• 대한환경공학회지
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• 제39권4호
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• pp.220-228
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• 2017

많은 산업 및 도로이동오염원 등으로부터 발생되는 미세먼지는 인간건강과 호흡기에 큰 영향을 미치고 있으며 이에 대한 중요성이 점차 증가하고 있다. 세계보건기구(WHO)에서도 미세먼지($PM_{10}$) 및 초미세먼지$PM_{2.5}$)를 석면 및 비소 등의 물질과 같은 등급인 1급 발암물질로 지정한 이후로 우리나라에서도 지속적인 관심과 연구를 진행해오고 있다. 현재 환경부와 각 지자체별로 미세먼지 및 대기오염정보를 구축하여 제공하고 있지만, 특히 미세먼지 주의보 및 경보발령에 있어서 미세먼지 $PM_{10}$ 및 $PM_{2.5}$ 자료만을 활용하고 있고 미세먼지형성에 영향을 주는NOx, SOx, $NH_3$자료는 활용 및 고려를 하지 않고 있다. 또한 국내 산업별 및 지자체별로 세부적인 미세먼지형성 가능성(particulate matter formation potential) 및 발생되는 미세먼지로 인한 인체호흡기 영향평가(respiratory effects)와 관련된 연구는 많이 진행이 되고 있지 않다. 이에 본 연구의 목적은 국내 11개 산업별 및 시도별로 2001년과 2013년 환경부 및 국립환경과학원에서 제시하고 있는 NOx, SOx, $PM_{10}$, $NH_3$ 자료를 활용하여 미세먼지형성(particulate matter formation potential) 평가와 이로 인한 인체 호흡기 영향을 평가 및 산정하여 비교 제시하고자 하였다. 본 연구결과로는 산업별 및 시도별로 미세먼지형성과 인간건강에 영향을 제시하였으며, 향후 미세먼지 관련 연구에 중요하게 활용할 수 있을 것으로 사료된다.

• 한국멀티미디어학회논문지
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• 제20권8호
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• pp.1208-1215
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• 2017

Recently, people's attention and worries about fine particulate matter have been increasing. Due to the construction and maintenance costs, there are insufficient air quality monitoring stations. As a result, people have limited information about the concentration of fine particulate matter, depending on the location. Studies have been undertaken to estimate the fine particle concentrations in areas without a measurement station. Yet there are limitations in that the estimate cannot take account of other factors that affect the concentration of fine particle. In order to solve these problems, we propose a framework for estimating the concentration of fine particulate matter of a specific area using meteorological data and traffic data. Since there are more grids without a monitor station than grids with a monitor station, we used a domain adversarial neural network based on the domain adaptation method. The features extracted from meteorological data and traffic data are learned in the network, and the air quality index of the corresponding area is then predicted by the generated model. Experimental results demonstrate that the proposed method performs better as the number of source data increases than the method using conditional random fields.

• 식품과학과 산업
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• 제54권1호
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• pp.29-33
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• 2021

Particulate matter (PM) is an air pollutant that causes serious environmental problems in Korea and other countries. The annual average PM10 concentration in Korea is around 40 ㎛/㎥, which is more than twice as high as the WHO recommended standard. When consumed with food, fine PM can pose a risk to humans. However, the risk of fine PM has been focused on the risk of fine PM introduced through the respiratory system. We investigated the quantitative measuring methods of PM10 on food surface to identify possible risk analysis of fine PM. The surfaces of food with artificially contaminated PM10 were observed with a scanning electron microscope(SEM). An automatic object-based image analysis was used to analyze the amount and size distribution of particulate matter contained in SEM micrographs.

• 한국건축시공학회:학술대회논문집
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• 한국건축시공학회 2023년도 가을학술발표대회논문집
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• pp.201-202
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• 2023

Now, there are many cases where materials are maintained at construction sites or standard construction prices are not in accordance with the applicable regulations, resulting in a lot of fine dust. Therefore, a particulate matter measurement system is applied not only to manage particulate matter at construction sites but also to reduce particulate matter .This study aims to evaluate the applicability of this particulate matter measurement system to the construction site through long-term measurement experiments using a light scattering method particulate matter measurement instrument at the construction site.

• 한국환경보건학회지
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• 제46권6호
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• pp.719-725
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• 2020

