• Journal of Environmental Science International
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• v.29 no.3
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• pp.283-297
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• 2020

Technology used by human beings has developed drastically over the years. Although people enjoy affluent lives as a result of this development, the depletion of resources has brought about a variety of environmental problems such as emission of fine dust, treatment of waste water, and global warming. Although studies on environmental pollution are being conducted continuously, there are a limited number of studies that analyze research trends from quantitative and qualitative perspectives. In order to examine the current research landscape, we employed Scopus to combine research interest in environmental science with bibliographic analysis. Among 74,089 papers published in 57 journals of environmental science, 3,212 papers were published by Korean authors and citations per publications and Field-Weighted Citation Impact (FWCI) of those papers were 7.3 and 1.0, respectively. By assessing the bibliometric indicators in the field of environmental science, this study provides insight into research trends and related data to aid researchers in developing research strategies.

• Journal of Electrical Engineering and Technology
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• v.13 no.5
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• pp.2107-2115
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• 2018

Over recent years, high-concentration of particulate matters (e.g., a.k.a. fine dust) in South Korea has increasingly evoked considerable concerns about public health. It is intractable to track and report $PM_{10}$ measurements to the public on a real-time basis. Even worse, such records merely amount to averaged particulate concentration at particular regions. Under this circumstance, people are prone to being at risk at rapidly dispersing air pollution. To address this challenge, we attempt to build a predictive model via deep learning to the concentration of particulates ($PM_{10}$). The proposed method learns a binary decision rule on the basis of video sequences to predict whether the level of particulates ($PM_{10}$) in real time is harmful (>$80{\mu}g/m^3$) or not. To our best knowledge, no vision-based $PM_{10}$ measurement method has been proposed in atmosphere research. In experimental studies, the proposed model is found to outperform other existing algorithms in virtue of convolutional deep learning networks. In this regard, we suppose this vision based-predictive model has lucrative potentials to handle with upcoming challenges related to particulate measurement.

• Journal of Environmental Science International
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• v.30 no.12
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• pp.993-1003
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• 2021

It is known that the effect of traditional agricultural techniques of burning farmland such as paddy fields and fields gradually declines and affects both the fauna and flora of the rice paddy as well as pests. Therefore, in this study, a study was conducted to investigate the effects of burning rice paddy fields and rice paddy fields levee on the control effect of winter pests inhabiting agricultural land and the amount of pests generated and damaged during the growing season. As a result of this study, the pest control effect of incineration reduces not only the density of pests, but also beneficial insects (natural enemies) and non-reptiles. It is judged that burning has a very low insect control effect. It is expected to be used as basic data to create a sustainable agricultural environment, such as minimizing various negative effects such as pest control effects, wildfires, and air pollution caused by incineration, and suppressing unnecessary incineration and fine dust generation.

• Proceedings of the Korea Information Processing Society Conference
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• 2020.05a
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• pp.508-511
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• 2020

미세먼지(PM10, PM2.5)는 배출가스 증가와 함께 빠르게 악화되어 왔으며, 다양한 화학성분 뿐만 아니라 금속 성분이 포함되어 있어 인체에 큰 유해성을 발생한다. 이에 정부는 미세먼지 저감 정책 및 법률을 통해 개선하고자 했지만, 2013년부터 그 효력을 잃기 시작하였다. 이에 본 연구에서는 미세먼지 저감 정책 및 법률을 수립하는데 있어 가장 중요한 요소인 미세먼지 농도를 예측하는 연구를 진행한다. 이전 연구들에서 미세먼지 영향 요소들이 시계열 기반의 데이터(기상인자와 대기오염 인자)인 것을 확인하였기에, 시계열 데이터에 좋은 성능을 보이는 LSTM 알고리즘을 사용하여 학습 후, 서울시 '구별' '시간단위' 미세먼지 농도 예측에 대한 예측 오차(RMSE, MAE) 성능을 비교하였다. 실험 결과 PM10의 경우 (7.2, 4.78), PM2.5의 경우 (4.7, 3.2)의 예측 오차를 보였으며, 금천구의 경우 PM10이 (5.3, 3.71), PM2.5에서 (3.5, 2.5)로 가장 좋은 성능을 보였다.

