In this study, a two-stage electrostatic precipitator (ESP) was developed using a novel automatic dry cleaning device to reduce the ultrafine particles in subway stations. Collection efficiency was evaluated with a pilot scale ESP (1.2m× 1.2m) and the scale of the test duct was half of the subway air handling unit. The maximum collection efficiency for 0.3 μm particles was 96.9%. In addition, we studied a method of automatic dry cleaning for maintenance of the ESP. The cleaning efficiency was analyzed according to the cleaning flow rate for each particle loading amount to achieve a recovery rate over 90%. In addition, we derived the equation to estimate the reduction in collection efficiency according to the particle loading amount. It was confirmed that the performance of the contaminated ESP was restored to the initial state by the automatic dry cleaning in this study and that the electrical energy consumption was 5 times lower compared to utilizing conventional water cleaning.

In order for records to be preserved for a long time without physical and chemical transformation, the preservation environment of the library is very important, and environmental problems must be improved through periodic investigation on the preservation environment. Against this background, this study derived fine dust (PM10) and ultrafine dust (PM2.5) concentration data for the libraries, hallways, and workrooms of the National Archives of Korea over two years. There was a difference in the concentration of fine dust and ultrafine dust among facilities, and there was a change in the concentration depending on the month. Both fine dust and ultrafine dust concentrations were present at less than 10 μg/m³ in the libraries. In the hallways, both fine and ultrafine dust concentrations were highest in July. In the workplaces, the monthly fluctuations in the concentration of fine dust and ultrafine dust were large. And the concentration of fine dust and ultrafine dust in the workplaces were higher than those in the library and hallways. Overall, the concentration of fine dust and ultra-fine dust was measured below the maintenance standards stipulated by the Indoor Air Quality Management Act of the Ministry of Environment of Korea in all the investigated facilities. The results of this study are expected to be used as fundamental information to manage the indoor air quality of the facilities of the National Archives.

PURPOSES : In this study, the characteristics of fine particulate matter (PM2.5) concentrations under different weather conditions of different types of bus stops, such as enclosed-type and open-type bus stops, were analyzed using statistical methods. METHODS : Data was collected inside and outside an enclosed bus stop on sunny and rainy days to compare and analyze the characteristics of fine particulate matter concentration in the target bus stop. The probability distributions were estimated for each data point using the Anderson–Darling test. Based on the estimated probability distributions, probability density functions were computed, and the values were used to estimate and compare probability for each air quality index inside and outside the bus stop under different weather conditions RESULTS : For the results of descriptive statistics, the average concentrations of fine particulate matter inside and outside the bus stop were 42.296 and 35.482 μg/m3 on a sunny day and 40.831 and 39.321 μg/m3 on a rainy day, respectively. Results of the statistical method, obtained using the Anderson-Darling test, indicate that the probability of the air quality index inside the bus stop reaching high concentrations on a sunny day was "high" or "very high," compared to that outside the bus stop. However, on rainy days, the differences in fine particulate matter concentrations inside and outside the bus stops were difficult to identify based on statistical evidence. CONCLUSIONS : It was found that the open-type bus stop had an advantage of preventing fine particulate matter effects on sunny days, compared to the enclosed-type bus stops. Furthermore, there were slight differences in fine particulate matter concentrations inside and outside the bus stop on a rainy day because of atmospheric flow and stormwater.

High concentrations of PM2.5 were generated in new apartments before moving in, and PM2.5 reduction efficiencies using air cleaners and ventilation systems were evaluated. The experimental results for different air cleaner capacities showed that the PM2.5 reduction efficiencies for 46.2 m2, 66 m2, and 105.6 m2 areas were 81.7%, 92.9%, and 92.5%, respectively. Thus, the larger the air cleaning application area, the higher the PM2.5 reduction efficiency. However, there was no difference in the efficiency of overcapacity air cleaners above a certain capacity. The efficiencies of air cleaners located at the living room center, interior wall, and edge were 81.7%, 79.2%, and 75.8%, respectively. There was, therefore, no significant difference in the PM2.5 reduction efficiencies of air cleaners in different locations. Furthermore, the PM2.5 reduction efficiencies at distances of 1 m, 2 m, and 3 m were 81.7%, 81.3%, and 81.7%, respectively. Therefore, there was also no significant difference in efficiency with distance. The PM2.5 concentration decreases rapidly during natural ventilation. Therefore, when the indoor PM2.5 is higher than the outdoor PM2.5, the air cleaner should be used after natural ventilation. The efficiency of PM2.5 reduction using an air supply-type ventilation system in apartments was 35%, which is not high. The simultaneous operation of the ventilation system and kitchen range hood was effective, showing a PM2.5 reduction efficiency of 69.1%. However, a water sprayer was not effective, showing a PM2.5 reduction efficiency of 24.3%. The results of this study suggest that PM2.5 reduction performance should be standardized by evaluating the efficiency of different ventilation systems. Effective usage and maintenance standards for ventilation systems need to be disseminated, and ventilation systems and air cleaners should be used effectively.

