TY - CONF A1 - Moufid, M. A1 - Tiebe, Carlo A1 - El Bari, N. A1 - Bartholmai, Matthias A1 - Bouchikhi, B. T1 - Advance in electronic nose technology developed for the detection and discrimination of ethanol, ammonia, and hydrogen sulfide gases N2 - This work focuses on the design and fabrication of low-cost and fast-response of an electronic nose (E-nose) based on semiconductor gas sensors, for discriminating some synthetic gases such as ammonia (NH3), ethanol (C2H5OH), and hydrogen sulfide (H2S). Additionally, the capability of separating different concentration levels of each considered gases was checked. Dataset treatment of E-nose by using Principal Component Analysis (PCA) showed a good discrimination of the different synthetic gases. Furthermore, perfect classification was reached of different concentration levels of the analysed gases by using Discriminant Function Analysis (DFA). In the light of these results, it could be stated that the developed E-nose system constitutes an inexpensive, rapid, simple to use, and efficient tool for synthetic gases detection. T2 - IEEE International Symposium on Olfaction and Electronic Nose (ISOEN) CY - Aveiro, Portugal DA - 29.05.2022 KW - Electronic nose KW - Metal oxide semiconductor KW - Chemometric techniques KW - Environmental analysis PY - 2022 SN - 978-1-6654-5860-3 DO - https://doi.org/10.1109/ISOEN54820.2022.9789636 SP - 1 EP - 3 AN - OPUS4-56574 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Moufid, M. A1 - Tiebe, Carlo A1 - El Bari, N. A1 - Hamada, D. A. A1 - Bartholmai, Matthias A1 - Bouchikhi, B. T1 - Pollution parameters evaluation of wastewater collected at different treatment stages from wastewater treatment plant based on E-nose and E-tongue systems combined with chemometric techniques N2 - Wastewater contains harmful chemicals and heavy metals that are known to cause various environmental and health problems. Therefore, the water quality control using sensitive, simple, fast, accurate, and portable tools is of great importance. This study aimed to evaluate the pollution parameters of wastewaters collected at different treatment stages from a wastewater treatment plant (WWTP) that treats domestic and industrial wastewaters by using an electronic nose (E-nose) and a voltammetric electronic tongue (E-tongue) combined with chemometric techniques. Water and wastewater pollution parameters determination were performed using inductively coupled plasma optical emission spectrometry for the determination of cations, and anions by using ion chromatography. Chemometric techniques, such as Principal Component Analysis (PCA), Discriminant Function Analysis (DFA), Support Vector Machines (SVMs), and Hierarchical Cluster Analysis (HCA), were used to process the E-nose and E-tongue datasets to describe the similarities between the samples. In addition, Partial Least Squares Regression (PLSR) model was constructed using electronic sensing data to simultaneously predict the concentration values of physicochemical parameters. The obtained correlation coefficient, for training and testing sets, is higher than 0.91 for the prediction of the concentration of all physicochemical parameters, except for iron (Fe) which remains 0.84. These results suggest that simple, portable, and inexpensive tools such as electronic nose and tongue are suitable for wastewater analysis. KW - Wastewater KW - Electronic nose KW - Voltammetric electronic tongue KW - Water quality control KW - Chemometric techniques KW - Gas sensing PY - 2022 DO - https://doi.org/10.1016/j.chemolab.2022.104593 VL - 227 SP - 1 EP - 12 PB - Elsevier B.V. AN - OPUS4-55652 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Hofmann, Michael A1 - Moufid, M. A1 - El Bari, N. A1 - Tiebe, Carlo A1 - Bouchikhi, B. T1 - Testing of a developed multigas sensor system for outdoor odour nuisance monitoring N2 - This work presents the testing of a developed elec¬tronic nose for outdoor odour nuisance monitoring. The sensor system consists of a sampling system, a measuring cell equipped with commercially available low-cost gas sensor elements and a data acquisition system. The sensor testing showed that the developed prototype is able to distinguish, identify and partially quantify individual odorous substances like ethanol, ammonia and hydrogen sulphide. Ethanol and ammonia could even be detected below or near their odour threshold. T2 - ALLSENSORS 2019, The Fourth International Conference on Advances in Sensors, Actuators, Metering and Sensing CY - Athens, Greece DA - 24.02.2019 KW - Electronic nose KW - Outdoor odour KW - Machined olfaction KW - Sensor testing PY - 2019 UR - https://www.thinkmind.org/index.php?view=article&articleid=allsensors_2019_2_40_70065 SN - 978-1-61208-691-0 SN - 2519-836X SP - 27 EP - 28 PB - The ThinkMind Digital Library AN - OPUS4-47505 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Moufid, M. A1 - Hofmann, Michael A1 - El Bari, N. A1 - Tiebe, Carlo A1 - Bartholmai, Matthias