◽  
...  
Keyword(s):  
Air Quality ◽  
Volatile Organic Compounds ◽  
Organic Compound ◽  
Organic Compounds ◽  
Volatile Organic Compound ◽  
Indoor Air ◽  
Deep Neural Networks ◽  
Evaluation Methods ◽  
Data Evaluation ◽  
Volatile Organic

With air quality being one target in the sustainable development goals set by the United Nations, accurate monitoring also of indoor air quality is more important than ever. Chemiresistive gas sensors are an inexpensive and promising solution for the monitoring of volatile organic compounds, which are of high concern indoors. To fully exploit the potential of these sensors, advanced operating modes, calibration, and data evaluation methods are required. This contribution outlines a systematic approach based on dynamic operation (temperature-cycled operation), randomized calibration (Latin hypercube sampling), and the use of advances in deep neural networks originally developed for natural language processing and computer vision, applying this approach to volatile organic compound measurements for indoor air quality monitoring. This paper discusses the pros and cons of deep neural networks for volatile organic compound monitoring in a laboratory environment by comparing the quantification accuracy of state-of-the-art data evaluation methods with a 10-layer deep convolutional neural network (TCOCNN). The overall performance of both methods was compared for complex gas mixtures with several volatile organic compounds, as well as interfering gases and changing ambient humidity in a comprehensive lab evaluation. Furthermore, both were tested under realistic conditions in the field with additional release tests of volatile organic compounds. The results obtained during field testing were compared with analytical measurements, namely the gold standard gas chromatography mass spectrometry analysis based on Tenax sampling, as well as two mobile systems, a gas chromatograph with photo-ionization detection for volatile organic compound monitoring and a gas chromatograph with a reducing compound photometer for the monitoring of hydrogen. The results showed that the TCOCNN outperforms state-of-the-art data evaluation methods, for example for critical pollutants such as formaldehyde, achieving an uncertainty of around 11 ppb even in complex mixtures, and offers a more robust volatile organic compound quantification in a laboratory environment, as well as in real ambient air for most targets.

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