PURPOSES : This study analyzes the characteristics of generated fine particulate matter (PM2.5) and nitrogen oxide (NOX) at roadsides using a statistical method, namely, a generalized linear model (GLM). The study also investigates the applicability and capability of a machine learning methods such as a generalized regression neural network (GRNN) for predicting PM2.5 and NOX generations. METHODS : To analyze the characteristics of PM2.5 and NOX generations at roadsides, data acquisition was conducted in a specific segment of roads, and PM2.5 and NOX prediction models were estimated using GLM. In addition, to investigate the applicability and capability of a machine learning methods, PM2.5 and NOX prediction models were estimated using a GRNN and were compared with models employing previously estimated GLMs using r-square, mean absolute deviation (MAD), mean absolute percentage error (MAPE), and root mean square error (RMSE) as parameters. RESULTS : Results revealed that relative humidity, wind speed, and traffic volume were significant for both PM2.5 and NOX prediction models based on estimated models from a GLM. In addition, to compare the applicability and capability of the GLM and GRNN models (i.e., PM2.5 and NOX prediction models), the GRNN model of PM2.5 and NOX prediction was found to yield better statistical significance for r-square, MAD, MAPE, and RMSE as compared with the same parameters used in the GLM. CONCLUSIONS : Analytical results indicated that a higher relative humidity and traffic volume could lead to higher PM2.5 and NOX concentrations. By contrast, lower wind speed could affect higher PM2.5 and NOX concentrations at roadsides. In addition, based on a comparison of two statistical methods (i.e., GLM and GRNN models used to estimate PM2.5 and NOX), GRNN model yielded better statistical significance as compared with GLM.

PURPOSES : The objective of this study is to figure out the trend and characteristics of fine particulate matter (PM2.5) and nitrogen oxide (NOx) concentration in underpass sections. The effect of traffic and meteorological condition on PM2.5 / NOx concentration was analyzed using field monitoring data. METHODS : Based on the literature review, PM2.5 and NOx concentration data were monitored using DustTrak II aerosol monitoring system and Serinus 40 oxides of nitrogen analyzer, respectively. Meteorological and traffic information was collected using automatic weather system and traffic volume counter, respectively. RESULTS : PM2.5 has a positive and negative correlation with relative humidity and wind speed, respectively. Meanwhile, NOx was found to have no correlation with meteorological conditions. The NO/NO2 ratio tends to change with traffic volume, indicating higher correlation between NO and traffic volume; the observed NO2 is mostly a secondary material produced by NO oxidation. CONCLUSIONS : Our study provides clear characteristics of NOx and PM2.5 and correlations with meteorological and traffic information in the underpass sections. It is found from this study that the increase in wind speed causes reduction in the concentration of PM2.5 owing to the diffusion and dispersion phenomena. On the other hand, the meteorological conditions were found to barely have correlations with NOx concentrations in this study. The traffic volume could significantly affect the NOx concentration and NO / NO2 ratio, which is directly correlated to the emissions from vehicles.

The goal of this study was to measure the indoor and outdoor fine and ultrafine particulate matter concentrations (PM10, PM1.0) of some houses in Yeosu and in S university in Asan from March to September 2018. PM10 concentration in indoor air in Yeosu area was 18.25 μg/m3, while for outdoor air it was 14.53 μg/m3. PM1.0 concentration in indoor air in the Asan area was 1.70 μg/m3, while for outdoor air it was 1.76 μg/m3, showing a similar trend. Heavy metal concentrations in the Yeosu region were the highest, at Mn 2.81 μg/m3, Cr 1.30 μg/ m3, and Ni 1.11 μg/m3 indoors. Outside, similar concentrations were found, at Cr 3.44 μg/m3, Mn, 2.60 μg/m3, and Ni 1.71 μg/m3. Our analysis of indoor and outdoor PM concentrations in the Asan region, which was carried out using the MOUDI (Micro-orifice Uniform Deposit Impactor) technique, found that PM concentration is related to each particle size concentration, as the concentration of 18 μm and 18-10 μm inside tends to increase by 3.2- 1.8 μm and 0.56-0.32 μm.

