• Biomolecules & Therapeutics
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• v.29 no.2
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• pp.220-226
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• 2021

The role of particulate matter (PM) in health problems including cardiovascular diseases (CVD) and pneumonia is becoming increasingly clear. Polycyclic aromatic hydrocarbons, major components of PM, bind to aryl hydrocarbon receptor (AhRs) and promote the expression of CYP1A1 through the AhR pathway in keratinocytes. Activation of AhRs in skin cells is associated with cell differentiation in keratinocytes and inflammation, resulting in dermatological lesions. Oleanolic acid, a natural component of L. lucidum, also has anti-inflammation, anticancer, and antioxidant characteristics. Previously, we found that PM10 induced the AhR signaling pathway and autophagy process in keratinocytes. Here, we investigated the effects of oleanolic acid on PM10-induced skin aging. We observed that oleanolic acid inhibits PM10-induced CYP1A1 and decreases the increase of tumor necrosis factor-alpha and interleukin 6 induced by PM10. A supernatant derived from keratinocytes cotreated with oleanolic acid and PM10 inhibited the release of matrix metalloproteinase 1 in dermal fibroblasts. Also, the AhR-mediated autophagy disruption was recovered by oleanolic acid. Thus, oleanolic acid may be a potential treatment for addressing PM10-induced skin aging.

• Journal of The Korean Society of Agricultural Engineers
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• v.64 no.1
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• pp.99-110
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• 2022

In this study, the generation and emission characteristics of particulate matter and gaseous matter in a mechanically ventilated layer house were evaluated. Each concentration of PM₁₀, PM_2.5, inhalable dust, respirable dust, and NH₃ was measured and compared with occupational limit considering seasons and respiratory disorder. CAPPS (Clean Air Policy Support System) of the Ministry of Environment proposes the emission factors of PM₁₀, PM_2.5, and NH₃ for a layer houses however, emission factors are still calculated from foreign factors such as CONINAIR values. As a result, it is urgent to develop national emission factors for domestic layer house. Emission coefficients of the studied mechanically-ventilated layer house in a summer season were calculated as 0.052 kg/head/year for PM₁₀, about 12% lower than that of CAPSS, and 0.0068±0.0038 kg/head/year for PM_2.5, showing no significant difference. Emission factor of NH₃ was calculated as 0.159±0.031 kg/head/year, about 51% lower than that of CAPSS.

• Economic and Environmental Geology
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• v.54 no.4
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• pp.475-482
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• 2021

This study proposed a strategy with literature review on effective monitoring of dispersion of the particulate matters (PM) emitted from domestic open pit lime mines. The mines generally produced a large amount of PM through the mine processes such as crushing and transportation of raw or crushed ores. The PM emission from mine facilities or transportation can be assessed using empirical equations which was prepared through the experimental tests to produce PM from ores. For effective monitoring of mine PM dispersion, this study showed a preliminary application of the monitoring network with multiple low-cost sensors around a main PM emission source for each mine site. Therefore, two domestic limestone mine sites were selected for this study, and install the monitoring network with low-cost PM sensors and LTE (Long-term evolution) data communication. Then, preliminary resultant PM data plotted according to monitoring duration showed typical PM dispersion patterns. The quantification of the PM dispersion patterns should be roughly prepared by a PM size-dependent dispersion modeling.

• Proceedings of the Korea Air Pollution Research Association Conference
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• 1999.10a
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• pp.289-292
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• 1999

In recent year, there has been a progressive increase in urban air pollution that is Characterized by high concentrations of atmospheric particulate matter (PM10), resulting primarily from increase of automobils, especially diesel engine powered cars. Although the mechanisms of underling respiratory morbidity due to PM10 are not nuclear, it is thought that the fine particles (PM2.5) are of gratest concern to health since they can be breathed most deeply into the lung, where they are likely to be more toxic than the larger particles.(omitted)

• Proceedings of the National Institute of Ecology of the Republic of Korea
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• v.2 no.1
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• pp.62-69
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• 2021

This study aimed to verify the suitability of an air quality regulating service for wetland ecosystem service evaluation by investigating the effect of reducing particulate matter (PM) on vegetation in wetlands. We installed tunnel-type experimental plots at Yonghwasil Pond in the National Institute of Ecology and set up the input and output of PM by applying the natural vegetation of the relevant wetlands. We took measurements by replicating four different conditions four times each. The air quality regulating service in each experimental plot was measured based on PM10 concentration; further, the difference between the input and the output concentration of PM passing through the Phragmites australis community tunnel was measured using a light scattering method. For the Phragmites australis community in the outdoor conditions and bare land, the PM concentration was measured with the same specifications as tunnel-type experimental plots without setting up the input and output. For the tunnel-type experimental plots, PM10 concentration was significantly lower in the output than in the input. Furthermore, in the outdoor conditions, a comparison between the Phragmites australis community and bare land showed that the concentration was relatively low in the former than in the latter. This confirmed the PM reducing effect due to the blockage and absorption of PM depending on the growth of Phragmites australis. Based on the results of this study, we assessed the air quality regulating service in wetlands as an evaluation indicator.

