Several samplers using gravimetric methods such as high-volume air sampler, MiniVol portable sampler, personal environmental monitor(PEM) and cyclone were applied to determine the concentrations of fine particles in atmospheric condition. Comparative evaluation between high-volume air sampler and MiniVol portable sampler for PM10, and between MiniVol portable sampler and PEM was undertaken from June, 2003 to January 2004. Simultaneously, meteorological conditions such as wind speed, wind direction, relative humidity and temperature was measured to check the factors affecting the concentrations of fine particles. In addition, particle concentrations by cyclone with an aerodynamic diameter of 4 ㎛ were measured. Correlation coefficient between high- volume air sampler and portable air sampler for PM10 was 0.79 (p<0.001). However, the mean concentration for PM10 by high-volume air sampler was significantly higher than that by MiniVol portable sampler (p=0.018). Correlation coefficient between Minivol portable sampler and PEM for PM2.5 was 0.74 (p<0.001), and the measured mean concentrations for PM2.5 did not show significant difference. Difference of the measured concentrations of fine particle might be explained by wind speed and humidity among meteorological conditions. Particle concentration differences by measurement samplers were proportional to the wind speed, but inversely proportional to the relative humidity, though it was not a significant correlation.

Indoor air quality is affected by source strength of pollutants, ventilation rate, decay rate, outdoor level, and so on. Although technologies measuring these factors exist directly, direct measurements of all factors are not always practical in most field studies. The purpose of this study was to develop an alternative method to estimate these factors by application of multiple measurements. For the total duration of 30 days, daily indoor and outdoor NO2 concentrations were measured in 30 houses in Brisbane, Australia, and for 21 days in 40 houses in Seoul, Korea, respectively. Using a box model by mass balance and linear regression analysis, penetration factor (ventilation divided by sum of air exchange rate and deposition constant) and source strength factor (emission rate divided by sum of air exchange rate and deposition constant) were calculated. Subsequently, the ventilation and source strength were estimated. In Brisbane, the penetration factors were 0.59±0.14 and they were unaffected by the presence of a gas range. During sampling period, geometric mean of natural ventilation was estimated to be 1.10±1.51 ACH, assuming a residential NO2 decay rate of 0.8 hr-1 in Brisbane. In Seoul, natural ventilation was 1.15±1.73 ACH with residential NO2 decay rate of 0.94 hr-1. Source strength of NO2 in the houses with gas range (12.7±9.8 ppb/hr) were significantly higher than those in houses with an electric range (2.8±2.6 ppb/hr) in Brisbane. In Seoul, source strength in the houses with gas range were 16.8±8.2 ppb/hr. Conclusively, indoor air quality using box model by mass balance was effectively characterized.

Volatile organic compounds (VOCs) are present in essentially all natural and synthetic materials from petrol to flowers. In this study, indoor and outdoor VOCs concentrations of houses, offices and internet-cafes were measured and compared simultaneously with personal exposures of each 50 participants in Asan and Seoul, respectively. Also, factors that influence personal VOCs exposure were statistically analyzed using questionnaires in relation to house characteristics, time activities, and health effects. All VOCs concentrations were measured by OVM passive samplers (3M) and analyzed with GC/MS. Target pollutants among VOCs were Toluene, o-Xylene, m/p-Xylene, Ethylbenzene, MIBK, n-Octane, Styrene, Trichloroethylene, and 1,2-Dichlorobenzene. Indoor and outdoor VOCs concentrations measured in Seoul were significantly higher than those in Asan except Ethylbenzene. Residential indoor/outdoor (I/O) ratios for all target compounds ranged from 0.94 to 1.51 and I/O ratios of Asan were a little higher than those of Seoul. Relationship between personal VOCs exposure, and indoor and outdoor VOCs concentrations suggested that time-activity pattern could affect the high exposure to air pollutant. Factors that influence indoor VOCs level and personal exposure with regard to house characteristics in houses were building age, inside smoking and house type. In addition insecticide and cosmetics interestingly affected the VOCs personal exposure. Higher exposure to VOCs might be caused to be exciting increase and memory reduction, considering the relationship between measured VOCs concentrations and questionnaire (p<0.05).

Indoor and outdoor nitrogen dioxide (NO2) concentrations were measured and compared with measurements of personal exposures of 95 persons in Seoul, Korea and 57 persons in Brisbane, Australia, respectively. Time activity diary was used to determine the impact on NO2 exposure assessment and microenvironmental model to estimate the personal NO2 exposure. Most people both Seoul and Brisbane spent their times more than 90% of indoor and more than 50% in home, respectively. Personal NO2 exposures were significantly associated with indoor NO2 levels with Pearson coefficient of 0.70 (p<0.01) and outdoor NO2 levels with Pearson coefficient of 0.66 (p<0.01) in Seoul and of 0.51 (p<0.01) and of 0.33 (p<0.05) in Brisbane, respectively. Using microenvironmental model by time weighted average model, personal NO2 exposures were estimated with NO2 measurements in indoor home, indoor office and outdoor home. Estimated NO2 measurements were significantly correlated with measured personal exposures (r = 0.69, p<0.001) in Seoul and in Brisbane (r = 0.66, p<0.001), respectively. Difference between measured and estimated NO2 exposures by multiple regression analysis was explained that NO2 levels in near workplace and other outdoors in Seoul (p = 0.023), and in transportation in Brisbane (p = 0.019) affected the personal NO2 exposures.

The personal exposures of nitrogen dioxide(NO2), microenvironmental levels and daily time activity patterns on Seoul subway station workers were measured from February 10 to March 12, 1999. Personal NO2 exposure for 24 hours were 29.40±9.75 ppb. NO2 level of occupational environment were 27.87±7.15 ppb in office, 33.60±8.64 ppb in platform and 50.13±13.04 ppb in outdoor. Personal exposure time of subway station workers was constituted as survey results with 7.94±3.00 hours in office, 2.82±1.63 hours in platform and 1 hours in outdoor. With above results, personal NO2 exposure distributions on subway station workers in Seoul were estimated with Monte Carlo simulation which uses statistical probabilistic theory on various exposure scenario testing. Some of distributions which did not have any formal patterns were assumed as custom distribution type. Estimated personal occupational NO2 exposure using time weighted average (TWA) model was 31.29±5.57 ppb, which were under Annual Ambient Standard (50 ppb) of Korea. Though arithmetic means of measured personal NO2 exposure was lower than that of occupational NO2 exposure estimated by TWA model, considering probability distribution type simulated, probability distribution of measured personal NO2 exposures for 24 hours was over ambient standard with 3.23%, which was higher than those of occupational exposure (0.02%). Further research is needed for reducing these 24 hour NO2 personal excess exposures besides occupational exposure on subway station workers in Seoul.