Odour Detection Methods: Olfactometry and Chemical Sensors

The complexity of the odours issue arises from the sensory nature of smell. From the evolutionary point of view olfaction is one of the oldest senses, allowing for seeking food, recognizing danger or communication: human olfaction is a protective sense as it allows the detection of potential illnesses or infections by taking into account the odour pleasantness/unpleasantness. Odours are mixtures of light and small molecules that, coming in contact with various human sensory systems, also at very low concentrations in the inhaled air, are able to stimulate an anatomical response: the experienced perception is the odour. Odour assessment is a key point in some industrial production processes (i.e., food, beverages, etc.) and it is acquiring steady importance in unusual technological fields (i.e., indoor air quality); this issue mainly concerns the environmental impact of various industrial activities (i.e., tanneries, refineries, slaughterhouses, distilleries, civil and industrial wastewater treatment plants, landfills and composting plants) as sources of olfactory nuisances, the top air pollution complaint. Although the human olfactory system is still regarded as the most important and effective “analytical instrument” for odour evaluation, the demand for more objective analytical methods, along with the discovery of materials with chemo-electronic properties, has boosted the development of sensor-based machine olfaction potentially imitating the biological system. This review examines the state of the art of both human and instrumental sensing currently used for the detection of odours. The olfactometric techniques employing a panel of trained experts are discussed and the strong and weak points of odour assessment through human detection are highlighted. The main features and the working principles of modern electronic noses (E-Noses) are then described, focusing on their better performances for environmental analysis. Odour emission monitoring carried out through both the techniques is finally reviewed in order to show the complementary responses of human and instrumental sensing

Real-time Odour Dispersion Modelling for Industrial Sites Application: State of the Art and Future Perspectives

In the field of odour impact assessments resulting from industrial activities, the use of atmospheric dispersion models appears to be crucial. These mathematical tools are able to estimate the ambient air odour concentration at the receptors nearby a plant, as indicated in some guidelines and laws. Generally, the odour concentration is evaluated through emission olfactometry monitoring, and subsequently, based on the dispersion modelling software, impact maps are created at specific percentiles (odour concentrations that are reached for a certain number of hours a year). However, in this way, it is not possible to know the specific odour event as it occurs; therefore, it would be ideal to have a real-time estimation of the odour fallout in the plant's surroundings. Currently, there exist some scientific papers and several commercial which propose some kind of real-time odour monitoring. Overall, these tools aim to monitor the odour events that occur on-site in real-time and to model atmospheric dispersion. The present work seeks to summarise what is currently available for real-time estimation of odour emission and dispersion, with the purpose of highlighting the potential, the eventual limitations, and the principal aspects to be studied and investigated. These considerations may help to develop a newer approach in order to stimulate the research towards the highest possible accuracy of these systems

Airborne chemical sensing with mobile robots

Airborne chemical sensing with mobile robots has been an active research areasince the beginning of the 1990s. This article presents a review of research work in this field,including gas distribution mapping, trail guidance, and the different subtasks of gas sourcelocalisation. Due to the difficulty of modelling gas distribution in a real world environmentwith currently available simulation techniques, we focus largely on experimental work and donot consider publications that are purely based on simulations

Environmental odour management by artificial neural network – A review

Unwanted odour emissions are considered air pollutants that may cause detrimental impacts to the environment as well as an indicator of unhealthy air to the affected individuals resulting in annoyance and health related issues. These pollutants are challenging to handle due to their invisibility to the naked eye and can only be felt by the human olfactory stimuli. A strategy to address this issue is by introducing an intelligent processing system to odour monitoring instrument such as artificial neural network to achieve a robust result. In this paper, a review on the application of artificial neural network for the management of environmental odours is presented. The principal factors in developing an optimum artificial neural network were identified as elements, structure and learning algorithms. The management of environmental odour has been distinguished into four aspects such as measurement, characterization, control and treatment and continuous monitoring. For each aspect, the performance of the neural network is critically evaluated emphasizing the strengths and weaknesses. This work aims to address the scarcity of information by addressing the gaps from existing studies in terms of the selection of the most suitable configuration, the benefits and consequences. Adopting this technique could provide a new avenue in the management of environmental odours through the use of a powerful mathematical computing tool for a more efficient and reliable outcome. Keywords: Electronic nose, Environmental pollution, Human health, Odour emission, Public concer

