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Academic literature on the topic 'Odour'

Author: Grafiati

Published: 4 June 2021

Last updated: 10 March 2023

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Journal articles on the topic "Odour"

1

Witherspoon, J. R., A. Sidhu, J. Castleberry, L. Coleman, K. Reynolds, T. Card, and G. T. Daigger. "Odour emission estimates and control strategies using models and sampling for East Bay Municipal Utility District's collection sewage system and wastewater treatment plant." Water Science and Technology 41, no. 6 (March 1, 2000): 65–71. http://dx.doi.org/10.2166/wst.2000.0094.

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For several years, public complaints regarding odours generated by East Bay Municipal Utility District's (EBMUD's) wastewater treatment plant and sewage collection system (SCS) have been increasing. In response, an Odor Control Master Plan was completed to develop near- and long-term odour abatement strategies for their wastewater system. The plan's strategies include using an advisory committee to assist in setting odour threshold levels, prioritizingodour sources, issuing an odour-status newsletter, and reviewing odour control options. The objective is to provide an odour-free community environment at least 99 percent of the year. This paper provides innovative approaches to estimate odour emissions and identify viable odour control options for SCSs through complete wastewater treatment. This paper also presents a CH2M HILL SCS odour model comparison to a comprehensive EBMUD sewage system corrosion study, illustrating that areas having high predicted odours also have high corrosion rates.

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Both, R., K. Sucker, G. Winneke, and E. Koch. "Odour intensity and hedonic tone - important parameters to describe odour annoyance to residents?" Water Science and Technology 50, no. 4 (August 1, 2004): 83–92. http://dx.doi.org/10.2166/wst.2004.0227.

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The Guideline on Odour in Ambient Air has been in use for many years for odour regulation in Germany . The main parameter that the odour regulation authority has to take into account is the odour frequency expressed as odour hours per year. In the guideline, limit values are given for the maximum odour frequency per year. These limit values are based on field investigations in which significant relationships between odour impact and odour annoyance was found. In these investigations, odour intensity did not yield a better description of the degree of annoyance caused to the residents. The hedonic tone was not mentioned. In a new research project finished in 2003, the influence of odour intensity and hedonic tone, in addition to odour frequency, has been assessed. Two installations emitting pleasant odours, two emitting neutral and two emitting unpleasant odours, have been selected. In each case grid field measurements by a panel were carried out, and the annoyance of the residents was assessed using a special questionnaire. The results of this project are: (1) A new method to measure odour intensity and hedonic tone in the field with data record forms was developed and validated. With this method, reliable and reproducible results are obtained. (2) The parameter odour frequency based on the system of “odour hours” is suitable and sufficient to predict the odour annoyance caused by unpleasant/neutral odours. (3) In the case of pleasant odours, hedonic tone has an abundantly clear effect on the dose-response relationship between odour frequency and annoyance. Pleasant odours have a significant lower annoyance potential than unpleasant/neutral odours. (4) The odour intensity has no additional influence on this relationship. If odours are recognisable then they can cause annoyance.

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Hazlett, Brian. "Conditioned reinforcement in the crayfish Orconectes rusticus." Behaviour 144, no. 7 (2007): 847–59. http://dx.doi.org/10.1163/156853907781476409.

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AbstractThe crayfish Orconectes rusticus can form a learned association between alarm odour (an unlearned signal of elevated predation risk) and a formerly neutral odour. In this study the odours of gyrinid beetles and of the snail Campeloma decisum were each paired with alarm odour and subsequently those odours significantly reduced feeding behaviours in the presence of food odour. To test for second-order (=conditioned) reinforcement, crayfish were first exposed simultaneously to one of the neutral odours and alarm odour and later exposed simultaneously to the two formerly neutral odours. When tested with the second neutral odour (which was not paired with alarm odour) the crayfish showed significant reductions in food-related behaviours, thus demonstrating second-order conditioning.

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Decottignies, V., A. Huyard, R. F. Kelly, and B. Barillon. "Development of a diagnostic tool: the wastewater collection network odour wheel." Water Science and Technology 68, no. 4 (August 1, 2013): 839–47. http://dx.doi.org/10.2166/wst.2013.265.