Objectives: With the growth of national interest in fine particulate matter, many complaints about pollutants emitted from air pollution emitting facilities have arisen in recent years. In particular, it is thought that a large volume of particulate pollutants are discharged from workplaces that use Solid Refuse Fuel (SRF). Therefore, particulate contaminants generated from SRF were measured and analyzed in this study in terms of respective particle sizes. Methods: In this study, particulate matter in exhaust gas was measured by applying US EPA method 201a using a cyclone. This method measures Filterable Particulate Matter (FPM), and does not consider the Condensable Particulate Matter (CPM) that forms particles in the atmosphere after being discharged as a gas in the exhaust gas. Results: The mass concentration of Total Suspended Particles (TSP) in the four SRF-using facilities was 1.16 to 11.21 mg/Sm3, indicating a very large concentration deviation of about 10 times. When the fuel input method was the continuous injection type, particulate matter larger than 10 ㎛ diameter showed the highest particle size fraction, followed by particulate matter smaller than 10 ㎛ and larger than 2.5 ㎛, and particulate matter of 2.5 ㎛ or less. Contrary to the continuous injection type, the batch injection type had the smallest particle size fraction of particulate matter larger than 10 ㎛. The overall particulate matter decreased as the operating load factor decreased from 100% to 60% at the batch input type D plant. In addition, as incomplete combustion significantly decreased, the particle size fraction also changed significantly. Both TSP and heavy metals (six items) satisfied the emissions standards. The measured value of the emission factor was 38-99% smaller than the existing emissions factor. Conclusions: In the batch injection facility, the particulate matter decreased as the operating load factor decreased, as did the particle size fraction of the particulate matter. These results will help the selection of effective methods such as reducing the operating load factor instead of adjusting the operating time during emergency reduction measures.

• 한국환경과학회지
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• 제32권2호
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• pp.131-137
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• 2023

Filter and microbalance sensitivity in measuring fine particulate matter mass is greatly influenced by particulate properties and environmental factors. Temperature and humidity control inside a measuring chamber with a microbalance, and neutralization of static charges on filters are essential for consistent filter weighing. Commercial weighing chambers are expensive with a unit price of tens of millions won. This study developed an inexpensive weighing chamber for weighing fine particulate matter and evaluatedits weighing performance. A microbalance with 1 ㎍ precision was used to measure the weight of a filter. The microbalance was set in a transparent acrylic enclosure (100 × 60 × 65 cm³) equipped with temperature and humidity control equipments. Weighing performance of the chamber was examined using Teflon filters with or without different particulate sample types. Temperature and humidity were maintained at approximately 23.2±1.2 ℃ and 36.2±1.8℃ for 8 days, respectively.

• 한국가시화정보학회지
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• 제22권1호
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• pp.34-39
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• 2024

With the fine particulate matter (PM) poses a serious threat to public health and the environment. The ultrafine PM in particular can cause serious problems. This study investigates the effectiveness of a submicron dry fog system in removing fine PM. Two methods are used to create fine dust particles: burning incense and utilizing an aerosol generator. Results indicate that the dry fog system effectively removes fine dust particles, with a removal efficiency of up to 81.9% for PM₁₀ and 61.9% for PM_2.5 after 30 minutes of operation. The dry fog, characterized by a mean size of approximately 1.5 ㎛, exhibits superior performance in comparison to traditional water spraying methods, attributed to reduced water consumption and increased contact probability between water droplets and dust particles. Furthermore, experiments with uniform-sized particles which sizes are 1 ㎛ and 2 ㎛ demonstrate the system's capability in removing ultrafine PM. The proposed submicron dry fog system shows promise for mitigating fine dust pollution in various industrial settings, offering advantages such as energy consumption and enhanced safety for workers and equipment.

• 한국환경생태학회지
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• 제32권5호
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• pp.541-552
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• 2018

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.

• 자동차안전학회지
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• 제10권3호
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• pp.27-31
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• 2018

The People have a bad perception about diesel vehicle because of serious air pollution, increase fine dust and global vehicle company's diesel gate. Starting the project in 2005, Ministry of Environment has been supporting that is exhaust gas reduction devices (DPF) on diesel vehicles in the metropolitan area. During the period of 2017.01.01 to 2017.12.31, 10,030 diesel vehicles installed exhaust gas reduction devices (DPF). Among them, 9,921 diesel vehicles that they have sufficient data for analysis were analyzed amount of particulate matter reduction before and after exhaust gas reduction devices (DPF) was installed. Opacity smoke meter measures the concentration of particulate matter. So concentration of particulate matter was converted into a mass unit, and then calculated the total amount of reduced particulate matter. It was estimated that social benefits is costs required to remove it from the total amount of particulate matter.

• 한국빅데이터학회지
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• 제9권1호
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• pp.127-140
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• 2024

이 연구는 녹색 교통 지역에서 차량 등급 운행 제한이 초미세먼지 농도에 미치는 영향을 연도별로 조사하였다. 연구 결과, 차량 등급 운행 제한이 초미세먼지 농도를 줄이는 데 긍정적인 영향을 미쳤다. 녹색 교통 지역 정책은 차량 유출을 감소시키고 대중 교통 및 친환경 교통수단을 활용하도록 유도하여 대기질을 향상시킨 것으로 나타났다. 특히 초미세먼지 농도의 감소는 주요 결과 중 하나로 나타났으며, 이는 도시 내 거주민들의 건강 개선에 긍정적인 영향을 미칠 것으로 기대된다. 연구에서는 차량 등급 운행제한 정책의 효과와 관련하여 다양한 요인과 변수를 고려하였으며, 정책의 시행 방식, 지역 특성 및 다른 환경 요인도 논의 될 필요성이 있다고 판단 하였다. 이러한 연구 결과는 초미세먼지 관리와 도시 계획의 측면에서 중요한 시사점을 제공하며, 미래의 도시 지속 가능성을 고려할 때 참고 자료 및 향후 연구가 지속적으로 필요 할 것으로 예측 된다.