PURPOSES : This study analyzes the characteristics of nitrogen oxide concentration by applying titanium dioxide to existing roads in urban areas, using correlation analysis and a generalized linear model. METHODS : To analyze the characteristics of nitrogen oxide concentration with/without applying titanium dioxide to the urban road segment, data acquisition was conducted for nitrogen oxide concentration, weather information, and traffic information, etc., and a correlation analysis was conducted for each factor, with/without applying titanium dioxide to the roads. In addition, nitrogen oxide concentration generation models with/without the application of titanium dioxide to the roads were estimated using a generalized linear model. RESULTS : The results demonstrate that relative humidity and temperature were found to be slightly correlated with the nitrogen oxide concentration, both with and without the application of titanium dioxide to the roads; however, wind speed, solar radiation, and traffic volume were found to have somewhat low correlation according to the results of a correlation analysis. Moreover, relative humidity, temperature, solar radiation, and traffic volume were significant when titanium dioxide was applied to the roads, based on the estimated model from a generalized linear model, and the wind speed, solar radiation, and traffic volume were significant for the absence of titanium dioxide on the roads. CONCLUSIONS : Analytical results indicated that the characteristics of nitrogen oxide concentration vary depending on the application of titanium dioxide to the roads. In particular, when titanium dioxide was applied to the roads, the relative humidity and temperature were analyzed; according to both analyses, i.e., correlation analysis and a generalized linear model, the nitrogen oxide concentration was affected.

The purpose of this study is to evaluate the performance of a tube and badge type NO2 passive air sampler. The principle of the method is a colorimetric reaction of NO2 with N-1-naphthylethylendiamine under acidic conditions. The sampling rates for the tube and badge type passive air samplers was determined 12.3 ± 4.4 mL/min and 27.3 ± 4.9 mL/min, respectively, as obtained from the slope of the linear correlation between the NO2 mass collected by the passive air sampler and the NO2 concentration with the NO2 analyzer. The tube and badge type passive air sampler were moderately correlated with a correlation coefficient of 0.9112. The measurement for the precision and accuracy of the passive air sampling was carried out with duplicate measurement of passive air samplers. The passive air sampler had good precision and accuracy for measuring NO2 in atmosphere. A good correlation was observed between the passive air sampler and the NO2 analyzer with a coefficient of determination of 0.9153 (tube type) and 0.9514 (badge type). This passive air sampler would be suitable for the NO2 concentration monitoring in atmosphere.

The objective of this study is to offer basic scientific data to support policy decision-making for the improved control of nitrogen dioxide(NO₂) and nitrous acid(HONO) in residence. The survey on concentration of NO₂and HONO in 20 houses in Seoul and Daegu was performed from January to February, 2013. Average NO₂concentrations in the kitchen, living room, and room were 25.7 ± 7.7 ppb, 24.3 ± 8.5 ppb, and 19.6 ± 5.6 ppb, respectively. Also, average HONO concentration were 3.6 ± 1.0 ppb, 3.1 ± 0.9 ppb, and 3.1 ± 0.9 ppb, respectively. NO₂and HONO concentration in kitchen were significantly higher than the concentration in the living room and room(p<0.05). Concentration ratios of HONO/NO2 were ranged to 0.070 0.277 for indoor air and 0.004 0.161 for outdoor air. Indoor HONO/NO2 ratios were higher than the outdoor HONO/NO₂ratios.

Personal or population exposure to hazardous air pollutants has often been assessed by time-weighted average model with combining concentrations of indoor environments and time-activity pattern, which were mainly a single measurement. However, daily levels of air pollutants in indoor environments may greatly be changed because of source emission, ventilation, decay rate and so on. Subsequently exposure by a single measurement in indoor environments could not be assessed properly. In this study, we measured the consecutive 21 daily indoor and outdoor measurements of nitrogen dioxide (NO₂) with 37 houses and 19 shops such as restaurants and coffee shops beside street by using of passive samplers. Considering that average concentration during 21 days was true value, paired t-test was conducted. Daily variations of NO₂ in houses with constant or low emission source were different from those in restaurants with irregular or high emission source. These results can be explained that the NO₂ emission of indoor sources could affect the validity of measurement periods.

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.

Exposure to nitrogen dioxide (NO₂) can produce adverse health effects. Various indoor and outdoor combustion sources make NO₂ the most ubiquitous pollutant in the indoor environment. Indoor air quality can be affected by indoor sources, ventilation, decay and outdoor levels. Although technologies exist to measure these factors, direct measurements are often difficult. In the present paper, we used a mass balance model and regression analysis, penetration factor (ventilation rate divided by the sum of ventilation rate and deposition constant) and source strength factor (source strength divided by the sum of ventilation rate and deposition constant) were calculated using multiple indoor and outdoor measurements with 10 houses. Subsequently, mean contributions of indoor and outdoor sources were 28.86% and 81.09%, respectively, suggesting that both indoor and outdoor sources had contributions to indoor concentrations of NO₂.

