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.

PURPOSES : A pilot experimental study on the formation of fine particulate matter through photochemical reactions using precursor gas species (volatile organic compounds (VOCs), NH3, SO2, and NOx) was conducted to evaluate the large-scale environment chamber for investigating the pathway of aerosol formation and the subsequent assessment techniques used for reducing fine particulate matter. Two small-scale environment chambers (one experimental group and one control group), each with a width, depth, and height of 3 m, 2 m, and 2.3 m, respectively, were constructed using ethylene tetrafluoroethylene (ETFE) films. METHODS : The initial conditions of the fine particles and precursor gases (NOx and VOCs) for the small-scale environment chamber were set up by injecting diesel vehicle exhaust. NH3 and H2O2 were added to the small-scale environment chamber for the photochemical reaction to form organic and inorganic aerosols. The gas phase of the VOCs and the chemical compositions of aerosols were investigated using a proton transfer reaction time-of-flight mass spectrometer and the aerodyne high-resolution time-of-flight aerosol mass spectrometer at 1 and 10 s time resolutions, respectively. Gas phases of NO and NO2 were measured using Serinus 40 NOx at a 20 s time resolution. RESULTS : The small-scale environment chambers built using ETFE films were proved to supply sufficient natural sunlight for the photochemical reaction in the environment chambers at an average of approximately 89% natural sunlight transmission at 300–1000 nm. When the intermediates of NH3 and H2O2 for the atmospheric chemical reaction were injected for the initial condition of the small-scale environment chamber, nitrate and ammonium in the experimental group increased to 4747% and 1837%, respectively, compared to the initial concentrations (5.4 μg/m3 of nitrate and 5.2 μg/m3 of ammonium), indicating the formation of secondary inorganic aerosols of ammonium nitrate (NH4NO3). This implies that it is necessary to inject intermediates (NH3 and H2O2) for the formation of fine particulate matter when simulating the atmospheric photochemical reaction for assessing the environment chamber. CONCLUSIONS : This study has shown that small-scale environment chambers can simulate the atmospheric photochemical reaction for the reduction of fine particulate matter and the formation of the aerosol pathway. The results of this study can be applied to prevent time and economic losses that may be incurred in a full-scale environment chamber.

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.

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 3~5세 유아교육기관 재원생 어머니들의 일상생활 속 미세먼지에 대한 인식을 알아보고 숲체험 프로그램 참가에 따른 숲과 미세먼지에 대한 인식의 차이를 분석하였다. 연구 대상은 숲체험 참가한 학모 61명과 숲체험에 참가하지 않은 학모 61명으로 총 122명에게 설문 조사를 하였다. 총 122명 중 82.8%의 학모들은 미세먼지에 대한 관심이 있고 자주 확인하는 빈도도 84.4%으로 높았지만 이에 대한 지식과 대처방안 및 줄이기 위한 적극적인 실천은 부족 하였다. 숲과 미세먼지에 대한 인식은 숲체험에 참여한 학모들에게서 숲의 역할 및 도심과 비교한 숲 환경의 차이에 대한 긍정적인 인식이 높았다. 따라서 어머니들이 먼저 숲을 적극적으로 체험 할 수 있는 기회가 확대 된다면 유･아동들의 숲체험이 활성화 될 뿐만 아니라 미세먼지를 비롯한 현재의 유해환경을 개선하는데도 기여 할 것이라고 생각한다.

It was investigated the state information for the atmospheric conditions around Dang-jin industrial complex in Chungnam area may be polluted by the constructing steel industrial complex. It is aimed at characterization of the fine particulate matter and other air pollutants involved in it. Samples were collected two sites for monitoring point representing steel industrial complex and one site which is placed a remote and secluded from this industrial complex, and the concentration of PM10, heavy metals, and ion components were analyzed. As a results, PM10 average concentration was 64.6㎍/㎥ for the adjacent site before Hyundai Steel Company, 70.5㎍/㎥ in Bugok immigration settlement complex, and 56.5㎍/㎥ for Jeonggok-ri contrastive point. The distribution of heavy metals was detected as very low level for all sampling points. According to the result of statistical evaluation for the heavy metal analysis, variation range of Cu, Mn, Ca, Fe, and Mg were significant higher than others. Also, the seasonal concentration change trend of heavy metals was remarkable strong in spring and low in summer because of instable meteorological phenomena such as yellow dust happened in spring. Monthly changing pattern of a sulphate ion has kept unusually high level for summer period different other components. Relationship among PM10, heavy metal, and ion component were analyzed that high positive correlation coefficient for PM10 between Fe, Mn, Pb, Ca, Mg, Cd, Al in order and PM10 between NO3-, Cl- successively. Accordingly, it is suggested that a present atmospheric conditions of the surrounding area of Dang-jin steel industrial complex is considered to be good level. Although air pollutants in emissions from their complex were below the existing emission limit, it is regarded that the systematic and continuous research is needed to preserve clean air through atmospheric monitoring, source tracing research, and citizen's surveillance for the fine particulate matter.

