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.

In this study, we evaluated the filtering effect of the fine dust mask. Our objective research has secured credibility in the private sector. The performance of domestic fine dust masks is evaluated by three dust collection efficiencies, inspiratory resistance, and leakage rate according to KF grade in the health mask standard guidelines issued by the Ministry of Food and Drug Safety. Based on this, eight types of fine dust masks were evaluated for dust collection efficiency and face intake resistance. All masks showed good performance as the collection efficiency was 90%. The higher the KF grade, the higher the collection efficiency, but the inspiratory resistance had no correlation with the grade. According to the manufacturer's operation method, masks below the standard value may be distributed. Masks that are currently on the market have shown results that can be trusted. However, we hope that the system will be improved to validate whether the masks that meet the threshold are still being distributed.

The cooking-generated particles are major indoor sources of air pollution. Recently, the performance of the range hood is focused on particle removal performance. Range hood with an auxiliary air supply system can improve the fine and ultrafine particles removal efficiency by making a supply air during cooking activities. The particles were measured in the experimental building by varying ventilation types. Only operating range hood during the cooking activities was not enough to reduce the cooking-generated particles. Despite operating range hood systems, fine and ultrafine particle concentrations were maintained when cooking was finished. The range hood with a make-up air supply system can reduce the indoor particle concentration below background conditions when those systems were operated after cooking. In this study, the assessment of cooking-generated particle removal efficiency of the range hood with an auxiliary air supply system was conducted. The removal efficiency of ultrafine particles showed trends similar to the removal efficiency of fine particles.

충남 금산지역 잎들깨 시설하우스에서 차먼지응애(Polyphagotarsonemus latus)는 5월 하순 최초 발생하기 시작하여 6월 중순에 1차 최대 발생양상을 보인 후 7월 상순부터 급격히 밀도가 증가하여 7월 중순 가장 밀도가 높은 2차 최대 발생양상을 보였다. 방제방법에 따라 발생양상에는 차이가 없었으나 밀도에는 차이를 보여 화학약제를 사용하는 하우스에서 가장 높았고 유기농업자재를 사용하는 하우스에서 가장 낮았다. 이는 크기가 작아 육안으로 관찰할 수 없는 차먼지응애를 방제하기 위해 화학약제를 사용할 경우, 농약 잔류 문제로 지속적인 사용을 못하므로 밀도가 높아지고, 유기농업자재를 사용하는 경우에서는 농약잔류에 대한 걱정 없이 유기농업자재를 지속적으로 사용함으로써 방제가 이루어졌던 것으로 판단된다. 잎들깨 주간내 발생양상을 조사한 결과, 차먼지응애는 접종 25일 후 최대 발생밀도를 보였고, 중엽, 성엽, 신초의 순으로 알과 약성 충의 총밀도가 조사되었다. 그러나 엽장과 차먼지응애 밀도와의 상관성 분석 결과, 상관성이 없어 차먼지응애 발생예찰시 어떤 샘플을 채취해도 정확한 예찰이 이루어질 것으로 판단된다.

PURPOSES : Over the years, the concentration of fine dust is gradually increasing, thereby aggravating the seriousness of the situation. Accordingly, this study intends to install a clean road system using low impact development (LID) techniques on the roadside in order to reduce the scattering of dust on roads effectively. This system stores rainwater collected through gutters in rainy weather and sprays water onto the pavement surface to reduce the scattering of road dust. METHODS : The developed clean road system consists of a water tank, controller, rain detection sensor, and solar cell. Based on this, a test-bed construction was used to evaluate its applicability. By applying the developed system, actual applicability was evaluated through total suspended solid (TSS) test and fine dust measurement. TSS test was conducted to measure the reduction rate of scattering dust on the road owing to the water injected by the clean road system. A spray nozzle was used for the TSS test, and a nebulization nozzle was used for the measurement of fine dust. In order to increase the reliability of the test, three measurements were taken each, for normal road as well as unfavorable conditions road that reproduced the construction site. RESULTS : In this study, fine dust concentration measurement and TSS test were conducted to evaluate the practical applicability of the developed clean road system. From the TSS test, it was found that for both general roads and roads depicting bad conditions, the TSS value after the first spray was the highest, and the value after the second spray was sharply reduced, such that most of the re-dispersed dust was washed out after the first spray, and similar TSS value results were obtained after the third spray. Based on this result, the result of fine dust measurement showed similar fine dust reduction effect of 9%-15.9% regardless of the concentration of fine dust in the atmosphere. These results indicate that the concentration of fine dust in the atmosphere does not significantly affect of the degree of reduction in fine dust. CONCLUSIONS : In this study, a clean road system for reducing fine dust on the road was developed and its applicability was evaluated. In a future study, we intend to check the performance of the drainage pavement through performance evaluation of water permeability coefficient test and performance test in the form of drainage pavement. Through this, we intend to evaluate the applicability of the clean road system to which drainage pavement is applied. Moreover, we will develop a clean road system that applies drainage packaging, and analyzes the degree of fine dust reduction according to the spray angle, spray amount, and spray time of the clean road system in order to study the spray system with the optimum amount of fine dust reduction. In addition, in order to reduce fine dust in the winter, when fine dust is mainly generated, it is planned to install heating wires in spray pipes where freezing is expected. Lastly, the black ice prevention effect will be analyzed by mixing a certain amount of sodium chloride when spraying water.