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The assessment of nuisance odour problems and the application of an effective odour management programme for the associated industrial activity may be achieved using a representative odour wheel and Odour Profile Analysis methodology. The odour wheel is a very useful tool for conducting odour quality control monitoring and developing a constructive dialogue regarding nuisance odours with the public. Previously, odours from wastewater treatment plant activities have been identified and described with a dedicated odour wheel. The oxidation state of the organic chemicals responsible for a given odour depends on multiple parameters specific to the individual wastewater collection networks (residence time of wastewater, topographic disposition and network slope, aeration and on line chemical treatment processes). This is especially important for odorous nitrogen, sulfur and volatile fatty acids. Trained sensory odour panels combined with chemical analyses have been used to study wastewater collection network odours and to adapt the wastewater odour wheel accordingly. The wastewater collection network odour wheel has been produced using the results of five sampling campaigns; eight out of the 11 odour families constituting the wastewater odour wheel have been identified and consequently validated for sewer networks. Different groups of odours have been perceived according to the presence or absence of wastewater effluents at the various sampling points.

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Suffet, I. H., and P. Rosenfeld. "The anatomy of odour wheels for odours of drinking water, wastewater, compost and the urban environment." Water Science and Technology 55, no. 5 (March 1, 2007): 335–44. http://dx.doi.org/10.2166/wst.2007.196.

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In the drinking water and air pollution fields, odour quality characterisation and intensity of each odour characteristic needs to be developed to evaluate the causes of the odours present. Drinking water quality characterisation has matured to the point where an “odour wheel” is described and the primary chemicals producing the odour are known and therefore a potential treatment can be defined from the odours reported. Sufficient understanding of the types of odorous compounds that can arise from wastewater and compost treatment processes and odours in the urban environment are starting to emerge. This article presents the anatomy of the odour wheels. It is hoped that the foundation of odour wheels will evolve as odour quality data are reported and linked with chemical causation. The compost and urban odour wheels are presented in print for the first time.

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Lobmaier, Janek S., Urs Fischbacher, Urs Wirthmüller, and Daria Knoch. "The scent of attractiveness: levels of reproductive hormones explain individual differences in women's body odour." Proceedings of the Royal Society B: Biological Sciences 285, no. 1886 (September 12, 2018): 20181520. http://dx.doi.org/10.1098/rspb.2018.1520.

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Individuals are thought to have their own distinctive body odour which reportedly plays an important role in mate choice. In the present study we investigated individual differences in body odours of women and examined whether some women generally smell more attractive than others or whether odour preferences are a matter of individual taste. We then explored whether levels of reproductive hormones explain women's body odour attractiveness, to test the idea that body odour attractiveness may act as a chemosensory marker of reproductive fitness. Fifty-seven men rated body odours of 28 healthy, naturally cycling women of reproductive age. We collected all odours at peak fertility to control for menstrual cycle effects on body odour attractiveness. Women's salivary oestradiol, progesterone, testosterone and cortisol levels were assessed at the time of odour collection to test whether hormone levels explain body odour attractiveness. We found that the men highly agreed on how attractive they found women's body odours. Interestingly, women's body odour attractiveness was predicted by their oestradiol and progesterone levels: the higher a woman's levels of oestradiol and the lower her levels of progesterone, the more attractive her body odour was rated. In showing that women's body odour attractiveness is explained by levels of female reproductive hormones, but not by levels of cortisol or testosterone, we provide evidence that body odour acts as a valid cue to potential fertility.

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Pérez, A., C. Manjón, J. V. Martínez, J. M. Juárez-Galan, B. Barillon, and L. Bouchy. "Odours in sewer networks: nuisance assessment." Water Science and Technology 67, no. 3 (February 1, 2013): 543–48. http://dx.doi.org/10.2166/wst.2012.595.

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As odour nuisance can affect the quality of life, the population is more and more demanding and in many cities sewers are a critical source of odours. Both factors can lead to increasing numbers of complaints due to the odour nuisance perceived by the residents, affecting also the public image of the sewer management companies. Odours associated with sewer networks are very heterogeneous, in as much as the different ‘types of odours’ encountered are sewer site specific. The state of the art indicates that there are three parameters that play an important role with the nuisance generated by an odour: hedonic odour tone, odour concentration and odour intensity. This paper presents the results of the study on odour nuisance carried out in different points of the sewer network, with the aim to assess the nuisance generated and identify which points of the sewer should be targeted to implement corrective actions. Considering the different parameters assessed, pumping stations have been identified as critical points of odour nuisance in the sewers, being recommended to implement an odour treatment system in order to guarantee the odour comfort of residents.

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McDonald, S., A. Lethorn, C. Loi, C. Joll, H. Driessen, and A. Heitz. "Determination of odour threshold concentration ranges for some disinfectants and disinfection by-products for an Australian panel." Water Science and Technology 60, no. 10 (November 1, 2009): 2493–506. http://dx.doi.org/10.2166/wst.2009.662.