• Advances in environmental research
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• v.10 no.1
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• pp.17-41
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• 2021

Kazakhstan's cities experience high concentrations levels of atmospheric particulate matter (PM), which is well-known for its highly detrimental effect on the human health. A further increase in PM concentrations in the future could lead to a higher air pollution-caused morbidity and mortality, causing an increase in healthcare expenditures by the government. However, to prevent elevated PM concentrations in the future, more stringent standards could be implemented by lowering current maximum allowable PM concentration limit to Organization for Economic Co-operation and Development (OECD)'s limits. Therefore, this study aims to find out what impact this change in environmental policy towards PM has on state economy in the long run. Future PM10 and PM2.5 concentrations were estimated using multiple linear regression based on gross regional product (GRP) and population growth parameters. Dose-response model was based on World Health Organization's approach for the identification of mortality, morbidity and healthcare costs due to air pollution. Analysis of concentrations revealed that only 6 out of 21 cities of Kazakhstan did not exceed the EU limit on PM10 concentration. Changing environmental standards resulted in the 71.7% decrease in mortality and 77% decrease in morbidity cases in all cities compared to the case without changes in environmental policy. Moreover, the cost of morbidity and mortality associated with air pollution decreased by $669 million in 2030 and $2183 million in 2050 in case of implementation of OECD standards. Thus, changing environmental regulations will be beneficial in terms of both of mortality reduction and state budget saving.

• Journal of the Korea Society of Computer and Information
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• v.27 no.7
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• pp.83-92
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• 2022

In this paper, we designed an algorithm that can control the state of PM by learning the chain failure pattern of PHM based air conditioning facility. It is an inevitable spread of PM due to the downtime caused by the failure of the air conditioning facility. The algorithm developed by us is to establish a PM management system through PHM, and it is an algorithm that maintains a constant stabilization state through learning the stop/operation pattern of the air conditioner and manages PM based on this. As a result of the simulating at a subway station for the performance qualification of the algorithm, it was verified that the concentration of PM reduces by 30% on average. In the case of stations with many passengers using the subway, the concentration of PM exceeded the Ministry of Environment Standards(100 ㎍/m³), but it was verified that the concentration of PM was improved at all stations where the simulation was conducted. In the future research is to expand the system to comprehensively manage not only PM but also pollutants such as CO₂, CO, and NO₂ in subway stations.

• Journal of Korean Society for Atmospheric Environment
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• v.31 no.3
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• pp.287-301
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• 2015

This study was conducted to investigate size distribution characteristics of water-soluble ionic components in the airborne particulate matter (PM) collected from an urban area in Busan using a MOUDI cascade impactor from March to October 2010. The inorganic constituents in the fine particles (${\leq}1.8{\mu}m$) predominantly consisted of sulfate, nitrate, ammonium, and potassium. Sulfate and ammonium concentrations showed a high correlation and similar equivalent concentrations in the fine modes including $0.18{\sim}0.32{\mu}m$, $0.32{\sim}0.56{\mu}m$, and $0.56{\sim}1.0{\mu}m$. This indicates that the main chemical component in the fine particles would be forms of ammonium sulfate such as $(NH_4)_3H(SO_4)_2$, $(NH_4)_2SO_4$, and $(NH_4)HSO_4$. Back trajectory analysis showed that relatively higher concentrations of ammonium, nitrate, and sulfate in the fine mode, compared to the coarse mode, are caused both by domestic sources and long-range transports originated from China continent. High concentration episodes of PM both in the fine mode and the coarse mode were attributed both by anthropogenic sources, such as ship emissions and traffic emissions, and by natural sources such as seawater (sea salt), respectively.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.42 no.4
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• pp.203-210
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• 2019

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.

• Journal of Environmental Health Sciences
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• v.43 no.3
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• pp.202-213
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• 2017

Objectives: HRA (Health Risk Assessment) is an important tool for measuring the health impacts of air pollution. HRA is already being used widely as an important reference for crafting air pollution policies. However, the absence of a domestic CRF (Concentration Response Function) standard, which is a main component for HRA, could cause confusion amongst policy-makers. The purpose of this study is to tabulate a domestic CRF standard for a PM (Particulate Matter)-related HRA. Methods: This study suggested a domestic CRF standard for HRA thorough a literature review. The literature review for meta-analysis was limited to the English language for epidemiological studies published from January 1980 to March 2016. This meta-analysis was conducted by assuming both fixed- and random-effects of CRF. In addition, studies that reported HRA of air pollution for WHO (World Health Organization), the EC (European Commission), and the EPA (Environmental Protection Agency) were reviewed to compare the CRFs of South Korea to the recommended CRFs of WHO, the EC, or the EPA. Additionally, a domestic CRF standard was supplemented by these. Results: Nineteen studies were selected for the CRF for South Korea. Fifty-three CRFs were derived for meta-analysis. CRFs with a standard for PM-related HRA were divided according to the following four criteria: air pollution, exposure characteristics, type of health impact, and age group. Finally, a domestic CRF standard was created comprised of 21 CRFs. Among these, six CRFs were derived from the results of foreign HRA studies. Conclusions: This study is important in that a domestic CRF standard is first suggested. In addition, this study suggests a further area of study for using HRA as a policy tool and a direction of epidemiological study.