In this study, actual odor conditions were investigated in restaurants, livestock facilities, and major odor discharge facilities around daily life, and an odor modeling program was performed to find ways to improve odors in odor discharge facilities. The odor modeling results of restaurants around daily life showed that the complex odor concentration of large restaurants, which are close to residential areas, is higher than the acceptable complex odor standard at the receiving point. It was judged that a plan to increase the height of the restaurant odor outlets and a plan to reduce the amount of odor discharge was necessary. As a result of modeling the life odor of livestock housing facilities, when the distance from the housing facility is far away, the actual emission concentration is much lower than the acceptable emission concentration at the receiving point. It was judged that such facilities need to be reviewed for ways to reduce the emission of odorous substances, such as sealing the livestock housing facilities or improving the livestock environment. The main odor emission business sites that show complex odor concentration as 1,000 times or greater than the outlet odor emission standard were businesses associated with surfactant preparation, compounded feed manufacturing, textile dyeing processing, and waste disposal. Due to the separation distance and high exhaust gas flow rate, it was found that odor reduction measures are necessary. In this study, it was possible to present the allowable odor emission concentration at the discharge facilities such as restaurants, livestock houses, and industrial emission facilities by performing the process of verifying the discharge concentration of the actual discharge facility and the result of living odor modeling. It is believed that suitable odor management and prevention facilities can be operated.

MIt is important to estimate odor impact from the emission sources located in the industrial complex to near-by residential area. To understand modeling capacity in describing the odor dispersion, we examined an accuracy of odor modeling comparing with concentric measurements of sensory odors from the industrial complex. The odor measurements were carried out 6 times at 10 sites along the concentric circles and they were compared with odor modeling results using CALMET and CALPUFF. Although there are some discrepancies between the modeled and measured odor intensities, the model could depict key characteristics of odor dispersion patterns. The uncertainties in emission data and meteorology were main causes of the discrepancies. The odor modeling procedure developed in this study can be used in odor forecasting system and odor impact assessment. In order to improve the accuracy of odor modeling, the improvement of odor emission data and systematic monitoring of the odor using sensor network are necessary in future.

This study was carried out to find the optimal methods in odor dispersion modeling. The CALMET and CALPUFF recommended by US EPA were used in the study. The accuracy of 3 dimensional meteorological field was one of the important parameters in the modeling, To understand the sensitivity of CALMET according to meteorological input data, four Cases were tested and compared with the measurements. The four Cases with various input data were followed : Case 1 was surface and upper measured data, Case 2 was MM5 data only, Case 3 was surface weather station and MM5 data, Case 4 was surface weather station, upper-air weather station and MM5 data. The comparisons of wind speeds, wind direction and temperatures by CALMET model with observations under various input data showed that Case 4 was more accurate than the other Cases. The results of CALPUFF dispersion modeling were compared with odor complains data and they showed that there were similar patterns even if some discrepancies existed. CALPUFF dispersion modeling was also compared with odor monitoring station data, and there was a good agreement in the threshold odor concentrations. In order to get more accurate result for odor modeling, we need following additional measures: First, fine tuning of odor emission data with the consideration of variations of emission fate according to operation hour of the odor emitting facilities. Second, construction of continuous monitoring system(on-line GC, odor a sensor etc.) was necessary to monitor the odor compound concentrations.

A three-dimensional Computational Fluid Dynamics (CFD) with the renormalization group (RNG) k-ε turbulence model was used to simulate flow patterns and corresponding dispersion of passive H₂S pollutant in urban area with complex terrains. The major emission sources of H₂S considered in this study include the sewage disposal plant and the leather waste water disposal plant located the northwest direction from the residential area. In order to describe the flow and dispersion characteristics of H₂S in the complex terrain, the terrain data in the modeling domain was processed as the input data for the CFD model, while the previous studies were conducted in flat terrains. The recirculating flow zone was formed behind the buildings, and the pollutant concentration in the zone was noticeably high because of limited ventilation. The velocity profile and ventilation rate along the height were calculated to identify the effective zone of weak flow and re-circulation by the buildings and complex terrains. According to this study, the CFD modeling was demonstrated to be highly effective to simulate the effect of buildings and complex terrains on the flow and dispersion of odors. Detailed studies are desirable to further validate the odor dispersion with measurements under more complex flow conditions.

In order to validate the meteorological and odor dispersion modeling methods, the measured meteorological parameters such as wind speed and direction and odor intensities were compared with those calculated from the models. The CALMET and CALPUFF models which were recommended by USEPA were used to predict the meteorological variable and odor concentrations. The average time of odor concentration was 10 mins. to consider instantaneous response nature of the odors. The results showed that model predictions were in good agreement with the measurements. It is expected that the modeling method presented in this paper will be useful to assess the impact of odors from industrial complex to near-by residential areas.

Odor emission effects of unit processes in 10 livestock farms and 3 manure treatment facilities in Y and I cities, Kyonggido, were simulated using puff model after the odor emission rates were measured. 2 degree level of odor intensity and 1 degree level of it were predicted by the puff model in the adjacent area of odor emission source and within the 8km radius range of it, respectively. As real time odor modelling system was operated at specific manure based fertilizer making facility located in Y city, the highest odor concentration was predicted at the entrance of that facility and relatively lower odor intensity was estimated at the place more or less be aparted from the emission sources. The higher odor intensity was evaluated at dawn and evening because the odor was accumulated in case of stable air condition.

In this study, the environmental behavior of malodor pollutants (MPs:　H2S, CH3SH, DMS, and DMDS) was investigated around areas influenced by strong anthropogenic processes based on observations and modeling study (a CALPUFF dispersion model). The MP emission concentrations were measured from 8 industrial source regions (tire plants (S1-S3), waste water disposal plant (S4), and oil refinery (S5) in an urban center area and paper mill/incineration plant (S6) and livestock feedlots (S7-S8) in Ungsang area) in Yangsan city during a fall period in 2008 (21 October 2008). Overall, the most MPs emitted from the urban center area were found to affect the malodor pollution in their downwind areas during early morning (06:00 LST) and nighttime (18:00 and 21:00 LST), compared with those in the Ungsang area. For malodor intensity, the most MPs in the urban center area (especially S1 and S2) were found to be a significant contributor, whereas CH3SH and H2S in the Ungsnag area (especially S6) were the dominant contributor. The model study showed agreement in the spatial distributions of simulated MPs with those of the observations. The largest impact of MPs in the urban center area on the malodor pollution in its residential areas occurred at S1, S2, and S3 sites during nighttime, while that of MPs in the Ungsang area occurred at S6 and S8 sites. This may be caused mainly by the high MP emissions and in part by wind conditions (prevailing northeasterly winds with low wind speeds of 2-3 m/s).