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Taste-and-odour complaints are a leading cause of consumer dissatisfaction with drinking water. The aim of this study was to determine odour threshold concentration ranges and descriptors, using a Western Australian odour panel, for chlorine, bromine, chlorine added to bromide ions, the four major regulated trihalomethanes (THMs), and combined THMs. An odour panel was established and trained to determine odour threshold concentration ranges for odorous compounds typically found in drinking water at 25°C, using modified flavour profile analysis (FPA) techniques. Bromine and chlorine had the same odour threshold concentration ranges and were both described as having a chlorinous odour by a majority of panellists, but the odour threshold concentration range of bromine expressed in free chlorine equivalents was lower that that of chlorine. It is likely that the free chlorine equivalent residuals measured in many parts of distribution systems in Western Australia are comprised of some portion of bromine and that bromine has the potential to cause chlorinous odours at a lower free chlorine equivalent concentration than chlorine itself. In fact, bromine is the likely cause of any chlorinous odours in Western Australian distributed waters when the free chlorine equivalent concentration is between 0.04 and 0.1 mg L−1. Odour threshold concentrations for the four individual THMs ranged from 0.06–0.16 mg L−1, and the odour threshold concentration range was 0.10 ± 0.09 mg L−1 when the four THMs were combined (in equal mass concentrations). These concentrations are below the maximum guideline value for total THM concentration in Australia so odours from these compounds may possibly be observed in distributed waters. However, while the presence of THMs may contribute to any sweet/fragrant/floral and chemical/hydrocarbon odours in local drinking waters, the THMs are unlikely to contribute to chlorinous odours.

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Calafat, Consuelo, and Aurea Gallego-Salguero. "Livestock odour dispersion and its implications for rural tourism: case study of Valencian Community (Spain)." Spanish Journal of Agricultural Research 18, no. 2 (June 10, 2020): e0106. http://dx.doi.org/10.5424/sjar/2020182-15819.

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Aim of study: To study the relationship between the problem odours caused by livestock farms and the evolution of rural tourism.Area of study: A coastal region in Spain, the Valencian Community.Material and methods: The odour emission rates of 4,984 farms have been calculated, and the ambient odour concentration was determined to assess the odour nuisance. The odour concentration was modelled by applying the Gaussian model based on emission data and the most unfavourable meteorological conditions of the 45 climatic stations distributed throughout the analysis area. The dispersion model was implemented in a geographic information system, deducing the municipalities affected using the odour concentration thresholds. Furthermore, the evolution of rural tourism in municipalities was studied during the period of 2006-2017. The relationship between the evolution of rural tourism and the effects of odours is studied by means of a bivariate spatial correlation analysis.Main results: Pigs are the predominant species in areas with the greatest odour emission problems; ~ 29% of farms can result in annoyances among the population with odour concentrations greater than 5 OU/m3, and 46% of municipalities can be affected by odour problems. These odour nuisances had negative consequences in the municipality where measures were carried out to favour rural development, such as rural tourism. Municipalities were detected in which the problem of odours can be a deterrent to rural tourism, whereas in other municipalities it was observed that minimizing livestock activity can be a method to promote rural tourism.Research highlights: This study provides a methodology that allows modeling the odour dispersion of livestock and relates its implications to rural tourism. Municipalities have been identified where livestock odours can cause a stagnation of the rural tourism income.

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Hierl, Katharina, Ilona Croy, and Laura Schäfer. "Body Odours Sampled at Different Body Sites in Infants and Mothers—A Comparison of Olfactory Perception." Brain Sciences 11, no. 6 (June 21, 2021): 820. http://dx.doi.org/10.3390/brainsci11060820.

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Body odours and their importance for human chemical communication, e.g., in the mother–child relationship, are an increasing focus of recent research. Precise examination of sampling methods considering physiology and feasibility aspects in order to obtain robust and informative odour samples is therefore necessary. Studies comparing body odour sampling at different body sites are still pending. Therefore, we sampled axilla, breast, and head odour from 28 mother–infant dyads and examined whether odour perception differs with regard to the body site. The participating mothers were asked to evaluate their own and their infant’s body odour samples, as well as odours of two unfamiliar mother–infant dyads. We tested whether maternal pleasantness and intensity evaluation, as well as recognition ability of the odours differed between the body sites. In infants, the head odour exhibited slightly lower pleasantness ratings than axilla and breast, and intensity ratings did not differ between body sites. In mothers, body site affected intensity ratings but not pleasantness ratings, as the breast odour was rated as less intense compared with head and axilla. Across all body sites, mothers rated the own and their infant’s odour as less intense when compared with unfamiliar samples. Recognition ability did not differ between body sites, and in line with previous studies, mothers were able to recognize their own and their own infant’s odour above chance. In sum, our study extends the previous methodological repertoire of body odour sampling and indicates that the axilla, breast, and head of adults as well as infants serve as informative odour sources.

