• Journal of Service Research and Studies
• /
• v.10 no.1
• /
• pp.55-67
• /
• 2020

Fine dust has recently become one of the greatest concerns of Korean people and has been a target of considerable efforts by governments and local governments. In the academic world, many researches have been carried out in relation to fine dust, but the research on the economic field has been relatively few. So we wanted to know how fine dust affects the economy. Big data of PM10 concentration for fine dust and fine dust theme stock price were collected for five years from 2013 to 2017. Regression analysis was performed using the linear regression model, the generalized least squares method. As a result, the change in the fine dust concentration was found to have a effect on the related theme stocks' price. When the fine dust concentration increased compared to the previous day, the fine dust theme stocks' price also showed a tendency to increase. Also, according to the analysis of stock price change from 2013 to 2017 based on fine dust theme stocks, companies with large regression coefficients were changed every year. Among them, the regression coefficients of Monalisa were repeatedly high in 2014, 2015, 2017, Samil Pharmaceutical in 2015, 2016 and 2017, and Welcron in 2016 and 2017, and the companies were judged to be sensitive to the concentration of fine dust. The companies that responded the most in the past 5 years were Wokong, Welcron, Dongsung Pharmaceutical, Samil Pharmaceutical, and Monalisa. If PM2.5 measurement data are accumulated enough, it would be meaningful to compare and analyze PM2.5 concentration with independent variables. In this study, only the fine dust concentration is used as an independent variable. However, it is expected that a more clear and well-explained result can be found by adding appropriate additional variables to increase the explanatory power.

• Journal of Korean Society of Environmental Engineers
• /
• v.37 no.4
• /
• pp.197-203
• /
• 2015

Particulate matter (PM) has emitted in many regions of the world and is causing many health-related problems. Thus reasonable politics and solutions are needed to reduce PM in Seoul. Further it is required to clearly explain the major portions of chemical components contained in $PM_{10}$ to figure out the characteristics of $PM_{10}$, and to develop effective reduction measures in order to decrease the adverse effects of $PM_{10}$. $PM_{10}$ samples were collected in Seoul and analyzed their ions to examine the physical and chemical characteristics of ionic species. Since hydrogen ion ($H^+$) and carbonate ion (${CO_3}^{2-}$)) cannot be analyzed by Ion chromatography (IC), concentrations of $H^+$ and ${CO_3}^{2-}$ were initially estimated by pH and equivalent differences between anions and cations in this study. Starting from the study findings, good combination results for compositional patterns between anions and cations were obtained by applying a mathematical modelling technique that was based on the mass balance principle. The ions in $PM_{10}$ were combined with $H^+$, ${CO_3}^{2-}$, and supplement for $NO_3{^-}$, $Cl^-$ formed such compounds $NH_4Cl$, $NH_4NO_3$, $CaSO_4$, $(NH_4)_2SO_4$, $NaNO_3$, NaCl, $Na_2CO_3$, and $(NH_4)_2CO_3$ in the study area.

• Journal of Climate Change Research
• /
• v.9 no.4
• /
• pp.423-433
• /
• 2018

Particulate matter air pollution is a serious problem affecting human health and visibility. The variations in $PM_{10}$ concentrations are influenced by not only local emission sources, but also atmospheric circulation conditions. In this study, we investigate the temporal features of $PM_{10}$ concentrations in South Korea and the atmospheric circulation patterns associated with high concentration episodes of $PM_{10}$ during winter (December-January-February) 2001-2016. Based on those analyses, a Korea Particulate matter Index (KPI) is developed to represent the large-scale atmospheric pattern associated with high concentration episodes of $PM_{10}$. The atmospheric patterns are characterized by persistent high-pressure anomalies, weakened lower-level north-westerly anomalies, and northward shift of the upper-level meridional wind anomalies near the Korean Peninsula. To evaluate the change in occurrence of high concentration episodes of $PM_{10}$ under a possible future warmer climate, we apply KPI analysis to CMIP5 climate simulations. Here, historical and two representative concentration pathway (RCP) scenarios (RCP 4.5 and RCP 8.5) are used. It is found that the occurrence of atmospheric conditions favorable for high $PM_{10}$ concentration episodes tends to increase over South Korea in response to climate change. This suggests that large-scale atmospheric circulation changes under future warmer climate can contribute to increasing high $PM_{10}$ concentration episodes in South Korea.

• Environmental and Resource Economics Review
• /
• v.28 no.4
• /
• pp.467-495
• /
• 2019

Uncertainty of renewable energy such as photovoltaic(PV) power is detrimental to the flexibility of the power system. Therefore, precise prediction of PV power generation is important to make the power system stable. The purpose of this study is to forecast PV power generation using meteorological data including particulate matter(PM). In this study, PV power generation is predicted by support vector machine using RBF kernel function based on machine learning. Comparing the forecasting performances by including or excluding PM variable in predictor variables, we find that the forecasting model considering PM is better. Forecasting models considering PM variable show error reduction of 1.43%, 3.60%, and 3.88% in forecasting power generation between 6am~8pm, between 12pm~2pm, and at 1pm, respectively. Especially, the accuracy of the forecasting model including PM variable is increased in daytime when PV power generation is high.