• Journal of the Korean Society of Safety
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• v.32 no.5
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• pp.157-167
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• 2017

Millions of People die every year from diseases caused by exposure to outdoor air pollution. Especially, one of the most severe types of air pollution is fine particulate matter (PM10, PM2.5). South Korea also has been suffered from severe PM. This paper analyzes regional risks induced by PM10 and PM2.5 that have affected domestic area of Korea during 2014~2016.3Q. We investigated daily maxima of PM10 and PM2.5 data observed on 284 stations in South Korea, and found extremely high outlier. We employed extreme value distributions to fit the PM10 and PM2.5 data, but a single distribution did not fit the data well. For theses reasons, we implemented extreme mixture models such as the generalized Pareto distribution(GPD) with the normal, the gamma, the Weibull and the log-normal, respectively. Next, we divided the whole area into 16 regions and analyzed characteristics of PM risks by developing the FN-curves. Finally, we estimated 1-month, 1-quater, half year, 1-year and 3-years period return levels, respectively. The severity rankings of PM10 and PM2.5 concentration turned out to be different from region to region. The capital area revealed the worst PM risk in all seasons. The reason for high PM risk even in the yellow dust free season (Jun. ~ Sep.) can be inferred from the concentration of factories in this area. Gwangju showed the highest return level of PM2.5, even if the return level of PM10 was relatively low. This phenomenon implies that we should investigate chemical mechanisms for making PM2.5 in the vicinity of Gwangju area. On the other hand, Gyeongbuk and Ulsan exposed relatively high PM10 risk and low PM2.5 risk. This indicates that the management policy of PM risk in the west side should be different from that in the east side. The results of this research may provide insights for managing regional risks induced by PM10 and PM2.5 in South Korea.

• Land and Housing Review
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• v.11 no.4
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• pp.93-98
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• 2020

This study examined the particulate removal performance of three different types of air filters inside a heat exchanger. Of interest was the ability of each filter type in reducing the transmission of outdoor particulate matter of PM10 from entering an apartment while the heat exchanger was in operation. The study tested one commonly used medium filter (E11 grade) and two HEPA filters (H13 grade) of different thicknesses. Two different concentrations of particulate matter were used in the experiment to address different ambient air quality conditions in Korea, 32.75 ㎍/㎥ and 67.26 ㎍/㎥. Study results indicated that under the particulate matter concentration of 32.75 ㎍/㎥, all three filters were capable of removing more than 95% of the fine dust. However at a particulate matter concentration of 67.26 ㎍/㎥, the medium E11 grade filter was only able to remove about 90% of the particulates whereas the HEPA H13 grade filters were able to remove 95% or more of the particulates. The thicker HEPA filter (40T) was also more effective in removing particulates than the thinner HEPA filter (20T) by about 1.6 to 3 percentage points. Based on the findings of this study, it is recommended that HEPA filters of 20T thickness or greater be used during the high air pollution seasons of winter and spring in Korea while medium filters can be used during the other seasons to reduce outdoor air pollution transmission indoors.

• Journal of Korean Society for Atmospheric Environment
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• v.22 no.5
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• pp.604-613
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• 2006

The chemical composition of $PM_{2.5}$ such as ${SO_4}^{2-},\;{NO_3}^-,\;Cl^-,\;{NH_4}^+,\;Ca^{2+},\;K^+,\;Na^+,\;Mg^{2+}$, OC, and EC and the concentrations of reactive trace gases including $O_3,\;CO,\;NOx,\;SO_2,\;and\;H_2O_2$ were measured at Gosan in Jeju Island during March $13{\sim}30$, as a part of the Atmospheric Brown Clouds-East Asian Regional Experiment 2005(ABC-EAREX2005). The average mass concentrations of $PM_{2.5}$ was 27.3 ${\mu}g/m^3$, of which OC showed the highest concentration as 4.22 ${\mu}g/m^3$ and nss ${SO_4}^{2-}$ was the second highest as 3.34 ${\mu}g/m^3$. During that period, average concentrations of CO and $O_3$ was about 300 ppbv and 56 ppbv, respectively. For the whole experiment, the correlations of CO with ${SO_4}^{2-}$ and EC were very good, which suggests that CO can be used as tracer for the formation of fine aerosols. Several pollution and dust episodes were identified by the enhancement of CO, OC, EC, nss ${SO_4}^{2-},\;or\;Ca^{2+}$ concentrations or their ratios. In conjunction with factor analysis, air trajectory analysis, and comparison with emission inventories, these results indicate the spring aerosols collected at Gosan was strongly influenced by Asian outflows.