A1 - Bouchikhi, B. T1 - Wastewater monitoring by means of e-nose, VE-tongue, TD-GC-MS, and SPME-GC-MS N2 - The presence of wastewater and air pollution has become an important risk factor for citizens, not only in terms of problems related to health risks, but also because of its negative impact on the country's image. For this reason, malodorous emission monitoring and control techniques are in high demand in urban areas and industries. The aim of this work is first to build an electronic nose (e-nose) and a Voltammetric Electronic tongue (VE-tongue) in order to study their ability to discriminate between polluted and clean environmental samples. Secondly, Thermal Desorption-Gas Chromatography-Mass Spectrometry (TD-GC-MS), and Solid Phase Micro Extraction-Gas Chromatography–Mass Spectrometry (SPME-GC-MS) are utilized to explain this discrimination by identifying specific compounds from these samples. Indeed, the e-nose, consisted of metal oxide semiconductor gas sensors, is used for the assessment of the studied odorous air and headspace samples from water and wastewater sites. Moreover, the VE-tongue, based on metal electrodes, is utilized to determine the patterns of the sensor array responses, which serve as fingerprints profiles of the analyzed liquid samples. Chemometric tools, such as Principal Component Analysis (PCA), Hierarchical Cluster Analysis (HCA), and Support Vector Machines (SVMs) are operated for the processing of data from the e-nose and the VE-tongue. By using the both systems, the analyses of headspace and liquid samples from the seven sites allow better discrimination. To explain the cause of the obtained discrimination, TD-GC-MS and SPME-GC-MS analyses are well performed to identify compounds related sites. According to these outcomes, the proposed e-nose and VE-tongue are proved to be rapid and valuable tools for analysis of environmental polluted matrices. KW - Wastewater KW - Electronic nose KW - Voltammetric electronic tongue KW - Thermal desorption-gas chromatography-mass spectrometry KW - Solid phase micro extraction-gas chromatography–mass spectrometry PY - 2021 DO - https://doi.org/10.1016/j.talanta.2020.121450 VL - 221 SP - 121450 PB - Elsevier B.V. AN - OPUS4-51099 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Moufid, M. A1 - Tiebe, Carlo A1 - El Bari, N. A1 - Bartholmai, Matthias A1 - Bouchikhi, B. T1 - Characterization of Unpleasant Odors in Poultry Houses Using Metal Oxide Semiconductor-Based Gas Sensor Arrays and Pattern Recognition Methods N2 - In this study, the ability of an electronic nose developed to analyze and monitor odor emissions from three poultry farms located in Meknes (Morocco) and Berlin (Germany) was evaluated. Indeed, the potentiality of the electronic nose (e-nose) to differentiate the concentration fractions of hydrogen sulfide, ammonia, and ethanol was investigated. Furthermore, the impact change of relative humidity values (from 15% to 67%) on the responses of the gas sensors was reported and revealed that the effect remained less than 0.6%. Furthermore, the relevant results confirmed that the developed e-nose system was able to perfectly classify and monitor the odorous air of poultry farms. T2 - 1st International Electronic Conference on Chemical Sensors and Analytical Chemistry CY - Online meeting DA - 01.07.2021 KW - Pattern recognition methods KW - Gas sensors KW - Electronic nose KW - poultry odorous air monitoring PY - 2021 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-544005 UR - https://csac2021.sciforum.net/ DO - https://doi.org/10.3390/CSAC2021-10481 VL - 5 IS - 52 SP - 1 EP - 7 PB - MDPI AN - OPUS4-54400 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Moufid, M. T1 - An electronic nose for the detection and discrimination of environmental pollutant gases in the aglomeration of the city of meknes N2 - The ambient air quality around residential areas is influenced by industrial objects, including industrial sewage, livestock farming and landfill sites. These sites are generating malodours or toxic gases involving degradation of ambient air quality, which may constitute a risk in human health if maximum emission limits are exceeded. Therefore, appropriate tools allowing detection of harmful or bad odorous, subsequently contributing to a reduction of odour nuisance are greatly needed. The aim of this study was to demonstrate the capability of an electronic nose E-nose to discriminate various gas samples collected from six different sites from the agglomeration of Meknès city corresponding to municipal landfill, in the city at 2 km of landfill, industrial estate wastewater, traffic road, and sheep breeding. The investigations were carried out with an E-nose system based on an array of six-commercial MQ sensors. Further, a pattern recognition technique known as Principal Component Analysis (PCA), Linear Discriminent Analysis (LDA), and Support Vector Machines (SVMs) was implemented to study the discrimination