Environmental fundamental facilities have different odor emission characteristics depending on the type of treatment facilities. To overcome the limitations of the olfactometry method, research needs to be conducted on how to calculate the dilution factor from the individual odor concentrations. The aim of this study was to determine the air dilution factor estimated from manually measured concentration data of individual odor substances (22 specified odor species) in three environmental treatment facilities. In order to calculate the optimum algorism for each environmental fundamental facility, three types of facilities were selected, the concentration of odor substances in the exhaust gas was measured, and the contribution of the overall dilution factor was evaluated. To estimate the dilution factor, four to six algorism were induced and evaluated by correlation analysis between substance concentration and complex odor data. Dilution factors from O municipal water treatment (MWT) and Y livestock wastewater treatment (LWT) facilities showed high level of dilution factors, because concentration levels of hydrogen sulfide and methylmercaptan, which had low odor threshold concentrations, were high. In S food waste treatment (FWT) facility, the aldehyde group strongly influenced dilution the factor (dominant substance: acetaldehyde, i-valeraldhyde and methylmercaptan). In the evaluation of four to six algorism to estimate the dilution factor, the vector algorism (described in the text) was optimum for O MWT and Y LWT, while the algorism using the sum of the top-three dominant substances showed the best outcome for S FWT. In further studies, estimation of the dilution factor from simultaneously monitored data by odor sensors will be developed and integrated with the results in this study.

This study aimed to investigate the characteristics of odor-causing substances in Yeosu national industrial complex, which is designated as an “Odor management Area,” in 2019 and the surrounding area. The sampling sites were divided into three areas: five sites within the industrial complex (Management area), one site within the borders of the complex (Boundary area), and two sites within residential areas (Affected area) affected by odors. The odor compounds were collected from March to September at dawn, daytime, and night. The analytical items were meteorological data, complex odor, legally-designated 22 odor compounds and other VOCs. Complex odor was exceeded on the limit three occasions at two sites in the management area. Ammonia, two types of sulfides, three types of aldehydes, and five VOCs were detected to be within the emission standards. Ammonia was the most frequently detected compounds. Aldehydes and sulfur compounds made a relatively high contribution to the level of odors. Therefore, aldehydes and sulfur compounds should be reduced first in order to prevent odors from occurring.

The effect of the change in air inflow velocity has been investigated at the opening of the malodor emission source to determine its influence on the Complex odor concentration. Both the Complex odor collection efficiency and concentrations were measured according to the change in airflow velocity. When the air inflow velocity was 0.1 m/s, it was observed that some of the generated gas streams were diffused to the outside due to low collection efficiency. In contrast, only the increased gas collection volume up to 0.5 m/s showed no substantial reduction of the Complex odor concentration, which indicates an increase in the size of the local exhaust system as well as the operation cost for the Complex odor control device. When the air inflow velocity reached 0.3 m/s, the Complex odor concentrations not only were the lowest, but the odorous gas could also be collected efficiently. The air inflow velocity at the opening of the malodor emission source was considered the key factor in determining the gas collection volume. Therefore, based on the results of this study, an optimal air inflow velocity might be suggestive to be 0.3 m/s.

This study was conducted to analyze the characteristics of odorous components that have been generated from the downtown sewer system based on twenty-three survey items for complex odor and designated offensive odor. As a result of the research, the contribution rates for the causative materials of the odor indicated 73.5% of hydrogen sulfide, 26.0% of methyl mercaptan, 0.4% of dimethyl sulfide, and 0.1% of dimethyl disulfide. The occurrence for the odorous materials according to sampling site revealed data of which contribution rates showed 56.9% of hydrogen sulfide and 36.8% of methyl mercaptan from the combined sewer system in the business district; whereas the combined sewer system in the residential area showed 16.4% of dimethyl sulfide and 4.3% of dimethyl disulfide. The seasonal occurrence rate of the odor materials was observed higher in summer and lower in winter And, the combined sewer system in the business district recorded the highest concentration of 4.61 ppm of hydrogen sulfide among the sampling site. An hourly occurrence rate for the odor materials consistently showed the greatest increase between 11:00 and 14:00 at each location and showed a decreasing tendency afterward.

The concentrations of volatile organic compounds (VOCs) and odor-inducing substances were measured using selected ion flow tube mass spectrometers (SIFT-MS) and a drone equipped with an air quality monitoring system. SIFT-MS can continuously measure the concentration of VOCs and odor-inducing substances in realtime without any pre-treating steps for the sample. The vehicle with SIFT-MS was used for real-time measurement of VOC concentration at the site boundaries of pollution sources. It is possible to directly analyze VOCs concentration generated at the outlets by capturing air from the pollution sources with a drone. VOCs concentrations of nine spots from Banwol National Industrial Complex were measured by a vehicle equipped with SIFT-MS and were compared with the background concentration measured inside the Metropolitan Air Quality Management Office. In three out of the nine spots, the concentration of toluene, xylene, hydrogen sulfide, and methyl ethyl ketone was shown to be much higher than the background concentration. The VOCs concentrations obtained using drones for high-concentration suspected areas showed similar tendencies as those measured using the vehicle with SIFTMS at the site boundary. We showed that if both the drone and real-time air quality monitoring equipment are used to measure VOCs concentration, it is possible to identify the pollutant sources at the industrial complex quickly and efficiently check sites with high concentrations of VOCs.

In this study, real-time monitoring of air quality using a real-time mobile monitoring system was conducted to identify the emission characteristics and current status of air pollutants and odorous substances that are mainly generated in domestic dyeing industrial areas and to trace the pollutant sources. The concentration of toluene in the industrial area was detected up to 926.4 ppb, which was 3 to 4 times higher than that of other industrial areas. The concentration of methylethylketone was 124.7 ppb and the concentration of dichloromethane was 129.5 ppb. Acrolein concentration was highest at E point at 521.6 ppb, methanol concentration was highest at D point at 208.8 ppb, and acetone concentration was highest at M and N points at 549.3 ppb. The most frequently detected concentration of pollutants in the air quality monitoring results in the industrial area was, in descending order, toluene > methanol > acrolein > dichloromethane > acetone, which was similar to the chemical emissions used in the industrial area by the Pollutant Release and Transfer Register data. The concentration of odorous substances measured in real time was compared with the concentration of minimum detection, and the concentration of hydrogen sulfide was about 10 times higher than the concentration of minimum detection at A point, which was judged to be the main odorous cause of A point. In the future, if the real-time mobile measurement system is constructed to automatically connect wind direction/wind speed, PRTR (Pollutant Release and Transfer Register) data and SEMS (Stack Emission Management System) data, etc., it was judged that more accurate monitoring could be performed.