Toxic gases detection and tolerance level classification using machine learning algorithms

Abstract— with rapid population increases, people are facing the challenge to maintain healthy conditions. One of the challenges is air pollution. Due to industrial development and vehicle usage air pollution is becoming a high threat to human life. This air pollution forms through various toxic contaminants. This toxic contamination levels increase and cause severe damage to the living things in the environment. To identify the toxic level present in the polluted air various methods were proposed by the authors, But failed to detect the tolerance level of toxic gases. This article discusses the methods to detect toxic gasses and classify the tolerance level of gasses present in polluted air. Various sensors and different algorithms are used for classifying the tolerance level. For this purpose “Artificial Sensing Methodology” (ASM), commonly known as e-nose, is a technique for detecting harmful gases. SO2-D4, NO2-D4, MQ-135, MQ136, MQ-7, and other sensors are used in artificial sensing methods (e-nose). “Carbon monoxide, Sulfur dioxide, nitrogen dioxide, and carbon dioxide” are all detected by these sensors. The data collected by sensors is sent to the data register from there it is sent to the Machine learning Training module (ML) and the comparison is done with real-time data and trained data. If the values increase beyond the tolerance level the system will give the alarm and release the oxygen

Electronic Noses for Biomedical Applications and Environmental Monitoring

This book, titled “Electronic Noses for Biomedical Applications and Environmental Monitoring”, includes original research works and reviews concerning the use of electronic nose technology in two of the more useful and interesting fields related to chemical compounds detection of gases. Authors have explained their latest research work, including different gas sensors and materials based on nanotechnology and novel applications of electronic noses for the detection of diverse diseases. Some reviews related to disease detection through breath analysis, odor monitoring systems standardization, and seawater quality monitoring are also included

Fast determination of gasoline related compounds in groundwater by differential ion mobility spectrometry