This study observed particulate matter (PM2.5 and PM10) in the downtown area of Jeju City, South Korea, to understand the chemical composition of particulates based on an analysis of the water-soluble ionic species contained in the particles. The mass fraction of the ionic species in the sampled PM10 and PM2.5 was 44.3% and 42.2%, respectively. In contrast, in Daegu City and Suwon City, the mass fraction of the ionic species in PM2.5 was higher than that in PM10. The chloride depletion percentage of PM10 and PM2.5 in Jeju City was higher than 61% and 66%, respectively. The contribution of sea-salt to the mass of PM10 (5.9%) and PM2.5 (2.6%) in Jeju City was similar to that in several coastal regions of South Korea. The mass ratio of Cl- to Na+ in the downtown area of Jeju City was comparable to that in some coastal regions, such as the Gosan Area of Jeju Island, Deokjeok Island, and Taean City. The mass fraction of sea-salt in PM10 and PM2.5 was very low, and the concentration of sodium and chloride ions in PM10 was not correlated with those in PM2.5 (R2 < 0.2), suggesting that the effects of sea-salt on the formation of particulate matter in Jeju City might be insignificant. The relationship between NH4 + and several anions such as SO4 2-, NO3 -, and Cl-, as well as the relationship between the measurement and calculation of ammonium ion concentration, suggested that sea-salts may not react with H2SO4, and (NH4)2SO4 may be a major secondary inorganic aerosol component of PM2.5 and PM10 in Jeju City.

This study was carried out to elucidate the chemical compositions of water-soluble inorganic ions in PM10 and PM2.5 aerosols collected during summer and winter in downtown Jejusi city. The ratios of NO3 - to the total mass of ionic species in PM10 and PM2.5 aerosols largely increase in winter compared to summer, while SO4 2- ratios in both aerosols appear to follow the opposite trend. Moreover, concentrations of Na+, Mg2+, Ca2+ and Cl- in PM10 and PM2.5-10 aerosols are higher in winter than in summer. The nitrate concentrations in PM10 and PM2.5 aerosols increase with an identical increase in excess ammonium during winter, however, nitrate formation during summer is not important owing to ammonium-poor conditions.

황사발생 전과 후인 2003년 10월 26일 00시부터 29일 18시까지 한국의 동쪽 연안에 있는 강릉시에서 PM10, PM2.5와 PM1 매 시각별 분포를 조사하였다. 황사가 고비사막으로부터 유입되기 전까지는 매 시각 PM10 농도가 20μg/m3 내외, PM2.5가 10μg/m3 내외, PM1가 5μg/m3 내외로 매우 낮은 농도를 나타내지만 황사가 유입된 10월 27일 09시부터 28일 05시까지는 PM10의 농도의 범위가 48.20~154.57μg/m3이며, 평상시 비해PM10의 농도가 3.8배로 높았다. 유사하게 PM2.5의 농도는 26.92~93.19μg/m3의 변화폭을 나타내며, 최대 3.4배로 높게 나타났고, PM1의 농도는 19.63~76.05μg/m3의 변화폭을 갖고, 최대 14.1배가 되었다. 황사가 나타나는 동안에는 수송된 황사먼지의 집중적인 유입과 동시에 도로 위의 차량의 밀집과 일몰 후 주거지역에서의 보일러 가동으로 출근시각인 09시와 퇴근시각인 17시에 PM의 고농도가 나타났다. 황사가 관측되기 전에는 미세입자와 극미세입자의 비율을 나타내는 (PM10-PM2.5)/PM2.5는 0.75~7.12, 극미세입자와 초극미세입자의 비율을 나타내는 (PM2.5-PM1)/PM1는 0.23~1.90로 나타났으며, 황사가 관측되는 기간에는 0.60~1.25와 0.21~0.37을 각각 나타내었다. 강릉시에 황사가 나타나기 전에는 2.5μm 큰 입자들이 2.5μm 이하의 극미세입자보다 PM10의 농도에 큰 영향을 주었으나, 황사가 관측되는 기간에는 2.5μm 이하의 극미세입자들이 PM10의 고농도 출현에 크게 기여하였다. 황사가 관측되는 기간에는 지역의 PM고농도에 2.5μm 이상의 큰 입자가 기여하는 일반적인 양상과 반대였다.