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.

본 연구에서는 복잡한 도심의 구조로 인한 미세먼지 농도의 강화 가능성에 대하여 데이터 마이닝 기술과 군집분석을 이용해 조사하였다. 데이터 마이닝 분석에서 미세먼지 농도와 서울지역 도시용도 데이터 사이에는 유의한 상관관계를 보이지 않았다. 그러나 전국 공공데이터를 기반으로 한 군집분석에서는 건물의 높이(층수)에서 특히 PM10과 강한 상관관계가 나타났다. 단일 케노피 모델(Single Canopy Model) 및 미기상 도시모델링 프로그램(ENVI-Met.4)을 사용한 모델링 분석을 실시하여 도시지역에서 모사된 대기 대류가 건물 분포 및 높이 유형의 배열에 따라 다양한 난류의 패턴을 구현함을 확인하였 다. 도시 건물의 복잡한 구조는 대류활동을 제어하여 정체상태를 유도하고 지표 부근의 미세먼지 강화가능성을 초래 하였다. 따라서 도심 구조와 형태에 따른 열환경의 변화로 인한 정체 효과는 미세먼지 산정에 있어서 반드시 고려되어야 한다. 복잡한 도시지역의 미세먼지 잔류확률에 대한 정보를 제공하기 위해서는 대기정체 현상이 중요한 의미로 해석될 수 있다.

PURPOSES : The purpose of this fundamental study is to estimate the concentration of resuspended road dust in urban areas. This involves examining and measuring the factors that affect the dust concentration and measuring these factors and the concentration directly and indirectly by analyzing the factor-effect relationship of the dust in actual operation. METHODS : From the literature review, the factors that influence resuspended road dust, including traffic, environment, and weather data of roads and their relationship analysis were obtained to determine the effects of each element on resuspended road dust. The data characteristics and the quantitative changes in the factors when a high concentration of resuspended road dust is generated are analyzed for each condition. The concentrations of the resuspended dust are presented from the perspective of each factor. RESULTS : When the vehicle speed increased from 60 to 80 km/h, the measured resuspended dust concentration increased by 8㎍/m3 on the average. When the traffic was grouped, the resuspended concentration at 1200-1400 veh/h was 15.84㎍/m3 higher than that of 500-800 veh/h. A high concentration of 60㎍/m3 or more was generated in the SCL high and middle sections, and a high concentration of 10㎍/m3 or more was generated in the SCL low section. Eight cases were observed in the SCL high and middle section at an intense atmospheric wind speed of 3 m/s or more than the SCL level of zero cases. A high concentration of 89.8㎍/m3 resuspended dust was observed after 31 h of rainfall, and the dust concentration gradually decreased by over 50 h. Hence, the passing time after the rainfall, SCL and wind speed, traffic and vehicle speed, and air background (observation) concentration, all have a direct effect on the resuspended dust concentration. Atmospheric temperature and relative humidity have a significant effect on atmospheric dust concentration. CONCLUSIONS : The quantitative indicators of the factors using an estimation model of resuspended road dust in urban areas can be obtained if the conditions for high concentrations of resuspended dust are established using the quantitative relationship of the resuspended road dust factors presented in this study.

This study was conducted as a part of the research for the “Development of Big Data Analysis Techniques and AI-based Integrated Support System for Energy-Environment Management.” We collected research results on characterization of distribution of fine dust and re-analyzed using meta-analysis techniques to build “big data” with high potential for school environments. The results of prior studies on the characteristics of fine dust concentration distribution in a school environment conducted in Korea were collected and re-analyzed the results using the metaanalysis technique. In this manner, the variables that could be used to derive the independent variables needed to produce the e-coding book prior to the big data collection, were first derived. The possibility of using the data as independent variables was then evaluated. In this study, three variables: “elementary school vs. middle school vs. high school,” “general classroom vs. special classroom,” and “new classroom vs. old classroom” were evaluated for their application as major classification variables with priority. The necessity of being derived as a major classification variable was examined by testing the difference in fine dust concentration distribution in the school environment by each variable case. Results showed that “elementary school vs. middle school vs high school” and “general classroom vs. special classroom” could be used as independent variables, while “new classroom vs. old classroom” was less likely to be used as an independent variable.