capability of the sensor array. PCA results demonstrate excellent discriminating ability of the dataset with a score of 99.47 %. Additionally, another measurement database containing 12 air atmospheric samples was projected on the previously built PCA model to check the stability of the E-nose. The LDA was applied to the same dataset and showed a good discrimination between the ambient air samples of the six sites. Furthermore, SVMs technique was also used to build a classifier and reached a score of 100 % success rate in the recognition of the analysed samples. The obtained results of six areas demonstrate the increasing interests and the applicability of E-noses for ambient air quality classification of six areas caused by emitted decomposed organic matters. T2 - Eighth International Workshop on Biosensors for Food Safety and Environmental Monitoring CY - Rabat, Morocco DA - 12.10.2017 KW - Pattern recognition methods KW - Electronic nose KW - Gas sensor KW - Malodour detection KW - Environmental analysis PY - 2017 AN - OPUS4-42525 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Moufid, M. A1 - Bouchikhi, B. A1 - Tiebe, Carlo A1 - Bartholmai, Matthias A1 - El Bari, N. T1 - Assessment of outdoor odor emissions from polluted sites using simultaneous thermal desorption-gas chromatography-mass spectrometry (TD-GC-MS), electronic nose in conjunction with advanced multivariate statistical approaches N2 - Poor air quality, particularly in urban areas, causes various diseases and degrades living standards. Air Quality could be affected by emissions of odor, Volatile Organic Compounds (VOCs), and other gases. Therefore, assessment and monitoring of odorous air quality using sensitive, simple, rapid, accurate and portable tools is very important for public health. This study aimed to characterize odor emissions to detect malfunctions in facilities and to prevent air pollution and olfactory nuisance in the environment. A gas chromatographic method, in conjunction with sensorial analysis were performed for odorous air samples analysis collected from neighborhood of Meknes city (Morocco). Advanced multivariate statistical approaches, such as Principal Components Analysis (PCA), Discriminant Function Analysis (DFA), Support Vector Machines (SVMs), and Hierarchical Cluster Analysis (HCA), were used to describe samples similarities. The electronic nose (e-nose) data processing exhibits a satisfactory discrimination between the odorous air samples. Twenty-four VOCs with known molecular formulas were identified with Thermal Desorption-Gas Chromatography-Mass Spectrometry (TD-GC-MS). A validated Partial Least Square (PLS) model foresees good calibration between e-nose measurement and TD-GCMS analysis. The finding indicates that TD-GC–MS approach in conjunction with e-nose unit could be suitable tool for environmental measurement-based odor emissions. KW - Electronic nose KW - TD-GC-MS KW - PLS regression KW - Multivariate analysis KW - Outdoor odor emissions PY - 2021 DO - https://doi.org/10.1016/j.atmosenv.2021.118449 SN - 1352-2310 VL - 256 SP - 118449 PB - Elsevier Ltd. AN - OPUS4-52626 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Moufid, M. A1 - Tiebe, Carlo A1 - El Bari, N. A1 - Bartholmai, Matthias A1 - Bouchikhi, B. T1 - Combining of TD-GC-MS and home developed electronic nose for road traffic air monitoring N2 - In this work, we demonstrate the ability of an electronic nose system based on an array of six-semiconductor gas sensors for outdoor air quality monitoring over a day at a traffic road in downtown of Meknes city (Morocco). The response of the sensor array reaches its maximum in the evening of the investigated day which may due to high vehicular traffic or/and human habits resulting in elevated concentrations of pollutants. Dataset treatment by Principal Component Analysis and Discriminant Function Analysis shows a good discrimination between samples collected at different times of the day. Moreover, Support Vector Machines were used and reached a classification success rate of 97.5 %. Thermal Desorption-Gas Chromatography-Mass Spectrometry (TD-GC-MS) technique was used to validate the developed e-nose system by identifying the composition of the analyzed air samples. The discrimination obtained by e-nose system was in good agreement with the TD-GC-MS results. This study demonstrates the usefulness of TD-GC-MS and e-nose, providing high accuracy in discriminating outdoor air samples collected at different times. This demonstrates the potential of using the e-nose as a rapid, easy to use and inexpensive environmental monitoring system. T2 - 2021 IEEE International Conference on Design & Test of Integrated Micro & Nano-Systems (DTS) CY - Sfax, Tunisia DA - 07.06.2021 KW - GC-MS KW - Electronic nose KW - Gas sensors KW - Urban air monitoring PY - 2021 DO - https://doi.org/10.1109/DTS52014.2021.9498110 SP - 1 EP - 6 AN - OPUS4-54401 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -