• Journal of Korea Multimedia Society
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• v.20 no.8
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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.

• Journal of Korean Society of Environmental Engineers
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• v.39 no.4
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• pp.220-228
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• 2017

Since the fine particulate matters occurred from mainly combustion in industry and road transport effect to human respiratory health, the interest and importance are getting increased. In 2013, the World Health Organization (WHO) concluded that outdoor air pollution is carcinogenic to humans, with the particulate matter component ($PM_{10}$ and $PM_{2.5}$) of air pollution most closely associated with increased cancer incidence, especially cancer of the lung. Therefore, many researches have been studied in the quantification and data development of fine particulate matters. Currently, the Ministry of Environment and cities/regions are developing the fine particulate matter data and air emission information. Particularly just $PM_{10}$ and $PM_{2.5}$ data is used in the fine particulate matters warning and alert. The data of NOx, SOx, $NH_3$, which have the particulate matter formation potential are not well considered. Also, the researches related with particulate matter formation potential and respiratory effects by industrial sectors and cities/regions are not conducted well. Therefore, the purpose of this study is to evaluate and calculate particulate matter formation potential and respiratory effects in 11 industrial sectors and cities using NOx, SOx, $PM_{10}$, $NH_3$ data (developed by Ministry of Environment and National Institute of Environmental Research) in 2001 and 2013. The results of this study will be provided the particulate matter formation potential and respiratory effects and will be used for future the fine particulate matter researches.

• Journal of Korean Society for Atmospheric Environment
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• v.19 no.2
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• pp.133-143
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• 2003

Numerous evidence have been reported that fine particulate matters can play an important role in threatening human health. Recently concerns on fine particle pollution from various engines may require re-examination of particulate emission standards. The particles emitted by most diesel engines are mainly divided into their size ranges such as Dp< 50 nm and 50 nm< Dp< 1,000 nm. In this work, the number concentration and the size distribution of fine particles emitted from an exhaust manifold of a railroad diesel engine were measured under load test conditions using a scanning mobility particle sizer (SMPS). The fine particles observed were within the range of 7 to 304 nm under different load conditions with two different dilution ratios. The fine particles exhibited unique patterns showing bimodal shapes in size distribution.

• Journal of Korean Society for Atmospheric Environment
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• v.19 no.E3
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• pp.99-120
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• 2003

Visibility impairment in an urban area is mainly caused by airborne fine particulate matters. Visibility in a clean air environment is more sensitive to the change of PM$_{2.5}$ particle concentrations. However, a proportionally larger reduction in fine particle concentration is needed to achieve a small increment of visibility improvement in polluted areas. Continuous optical monitoring of atmospheric visibility and extensive aerosol measurements have been made in the urban atmosphere of Kwangju, Korea. The mean for fine particulate mass from 1999 to 2002 at Kwangju was measured to be 23.6$\pm$20.3 $\mu\textrm{g}$/㎥. The daily average seasonal visual range was measured to be 13.1, 9.2, 11.0, and 13.9 km in spring, summer, fall, and winter, respectively. The mean light extinction budgets by sulfate, nitrate, organic carbon, and elemental carbon aerosol were observed to be 27, 14, 22, and 12%, respectively. It is highly recommended that a new visibility standard and/or a fine particle standard be established in order to protect the health and welfare of general public. Much more work needs to be done in visibility studies, including long-term monitoring of visibility, improvement of visibility models, and formulating integrated strategies for managing fine particles to mitigate the visibility impairment and climate change.e.

• Proceedings of the Korean Environmental Health Society Conference
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• 2003.06a
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• pp.89-93
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• 2003

Daily average concentrations of fine particulates have been measured simultaneously in Seoul and Asan area by using PM minivolTM portable air sampler(Air Metrics, U.S.A) from September 2001 to August 2002. The sampler were analyzed by ICP-OES(inductively coupled plasma optical emission spectrometry, optima 3000DV, Perkin Elmor) to determine the fine particulate concentrations of metallic elements(As, Mn. Ni, Fe, Cr, Cu, Cd, Pb, Zn, Si). The concentration of PM$\sub$2.5/ showed a high trend in the Seoul area. Zn showed a similar distribution ratio for the fine particle in both Seoul and Asan. Mn and Fe, Cr, Cd are highly correlated in the Seoul and Asan area(P<0.05).

• International Journal of Highway Engineering
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• v.19 no.6
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• pp.31-36
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• 2017

PURPOSES : The computational fluid dynamics of flow and fine particles in a road were set to determine the insert flow and occurrence characteristics. METHODS : The road extension was 100 m with two lanes. A one-ton truck traveled a 50-m distance. After a noise barrier was installed on one side of the road, the flow and a collision analysis were tested. RESULTS : The flow that occurred was 5 m/s beside the vehicle, and fine particulate was $5.0{\times}10^2{\mu}g/m^3$ after 20 m from the exhaust vent. CONCLUSIONS : After a collision analysis of the fine particulate on the noise barrier to find the most suitable position of the filter panel in height, the bottom 1 m was the most optimum position because 88.1% of the distribution was concentrated there.

• Food Science and Industry
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• v.54 no.1
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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.

• Applied Chemistry for Engineering
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• v.26 no.2
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• pp.229-233
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• 2015

In this study, we examined the removal characteristics of suspended particulate matters which are one of carcinogens to cause lung cancer. The fine dust capture by a pilot scale filtration system depends on several important variables such as humidity, initial fine dust injection volume, and flow rate. The average concentration of particulate matters in the test chamber decreased, but the ultimate collection efficiency did not change during the filtration under high humidity, compared to those of using ambient conditions The initial injection amount of fine dust did not influence the particle capturing efficiency. When the flow rate reduced from 0.6 m/s to 0.3 m/s, the dust collection time increased approximately 1.4 times. Among all variables tested, the flow rate showed the most significant effect on the removal efficiency of fine particulate matter.

• Journal of Environmental Science International
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• v.32 no.2
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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.

• Journal of the Korean Society of Visualization
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• v.22 no.1
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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.