In this study, we analyzed the concentration of cadmium and mercury in urine and lead in blood from 668 residents in the exposed and compared areas in Gwangyang-si and Yeosu-si, from July 2013 to December 2015. According to the lifestyle (past smoking, current smoking, passive smoking, drinking and exercise), the concentration of cadmium in urine was higher in the compared areas than in the exposed areas in Gwangyang. However, the concentration of cadmium in urine according to the lifestyle except drinking was higher in the exposed areas than in the compared areas in Yeosu. According to the past smoking and current smoking, the concentration of mercury in urine was higher in the compared areas than in the exposed areas in Gwangyang, but the passive smoking, drinking and exercise showed similar concentration levels both in the exposed and compared areas in Gwangyang. The concentration of mercury in urine according to the past smoking and current smoking was higher in the exposed areas than in the compared areas in Yeosu, but the concentration of mercury in urine according to the drinking and exercise was lower in the exposed areas than in the compared areas in Yeosu. According to the past smoking, the concentration of lead in blood showed similar concentration levels in the exposed and compared areas in Gwangyang, but regarding current and passive smoking, it was higher in the compared areas than in the exposed areas in Gwangyang. Especially, the concentration of lead in blood according to the drinking in Gwangyang showed statistically significant difference (p<0.05). The concentration of lead in blood according to the lifestyle was higher in the compared areas than in the exposed areas in Yeosu.

It is known that air pollutants such as fine dust and exhaust gas from vehicles are harmful to human health. In particular, the black carbon emitted by vehicles is known to cause a large number of premature deaths. This study analyzed the effect of a noise barrier on the inflow amount of black carbon from a nearby high traffic road to a school area, using numerical analysis performed at two elementary schools. Also, the correlation between the noise barrier’s shape, height and the inflow amount of black carbon was assessed. As a result, it was found that the higher the noise barrier, the lower the inflow amount of black carbon observed at the school A. However, the inflow amount of black carbon at school B was not greatly influenced by the height of the noise barrier. The inflow amount of black carbon at the schools could be changed not only by the height of the noise barrier, but also by the shape, height and position of the noise barrier and the school building.

An elementary school is an important public place for children and it is where they spend most of their days. Ten elementary schools of environmental pollutants were measured in the classroom, playground and school zones (June 19 ~ Nov 1, 2012). Dust measurements of some schools were more indoor air. Measurements of black carbon concentrations were higher overall school zones. Also, in the case of formaldehyde, benzene and some environmental standards were exceeded. In the case of outdoor pollutants not statistically significant, but in some cars and vans that were correlated with pollutants. Thus, strategies and actions are necessary that will protect the health of children in schools from environmental pollutants.

In this study, we estimated nitrogen dioxide (NO₂) concentrations in microenvironments where residential indoor, residential outdoor, other indoors, and transportation using measured personal exposure and multiple linear regression analysis of time-weighted average model, and compared with measured NO₂ concentration in microenvironments. Measured residential indoor, outdoor and other indoor NO₂ concentration was 22.22±9.59 ppb, 23.64±9.62 ppb, and 22.07±13.90 ppb, respectively. NO₂ concentrations in residential indoor and outdoor, total outdoor, other indoor, and transportation by multiple regression analysis were significantly estimated as 20.48 ppb, 32.79 ppb, 24.35 ppb, and 28.82 ppb, respectively (p= 0.000). Measured and estimated NO₂ concentration were similar with each other, therefore NO₂ concentrations in each microenvironment were able to be estimated using time-weighted average model and personal exposure with multiple regression analysis.