Das Grundwasser kann z.B. durch auslaufende Benzintanks verunreinigt werden. Die Analyse der Benzininhaltsstoffe im Grundwasser wird in der Regel im Labor unter Verwendung von Standardverfahren durchgeführt. Die Pobenahme und Analyse im Labor ist zeitaufwendig und teuer. Daher ist es sehr wichtig, Methoden zur schnellen Vor-Ort Analyse zu entwickeln. Obwohl schon Technologien für die schnelle Vor-Ort- Analyse von Benzin kontaminiertem Grundwasser entwickelt wurden und auch schon kommerziell erhältlich sind, sind diese jedoch nicht in der Lage Benzin aus komplexen Matrices zu unterscheiden. Die Differential-Ionenmobilitätsspektrometrie (DMS) kann verschiedene Benzininhaltsstoffe abhängig von den Mobilitäten der chemischen Verbindungen bei hohen und niedrigen elektrischen Felder trennen. Wird die DMS mit einer Mikro-Gaschromatographiesäule gekoppelt, so können die Zielbenzinverbindungen aus der komplizierten Benzinmatrix und der Umgebung in kurzer Zeit unterschieden werden. In dieser Arbeit wurde ein schnelles Verfahren, basierend auf der GC -DMS zur Detektion von Benzinihaltsstoffen im Grundwasser entwickelt. Die Benzininhaltsstoffe Benzol, Toluol, Ethylbenzol und Xylol ( BTEX ) wurden als Fingerprint Substanzen ausgewählt. Eine kurze MXT -5 Säule wurde für die Trennung der Zielverbindungen ( BTEX ) im Grundwasser verwendet. Die Analysenzeit betrug weniger als 2 min. Um die Nachweisgrenzen und die Empfindlichkeit zu verbessern, wird eine UV-Lampe (Krypton) als lonisierungsquelle anstelle 63Ni verwendet. Nach der Optimierung der Messbedingungen konnten für BTEX mit GC- UV -DMS folgende Nachweisgrenzen ermittelt werden: 0,15 mg / L für Toluol, 0,12 mg / L für Ethylbenzol, 0,15 mg / l für m-Xylol , 0, 16 mg / L für p- Xylol, 0,16 mg /l o -Xylol. Diese ermittelten Werte sind 30 bis 330 -fach niedriger als die durch GC - 63Ni -DMS erhaltenen Daten. Allerdings ist die ermittelte Nachweisgrenze von Benzol mit 0,08 mg/ L oberhalb der MCL, die von der WHO empfohlen wird . Schließlich wurde die GC - UV -DMS verwendet um die Konzentrationen der BTEX in 17 Realgrundwasserproben zu analysieren. Im Vergleich mit dem Referenzverfahren, sind die Ergebnisse der EXT mit den GC - UV -DMS erhaltenen Ergebnisse in guter Übereinstimmung mit denen der Referenzmethode. Um die Feldbedingungen zu simulieren, wird ein Simulationssystem aufgebaut. Die Temperatur-und Matrixkomponenten beeinflussen die Diffusion von BTEX im Grundwasser. Die Ergebnisse zeigen, dass mit der auf GC - UV -DMS basierende Methode, ein schnelles Online Monitoring von Grundwasser möglich ist.Groundwater can be contaminated when e.g. gasoline tanks leak. The analysis for gasoline related compounds in groundwater is generally done on lab using standard methods. Due to sampling and lab analysis, groundwater monitoring is time consuming and expensive. It is very important to develop methods to fast monitor before lab analysis. Although the technologies developed for rapid onsite analysis of gasoline contaminated groundwater exist in commercial market, they still face the technical limitation to distinguish the gasoline from complex matrices. Different ion mobility spectrometry (DMS) can separate different gasoline related compounds dependent on the mobilities of chemical compounds at high and low electric fields. Coupled to micro gas chromatography column, DMS can distinguish the target gasoline compounds from the complicated gasoline matrix and the surrounding environment in short time. In this work, a fast method based on GC-DMS for the detection of gasoline related compounds in groundwater has been developed. The gasoline related compounds benzene, toluene, ethylbenzene and xylene (BTEX) were selected as fingerprint substances. A short column MXT-5 was utilized for separating the target compounds (BTEX) in groundwater. The analysis time is less than 2 min. In order to improve the detection limits and the sensitivity, a krypton UV lamp is utilized as ionization source instead of 63Ni. After optimizing the operation condition, The detection limits of BTEX determined by GC-UV-DMS are 0,15 mg/L for toluene, 0,12 mg/L for ethylbenzene, 0,15 mg/L for m-xylene, 0,16 mg/L for p-xylene, 0,16 mg/L for o-xylene, respectively, which are 30 to 330 fold lower than those obtained by GC-63Ni-DMS. However, the detection limit of benzene is 0,08 mg/L, which is above the MCL recommended by WHO. Finally, the GC-UV-DMS is used to analyze the concentrations of BTEX in 17 real groundwater samples collected from contaminated sites. In comparison with the reference method, the results of EXT obtained by this GC-UV-DMS are in good agreement with those obtained by reference method. To simulate the on field condition, a simulation system is built up. Temperature and matrix components influence the diffusion of BTEX in groundwater. The results reveal that the method based on GC-UV-DMS is feasible to be applied as a fast system to monitor the groundwater

Volatolomics: A broad area of experimentation

Chemical analysis (detection and monitoring) of compounds associated with the metabolic activities of an organism is at the cutting edge of science. Volatile metabolomics (volatolomics) are applied in a broad range of applications including: biomedical research (e.g. disease diagnostic tools, personalized healthcare and nutrition, etc.), toxicological analysis (e.g. exposure tool to environmental pollutants, toxic and hazardous chemical environments, industrial accidents, etc.), molecular communications, forensics, safety and security (e.g. search and rescue operations). In the present review paper, an overview of recent advances and applications of volatolomics will be given. The main focus will be on volatile organic compounds (VOCs) originating from biological secretions of various organisms (e.g. microorganisms, insects, plants, humans) and resulting fusion of chemical information. Bench-top and portable or field-deployable technologies-systems will also be presented and discussed

