Literature DB >> 26452830

Application of electronic nose for industrial odors and gaseous emissions measurement and monitoring--An overview.

Sharvari Deshmukh1, Rajib Bandyopadhyay2, Nabarun Bhattacharyya3, R A Pandey4, Arun Jana5.   

Abstract

The present review evaluates the key modules of the electronic nose, a biomimetic system, with specific examples of applications to industrial emissions monitoring and measurement. Regulations concerning the odor control are becoming very strict, due to ever mounting environmental pollution and its subsequent consequences and it is advantageous to employ real time measurement system. In this perspective, systems like the electronic nose are an improved substitute for assessing the complex industrial emissions over other analytical techniques (odorant concentration measurement) and olfactometry (odor concentration measurement). Compared to tools like gas chromatography, electronic nose systems are easy to develop, are non-destructive and useful for both laboratory and on field purposes. Although there has been immense development of more sensitive and selective sensor arrays and advanced data mining techniques, there have been limited reports on the application of electronic nose for the measurement of industrial emissions. The current study sheds light on the practical applicability of electronic nose for the effective industrial odor and gaseous emissions measurement. The applications categorization is based on gaseous pollutants released from the industries. Calibration and calibration transfer methodologies have been discussed to enhance the applicability of electronic nose system. Further, industrial gas grab sampling technique is reviewed. Lastly, the electronic mucosa system, which has the ability to overcome the flaws of electronic nose system, has been examined. The review ends with the concluding remarks describing the pros and cons of artificial olfaction technique for the industrial applications.
Copyright © 2015 Elsevier B.V. All rights reserved.

Keywords:  Data analysis; Electronic nose; Industrial application; Industrial odor; Industrial sampling techniques; Sensors

Year:  2015        PMID: 26452830     DOI: 10.1016/j.talanta.2015.06.050

Source DB:  PubMed          Journal:  Talanta        ISSN: 0039-9140            Impact factor:   6.057


  23 in total

1.  Discrimination of Chinese Baijiu grades based on colorimetric sensor arrays.

Authors:  Hao Lin; Wen-Cui Kang; Hong-Juan Jin; Zhong-Xiu Man; Quan-Sheng Chen
Journal:  Food Sci Biotechnol       Date:  2020-04-19       Impact factor: 2.391

2.  Volatilome Analysis in Prostate Cancer by Electronic Nose: A Pilot Monocentric Study.

Authors:  Alessio Filianoti; Manuela Costantini; Alfredo Maria Bove; Umberto Anceschi; Aldo Brassetti; Mariaconsiglia Ferriero; Riccardo Mastroianni; Leonardo Misuraca; Gabriele Tuderti; Gennaro Ciliberto; Giuseppe Simone
Journal:  Cancers (Basel)       Date:  2022-06-14       Impact factor: 6.575

3.  Elimination of Drifts in Long-Duration Monitoring for Apnea-Hypopnea of Human Respiration.

Authors:  Peng Jiang; Rong Zhu
Journal:  Sensors (Basel)       Date:  2016-10-25       Impact factor: 3.576

4.  Array of Chemosensitive Resistors with Composites of Gas Chromatography (GC) Materials and Carbon Black for Detection and Recognition of VOCs: A Basic Study.

Authors:  Bartosz Wyszynski; Rui Yatabe; Atsuo Nakao; Masaya Nakatani; Akio Oki; Hiroaki Oka; Kiyoshi Toko
Journal:  Sensors (Basel)       Date:  2017-07-11       Impact factor: 3.576

Review 5.  Identification of Chinese Herbal Medicines with Electronic Nose Technology: Applications and Challenges.

Authors:  Huaying Zhou; Dehan Luo; Hamid GholamHosseini; Zhong Li; Jiafeng He
Journal:  Sensors (Basel)       Date:  2017-05-09       Impact factor: 3.576

6.  Assessment of the Indoor Odour Impact in a Naturally Ventilated Room.

Authors:  Lidia Eusebio; Marco Derudi; Laura Capelli; Giuseppe Nano; Selena Sironi
Journal:  Sensors (Basel)       Date:  2017-04-05       Impact factor: 3.576

7.  Online Sensor Drift Compensation for E-Nose Systems Using Domain Adaptation and Extreme Learning Machine.

Authors:  Zhiyuan Ma; Guangchun Luo; Ke Qin; Nan Wang; Weina Niu
Journal:  Sensors (Basel)       Date:  2018-03-01       Impact factor: 3.576

8.  A Novel Semi-Supervised Method of Electronic Nose for Indoor Pollution Detection Trained by M-S4VMs.

Authors:  Tailai Huang; Pengfei Jia; Peilin He; Shukai Duan; Jia Yan; Lidan Wang
Journal:  Sensors (Basel)       Date:  2016-09-10       Impact factor: 3.576

9.  Classification of Data from Electronic Nose Using Gradient Tree Boosting Algorithm.

Authors:  Yuan Luo; Wenbin Ye; Xiaojin Zhao; Xiaofang Pan; Yuan Cao
Journal:  Sensors (Basel)       Date:  2017-10-18       Impact factor: 3.576

Review 10.  Different Ways to Apply a Measurement Instrument of E-Nose Type to Evaluate Ambient Air Quality with Respect to Odour Nuisance in a Vicinity of Municipal Processing Plants.

Authors:  Bartosz Szulczyński; Tomasz Wasilewski; Wojciech Wojnowski; Tomasz Majchrzak; Tomasz Dymerski; Jacek Namieśnik; Jacek Gębicki
Journal:  Sensors (Basel)       Date:  2017-11-19       Impact factor: 3.576

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