Dynamic modelling of electronic nose systems

This thesis details research into the modelling of the dynamic responses of electronic nose systems to odour inputs. Most electronic nose systems contain an array of between 4 and 32 odour sensors, each of which respond in varying degrees to a range of different gaseous stimuli. In almost all electronic nose systems in use today, the steady-state responses of the odour sensors are extracted and passed to one of a variety of pattern recognition systems. The primary aim of this thesis is to investigate the use of information contained within the dynamic portion of the sensor response for odour classification. System identification techniques using linear time-invariant black box models are applied to both extracted steady state and full dynamic data sets collected from experiments designed to assess the ability of an electronic nose system to discriminate between the strain and growth phases of samples of cyanobacteria (blue-green algae). The results obtained are compared with those obtained elsewhere using the same data, analysed with nonlinear artificial neural networks. A physical model for the electrochemical mechanisms resulting in the measured responses is translated into a mathematical model. This model consists of a system of coupled nonlinear ordinary differential equations. The model is analysed, and the theoretical structural identifiability of the model is investigated and established. The parametric model is then fitted to data collected from experiments with simple (single chemical species) odours. An odour discrimination method is developed, based upon the extraction of physically significant parameters from experimental data. This technique is evaluated and compared with the previously explored black box modelling techniques. The discrimination technique is then extended to the analysis of complex odours, again using the cyanobacteria data sets. Successful classification rates are compared with those obtained earlier in the thesis, and elsewhere with neural networks applied to steady state data

Measuring odours in the environment vs. dispersion modelling: A review

Source characterization alone is not sufficient to account for the effective impact of odours on citizens, which would require to quantify odours directly at receptors. However, despite a certain simplicity of odour measurement at the emission source, odour measurement in the field is a quite more complicated task. This is one of the main reasons for the spreading of odour impact assessment approaches based on odour dispersion modelling. Currently, just a very limited number of reports discussing the use of tracer gas dispersion experiments both in the field and in wind tunnels for model validation purposes can be found in literature. However, when dealing with odour emissions, it is not always possible to identify a limited number of tracer compounds, nor to relate analytical concentrations to odour properties, thus giving that considering single odorous compounds might be insufficient to account for effective odour perception. For these reasons, the possibility of measuring of odours in the field, both as a way for directly assessing odour annoyance or for verifying that modelled odour concentrations correspond to the effective odour perception by humans, is still an important objective. The present work has the aim to review the techniques that can be adopted for measuring odours in the field, particularly discussing how such techniques can be used in alternative or in combination with odour dispersion models for odour impact assessment purposes, and how the results of field odour measurements and model outputs can be related and compared to each other

Olfaction-enhanced multimedia: Perspectives and challenges

This is the post-print version of the Article. The official published version can be accessed from the link below - Copyright @ 2011 Springer VerlagOlfaction—or smell—is one of the last challenges which multimedia and multimodal applications have to conquer. Enhancing such applications with olfactory stimuli has the potential to create a more complex—and richer—user multimedia experience, by heightening the sense of reality and diversifying user interaction modalities. Nonetheless, olfaction-enhanced multimedia still remains a challenging research area. More recently, however, there have been initial signs of olfactory-enhanced applications in multimedia, with olfaction being used towards a variety of goals, including notification alerts, enhancing the sense of reality in immersive applications, and branding, to name but a few. However, as the goal of a multimedia application is to inform and/or entertain users, achieving quality olfaction-enhanced multimedia applications from the users’ perspective is vital to the success and continuity of these applications. Accordingly, in this paper we have focused on investigating the user perceived experience of olfaction-enhanced multimedia applications, with the aim of discovering the quality evaluation factors that are important from a user’s perspective of these applications, and consequently ensure the continued advancement and success of olfaction-enhanced multimedia applications

Electronic noses for environmental monitoring applications

Electronic nose applications in environmental monitoring are nowadays of great interest, because of the instruments’ proven capability of recognizing and discriminating between a variety of different gases and odors using just a small number of sensors. Such applications in the environmental field include analysis of parameters relating to environmental quality, process control, and verification of efficiency of odor control systems. This article reviews the findings of recent scientific studies in this field, with particular focus on the abovementioned applications. In general, these studies prove that electronic noses are mostly suitable for the different applications reported, especially if the instruments are specifically developed and fine-tuned. As a general rule, literature studies also discuss the critical aspects connected with the different possible uses, as well as research regarding the development of effective solutions. However, currently the main limit to the diffusion of electronic noses as environmental monitoring tools is their complexity and the lack of specific regulation for their standardization, as their use entails a large number of degrees of freedom, regarding for instance the training and the data processing procedures