Nuevas contribuciones de las técnicas de movilidad iónica ambiental y clínico

Enmarcada dentro de las técnicas de vanguardia se encuentran las técnicas de movilidad iónica o IMS atendiendo a sus siglas en inglés. Entre sus ventajas cabe destacar, su rapidez, su sensibilidad a nivel de trazas y su simplicidad de análisis, las cuales han contribuido al creciente interés para su desarrollo y aplicación en áreas tales como farmacéutica, análisis forense, biomedicina y análisis ambiental [1]. La aplicación directa de las técnicas de IMS para la determinación de compuestos de interés en matrices complejas tales como muestras ambientales y biológicas constituye todavía un reto que resulta difícil de abordar debido a que muchos métodos analíticos y las herramientas necesarias para poder usarlos de forma rutinaria se encuentran actualmente en fase de desarrollo. Existiendo además el compromiso de mejorar los problemas asociados a la baja selectividad y en algunas ocasiones de sensibilidad, los cuales pueden solucionarse mediante el acoplamiento a columnas de cromatografía de gases y módulos de extracción para la separación y preconcentración de los analitos de interés. Como consecuencia de lo anteriormente expuesto, el objetivo principal de esta Tesis Doctoral ha sido el desarrollo de metodologías analíticas mediante el uso de IMS en el campo ambiental y clínico

Detecting Rhinosinusitis With an Electronic Nose Based on Differential Mobility Spectrometry

