도로에서 발생하는 대기오염의 주요 원인은 자동차 등의 연료연소로 인해 발생하는 미세먼지(PM), 질소산화물(NOX), 황산화물(SOX), 암모니아(NH3), 오존(O3) 등이며, 특히 미세먼지와 질소산화물은 도로를 이용하는 운전자와 보행자의 건강에 부정적인 영향을 미치는 것으로 알려져 있다. 본 연구에서는 버스정류장에 설치되는 미세먼지 저감시설의 미세먼지 저감효과를 분석하기 위하여 미세먼지 저 감능력을 실증할 수 있는 실대형 미세먼지 실증인프라와 실규모의 버스정류장을 이용하였다. 미세먼지 실증인프라에서 미세먼지 저감 시설이 설치되는 실험군(2곳)과 미설치되는 대조군(1곳)을 대상으로 미세먼지(PM10) 발생농도를 측정하였으며, 미세먼지 저감시설의 미 세먼지 저감효과를 분석하기 위하여 미세먼지(PM10)의 발생확률과 확률밀도함수를 산정할 수 있는 통계학적 방법인 Anderson-Darling 테스트(AD 테스트)를 이용하여 분석하였다. 미세먼지 저감시설의 미세먼지 저감효과는 대기질지수(AQI)의 기준을 준용하여 실험군ㆍ 대조군의 미세먼지 농도발생확률을 비교하여 정량적ㆍ정성적으로 분석하였다. 미세먼지(PM10) 농도발생확률 산정결과, AQI ‘보통’의 경우, 실험군 측정지점 1, 2와 대조군의 농도발생확률은 각각 77.24%, 63.26%, 0.00%로 대조군에 비해 실험군의 측정지점 1, 2에서 높 게 나타났으며, AQI ‘나쁨’의 경우, 실험군 측정지점 1, 2와 대조군의 농도발생확률은 각각 21.70%, 35.09%, 100.00%로 나타나 실험군 내의 미세먼지(PM10) 발생농도가 대조군과 비교해 개선되는 것으로 분석되었으며, 대조군 내부의 미세먼지 농도의 변화는 거의 없는 것으로 나타났다. 일반적으로 미세먼지를 측정하는 방식인 중량법과 베타선법을 통한 미세먼지 저감효과 분석방법은 시간당 평균으로 측정한 미세먼지 농도만 비교 가능하므로 정성적인 효과분석이 미비해 본 연구를 통해 소개한 통계학적 방법이 정량적 분석 뿐만 아 니라 정성적 분석에도 효과적일 것으로 기대하고 있다.

PURPOSES : High concentrations of particulate matter (PM) are emitted or generated from vehicle emissions in urban roads with dense transient populations. To reduce the effect of PM emission on bus stop users at roadsides, a plan to reduce PM emitted from the roadside must be devised. In this study, an atmospheric environment at a roadside is simulated in a large-scale environment chamber, and a test for reducing PM around the bus stop is conducted by installing a bus stop adapted to a PM reduction system. METHODS : Exhaust gas is injected into the experimental and reference chambers using diesel and gasoline vehicles for roadside airquality simulations. The two vehicles are operated in an idle state without an acceleration operation to emit exhaust gas uniformly, and the initial conditions are achieved by injecting car emissions for approximately 40 min. The initial condition is set to 1 ppm of NOx concentration in the environment chamber. Between the two environment chambers, a bus stop adapted to the PM reduction system is installed in the experimental chamber to conduct a PM reduction experiment pertaining to the air quality around the roadside. The experimental progress is set as the start time of the experiment based on the time at which the initial conditions are achieved; simultaneously, the PM reduction system in the experimental chamber is operated. After the simulation is commenced, the PM concentration, which changes over time, is measured using a high-resolution time-of-flight aerosol mass spectrometer (HR-ToF-AMS) without additional injection of car emissions or pollutants. The HR-ToF-AMS measures the chemical composition of non-refractory PM1.0 (NR-PM1.0) in real time. RESULTS : The NR-PM1.0 compound (organic aerosol (OA), NO3 -, SO4 2-) increases by 160% compared with the simulated initial concentration up to T90min in both environmental chambers; this is speculated to be due to secondary formation. The reference chamber indicates a slight decrease or a steady-state after T90min, whereas the experimental chamber indicates a gradually decrease as the experiment progresses. The bus stop adapted to the PM reduction system reduces the amount of black carbon in the experimental chamber by 37% at 200 min. This implies that the PM emitted from the roadside is filtered via the PM reduction system installed at the bus stop, and cleaner air quality can be provided to passengers. CONCLUSIONS : The PM reduction system evaluated in this study can be detached from and attached to the outdoor billboard of a bus stop. Since it adopts air filtration technology that uses a high-efficiency particulate air filter, it can be maintained and managed easily. In addition, it can provide an atmospheric environment with reduced PM emission to passengers as well as provide a better air-quality condition to passengers waiting for public transportation near roadsides.