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Dissertations / Theses on the topic "Odour"

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Yeung, Shu-pui, and 楊樹培. "Odour mitigation measures for odour reduction in the Kai Tak Nullah." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2003. http://hub.hku.hk/bib/B3125570X.

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Webb, Paul. "Electronic odour sensing systems." Thesis, University of Warwick, 1992. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.332850.

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Elliott, Joanne Margaret. "Conducting polymer odour sensors." Thesis, University of Southampton, 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.242764.

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Sohn, Jae Ho. "Process studies of odour emissions from effluent ponds using machine-based odour measurement." University of Southern Queensland, Faculty of Engineering and Surveying, 2005. http://eprints.usq.edu.au/archive/00001511/.

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Odours caused by intensive piggery operations have become a major environmental issue in the piggery industry in Australia. Effluent ponds are the major source of odours in typical piggeries. It is assumed that the odour emissions from ponds are mainly driven by pond loading rate. However, there are few data to corroborate this concept. Allied to this is the need for a convenient and low cost method of odour measurement, which can be used as an alternative method for current olfactometry. The present odour measurement methods using olfactometry is time-consuming, expensive and often impractical because of its fundamental problem of using subjective human panels. In addition, one of the major problems in odour measurement lies in the air sampling method. Wind tunnels have been accepted as a preferred method for the sampling of odour from area sources. However, current wind tunnels do not consider meteorological factors, which directly affect the odour emission rates. A machine-based odour quantification method and a novel wind tunnel were developed and evaluated in this Ph D study. These methods were then used in a demonstration trial to investigate the effects of pond loading rate on odour emissions. The AromaScan A32S electronic nose, and an artificial neural network were used to develop the machine based odour quantification method. The sensor data analysed by the AromaScan were used to train an ANN, to correlate the responses to the actual odour concentration provided by a human olfactometry panel. Preprocessing techniques and different network architectures were evaluated through network simulation to find an optimal artificial neural network model. The simulation results showed that the two-layer back-propagation neural network can be trained to predict piggery odour concentrations correctly with a low mean squared error. The trained ANN was able to predict the odour concentration of nine unknown air samples with a value for the coefficient of correlation, r2 of 0.59. A novel wind tunnel was developed for odour sampling. The USQ wind tunnel was designed to have a capability to control wind speed and airflow rate. The tunnel was evaluated in terms of the aerodynamics of the airflow inside the tunnel, nd the gas recovery efficiency rate, in order to further improve the performance of the wind tunnel. The USQ wind tunnel showed that sample recovery efficiencies ranging from 61.7 to 106.8%, while the average result from the entire trial was 81.1%. The optimal sample recovery efficiency of the tunnel was observed to be 88.9% from statistical analysis. Consequently, it can be suggested that the tunnel will give estimates of the odour emission rate with significant level of precision. However, the tunnel needs to be calibrated to compensate for the error caused by different airflow rates and odour emission rates. In addition, the installation of a perforated baffle upstream of the sampling section was suggested to improve its performance. To investigate the relationship between the pond loading rate and odour emission rate, replicable experimental studies were conducted using a novel experimental facility and the machine based odour quantification method. The experimental facility consisted of reactor vessels to simulate the operation of effluent ponds and the USQ wind tunnel for odour sampling. A strong relationship between organic loading rate (OLR) and physical and chemical parameters was observed except pH and NH3-N. The pH was not affected by OLR due to the buffering capacity of piggery effluent. EC and COD were suggested as indicators to estimate the operating condition of the piggery effluent ponds because the regression results show that these two parameters can be predicted accurately by OLR. The time averaged odour emission rates from the reactor vessels showed a strong relationship with OLR. Consequently, it can be concluded that heavily loaded effluent ponds would produce more odours. The effect of hydraulic retention time (HRT) was examined. The HRT was increased from 30 days to 60 days, resulting in a significant decrease in odour emission rates from the reactor vessels. This decrease ranged from 59.1% to 54.9%, with an average of 57.1%. Therefore, it can be concluded that the increasing HRT will decrease the odour emission rate. This trial confirmed the value of the project methodology in obtaining unambiguous data on odour emission processes. However, more data are required for a wider range of OLR, HRT and other pertained variables before a usable model can be formulated.