PURPOSES: The purpose of this study is to analyze characteristics of concentrations of fine particulate matter (PM2.5) among 3 different types of bus stops, specifically partially closed bus stop with front & back partition, partially closed bus stop with back partition, and bus stop with open space (referred to as bus stop types Ⅰ, Ⅱ, and Ⅲ, respectively) at urban roadside, using the Anderson-Darling test as statistical method. METHODS: For the purpose of this study, first of all, data on concentrations of PM2.5 on the 3 types of bus stops at urban roadside were acquired for certain days, with different levels of air quality index (AQI). Secondly, this study accomplished the data processing of removing outliers from acquired data, and the Anderson-Darling test was conducted to estimate probabilities of occurrence for concentrations of PM2.5 in the 3 types of bus stops. RESULTS : The average concentrations of PM2.5 for AQI‘ Very High’for bus stop types Ⅰ, Ⅱand Ⅲare 46-179㎍/m3, 66-194㎍/m3, 42- 134㎍/m3, respectively, and for AQI ‘High’for bus stop typesⅠ, Ⅱ and Ⅲ are 16-71㎍/m3, 26-84㎍/m3, and 14-69㎍/m3, respectively. Furthermore, probabilities of occurrence for concentration levels of PM2.5 in AQI were estimated for given measurement dates using the Anderson-Darling test as statistical method. As a result, for AQI ‘Very High,’the probabilities of occurrence for concentration levels ‘Very High’and‘ High’were determined more likely to occur regardless of bus stop type. With respect to each type of bus stop, the probabilities of ‘Very High’for bus stop type Ⅱ were 93.37% and 98.92%, higher than for the other bus stop types. For AQI ‘High’the probabilities of occurrence for concentration levels‘ Good’were found to be very low, at 0.00% to 3.07%, and occurred mainly for‘ Moderate’and‘ High’in this study. In particular, the probabilities of occurrence for concentration level‘ High’for bus stop type Ⅱwere analyzed to be greater than 90%, compared to those for the other bus stop types. CONCLUSIONS: Based on the result of this study, when PM2.5 is analyzed on certain days, probabilities of occurrence for concentration levels in AQI should be considered for each type of bus stop.

PURPOSES: The purpose of this study is to compare the concentrations of fine particulate matter (PM2.5) at different types of roadside bus stops in an urban environment, and analyze the tendencies in PM2.5 concentrations according to the air quality index. METHODS : To compare and analyze the characteristics of fine particulate matter at roadside bus stops, we collected data such as PM2.5 concentration, temperature, humidity etc., and performed a comparative analysis of their concentration levels at different types of bus stops (a partially closed bus stop with a front and back partition, a partially closed bus stop with only a back partition, and a bus stop with an open space). In addition, the daily variation in fine particulate matter concentration was analyzed. RESULTS: The average daily concentration levels of fine PM2.5 in the target area for a partially closed bus stop with a front and back partition, a partially closed bus stop with a back partition, and a bus stop with an open space were 18.40㎍/㎥ to 108.27㎍/㎥, 22.81㎍/㎥ to 135.51㎍/㎥, and 16.62㎍/㎥ to 81.52㎍/㎥, respectively. According to air quality index levels during the target measurement period, the bus stop with an open space had the least concentration levels of PM2.5 compared to the other bus stops. Furthermore, this study revealed that the PM2.5 concentration levels usually increased during the peak hour period in the morning and gradually increased after 2 pm until the end of the peak hour period at night, regardless of the bus stop type. CONCLUSIONS: Based on the results of this study, we demonstrated the effect of PM2.5 concentration levels on the atmospheric, weather, environmental, and transportation conditions in a target area, and the variation in concentration levels depending on the type of bus stop.

본 연구에서는 PMF 모델을 이용하여 PM2.5에 대한 오염원 확인 및 오염원별 기여도를 분석하였다. A시의 배출원별 기여도 순위는 Secondary Sulfate가 19.8%로 가장 기여도가 높고, 그 다음으로는 Mobile 19.5%, Industry 16.0%, Biomass Buring 14.1%, Secondary Nitrate 14.1%, Oil Combustion 11.6%, Aged Sea Salt 2.6%, Soil 2.5% 등으로 분석되었다. Sulfate와 Ammonium 농도가 배출원별 프로 파일에서 기여도가 가장 높은 오염원으로 분석되었는데, 이는 대기 중에서 가스상 전구물질(SOx와 암모니아 가스)이 광화학 반응하여 생성된 2차 에어로졸인 것으로 분석되었다.

