In the last two decades, improvements in materials, sensors and machine learning technologies have led to a rapid extension of electronic nose (EN) related research topics with diverse applications. The food and beverage industry, agriculture and forestry, medicine and health-care, indoor and outdoor monitoring, military and civilian security systems are the leading fields which take great advantage from the rapidity, stability, portability and compactness of ENs. Although the EN technology provides numerous benefits, further enhancements in both hardware and software components are necessary for utilizing ENs in practice. This paper provides an extensive survey of the EN technology and its wide range of application fields, through a comprehensive analysis of algorithms proposed in the literature, while exploiting related domains with possible future suggestions for this research topic.

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Electronic Nose and Its Applications: A Survey

Formaldehyde and volatile organic compound (VOC) emissions from particleboard: Identification of odorous compounds and effects of heat treatment

The identification and health risk assessment of odor emissions from waste landfilling and composting.

Volatile organic compounds (VOCs) encompass hundreds of high production volume chemicals that have been used in a wide range of household and industrial products Widespread use of products that contain VOCs resulted in their ubiquitous occurrence in the environment, with elevated concentrations frequently found in indoor environments Human exposure to VOCs is pervasive and has been a topic of concern, due to the mutagenic, neurotoxic, genotoxic, and carcinogenic potentials of these chemicals Although several previous articles described toxic effects of VOCs, relatively less is known on their human exposure and body burdens VOCs have been determined in human breath condensate, blood, feces, and urine This review updates the information on the environmental occurrence, toxicity, sources and pathways of human exposure, metabolism and elimination, and biomonitoring of exposure to VOCs Indoor air is a major source of human exposure to VOCs Higher atmospheric concentrations of VOCs have been reported in Asian countries than in North American and European countries Elevated concentrations of four widely studied VOCs namely, benzene, toluene, ethylbenzene and xylene (BTEX) were reported in air from newly constructed or renovated homes (13–350 μg/m3) and e-waste workshops (245–3,10,000 μg/m3) BTEX were also found in consumer products such as shoe polish, whiteout, leather cleaner and ink at notable concentrations (eg, ~92,600 μg/g) Traditional methods of exposure assessment of VOCs entailed measurement of these chemicals in indoor air and determination of inhalation exposure dose SStudies on VOC exposure assessment mainly focused on occupationally exposed individuals Recent developments in biomonitoring of urinary metabolites of VOCs present accurate assessment of exposures and internal body burdens Biomonitoring studies of VOCs offer novel biomarkers for the assessment of airway inflammation, lung injury, neurological disorders, immune dysfunction and cancers in populations Considering the very high production volume (at billions of pounds annually), known toxicity, and widespread human exposures, significance of VOCs in eliciting adverse health effects in populations will be a subject of increasing public health concern for years to come

A review of environmental occurrence, toxicity, biotransformation and biomonitoring of volatile organic compounds

Assessment of the health risks and odor concentration of volatile compounds from a municipal solid waste landfill in China.

Evaluation of the chemical composition and correlation between the calculated and measured odour concentration of odorous gases from a landfill in Beijing, China

Assessment of odor activity value coefficient and odor contribution based on binary interaction effects in waste disposal plant

The olfactory evaluation function (e.g., odor intensity rating) of e-nose is always one of the most challenging issues in researches about odor pollution monitoring. But odor is normally produced by a set of stimuli, and odor interactions among constituents significantly influenced their mixture's odor intensity. This study investigated the odor interaction principle in odor mixtures of aldehydes and esters, respectively. Then, a modified vector model (MVM) was proposed and it successfully demonstrated the similarity of the odor interaction pattern among odorants of the same type. Based on the regular interaction pattern, unlike a determined empirical model only fit for a specific odor mixture in conventional approaches, the MVM distinctly simplified the odor intensity prediction of odor mixtures. Furthermore, the MVM also provided a way of directly converting constituents' chemical concentrations to their mixture's odor intensity. By combining the MVM with usual data-processing algorithm of e-nose, a new e-nose system was established for an odor intensity rating. Compared with instrumental analysis and human assessor, it exhibited accuracy well in both quantitative analysis (Pearson correlation coefficient was 0.999 for individual aldehydes (n = 12), 0.996 for their binary mixtures (n = 36) and 0.990 for their ternary mixtures (n = 60)) and odor intensity assessment (Pearson correlation coefficient was 0.980 for individual aldehydes (n = 15), 0.973 for their binary mixtures (n = 24), and 0.888 for their ternary mixtures (n = 25)). Thus, the observed regular interaction pattern is considered an important foundation for accelerating extensive application of olfactory evaluation in odor pollution monitoring.

The Regular Interaction Pattern among Odorants of the Same Type and Its Application in Odor Intensity Assessment

Odor intensity (OI) indicates the perceived intensity of an odor by the human nose, and it is usually rated by specialized assessors. In order to avoid restrictions on assessor participation in OI evaluations, the Vector Model which calculates the OI of a mixture as the vector sum of its unmixed components’ odor intensities was modified. Based on a detected linear relation between the OI and the logarithm of odor activity value (OAV—a ratio between chemical concentration and odor threshold) of individual odorants, OI of the unmixed component was replaced with its corresponding logarithm of OAV. The interaction coefficient (cosα) which represented the degree of interaction between two constituents was also measured in a simplified way. Through a series of odor intensity matching tests for binary, ternary and quaternary odor mixtures, the modified Vector Model provided an effective way of relating the OI of an odor mixture with the lnOAV values of its constituents. Thus, OI of an odor mixture could be directly predicted by employing the modified Vector Model after usual quantitative analysis. Besides, it was considered that the modified Vector Model was applicable for odor mixtures which consisted of odorants with the same chemical functional groups and similar molecular structures.

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Luchun Yan

Papers

Assessment of the health risks and odor concentration of volatile compounds from a municipal solid waste landfill in China.

Evaluation of the chemical composition and correlation between the calculated and measured odour concentration of odorous gases from a landfill in Beijing, China

Assessment of odor activity value coefficient and odor contribution based on binary interaction effects in waste disposal plant

The Regular Interaction Pattern among Odorants of the Same Type and Its Application in Odor Intensity Assessment

Use of a Modified Vector Model for Odor Intensity Prediction of Odorant Mixtures