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Andersson, Johan. "Odour Communication in Pieris Butterflies." Doctoral thesis, KTH, Chemistry, 2004. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-3699.

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McQueen, Rachel, and n/a. "Axillary odour in apparel textiles." University of Otago. Department of Clothing and Textile Sciences, 2007. http://adt.otago.ac.nz./public/adt-NZDU20070307.120703.

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The axilla is a major source of human body odour from which the characteristic musky, urinous or acidic odours emanate, and are predominantly due to bacterial metabolism of the protein-rich fluid secreted by the apocrine and sebaceous glands located in this area (Senol and Fireman, 1999). Clothing has been implicated in contributing to body odour intensity, possibly even increasing the intensity (Dravnieks, et al., 1968; Shelley, et al., 1953) by the transfer of secretions, skin debris and bacteria from the body to the fabric substrate. Despite much anecdotal evidence indicating that some fibres and fabrics are better at limiting odour intensity than others, there appears to be no published research confirming this. The purpose of this study therefore, was to determine whether fabrics varying in fibre content (cotton, wool, polyester) and fabric knit structure (interlock, single jersey, 1x1 rib) differed in the extent to which they retained and emanated axillary odour following wear, and whether the intensity of odour was linked to the number of bacteria transferred to the fabrics. A procedure for collecting odour on fabrics was developed as was a method for evaluating odour through use of a sensory panel. Total aerobic bacteria and aerobic coryneform bacteria extracted from the fabrics were counted to determine if an association between bacterial counts and fabrics existed. Sensory analysis recognises the unique capability of humans as odour-detecting instruments whereas, instrumental analysis has the potential to offer information on the concentration and identification of axillary compounds, which a human assessor cannot. To investigate a new method for detecting axillary odour on apparel fabrics, proton transfer reaction mass spectrometry (PTR-MS) was used to analyse volatiles emitted from fabrics differing in fibre type. After removal of garments from the human body, axillary odour can be detected on fabrics, with the intensity of odour being strongly influenced by the fibre type from which the fabrics had been made. Polyester fabrics emanated odour of high intensity, cotton that of mid-low odour intensity, and wool fabrics were low odour. Fabric structural properties such as thickness, mass per unit area and openness of knit structure also had an effect on odour intensity. However, as the principal factor influencing odour intensity was fibre, only fabrics characterised by a high intensity (i.e. polyester) were influenced by structural properties. Differences in odour intensity among fabrics were not necessarily related to bacterial numbers, and no �inherent antimicrobial� properties were evident for any of the fabrics. Bacterial populations persisted in all fabrics up to 28 days. A decline in numbers was apparent for high-odour polyester fabrics, while numbers in low-odour wool fabrics remained relatively stable. PTR-MS detected compounds likely to be short-chain carboxylic acids which increased in the headspace above the polyester fabrics after 7 days. However, this increase was not evident for either the wool or cotton fabrics. Therefore, bacterial numbers per se cannot be a predictor of the odour intensity emanating from fabrics at least on the basis of these fabrics and fibres. The intensity of axillary odour emanating from fabrics was found inversely related to fibre hygroscopicity. Keywords:fibre content, fabric structure, axillary odour, sensory analysis, bacteria, corynebacteria, instrumental analysis, PTR-MS

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Qu, Guoliang. "The measurement of odour concentration." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 2000. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape2/PQDD_0014/NQ60016.pdf.

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King, Russell. "Odour responses and discrimination strategies." Thesis, University of Cambridge, 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.313895.

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Huotari, M. (Matti). "Odour sensing by insect olfactory receptor neurons: measurements of odours based on action potential analysis." Doctoral thesis, University of Oulu, 2004. http://urn.fi/urn:isbn:9514275918.

