• Journal of Korean Society for Atmospheric Environment
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• v.18 no.5
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• pp.393-400
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• 2002

Separation distance between industrial source and residential areas to avoid odor annoyance was investigated using AUSPLUME model. A Gaussian plume model (AUSPLUME) for the dispersion was used to calculate odor emission from ground level area source. Using the dispersion model to calculate ambient odor concentrations, the separation distance between industrial source and residental areas was defined by %HA (percentage of highly annoyed person) and odor percentile concentration (C98). The result was compared with the separation distance of various nation guidelines for livestock buildings. The calculated separation distance for industrial source showed similar pattern comparing with various guidelines for livestock buildings.

• Journal of Korean Society for Atmospheric Environment
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• v.27 no.1
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• pp.87-96
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• 2011

In this study, the AERMOD dispersion model was used for predicting odor concentrations and back-calculating industrial area source odor emission rate. The studied area was Sihwa industrial complex in Korea. Odor samples were collected during two days over a year period in 2009. The comparison between the predicted and observed concentrations indicates that the AERMOD model could fairly well predict average downwind odor concentrations. The results show odor emission rates of Sihwa industrial complex area source were ranged from 0.204 to 2.320 $OUms^{-1}$ (average 0.476 $OUms^{-1}$). The results also show wind speed and direction are important parameters to the odor dispersion.

• Journal of Korean Society for Atmospheric Environment
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• v.23 no.1
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• pp.1-13
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• 2007

This study was carried out to evaluate the applicability of the odor source tracking using wind field and fingerprint as a solution tool. First of all, CALMET and HYSPLIT modeling system, and database of odor discharge companies were utilized to track odor from industrial complexes. Secondly, industrial odor fingerprint was made by listing on the 19 domestic industries, and compared with foreign data to assess the representative, and thus the similarity was 86.7%. On the modeling experiment, Sihwa industrial complex did not show any difference because the matching rates of day and night were 49.5% and 50.0%, respectively. However, the Banwol and Sihwa industrial complexes did show some differences due to odor facility density. Separately, in this study, odor samples were obtained from 10 odor discharging companies, located in the Sihwa and Banwol industrial complexes, They were compared with the results of odor tracking modeling. The matched companies were 4 of 10 by three cases of tracking, while the fingerprint and industry of odor monitoring networks and companies matched each other. Therefore, this study confirmed the approach applicability of source tracking system using the fingerprint.

• Journal of Environmental Science International
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• v.11 no.4
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• pp.383-389
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• 2002

Odor sources of a chemical plant in Ulsan were surveyed and temperatures, humidities and flow rates of each exhaust gas were measured. The air samples collected from each source were transferred to the laboratory for sensory test and their odor concentrations were investigated. The odor emission rate of each source was estimated from the recorded results and assigned the sources expected to be needed for the odor prevention policy using the simple prediction equation of the affection by malodor to the nearest residential area. From the total odor emission rate of the examined plant and the relation table for expectable affection area it was concluded that total odor emission of this plant might be decreased for the prevention of residential complaint.

• Journal of Korea Multimedia Society
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• v.13 no.8
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• pp.1171-1182
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• 2010

In this paper, odor classification and source analysis methods are proposed to trace odor sources in th air at the specific place and period. It is necessary to generate representative patterns in order to classify the various odors efficiently. We, therefore, create 67 kinds of odor representative patterns measured from the main sources. considering the air mixed with various odors, several mixed representative patterns for odor sources are generated with the combination of two or three different odors. In addition, the weight of odor sources for an odor from a civil complaint region are computed using pseudo inverse method. As a result, we can trace and identify the odor sources to lead to a specific odor and the contribution of each source. The results of this study will be useful for settling the civil complaint related with odors.

• Asian Journal of Atmospheric Environment
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• v.5 no.1
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• pp.1-7
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• 2011

This study assesses the dispersion and emission rates of odor form industrial area source. CALPUFF and AERMOD Gaussian models were used for predicting downwind odor concentration and calculating odor emission rates. The studied region was Seobu industrial complex in Korea. Odor samples were collected five days over a year period in 2006. In-site meteorological data (wind direction and wind speed) were used to predict concentration. The BOOT statistical examination software was used to analyze the data. Comparison between the predicted and field sampled downwind concentration using BOOT analysis indicates that the CALPUFF model prediction is a little better than AERMOD prediction for average downwind odor concentrations. Predicted concentrations of AERMOD model have a little larger scatter than that of CALPUFF model. The results also show odor emission rates of Seobu industrial complex area were an order of 10 smaller than that of beef cattle feed lots.

• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.6
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• pp.698-703
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• 2006

This paper proposes an approach to search for the odor source using an autonomous mobile robot equipped with vision and odor sensors. The robot is initially navigating around the specific area with vision system until it looks for an object in the camera image. The robot approaches the object found in the field of view and checks it with the odor sensors if it is releasing odor. If so, the odor is classified and localized with the classification algorithm based on neural network The AMOR(Autonomous Mobile Olfactory Robot) was built up and used for the experiments. Experimental results on the classification and localization of odor sources show the validity of the proposed algorithm.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.1
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• pp.49-54
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• 2011

In this paper, we represent a mobile robot which can recognize chemical odor, measure concentration, and track its source indoors. The mobile robot has the function of smell that can sort several gases in experiment such as ammonia, ethanol, and their mixture with neural network algorithm and measure each gas concentration with fuzzy rules. In addition, it can not only navigate to the desired position with vision system by avoiding obstacles but also transmit odor information and warning messages earned from its own operations to other nodes by multi-hop communication in wireless sensor network. We suggest the way of odor sorting, concentration measurement, and source tracking for a mobile robot in wireless sensor network using a hybrid algorithm with vision system and gas sensors. The experimental studies prove that the efficiency of the proposed algorithm for odor recognition, concentration measurement, and source tracking.

• The Research Journal of the Costume Culture
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• v.10 no.5
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• pp.555-564
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• 2002

The purpose of this research was to analysis compounds of unpleasant odor from the cotton fabrics in dehydration and drying process during washing. The cotton fabrics were treated with various commercial detergents and fabric softener or cationic surfactants such as Cetyltrimethylammonium bromide(CTAB) and Benzalkonium chloride(BC), then dehydrated and dried. The compounds of odor impregnated in fabric were detected by using CC-MS. The results are as follows: The fabrics treated with a powder-type detergent, CTAB and BC gave out compounds unpleasant odor. n-Butyraldehyde and isobutyaldehyde produced during microorganism growth were revealed as source of the compounds of the unpleasant odor. However, no aldehydes were detected from the fabrics treated with commercial fabric softener which seems to act as a deodorizer.

• Journal of Environmental Science International
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• v.14 no.1
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• pp.81-89
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• 2005

As a typical example of simultaneous analysis of the odorous compounds, the volatile organic compounds from inventory sources in Seongseo industrial area were concentrated and analyzed with thermal desorber/GC/MSD, and major malodorous compounds were estimated. Odor intensity and odor concentration was analyzed simultaneously During a period from November in 2002 to December in 2003, this study was conducted to evaluate malodor emission characterization in major treatment facilities. The major components were Dimethyl sulfide, Dimethyl disulfide, Methyl mercaptane, Ammonia, Benzene, Toluene, m,p-xylene, o-xylene, Styrene, 1,2,4­T.M.B and 1,3,5-T.M.B. Among the six major inventory sources, the odor unit concentration of Night-soil disposal facilities was the highest, $669\~2344\;ou/m^{3}.$