This research investigated the effect of the eruption of Japan Sakurajima volcano on the concentration of ultrafine particle when the north Pacific high pressure exists in the Busan in summer. As a result of analyzing the forward trajectory using the HYSPLIT model, the air parcel from Sakurajima volcano passed through the sea in front of Busan at 1500 LST on July 17, 24 hours after the volcanic eruption. As a result of analyzing the PM10 and PM2.5 concentrations in the Busan for two days from July 16 to 17, 2018, the Sakurajima eruption in Japan, it can be seen that there was a high increase in PM10 and PM2.5 concentrations compared to the previous day. As a result of analyzing the backward trajectory, the air mass that reached Busan at 1300 LST on July 17, 2018 has moved near the Sakurajima volcano at 1,500 m, 2,000 m, and 3,000 m. The concentration of SO4 2- in PM2.5, the concentration of all three stations in Busan showed a sharp increase from 1000 LST on July 17th. Looking at the NH4 + concentration in PM2.5, it shows a very similar variation trend to SO4 2-, and the correlation coefficient between the two components is 0.96 for Jangrimdong and Yeonsandong, and 0.85 for Busan New Port. Looking at the NO3 - concentration in PM2.5, the same high concentrations as SO4 2- and NH4 + were not observed in the afternoon of July 17th.

The purpose of this study is to elucidate the spatio-temporal characteristics of ultrafine dust generation in East Asia and the synoptic climate patterns related to its dispersal which has its adverse effects on public health across East Asia. To achieve this purpose, Level 3 monthly Aerosol Optical Depth (AOD) data extracted from MODIS satellite imagery (MOD08_M3) representing particle matters less than 2.5 micrometer (PM2.5) and the NCEP-NCAR reanalysis I upper-level climatic data associated with the exacerbation of ultrafine dust problem are analyzed for the recent 20-year (2001-2020) period. Analyses of long-term average MOD08 data show that high AOD value exceeding 0.5 or more frequently occurred in populous cities in East Asia but mainly in the vicinity of densely populated large rivers and the eastern lowlands in China between mid-winter and mid-spring, which is attributable to the accumulation effects of continuous fossil fuel consumption for heating and manufacturing. Despite the overall decreasing trend of ultrafine dust across China in the 2010s, the weakened westerlies in the warmer climate as well as its continuous generation from the densely populated industrial regions of China provide a favorable synoptic climate condition for frequent severe ultrafine dust problems across East Asia including South Korea. These results indicate that ultrafine dust from China is a long-lasting transboundary environmental problem across East Asia, which needs long-term international cooperation in developing the sustainable policies.

This research investigated the characteristics of fine particle concentration and ionic elements of PM2.5 during sea breeze occurrences during summertime in Busan. The PM10 and PM2.5 concentrations of summertime sea breeze occurrence days in Busan were 46.5 ㎍/㎥ and 34.9 ㎍/㎥, respectively. The PM10 and PM2.5 concentrations of summertime non-sea breeze occurrence days in Busan were 25.3 ㎍/㎥ and 14.3 ㎍/㎥, respectively. The PM2.5/PM10 ratios of sea breeze occurrence days and non-sea breeze occurrence days were 0.74 and 0.55, respectively. The SO4 2-, NH4 +, and NO3 - concentrations in PM2.5 of sea breeze occurrence days were 9.20 ㎍/㎥, 4.26 ㎍/㎥, and 3.18 ㎍/㎥ respectively. The sulfur oxidation ratio (SOR) and nitrogen oxidation ratio (NOR) of sea breeze occurrence days were 0.33 and 0.05, respectively. These results indicated that understanding the fine particle concentration and ionic elements of PM2.5 during sea breeze summertime conditions can provide insights useful for establishing a control strategy of urban air quality.

The objective of this study was to estimate the trends of air quality in the study area by analyzing monthly and seasonal concentration trends obtained from sampled data. To this aim, the mass concentrations of PM2.5 in the air were analyzed, as well as those of metals, ions, and total carbon within the PM2.5. The mean concentration of PM2.5 was 22.7 ㎍/㎥. The mass composition of PM2.5 was as follows: 31.1% of ionic species, 2.2% of metallic species, and 26.7% of carbonic species (EC and OC). Ionic species, especially sulfate, ammonium, and nitrate, were the most abundant in the PM2.5 and exhibited a high correlation coefficient with the mass concentration of PM2.5. Seasonal variations of PM2.5 showed a similar pattern to those of ionic and metallic species, with high concentrations during winter and spring. PM2.5 also had a high correlation with the ionic species NO3 - and NH4 +. In addition, NH4 + was highly correlated with NO3 -. Through factor analysis, we identified four controlling factors, and determined the pollution sources using the United States Environmental Protection Agency(U.S. EPA) pollution profile. The first factor, accounting for 19.1% of PM2.5 was attributed to motor vehicles and heating-related sources: the second factor indicated industry-related sources and secondary particles, and the other factors indicated soil, industry-related and marine sources. However, the pollution profile used in this study may be somewhat different from the actual situation in Korea, since it was obtained from US EPA. Therefore, to more accurately estimate the pollutants present in the air, a pollution profile for Korea should be produced.