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Abstract This thesis is a study of the odour responses of insect olfactory (or odorant) receptor neurons (ORN) of blowfly (Calliphora vicina), mosquito (Aedes communis), fruitflies (Drosophila melanogaster and D. virilis) and large pine weevil (Hylobius abietis). A power-law dependence (similar to Stevens' law in psychophysics) was obtained for the action potential rate of ORN responses vs. odour concentration in measurements with metal microelectrodes from blowfly ORNs and an analysis system was developed for the extracellularily recorded action potentials (or nerve pulses). Odour exposure sequences were used to study action potential rates quantitatively as a function of odour concentration in air exposure. For an odour exposure sequence, a known initial amount of the odour compound in a filter paper inside a Pasteur pipette at the beginning of repeated exposures caused a gradual dilution of the odour concentration in the exposure sequence. The concentration at each exposure was calculated according to the discrete multiple headspace extraction and dilution (DMHED) method. The estimated odour concentration was assumed to obey in the method an exponential law with respect to the exposure number in the sequence. Despite that many uncontrollable parameters remain for measuring quantitatively the characteristics of the ORNs, the results obtained, e.g., sensitivity, specificity, adaptability, and the power-law realation are both biologically and technically very interesting. A time-to-voltage converter (TVC) was utilized for the response analysis in determining action potential intervals originating from a single ORN. A precision analysis of TVC was also performed. With the mosquito (Aedes communis), fruitflies (Drosophila melanogaster and D. virilis) and large pine weevil (Hylobius abietis) antennae were tested for inhibitory and excitatory effects to find out repellents and attractants. Human sweat was found to cause strong stimulus exposure in the responses of the mosquito ORNs and Neutroil® caused inhibitory responses in pine weevil ORNs, respectively. The power-law exponents for blowfly ORNs were about 0.19 in the case of 1-hexanol (HX), 0.065 in the case of 1,4-diaminobutane (14DAB) and 0.32 in the case of butyric acid (BA). The corresponding Stevens' law exponent values 0.39 and 0.33 have been reported for HX and BA, respectively, by Patte et al. (1975).

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Ma, Yue 1971. "Software development for odour impact assessment." Thesis, McGill University, 2003. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=80128.

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Odour impacts are the source of many complaints in communities and, as such, methods for odour impact assessment are needed. Such assessments would benefit from the development of parameters that could be used to quantify and reflect the magnitudes of odour impacts experience by the community. Therefore, numerous parameters that can be used to assess odour impacts have been proposed in this research. These parameters account for variations in odour concentration, probability of response, degree of annoyance and population density that clearly influence the degree of impact of an odorous emission on a community. Most of these parameters require the evaluation of areas enclosed within contours and volumes under contours and, as such, are calculation intensive. In order to simplify the calculation of these parameters, algorithms have been developed and implemented into a user-friendly interface called OdorImp. This software was tested by applying it to three sets of synthetic data and two sets of data arising from actual case-studies. Comparisons were made between the results from OdorImp and exact values derived from simple cases and other values calculated using a commercial contour-evaluation program. It was demonstrated that the algorithms implemented in OdorImp are accurate and can be used to reliably evaluate the proposed odour impact parameters.

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Books on the topic "Odour"

1

Munang, Milton M. Odour nuisance. Manchester: UMIST, 1998.

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Body odour. London: Thorsons, 1994.

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Thilagavathi, G., and R. Rathinamoorthy. Odour in Textiles. Boca Raton: CRC Press, 2022. http://dx.doi.org/10.1201/9781003141426.

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Bajpai, Pratima. Biological Odour Treatment. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-07539-6.

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Belgiorno, Vincenzo, Vincenzo Naddeo, and Tiziano Zarra, eds. Odour Impact Assessment Handbook. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2012. http://dx.doi.org/10.1002/9781118481264.

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Brown, Amy. The odour of sanctity. Wellington (New Zealand): Victoria University Press, 2013.

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Corcoran, Paul. Electronic odour sensing systems. [s.l.]: typescript, 1992.

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Agency, Ireland Environmental Protection, ed. Odour impacts and odour emission control measures for intensive agriculture: Final report. Wexford: Environmental Protection Agency, 2001.

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New Zealand. Office of the Parliamentary Commissioner for the Environment. Odour nuisance control in New Zealand. Edited by Harford Barbara. Wellington, N.Z: The Commissioner, 1991.

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C, Nielsen V., Voorburg J. H, L'Hermite P. 1936-, and Commission of the European Communities. Expert Odours Group., eds. Odour and ammonia emissions from livestock farming. London: Elsevier Applied Science, 1991.

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Book chapters on the topic "Odour"

1

Dikecligil, Gulce Nazli, and Jay A. Gottfried. "Odour aesthetics." In The Routledge International Handbook of Neuroaesthetics, 148–71. London: Routledge, 2022. http://dx.doi.org/10.4324/9781003008675-9.

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Bajpai, Pratima. "General Introduction." In Biological Odour Treatment, 1–8. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-07539-6_1.

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Bajpai, Pratima. "Emissions from Pulping." In Biological Odour Treatment, 9–16. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-07539-6_2.

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Bajpai, Pratima. "Biological Methods for the Elimination of Odourous Compounds." In Biological Odour Treatment, 17–44. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-07539-6_3.