Sairauksia voidaan mahdollisesti diagnosoida hajuaistin avulla. Koiran hajuaisti on ihmisen hajuaistia parempi ja kenties tunnetuin esimerkki koirien hajuaistin hyödyntämisestä on huumekoirien käyttö lentokentillä. Tutkimukset ovat myös osoittaneet, että koirat pystyvät tunnistamaan esimerkiksi syöpiä ja mikrobien aiheuttamia infektioita erilaisista näytteistä. Hajuaistilla aistittavat molekyylit ovat haihtuvia orgaanisia yhdisteitä. Nykyään niitä voidaan analysoida tarkoitukseen soveltuvilla laitteilla kuten elektronisella nenällä, joka tuottaa kokonaiskuvan kyseisen näytteen sisältämien molekyylien seoksesta. Liikkuvuuserospektrometria (differential mobility spectrometry, DMS) ei ole elektroninen nenä alkuperäisen määritelmän mukaan, mutta tuottaa vastaavanlaista informaatiota kuin perinteiset elektroniset nenät. Lisäksi se erottaa molekyylejä paremmalla herkkyydellä. DMS:n käyttöä ei kuitenkaan ole aikaisemmin tutkittu korva-, nenä- ja kurkkutautien saralla. Äkillisen nenän sivuontelotulehduksen aiheuttaa tyypillisesti virus tai bakteeri. Näiden aiheuttama oirekuva on kuitenkin hyvin samankaltainen ja vaikea erottaa oireiden tai kliinisen tutkimuksen perusteella. Äkillistä viruksen aiheuttamaa nenän sivuontelotulehdusta hoidetaan liian usein antibiootilla. Pitkäaikaisen nenän sivuontelotulehduksen oirekuvaan kuuluu muun muassa yli 12 viikkoa kestäneet nenän tukkoisuus ja niistämisen tarve. Kuitenkin monet muutkin nenän ja nenän sivuonteloiden sairaudet tai anatomiset syyt voivat aiheuttaa vastaavanlaisia oireita. Pitkäaikaisen nenän sivuontelotulehduksen diagnoosin varmentaminen vaatiikin nenän sivuonteloiden kuvantamista tietokonetomografialla, jota ei kuitenkaan ole käytettävissä perusterveydenhuollossa. Äkillisen ja pitkäaikaisen nenän sivuontelotulehduksen diagnosoimisen tueksi olisi hyödyllistä saada nopea, luotettava ja potilaaseen vähän kajoava keino. Tämä väitöskirja keskittyy äkillisen ja pitkäaikaisen nenän sivuontelotulehduksen diagnostiikkaan DMS:llä ja koostuu neljästä osatyöstä. Ensimmäisessä osatyössä DMS:llä analysoitiin viittä nenän sivuontelotulehduksen aiheuttajabakteeria elatusmaljoilta. Toisessa osatyössä tutkittiin äkillistä nenän sivuontelotulehdusta sairastavia potilaita. Heille tehtiin poskiontelopunktio ja tällä menetelmällä saatu märkäerite analysoitiin DMS:llä, minkä jälkeen tuloksia verrattiin samasta märkäeritteestä tehtyyn bakteeriviljelyyn. Kolmannessa osatyössä selvitettiin hengitysilman keräämistä nenäontelosta näytteeksi ja sen analytiikkaa DMS:llä. Neljännessä osatyössä verrattiin hengitysilmanäytteitä DMS:llä pitkäaikaista nenän sivuontelotulehdusta sairastavien potilaiden ja nenän väliseinän vinoudesta kärsivien potilaiden välillä. Väitöskirjan kaikissa osatöissä data-analyysi tehtiin koneoppimismenetelmin, joiden avulla selvitettiin DMS:n herkkyyttä ja tarkkuutta erottaa näytteitä toisistaan. Tutkimuksissa havaittiin, että DMS erottaa erittäin hyvin toisistaan yleiset sivuontelotulehduksen aiheuttajat bakteerimalja-analyysin perusteella. Lisäksi havaittiin, että DMS erottaa erittäin hyvällä osuvuudella poskiontelon märkäeritteestä bakteeripositiivisen ja -negatiivisen näytteen verrattuna perinteiseen viljelymenetelmään. Hengitysilman keräys ja analysointi DMS:llä osoittautui käyttökelpoiseksi menetelmäksi. Pitkäaikaisesta nenän sivuontelotulehduksesta kärsivät potilaat pystyttiin erottamaan hyvin potilaista, joilla nenän tukkoisuuden aiheutti nenän väliseinän vinous. Alustavien tulosten perusteella DMS toimii hyvin nenän sivuontelotulehduksen diagnostiikassa. Tutkimukset osoittivat, että DMS soveltuu hyvin erilaisten näytetyyppien mittaukseen ja se erottaa ryhmiä varsin hyvin toisistaan. Ilman keräys nenäontelosta keräyspussiin osoittautui käyttökelpoiseksi menetelmäksi, jota voidaan hyödyntää tulevaisuudessa etenkin nenään ja nenän sivuonteloihin liittyvissä tutkimuksissa.The sense of smell can potentially be used to diagnose diseases. However, the sense of smell in humans has lower sensitivity and discrimination capability compared to animals such as dogs. Probably the most well-known example of using a dog’s sense of smell is drug detecting dogs at airports. Research studies have demonstrated that dogs can identify samples acquired from patients with cancer or infection. The molecules detected by sense of smell are volatile organic compounds (VOCs). Nowadays, it is possible to measure these compounds, for example, with an electronic nose (eNose). An eNose is a device that analyses gas-phase mixtures and produces a measurement signature that represents the spectrum of the molecules found in the mixture. Differential mobility spectrometry (DMS) is not a traditional eNose but produces comparable information and, in addition, has a higher sensitivity. DMS has not previously been used in otorhinolaryngologic studies. Acute rhinosinusitis (ARS) is typically caused by a virus or bacteria. As both produce similar symptoms, differentiating them based on symptoms or clinical examination is a challenging task, which often leads to the overprescription of antibiotics. Chronic rhinosinusitis (CRS) involves, for instance, nasal blockage and discharge lasting at least 12 weeks. As many other rhinologic diseases cause similar symptoms, the definite diagnosis of CRS warrants computed tomography imaging, which is not available in primary care. Therefore, there is a need for a rapid, accurate and non-invasive method to diagnose ARS and CRS. This dissertation examines the diagnostics of ARS and CRS with DMS and consists of four studies. First, five common rhinosinusitis bacteria in vitro were analysed with DMS. Second, maxillary puncture and aspiration of the contents were performed on patients with ARS. The acquired pus was analysed with DMS, and the results were compared to the traditional bacterial culture of the pus. Third, nasal air from volunteers was aspirated into collection bags using a pump built for this purpose. The results were then compared to room air samples and the feasibility of the method was evaluated. Fourth, patients with CRS without nasal polyps and patients with deviated nasal septum were studied. Aspirated nasal air was collected in the same way as in the third study and analysed with DMS. The ability of DMS to distinguish patients in different groups was then evaluated. The data analysis employed in the studies involved machine learning methods which were used to examine the sensitivity and specificity of DMS to distinguish samples. The results reveal that DMS can separate common rhinosinusitis bacteria in vitro with very good accuracy. Furthermore, DMS shows very good accuracy to distinguish bacterial positive and bacterial negative samples compared to bacterial cultures. The method used for aspirating the nasal air and subsequent analysis with DMS proved to be a useful method. The nasal air samples were perfectly distinguished from room air samples. In addition, DMS demonstrates good accuracy to discriminate patients with CRS without nasal polyps from patients with deviated nasal septum by analysing nasal air. The studies in this dissertation were pilot studies and the results are affected by small sample size. However, cross-validation provides confidence of the reliability of the classifier. The studies demonstrate that DMS can analyse different sample types and distinguish groups from each other. The aspiration of nasal air was shown to be practicable and can be used in further studies of rhinologic diseases