• Journal of Cadastre & Land InformatiX
• /
• v.51 no.2
• /
• pp.141-150
• /
• 2021

Fine dust is a substance that greatly affects human health, and various studies have been conducted in this regard. Due to the human influence of particulate matter, various studies are being conducted to predict particulate matter grade using past data measured in the monitoring network of Seoul city. In this paper, predictive model have focused on particulate matter concentration in May, 2019, Seoul. The air pollutant variables were used to training such as SO₂, CO, NO₂, O₃. The predictive model based on Adaboost, and training model was dividing PM₁₀ and PM_2.5. As a result of the prediction performance comparison through confusion matrix, the Adaboost model was more conformable for predicting the particulate matter concentration grade. Although air pollutant variables have a higher correlation with PM2.5, training model need to train a lot of data and to use additional variables such as traffic volume to predict more effective PM₁₀ and PM_2.5 distribution grade.

• Proceedings of the Korean Environmental Health Society Conference
• /
• 2005.11a
• /
• pp.147-149
• /
• 2005

수도권에 위치한 사무실 69개소의 미세먼지를 측정하고 사무실 내 근로자들의 건강자각증상 설문을 통해 미세먼지 농도에 따른 건강 자각증상의 상관성을 살펴보았다. 실태조사를 통한 사무실 실내 미세먼지 농도는 $PM_{10}$의 경우 $114.62{\pm}73.66{\mu}g/m^3$ 로 69개소 중 18개소가 기준을 초과하였고 , $PM_{2.5}$의 경우 $80.15{\pm}53.86{\mu}g/m^3$ 로 69개소 중 35개소가 기준을 초과하였다. 미세먼지와 건강자각증상과의 상관성을 살펴보면 미세먼지 농도가 높을수록 두통, 안구 건조, 목건조 증상이 증가하는 경향을 보였으며 그 외의 증상은 뚜렷한 상관관계를 보이지 않았다.

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

• Korean Journal of Environment and Ecology
• /
• v.34 no.5
• /
• pp.466-482
• /
• 2020

This study used 3D computational fluid dynamics (CFD) in the ENVI-met program to investigate how particulate matters (PM) generated on roads disperse through adjacent urban neighborhoods according to the urban development pattern. An urban area centered on a six-lane road in the vicinity of Miryang City Hall in Gyeongnam Province was selected to simulate the effect of the green space and building height on the PM concentration. The ENVI-met model considered the presence of green space and different building heights (high/low) on both sides of the road to examine the dispersion of PM. The result showed that the area of high-rise buildings and green space had the lowest PM concentration dispersed to the adjacent area, followed by the area of high-rise buildings and no green space. In contrast, the PM concentration remained relatively high for low-rise buildings, regardless of the green space. The reason for the low PM concentration in the area with high-rise buildings was a strong building wind, which caused PM to disperse to the outside, lowering the PM concentration quickly. These results indicate that the PM can disperse faster, and the PM concentration remains low in the urban neighborhood. On the other hand, green space had no significant effect on reducing PM in the urban neighborhood. In particular, when there are low-rise buildings on both sides of the road, the green space has no effect on the PM concentration in the urban neighborhood. Since this study considered only the case of PM emitted from the road, future studies should investigate other factors to figure out the dispersion model of PM and conduct on-site experiments.

• Environmental and Resource Economics Review
• /
• v.26 no.1
• /
• pp.57-83
• /
• 2017

The Japanese government's attempts to reduce fine particles (PM2.5) emission pollution in Japan have been largely ineffective. This is because PM2.5 in Japan originated from various sources including around half from oversea countries such as China. This prompts the Japanese government to start a new initiative to reduce PM2.5 at its origin by transferring local knowledge on air pollution reduction measures and technologies to China and working closely with the Chinese government. To promote further reduction in PM2.5, bilateral corporation between Japan and China should be extended to include Korea. It is recommended that an international convention should be in place to deal with transboundary air pollutants in East Asia. A successful East Asia corporation to reduce PM2.5 will not only contribute to clean air but also to future sustainable low carbon society in this region.

• Proceedings of the Korea Air Pollution Research Association Conference
• /
• 2003.05b
• /
• pp.189-190
• /
• 2003

최근 10년간 대기환경 개선대책으로 1차 오염물질인 이산화황과 총부유먼지(TSP)의 농도는 현저히 감소하고 있다. 그러나 자동차의 증가 등으로 미세먼지, 오존 등 2차 대기오염물질의 오염도는 오히려 증가하고 있는 추세에 있다. 특히 미세먼지는 시정에 영향을 주어 체감오염도를 증가시킬 뿐만 아니라 미세먼지 내에 함유된 각종 유해물질과 중금속 등은 인체에 직접적인 영향을 주는 것으로 알려져 있다. 더욱이 최근 미국 등을 중심으로 $PM_{2.5}$에 대한 연구가 활발하게 진행되고 있으며 1997년부터 대기환경 기준에 추가하여 미세먼지에 대한 보다 엄격한 대기질 관리를 수행하고 있다. (중략)