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Bajpai, Pratima. "New Reactors." In Biological Odour Treatment, 45–52. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-07539-6_4.

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Bajpai, Pratima. "Removal of Odours." In Biological Odour Treatment, 53–65. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-07539-6_5.

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Bajpai, Pratima. "Future Prospects." In Biological Odour Treatment, 67–72. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-07539-6_6.

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Shakoorjavan, Sima, Somaye Akbari, and Dawid Stawski. "Odour Evaluation Techniques in Textiles Area: Introduction of E-nose as a Potential Alternative Tool." In Odour in Textiles, 225–48. Boca Raton: CRC Press, 2022. http://dx.doi.org/10.1201/9781003141426-11.

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Broadhead, Rosie, Laure Craeye, and Chris Callewaert. "Odour Control or Inhibition Using Antimicrobial Finishing." In Odour in Textiles, 95–116. Boca Raton: CRC Press, 2022. http://dx.doi.org/10.1201/9781003141426-6.

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Rathinamoorthy, R., and G. Thilagavathi. "Herbal Antibacterial Agents as Odour Control Finish in Textiles." In Odour in Textiles, 117–42. Boca Raton: CRC Press, 2022. http://dx.doi.org/10.1201/9781003141426-7.

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Conference papers on the topic "Odour"

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Meišutovic-Akhtarieva, Marija, and Eglė Marčiulaitienė. "Research on Odours Emitted from Non-Hazardous Waste Landfill Using Dynamic Olfactometry." In Environmental Engineering. VGTU Technika, 2017. http://dx.doi.org/10.3846/enviro.2017.034.

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The article analyses the existing research on odour emissions from the passive odour source – municipal landfill for non-hazardous waste. The current research has been carried out in the Vilnius county, at the Kazokiškės landfill for regional municipal waste. Odour emissions were analysed using samples from waste of different age and at different outdoor air temperatures. The investigation determined the concentration of odourous volatile organic compounds (VOCs) formed in the landfill (mg/m3) and odour emissions (OUe/m2s). The odour concentration varied between 0.02 OUe/m2s (from 9 year old waste at 11oC) to 1.29 OUe/m2s (from 0–3 year old waste at minus 1 oC and minus 10 oC). It was determined that as temperature decreases (within the range of 11 to minus 10 oC), the concentration of odour emissions increases. The coefficient of correlation between the temperature of environment and the concentration of odours emitted from the landfill stood at minus 0.91.

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C A Ouellette, J C Segura, and J.J.R Feddes. "PERSISTENCE: ODOUR INTENSITY AND CONCENTRATION RELATIONSHIP FOR LIVESTOCK ODOURS." In 2006 CSBE/SCGAB, Edmonton, AB Canada, July 16-19, 2006. St. Joseph, MI: American Society of Agricultural and Biological Engineers, 2006. http://dx.doi.org/10.13031/2013.22092.

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Patil, Poonam, and Vinayak Kulkarni. "Odour detection and classification." In 2015 International Conference on Green Computing and Internet of Things (ICGCIoT). IEEE, 2015. http://dx.doi.org/10.1109/icgciot.2015.7380501.

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Barrington, S., L. Xingjun, D. Choinière, and S. Prasher. "Windbreaks for odour dispersion." In WASTE MANAGEMENT 2006. Southampton, UK: WIT Press, 2006. http://dx.doi.org/10.2495/wm060381.

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Xin, Jing. "Elizabeth's Epiphany in "Odour of Chrysanthemums"." In International Conference on Humanities and Social Science 2016. Paris, France: Atlantis Press, 2016. http://dx.doi.org/10.2991/hss-26.2016.90.

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Aeloor, Deepak, and Neeta Patil. "A survey on odour detection sensors." In 2017 International Conference on Inventive Systems and Control (ICISC). IEEE, 2017. http://dx.doi.org/10.1109/icisc.2017.8068688.

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Boeker, Peter, T. Haas, B. Diekmann, P. Schulze Lammer, Matteo Pardo, and Giorgio Sberveglieri. "Continuous Odour Measurement with Chemosensor Systems." In OLFACTION AND ELECTRONIC NOSE: Proceedings of the 13th International Symposium on Olfaction and Electronic Nose. AIP, 2009. http://dx.doi.org/10.1063/1.3156635.

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Marques, L., and A. T. De Almeida. "Electronic nose-based odour source localization." In 6th International Workshop on Advanced Motion Control. Proceedings. IEEE, 2000. http://dx.doi.org/10.1109/amc.2000.862824.