Gas phase biomarkers for disease diagnostics by ion-mobility

The detection of Volatile Organic Compounds (VOCs) has shown great potential as a noninvasive and rapid diagnostic tool for early cancer and disease detection. The use of VOCs for early disease detection has several advantages and can provide valuable insights into disease pathophysiology. This PhD research aimed to investigate the presence of VOCs in urine samples and the development of chemical fingerprints for various cancers, namely, bladder cancer, colorectal cancer, prostate cancer and hepatocellular cancer, and diseases such as fibrosis and urinary tract infection. This study investigated the possibility of using analytical techniques such as Gas Chromatography-Ion Mobility Spectrometry (GC-IMS), Gas Chromatography-Time of Flight-Mass Spectrometry (GC-TOF-MS), and Electronic Noses (eNoses) for the identification of these biomarkers. The study findings demonstrate the presence of particular VOCs in urine samples. We found that GC-IMS and GC-TOF-MS was able to distinguish between some of the cancers with 100% sensitivity and 100% specificity. During this research, a total of 46 VOCs were identified as relevant for the identification of these cancer groups, with some VOCs being specific to each type of cancer. 13 VOCs with the highest concentration in urine samples of bladder cancer patients were identified in the course of this study. The electronic noses utilized in this research were the AlphaMOS FOX 4000 and PEN3 eNose. The AlphaMOS FOX 4000 was able to distinguish between some of the cancer groups with 100% sensitivity and 100% specificity. Although, PEN3 eNose did not exhibit 100% sensitivity in distinguishing between the different cancer groups, it still demonstrated high levels of sensitivity and specificity. Overall, the study contributes to the advancement of research on the detection of VOCs and provides insights into the potential for using analytical techniques for the detection of VOCs in urine samples. However, there are some limitations to these technologies such as some of them require specialized training and expertise to operate and interpret results accurately and the cost of some of these technologies can be high, making them less accessible. Another limitation is that the detection of VOCs can be affected by factors such as sample collection, handling, and storage, which can impact on the accuracy of results. The second aim of this research presents the development of an in-house device based on Photo Ionisation Detector (PID) for the detection of VOCs. The thesis focuses on the xxii evaluation of the performance of the developed PID+ based device for detecting ISB. Throughout this thesis, we have examined the electronics of PID+. Experiments were conducted to assess the performance of the PID+ at various flow rates, ISB (Isobutylene) gas concentrations, bias voltages of detector plates, and amplifier circuit gains. The results of the study demonstrate the feasibility and efficacy of the developed device in detecting ISB with high response. It was observed that increasing the flow rate of the sample gas has the potential to improve the response time of the detector. Additionally, it was observed that the concentration of the target VOCs, in this case ISB gas, was a crucial factor that affected the response of the detector, with higher concentrations resulting in higher sensitivities. However, it was noted that elevating either the flow rate or the concentration of the target VOCs beyond a certain threshold could lead to the saturation of the output. During the testing of the two versions of PID+, the performance of the PID+ was significantly improved. Nevertheless, more extensive research is required to verify the validity of the results of this study with respect to various VOCs