• Journal of the Society of Cosmetic Scientists of Korea
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• v.47 no.3
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• pp.237-245
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• 2021

Particulate matter and ultra-particle matters generally refer to very small floating dust, such as 1/6 to 1/7 and 1/20 to 1/30, respectively, compared to the thickness of human hair, and contain various types of heavy metal ions. In addition to breathing, particle matters (PM) that flows in through the gaps in the pores of the skin can induce health problems in the body's tissues and skin, so it must be removed by blocking the inflow or by washing. Through this study, we confirmed the possibility that heavy metal ions can be adsorbed and removed by using Oryza sativa (Rice) bran oil (OSBO). In addition, the cell viability is much higher than that of grain-derived components through cytotoxicity experiments, and the cytoprotective effect of an external stimulus source can be expected. It was confirmed that the expression amount of COL1A1 mRNA increased, and accordingly, it was believed that wrinkles that might be caused by moisture lost by heavy metal ions in fine dust could be alleviated. Based on the results of these experiments, we tried to present a cosmetics containing OSBO, which is a wash-off formulation, in order to finally remove heavy metals.

• Journal of Ginseng Research
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• v.47 no.1
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• pp.81-88
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• 2023

Background: Air pollution has led to an increased exposure of all living organisms to fine dust. Therefore, research efforts are being made to devise preventive and therapeutic remedies against fine dust-induced chronic diseases. Methods: Research of the respiratory protective effects of KRG extract in a particulate matter (PM; aerodynamic diameter of <4 ㎛) plus diesel exhaust particle (DEP) (PM4+D)-induced airway inflammation model. Nitric oxide production, expression of pro-inflammatory mediators and cytokines, and IRAK-1, TAK-1, and MAPK pathways were examined in PM4-stimulated MH-S cells. BALB/c mice exposed to PM4+D mixture by intranasal tracheal injection three times a day for 12 days at 3 day intervals and KRGE were administered orally for 12 days. Histological of lung and trachea, and immune cell subtype analyses were performed. Expression of pro-inflammatory mediators and cytokines in bronchoalveolar lavage fluid (BALF) and lung were measured. Immunohistofluorescence staining for IRAK-1 localization in lung were also evaluated. Results: KRGE inhibited the production of nitric oxide, the expression of pro-inflammatory mediators and cytokines, and expression and phosphorylation of all downstream factors of NF-κB, including IRAK-1 and MAPK/AP1 pathway in PM4-stimulated MH-S cells. KRGE suppressed inflammatory cell infiltration and number of immune cells, histopathologic damage, and inflammatory symptoms in the BALF and lungs induced by PM4+D; these included increased alveolar wall thickness, accumulation of collagen fibers, and TNF-α, MIP2, CXCL-1, IL-1α, and IL-17 cytokine release. Moreover, PM4 participates induce alveolar macrophage death and interleukin-1α release by associating with IRAK-1 localization was also potently inhibited by KRGE in the lungs of PM4+D-induced airway inflammation model. KRGE suppresses airway inflammatory responses, including granulocyte infiltration into the airway, by regulating the expression of chemokines and inflammatory cytokines via inhibition of IRAK-1 and MAPK pathway. Conclusion: Our results indicate the potential of KRGE to serve as an effective therapeutic agent against airway inflammation and respiratory diseases.

• Journal of Environmental Health Sciences
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• v.49 no.4
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• pp.218-227
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• 2023

Background: Since 2019, the Ministry of Environment has implemented a seasonal fine dust management system from December to March, targeting high PM_2.5 levels with the aim of reducing PM_2.5 concentrations and protecting public health. The focus of improving the seasonal management system lies in the atmospheric PM_2.5 levels. Considering the primary goal of protecting public health, it is necessary to analyze the policy effects from an exposure perspective rather than a concentration-based approach. Objectives: This study aims to quantitatively assess the improvement of indoor PM_2.5 levels and the health impacts of the seasonal management system by comparing the periods before and during its implementation in residential environments. Methods: PM_2.5 concentrations within residential environments in a metropolitan area were measured using an optical particle counter (IAQ-C7, K-weather, Ltd, Korea) at one-minute intervals during the pre-implementation period (November 21~25, 2022) and during the implementation period (December 19~23, 2022). Based on the measured PM_2.5 concentrations, a quantitative evaluation of cancer and mortality risks was conducted according to age and gender. Results: The results of comparing indoor and outdoor PM_2.5 concentrations before and during the implementation of the seasonal management system showed a decrease of approximately 56.6% and 47.9%, respectively. Health risk assessments revealed that both the safety-limit-based and safety-target-based Hazard Quotients (HQ) exceeded the threshold of 0.1 for children under 19 years of age, both before and after the implementation. The mortality risk decreased by approximately 47.9% after the implementation, with children aged 0-9 showing the highest mortality risk at 0.9%. Conclusions: The findings of this study confirmed the positive health impacts of the seasonal management system across all age groups, particularly children under 19 who are more vulnerable to fine dust exposure.