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H Guo, Z Yu, and C Lague. "Livestock Odour Dispersion Modeling: A Review." In 2006 CSBE/SCGAB, Edmonton, AB Canada, July 16-19, 2006. St. Joseph, MI: American Society of Agricultural and Biological Engineers, 2006. http://dx.doi.org/10.13031/2013.22109.

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Neale A Hudson, Godwin A Ayoko, David Duperouzel, Mark Dunlop, Erin Gallagher, and Gary Collman. "Odour Emissions from Permeable Pond Covers." In International Symposium on Air Quality and Waste Management for Agriculture, 16-19 September 2007, Broomfield, Colorado. St. Joseph, MI: American Society of Agricultural and Biological Engineers, 2007. http://dx.doi.org/10.13031/2013.23845.

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Reports on the topic "Odour"

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Mosquera, J., T. van Hattum, H. J. C. van Dooren, and S. Bokma. Effect of floor type on the ammonia and odour emission from veal calves housing. Wageningen: Wageningen Livestock Research, 2017. http://dx.doi.org/10.18174/392090.

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Mosquera, J., T. van Hattum, G. M. Nijeboer, J. M. G. Hol, H. J. C. van Dooren, and S. Bokma. Ammonia and odour emission from a veal calves housing system with V-shaped manure belt and ‘Groene Vlag’ slatted floor. Wageningen: Wageningen Livestock Research, 2019. http://dx.doi.org/10.18174/478308.

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W.T. McKean. Low Odor, High Yield Kraft Pulping. Office of Scientific and Technical Information (OSTI), December 2000. http://dx.doi.org/10.2172/809123.

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Atema, Jelle. Odor Plume Tracing: Lobster Inspired Algorithms. Fort Belvoir, VA: Defense Technical Information Center, September 2001. http://dx.doi.org/10.21236/ada415619.

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Schmeisser, Elmar, Kimberly A. Pollard, and Tomasz Letowski. Olfaction Warfare: Odor as Sword and Shield. Fort Belvoir, VA: Defense Technical Information Center, March 2013. http://dx.doi.org/10.21236/ada577342.

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Beauchamp, Gary. Odor Signals of Immune Activation and CNS Inflammation. Fort Belvoir, VA: Defense Technical Information Center, December 2014. http://dx.doi.org/10.21236/ada612446.

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Abdul-Bari, Mohammed, and Rachel McQueen. Comparison of Odor Intensity between Nylon and Polyester. Ames: Iowa State University, Digital Repository, November 2016. http://dx.doi.org/10.31274/itaa_proceedings-180814-1575.

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Koseff, Jeffrey R. Hydrodynamic Interactions Between Olfactory Appendages and Odor Plumes. Fort Belvoir, VA: Defense Technical Information Center, April 2000. http://dx.doi.org/10.21236/ada375850.

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Beauchamp, Gary. Odor Signals of Immune Activation and CNS Inflammation. Fort Belvoir, VA: Defense Technical Information Center, October 2013. http://dx.doi.org/10.21236/ada596566.

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Koziel, Jacek, Yael Laor, Jeffrey Zimmerman, Robert Armon, Steven Hoff, and Uzi Ravid. Simultaneous Treatment of Odorants and Pathogens Emitted from Confined Animal Feeding Operations (CAFOs) by Advanced Oxidation Technologies. United States Department of Agriculture, January 2009. http://dx.doi.org/10.32747/2009.7592646.bard.

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A feasibility study was conducted, aiming to explore the potential effectiveness of UV/TiO2/O3 photooxidation technologies for simultaneous treatment of odorant and pathogen emissions from livestock and poultry operations. Several key parameters were tested in laboratory (US) and semi-pilot (Israel) scale conditions including: the effects of light energy dose (treatment time and light intensity), relative humidity and air temperature, UV wavelength, presence of photocatalyst (TiO2) and the presence of ozone. Removal and conversion of odor, target gases (sulfur-containing volatile organic compounds S-VOCs, volatile fatty acids (VFAs), phenolics, and ammonia), and airborne pathogens was tested. Up to 100% removal (below method detection level) of S-VOCs, VFAs, and phenolics, the overall odor, and up to 64.5% of ammonia was achieved with optimized treatment. Treatments involving deep UV band (185 nm) and photocatalyst (TiO2) were more efficient in removal/conversion of odorous gases and odor. The estimate of the operational cost of treatment was based on measured emissions of several odorous VOCs from full scale, commercial swine farm ranges from $0.15 to $0.59 per finisher pig. This figure represents significantly lower cost compared with the cost of biofiltration or air scrubbing.

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