The information about time spent in microenvironments plays a critical role for an exposure assessment of the person concerned, considering the personal exposure relies on the characterization of activity patterns of the population at risk and human activities impact the timing, location, and level of personal pollutant exposure. The purposes of this paper were to present indoor time activity patterns of Korean from a population-based study and to determine individual factors of time spent in microenvironments. The population based study collected time activity pattern of about 32,000 Korean for two consecutive days. The mean times spent at home, other indoors, outdoors, and transportation in related to the whole sample of 19.025 people are 14.23hrs(59.3%), 6.80hrs(28.3%), 1.26hrs(5.2%), and 1.75hrs(7.3%) in weekday, respectively. Database provides information on how the proportion of persons in different locations changes by time of day in weekday. Here, we see that over 90% of respondents were in a residence from about 11 PM to 5 AM, and the largest proportions of respondents in offices, factories, schools and public buildings occur between 8 AM and 5 PM.

The assessment of personal exposure is a critical component in population-based epidemiologic studies of air pollution. This study was conducted to apply and compare the four exposure estimation methods of individual-level to air pollution concentration in a cohort including 2,283 subjects in Gwangyang, Korea. Individual-level exposure of air pollution were estimated using multiple approaches, including average across all monitors, nearest monitor, and spatial interpolation by inverse distance weighting and kriging. The mean concentrations of PM10, NO2, SO2, CO, O3 by four exposure estimation methods were slightly different but not significantly different from each other. Cross-validation showed that kriging was more accurate than other exposure estimation methods because kriging has probably predicted individual exposure levels equivalent to residential locations after estimating the parameters of a model according to the spatial surface of air pollution concentration. These data support that spatial interpolation methods may provide better estimates than selecting the value from the nearest monitor and averaging across values from all monitors by reflecting spatial attributes of air pollution on personal level.

The purpose of this study is to assess the effects of heavy metal concentrations in the blood and urine of the general population. This research had been conducted from April to December 2008, studying 545 residents of Daejeon and Chungcheong Province. Through the concentrations of heavy metals(Pb, Cd, Hg, As, Mn) in the biota samples and questionnaires, the residents heavy metal exposure level and the influential factors according to personal characteristics or lifestyle were evaluated. As to the heavy metal concentration in the blood and urine of the comparing region, were As and Mn statistically significant(p<0.01, p<0.05). Blood lead and urinary mercury concentrations were higher in males than females. The heavy metal concentration for each age group increased blood mercury. The concentration of all heavy metals were higher in the drinkers than in the non-drinkers. Blood lead and mercury concentrations were higher in the smokers than in the non-smokers, but the urinary cadmium, arsenic and blood manganese was higher in the non-smokers than in the smokers. As to the blood lead and urinary cadmium concentration according to the food preference fish showed high concentration. To clarify the factors affecting the heavy metal concentration in biota among subjects multiple regression analysis was conducted. As a results, it turned out that as to lead content in blood, sex, age and smoking have influence on the subjects with explanatory adequacy of 14.0 %. These results demonstrated that the factors affected the concentrations of heavy metals in blood and urine. The results of this study could be used as the foundational data for setting the health risk assessment.

Perceived air quality (PAQ) is defined as evaluation of indoor air satisfaction and comfortable sensory by occupants. However, there are differences between criteria of indoor pollutants and lowest sensory thresholds. In this study, we compared indoor PAQ by questionnaire with measured benzene, toluene and nitrogen dioxide (NO2) concentrations in home indoors. The NO2 concentration was the highest in Seoul, while benzene and toluene were the highest in Asan. Average PAQ score in winter was higher than that in summer. Significant correlations between PAQs of home indoor air pollution and measured pollutant concentrations were not shown and correlation coefficients (r) ranged between -0.453<r<0.258. Several groups have been divided to analyze what may affect PAQ scores such as gender, city, home indoor smoking, passive smoking, and self-reported respiratory symptoms. Gender, city, and self-reported respiratory symptoms by indoor air quality were associated with high PAQ scores by using of logistic regression analysis. We are confirmed that no association between concentrations of home indoor pollutant and PAQ scores. Therefore we further need to develop new indicator indoor air pollutants, measurement, and evaluation by PAQ.