PURPOSES : In this study, we analyzed the characteristics of nitrogen oxide and fine particulate matter concentration for boarding positions at the bus stop of an exclusive bus lane, using a correlation analysis and a generalized linear model. METHODS : To analyze the air pollution characteristics for boarding positions at the bus stop, data on nitrogen oxide, fine particulate matter concentration, relative humidity, temperature, wind speed, solar radiation, and bus traffic volume were acquired. Using the collected data, a correlation analysis for nitrogen oxide and fine particulate matter was carried out for each boarding position. Additionally, the prediction models for each pollutant were estimated using a generalized linear model, to analyze their characteristics. RESULTS : Correlation analysis revealed that relative humidity and bus volume were positively correlated with both nitrogen oxide and fine particulate matter concentrations in all boarding positions, whereas temperature, wind speed, and solar radiation were negatively correlated. Based on the estimated models from the generalized linear model, the nitrogen oxide concentration at the first measurement point was found to be affected by relative humidity, temperature, and bus volume, whereas at the second measurement point, it was found to be affected by relative humidity, temperature, and solar radiation. Additionally, all factors were significant for fine particulate matter concentration at both boarding positions. CONCLUSIONS : The analytical results indicated that the characteristics of nitrogen oxide and fine particulate matter concentration at the bus stop of an exclusive bus lane varied significantly depending on the boarding positions. Particularly, it was found that the correlation between solar radiation, and nitrogen oxide and fine particulate matter was different because of the conversion of nitrogen oxide to fine particulate matter.

PURPOSES : The purpose of this study was to analyze the effect of reducing nitrogen oxide concentration in a photocatalyst (titanium dioxide) using statistical methods such as the Anderson-Darling test. METHODS : To compare and analyze the effect of reducing the nitrogen oxide concentrations in titanium dioxide, titanium dioxide was applied to the public road, and data acquisition in terms of nitrogen oxide concentration was conducted from roads with/without applying titanium dioxide (test section and reference section, respectively). Then, the probabilities of occurrence of nitrogen oxide concentrations in the test and reference sections were estimated and compared using the Anderson-Darling test. RESULTS : According to the comparison and analysis of probabilities in the nitrogen oxide concentration of the test and reference sections, the probabilities of nitrogen oxide concentration on December 4th were estimated as ‘High’ (17.5%, 37.9%), ‘Moderate’ (30.5%, 40.8%), and ‘Low’ (52.0%, 21.3%), respectively, and on December 5th, as ‘High’ (20.6%, 39.1%), ‘Moderate’ (26.2%, 33.0%), and ‘Low’ (53.2%, 27.9%), respectively. In addition, the probabilities of nitrogen oxide concentration in the test and reference sections were analyzed on December 6th as ‘High’ (16.5%, 36.8%), ‘Moderate’ (27.9%, 38.5%), and ‘Low’ (55.6%, 24.8%), respectively. CONCLUSIONS : Based on the results of this study, in the test section with application of titanium dioxide, the nitrogen oxide concentration was found to have a low probability, and in the reference section, the nitrogen oxide concentration was found to be higher than that in the test section. Therefore, it can be concluded that titanium dioxide applied to road facilities has a nitrogen oxide reduction effect.

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.

PURPOSES : The objective of this study is to determine the characteristics of nitrogen oxide (NOx) concentration in an exclusive median bus lane station. The hourly variations of NOx concentration and the effect of traffic volume on NOx concentration were analyzed using NOx measurement data and the number of vehicles at the station. METHODS : Data were collected using the chemiluminescence method for NOx concentration. Atmospheric information and traffic volume of buses were collected from the Korea Meteorological Administration and Bus Information System, respectively. RESULTS : As a result, the NO2 concentration in the test section was found to have a strong correlation with those in the atmospheric measurement station located near the test-bed. In addition, the average NOx concentrations in the test section were significantly higher than those of the other monitoring stations due to bus emissions. The average NOx concentration in the exit section was higher than that in the entry section owing to the vehicle’s frequent stops and fuel consumption due to acceleration. During the measurement period, the average NOx concentration was measured as approximately 33 % higher in the exit section than in the entry section. In addition, the NOx concentration at the bus station was found to increase as the bus dwell time increased, rather than the number of bus passages. CONCLUSIONS : This study provides clear characteristics of the NOx correlations with traffic information in an exclusive median bus lane station. It was shown that the NOx concentration at the bus station increased as the number of passes and bus dwell time increased. According to the coefficient of determination, the dwell time is more closely correlated to the NOx concentration at the bus station than the number of bus passes, indicating that it is a better parameter for predicting NOx concentration at bus stations.

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.

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.

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.