Recently, the importance of air filters used in air purifiers and ventilation systems is emphasized in Korea. As a result, air filter test reports are required by users to ensure the removal efficiency of particulate matter. However, the tests are conducted for the filter material alone, which lead to a possible discrepancy between the test report and actual efficiency when applied to actual devices. Therefore, in this study, the removal efficiency data of the filter test reports were compared with actual filter efficiency data after application to the ventilation systems for some ventilation systems in the market. For ventilation system A, the field test results using filter leakage test method were slightly lower than those in the test report but nearly the same. For ventilation system B, the field test result was much higher than reported in the test report. This was due to the broad range of particle sizes measured using the filter leakage test method. The field tests using the particle counter method showed that the removal efficiency of ventilation system A for 0.3 μm was under 50% which translates to less than half of those of the filter test reports. For ventilation system B, the removal efficiency was 15%~21%. much lower than reported in the filter test reports. The lower removal efficiencys are mainly assumed to be caused by leakage of the filter installation among other factors. Therefore, the field test methods for the particulate matter removal efficiency of ventilation systems should be established to verify actual efficiency and improve the efficiency in the future.

본 연구는 미세먼지 문제 속에서의 환경권 보장에 대한 연구이다. 미세먼지가 사회문제로 이슈화되고 이에 대한 국민의 환경권에 대한 논의를 한 뒤, 미세먼지와 관련된 판례에서 나타난 국민이 건강하게 좋은 환경에서 살아갈 권리를 조명한다. 특히 국내 판결에서 건강권과 관련하여 배출가스 또는 미세먼지가 질병에 미치는 영향의 과학적 입증이 필요함을 강조한다. 연구를 통해 국민의 환경권을 보장하고 환경 불평등을 완화하며 환경 정의를 실현하기 위해 미세먼지 문제의 해결이 요원함을 알 수 있었다. 미세먼지 농도와 환경기준 미달성률, 시도별 미세먼지 현황을 검토하며 국가 및 지자체가 법제를 통해 심화되는 미세먼지 문제를 해결하려는 노력을 알 수 있었다. 미세먼지로부터 받는 영향력이 소외계층에게 더욱 컸고, 지역별로도 미세먼지의 피해가 다양하게 나타났고 이에 대응한 조례들도 제정되고 있다. 또한 본 연구에서 미세먼지와 관련한 판결들을 분석하였고 각종 미세먼지의 원인과 손해, 국가배상, 배출금지와 관련된 판례에서 과학기술 연구 결과를 인용하고 그 측정치 내지 분석결과나 논문을 판단의 잣대로 삼았다는 것을 알 수 있었다. 우리나라에선 미세먼지가 국민 질병에 미치는 피해와 관련한 소송이 있었지만 법원이 인정하지 않았다. 한국은 지금까지 개별적 인과관계를 인정하지 않았지만 대법원과 헌법재판소에 판례에 따르면 실제 전국에 걸쳐 국민들이 대기환경으로 피해를 보고 있는 경우 국가가 책임을 회피하기는 어려울 것이다. 이러한 과학적 인과관계 입증의 어려움이 컸던 기존 판례의 어려움을 통해 보았을 때 미세먼지 문제를 해결하기 위한 과학기술정책과 법제의 지원이 필요하다. 한국에 부족한 미세먼지 관련 연구개발을 중흥하기 위한 국가 주도의 법정책이 필요하며 국가기후환경위원회를 통해 과학적 사실과 국민인식의 괴리를 좁히는 노력도 필요하다. 또한 항만지역 등 미세먼지발생이 높은 섹터에 대한 정보체계관리와 과학기술을 통한 배출물질과 오염의 인과관계를 밝히는 노력이 필요하며 이를 위한 법제 지원도 중요한 요소로 판단된다.

