The correlation analysis between odor sensor and air dilution olfactometry method with odor emission facilities was performed for the real-time evaluation of odor emitted from the 13 facilities. The total correlation was less significant for all facilities due to various emission characteristics of odor. The correlation for the individual facility, however, showed a higher correlation coefficient (R=0.7371~0.9897). Especially, the strong correlation (above 0.9) was observed for the industry type with the odor characteristics like tobacco, styrofoam, acetic acid, and burning smell. The repeated odor measurements using the odor sensor showed good reproducibility with the mean relative standard deviation of 5.06%. The odor sensor could be useful tools for identifying and evaluating odor with an olfactometry in field, if the use and proofreading of the odor sensor are improved by a standardized method.

The object of this study is to investigate the relationship between the air dilution sensory test and the threshold odor number (TON) method for evaluating the odor of domestic wastewater, plating plant wastewater, food plant wastewater and lake water. The dilution factor of raw wastewater evaluated by the air dilution sensory test was in the order of food plant > plating plant > domestic > lake, and that evaluated by the threshold odor number method was in the order of food plant > domestic > plating plant > lake. The same results were obtained when the raw wastewater and lake water were diluted 2 and 5 times with pure water. The relative geometric standard deviation determined from the threshold values of each panel on the air dilution sensory test was much larger than that calculated from results derived from the threshold odor number method. The relative geometric standard deviation obtained from samples with a low dilution factor was greater. There was a very good linear correlation (correlation coefficient = 0.968~1.000) between the air dilution sensory test and the threshold odor number method. But, the reduction in odor intensity (the slopes of regression curves) by dilution was dependent on the types of the odor-emission sources.

This study evaluated the concentration(OU/m3) of a complex odor being discharged from tire, feedstuff, bakery, paper, casting and painting manufacturing process, correlation between odor concentration(OU/m3) and the odor sensor was investigated. 4 type(A, B, C, D) gas sensors of metal oxide compounds are used in this study. Each odor sample of manufacturing process is diluted with odorless air and diluted odor samples were prepared for five different concentrations. Correlation results(R) of odor sample of tire, feedstuff, bakery, paper manufacturing process ware 0.86~0.99, and odor sample of casting, painting manufacturing process ware more than 0.93. Thus the odor concentration(OU/m3) evaluation by odor sensor was to determine the possible. In particular odor sensor B and D are likely to be effective for evaluation of odor concentration. However, odor samples before evaluation is needed the calibration process depending on the field odor sample to field apply.

2011년에 전국 79개 악취검사기관을 대상으로 공기희석관능법에 대한 숙련도 시험을 실시하였다. 악취방지법의 부지 경계선과 악취 배출원의 배출허용기준을 모사한 2개의 합성복합악취를 숙련도 시험물질(proficiency testing materials, PTM)로 사용 하였다. 부지 경계선 시료는 7ppm의 톨루엔과 7ppm m-자일렌의 복합악취로 구성하였으며, 배출구 시 료는 10ppm DMS (dimethyl sulfide)와 10ppm DMDS (dimethyl disulfide)의 복합악취로 구성하였다. 숙련도 시험 결과는 기준값으로 평균과 중간값을 사용하고, 목표표준편차로 일반 표준편차, 로버스트 표준편차 및 변동계수를 사용하여 Z-점수를 평가하였다. 시험결 과의 변동계수는 PTMs의 냄새강도가 증가함에 따라 감소하였다. 복합악취에 대한 숙련 도 시험 결과는 악취희석배율보다 로그 스케일의 악취지수를 사용하여 평가하는 것이 적 절했다. 두 PTMs에 대한 참여기관의 Z-점수를 변동계수, 표준편차, 그리고 로버스트 표 준편차를 사용하여 평가할 때, 참여기관의 95%가 숙련도 기준을 만족하였다. 목표 표준 편차를 변동계수의 20%로 설정하였을 때 참여기관의 만족도 비율은 부지경계와 출구 PTM 시료에 대해 각각 90%와 95%로 양호하였다. 이러한 결과들로부터 부지경계와 출 구의 복합악취를 모사한 두 합성 PTMs 모두 복합악취의 숙련도 시험물질로 적합하였다.

In this study, odors in N industrial complex in Incheon city were measured by using air dilution olfactory method, odor sensor and instrumental analysis method. Three industry categories which are plating industry, equipment manufacturing industry and petrochemical manufacturing industry were classified and the correlation of data was evaluated based on the measurement result. The correlation coefficient between the air dilution olfactory method and the odor sensor device utilizing method in 69 points was 0.562. The correlation coefficients in the classified industry categories were observed 0.889 in the plating industry, 0.723 in the equipment manufacturing industry and 0.832 in the petrochemicals manufacturing industry. It shows that when the correlation coefficient is over 0.75, they have a strong correlation. In this result, we could identify the ease of availability of the correlation using industry classification.

In this study, we attempted to evaluate the relationship between air dilution sensory test and instrumental detection method for samples containing various odorous compounds. For the purpose of our comparative study, the analysis of malodor compounds was made using a total of 70 samples collected from three industrial sectors which include: Food & beverage, Waste treatment and cleaning, and Miscellaneous facilities. The results of instrumental analyses converted into three different odor indices (the odor concentration (OC), odor quotient (OQ), and odor intensity (OI)) were used to statistically sort out individual odorous components with the major impact. The results of multiple regression analysis between air dilution ratio value and instrumental odor concentration (of individual 12 compounds) indicate that butyraldehyde, CH₃SH, NH₃, and H₂S are the major odorous compounds that contribute most significantly to odor strength for the sample types investigated in this study.

In this study, the characteristics of panel members with various factors on the odor judgement using a air dilution olfactory method were investigated. The frequency distribution curves of Dev(D/Ttotal) and Dev(D/T₃) were found to be a normal distribution, but it appears that values around median on the distribution curve of Dev(D/T₃) were relatively sparse. Factors of outlier deviate from a confidence interval of 99% were found to be male ＜ female, smoker ＜ non-smoker, experience ＜ non-experience, and bad ＜ common state of health. Data obtained from female panel members appears high positive(+) deviation on the odor judgement.