Potential of volatile organic compounds as markers of entrapped humans for use in urban search-and-rescue operations

Volatile organic compounds emitted by a human body form a chemical signature capable of providing invaluable information on the physiological status of an individual and, thereby, could serve as signs-of-life for detecting victims after natural or man-made disasters. In this review a database of potential biomarkers of human presence was created on the basis of existing literature reports on volatiles in human breath, skin emanation, blood, and urine. Approximate fluxes of these species from the human body were estimated and used to predict their concentrations in the vicinity of victims. The proposed markers were classified into groups of different potential for victim detection. The major classification discriminants were the capability of detection by portable, real-time analytical instruments and background levels in urban environment. The data summarized in this review are intended to assist studies on the detection of humans via chemical analysis and accelerate investigations in this area of knowledge.Comment: 38 page

Homekasvuston mittaaminen ioniliikkuvuusspektrometrillä

Tiivistelmä. Tässä diplomityössä tutkittiin, soveltuuko ioniliikkuvuusspektrometria homeen tunnistukseen sisäilmaa mittaamalla. Mikrobiologisille epäpuhtauksille altistumisella on todettu olevan terveysvaikutuksia. Tästä syystä on tärkeää havaita mahdolliset epäpuhtaudet sisäilmasta. Tutkimusta varten kehitettiin mittausjärjestelmä ja testattiin differentiaalista ioniliikkuvuusspektrometriä ja sen käyttöä sisäilma-anturina. Työssä käsiteltiin anturin teoriaa sähkötekniikan ja elektroniikan näkökulmasta. Aikaisempien tutkimusten perusteella selvitettiin homeiden aineenvaihduntatuotteista sellaisia yhdisteitä, joiden avulla homeita voitaisiin tunnistaa sisäilmaa mittaamalla. Tutkimuksen kohteena oli Stachybotrys chartarum-home, jota kasvatettiin kipsilevyllä mittauksia varten. Työssä testattiin anturin ja mittasysteemin kykyä tunnistaa aineenvaihduntatuotteita. Alustavien tulosten perusteella vaikuttaa siltä, että differentiaalista ioniliikkuvuusspektrometria voidaan käyttää tunnistamaan aktiivinen mikrobikasvusto kipsilevyltä. Työssä käytetyn mittausjärjestelmän näytteenottoa tulee jatkokehittää. Tämä työ antaa pohjan ioniliikkuvuusspektrometriin perustuvan mittajärjestelmän jatkokehittämiselle homekasvuston havaitsemiseen.Mold detection with ion mobility spectrometry. Abstract. The suitability of ion mobility spectrometry was investigated in this thesis for detection of molds by measuring indoor air. Exposure to microbial pollutants have been associated with health effects. It is important to detect potential contaminants for that reason. A measurement system was developed and differential ion mobility spectrometry was tested as an indoor air quality sensor. The sensor theory was explored from the perspective of electrical engineering. Based on previous studies, metabolic compounds that could be used to identify molds by measuring indoor air was investigated. The subject of the study was Stachybotrys chartarum-mold and it was cultivated on a plasterboard for test measurements. The ability of the sensor and measuring system to detect metabolic products was tested in the work. Based on preliminary results, differential ion mobility spectrometer can be used to detect microbial growth on plasterboard. The sampling of the measurement system used in the work must be further developed. This thesis provides a basis for the further development of a measurement system based on ion mobility spectrometry for detecting mold growth

Review of low-cost sensors for the ambient air monitoring of benzene and other volatile organic compounds

This report presents a literature review of the state of the art of sensor based monitoring of air quality of benzene and other volatile organic compounds. Combined with information provided by stakeholders, manufacturers and literature, the review considered commercially available sensors, including, PID based sensors, semiconductor (resistive gas sensor) and portable on-line measuring devices (sensor arrays). The bibliographic collection includes the following topics: sensor description, field of application in fixed, mobile, indoor and ambient air monitoring, range of concentration levels and limit of detection in air, model descriptions of the phenomena involved in the sensor detection process, gaseous interference selectivity of sensors in complex VOC matrix, validation data in lab experiments and under field conditions.JRC.C.5-Air and Climat