PURPOSES: Nitrogen oxide (NOx) is a particulate matter precursor, which is a harmful gas contributing to air pollution and causes acid rain. The approaching methods for NOx removal from the air are the focus of numerous researchers worldwide. Titanium dioxide (TiO2) and activated carbon are particularly useful materials for NOx removal. The mechanism of NOx elimination by using TiO2 requires sunlight for a photocatalytic reaction, while activated carbon absorbs the NOx particle into the pore itself after contact with the atmosphere. The mixing method of these two materials with concrete, coating, and penetration methods on the surface is an alternative method for NOx removal. However, this mixing method is not as efficient as the coating and penetration methods because the TiO2 and the activated carbon inside the concrete cannot come in contact with sunlight and air, respectively. Hence, the coating and penetration methods may be effective solutions for directly exposing these materials to the environment. However, the coating method requires surface pretreatment, such as milling, prior to securing contact, and this may not satisfy economic considerations. Therefore, this study aims to apply TiO2 and activated carbon on the concrete surface by using the penetration method. METHODS : Surface penetrants, namely silane siloxane and silicate, were used in this study. Photocatalyst TiO2 and adsorbent activated carbons were selected. TiO2 was formed by the crystal structures of anatase and rutile, while the activated carbons were plant- and coal-type materials. Each penetrant was mixed with each particulate matter reductant. The mixtures were sprayed on the concrete surface using concentration ratios of 8:2 and 9:1. A scanning electron microscopy with energy dispersive X-ray equipment was employed to measure the penetration depth of each specimen. The optimum concentration ratio was selected based on the penetration depth. RESULTS: TiO2 and activated carbon were penetrated within 1 mm from the concrete surface. This TiO2 distribution was acceptable because TiO2 and activated carbon locate to where they can directly come in contact with sunlight and air pollutant, respectively. Infiltration to the concrete surface was easily achieved because the concrete voids were bigger than the nanosized TiO2 and microsized activated carbon. The amount of penetration for each particulate matter reductant was measured from the concrete surface to a certain depth. CONCLUSIONS : The mass ratio on the surface can be predicted from the mass ratio of the particulate matter reductant measurement distributed through the penetration depth. The optimum mass ratio was also presented. Moreover, the mixtures of TiO2 with silane siloxane and activated carbon with silicate were recommended with an 8:2 concentration ratio.

본 논문에서는 선박용 디젤엔진의 미세먼지저감 장치에 장착된 다공판 및 믹서의 형상과 배치에 따른 압력강하와 유동균일도 특성에 대한 연구를 진행하였다. 미세먼지저감 장치에 장착된 다공판 및 믹서는 미세먼지저감 장치 내의 배출가스 및 산화/환원제의 유동 균일도를 높여 배출가스 저감 성능을 높이는 긍정적인 효과와 함께 시스템의 배압을 상승시키는 부정적인 효과도 동시에 지니고 있다. 본 연구에서는 5개의 다공판, 1개의 믹서를 Case 별로 조합하여 6개의 사양에 대해서 유동해석을 통해 각각 유동균일도 및 압력 강하를 계산하였으며, 최적의 다공판 및 믹서의 형상과 배치를 선정하였다.

Outdoor air pollution with particulate matter has become more severe in Korea. Ambient particle concentration affects the indoor environment through various routes through building envelopes. In this study, we investigated particle exposure in residential buildings. Indoor and outdoor particle sources determined the indoor concentrations and particle exposure. This paper measured indoor particles and CO2 concentrations in two different apartment buildings and conducted the survey for 24 hours. The I/O ratio of the occupant awake period was higher than the asleep period. The I/O ratio in the awake period is 0.93-3.65, while the I/O ratio in the asleep period is 0.31- 0.76.Indoor peak events such as cooking or cleaning temporarily increase the I/O ratio and emit the indoor particle sources. Decay rate constant is 0.49-6.84 (1/h) in the indoor peak events during the operation of the exhaust hood and natural ventilation. The size range of 0.3-0.5 μm size is over half for the proportions of emitted particles (55.6%). Daily exposure is divided into indoor sources (45.2%) and outdoor sources (54.8%). We found the differences for the proportion of particle exposure. The ratio of daily exposure in particles for 0.3-0.5 μm size is 43.1 (indoor)/ 56.9 (outdoor) %. However, indoor sources are higher than outdoor sources for the ratio of daily exposure in particles for the 0.5-10.0 μm size.

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.

Recently, a number of researchers have produced research and reports in order to forecast more exactly air quality such as particulate matter and odor. However, such research mainly focuses on the atmospheric diffusion models that have been used for the air quality prediction in environmental engineering area. Even though it has various merits, it has some limitation in that it uses very limited spatial attributes such as geographical attributes. Thus, we propose the new approach to forecast an air quality using a deep learning based ensemble model combining temporal and spatial predictor. The temporal predictor employs the RNN LSTM and the spatial predictor is based on the geographically weighted regression model. The ensemble model also uses the RNN LSTM that combines two models with stacking structure. The ensemble model is capable of inferring the air quality of the areas without air quality monitoring station, and even forecasting future air quality. We installed the IoT sensors measuring PM2.5, PM10, H2S, NH3, VOC at the 8 stations in Jeonju in order to gather air quality data. The numerical results showed that our new model has very exact prediction capability with comparison to the real measured data. It implies that the spatial attributes should be considered to more exact air quality prediction.