Indoor air quality can be affected by indoor sources, ventilation, outdoor levels, and removal. Various indoor and outdoor combustion sources make nitrogen dioxide(NO2), which is a by-product of high temperature fossil fuel combustion. Especially, the presence of gas ranges and smoking have been identified as two of the major factors contributing to indoor NO2 exposures. In this study, the relative efficiencies for NO2 removal by a large number of materials are presented. This work has demonstrated that reactions with indoor surfaces represents a significant sink for NO2, and that these reactions currently are effecting a considerable degree of control over indoor NO2 levels. It seems that this control could be enhanced by judicious selection of furnishings and construction materials. Improved understanding of that rates and mechanisms of the removal process will permit optimization of the process for indoor air quality improvement.

Activated carbons were obtained by activating wild cherry stones with different concentrations of phosphoric acid or zinc chloride at different temperatures. The adsorption of N2 at 77 K and of CO2 at 273 K was followed and the data were analyzes by considering different adsorption models. The activated carbons obtained measured high surface area with the most of the surface in all samples located in micropores. Fair agreement was found between the nitrogen surface areas calculated from the BET-, t-, α- and DR- methods, although the first three are based on surface coverage whereas the latter is based on micropore filling. The carbon dioxide surface areas calculated by the DA equation were smaller than the comparable nitrogen areas. This was ascribed to domination of surface coverage mechanism, the absence of activated diffusion process. Based on this explanation the CO2-surface areas as calculated by DA equation should be taken with great reservation.

시설 오이재배에서 조절가능한 환경요인들, 즉 광도, CO2 농도, 온도 그리고 엽중 질소 농도의 변화에 따른 양액재배 오이 엽의 총광합성 속도를 측정하였다. 광보상점은 10~20μmol.m-2 .s-1 정도로 낮았고 광포화점은 1000μmol.m-2 .s-1 이상이었으며, 오이의 총광합성 속도는 온도가 상승할수록 증가속도는 감소하지만 지속적인 증가를 보였으나 24~32℃ 사이에서 광합성 속도는 큰 차이를 보이지 않아 이 범위가 오이 생육에 대한 적정온도인 것으로 나타났다. CO2 보상점은 20-40μmol.mol-1 사이에 위치하였고 CO2포화점은 1200μmol.mol-1이상으로 나타났으며 엽중은 질소함량의 증가에 따른 잎의 총광합성 속도의 변화는 sigmoid형의 증가추세를 보였다. 요인들간의 상호작용 효과에서는 모든 경우 상승적으로 나타나, 한 요인의 수준이 증가함에 따라 타 요인의 수준의 증가에 따른 총광합성 속도도 상승적을 증가하였다. 각환경요인의 변화와 요인들간의 상호작용에 따른 총광합성 속도의 변화에 대한 수리적 모형을 개발하였다. 이들 모형은 시설 내 환경변이에 따른 오이의 생육 내지는 수량에서의 차이를 밝히는데 이용될 수 있으며 오이의 식물생장 모형이나 더 나아가 경영합리화를 위한 오이 생산 전문가 시스템의 개발에 필요한 기초 자료로 이용될 수 있을 것이다.

Indoor air quality can be affected by indoor sources, ventilation, decay and outdoor levels. Although technologies exist to measure these factors, direct measurements are often difficult. The purpose of this study was to develop an alternative method to characterize indoor environmental factors by multiple indoor and outdoor measurements. Using a mass balance model and regression analysis, penetration factor (ventilation rate divided by the sum of ventilation rate and deposition constant) and source strength factor (source strength divided by the sum of ventilation rate and deposition constant) were calculated using multiple indoor and outdoor measurements. Subsequently, the ventilation rate and NO2 generation rate were estimated. Mean of ventilation rate was 1.41 ACH in houses, assuming a residential NO2 deposition constant of 0.94 hr-1. Mean generation rate of NO2 was 16.5 ppbv/hr. According to house characterization, inside smoking and family number were higher NO2 generation rates, and apartment was higher than single-family house. In conclusion, indoor environmental factors were effectively characterized by this method using multiple indoor and outdoor measurements.

In this study, we evaluated the property change and relationship between hematological and biochemical parameters in exposure group and control group by multiple inhalation exposure, of NO2. In case of leukocyte, change of hematological property increased significantly in statistics (p<0.05) in mice experiment. in case of hematocrit of exposure group, it was of decreased significantly in statistics. the tendency of hemoglobin and hematocrit was similar to all for three case. in case of methmoglobin that of the exposure group in mice experiment was meaning increased(p<0.05). For the NO2 influence in biochemical property, total protein and triglyceride was decreased but not significant in statistics, albumin was decreased in the exposure group in the animal experiments. blood urea nitrogen and creatinine increased significantly in statistics in the animal experiments. uric acid and lactate dehydrogenase in serum increased significantly in the exposure group. We have to evaluate risk assessment for the NO2 of indoor air pollutant in low concentration and long time.

This study evaluated the hazard caused by NO2, an oxidant generated in the process of welding. We compared hematological and biochemical parameters in workers who chronically inhale NO2 and office workers not exposed to NO2. NO2 exposure affected the hematological and biochemical parameters. Increasing NO2 concentrationincreased the number of leukocytes, while decreasing the number of erythrocytes. Blood urea nitrogen, creatinine, uric acid, and lactate dehydrogenase were increased, while total protein and triglycerides were decreased. The mean concentration of NOx(NO2-/ NO3-) in the serum of welders and the control group was 35.97±2.85 and 55.40±5.81 μmol/L, respectively. The difference was significant (p<0.05), although NO2- was not detected in the serum.

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.

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.