• The Journal of the Korea Contents Association
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• v.21 no.3
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• pp.567-575
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• 2021

Residents in Dangjin, South Chungcheong Province, in which large-scale emissions facilities such as coal-fired power plants and steel mills are concentrated, are very much concerned about their health despite the local government's aggressive efforts to improve air quality and reduce greenhouse gases. To understand the impact of coal-fired power plants and external factors on local air pollution, the origins of local pollutants were investigated using stable carbon isotopes that are generally used as tracers of the provenance of fine or ultrafine dust. The origins of the pollutants were analyzed with the data library, built using the seasonally measured data for the two separate locations selected considering the distance from the coal-fired power plant and the analysis of previous studies, and with the back trajectory analysis. As a result of analyzing stable isotope ratios, the tendency of high concentration was found in the order of winter > spring > fall > summer. According to the data matching with the library, the mobile pollutants and open-air incineration had a relatively higher impact on the local air pollution. It is believed that this study, as a pilot study, should focus on securing the reliability of the study results through continuous monitoring and data accumulation.

• Journal of Environmental Health Sciences
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• v.47 no.6
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• pp.521-529
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• 2021

Background: The coronavirus disease (COVID-19) has caused changes in human activity, and these changes may possibly increase or decrease exposure to fine dust (PM_2.5). Therefore, it is necessary to evaluate the exposure to PM_2.5 in relation to the outbreak of COVID-19. Objectives: The purpose of this study was to compare and evaluate the exposure to PM_2.5 concentrations by the variation of dynamic populations before and after the outbreak of COVID-19. Methods: This study evaluated exposure to PM_2.5 concentrations by changes in the dynamic population distribution in Guro-gu, Seoul, before and after the outbreak of COVID-19 between Jan and Feb, 2020. Gurogu was divided into 2,204 scale standard grids of 100 m×100 m. Hourly PM_2.5 concentrations were modeled by the inverse distance weight method using 24 sensor-based air monitoring instruments. Hourly dynamic population distribution was evaluated according to gender and age using mobile phone network data and time-activity patterns. Results: Compared to before, the population exposure to PM_2.5 decreased after the outbreak of COVID-19. The concentration of PM_2.5 after the outbreak of COVID-19 decreased by about 41% on average. The variation of dynamic population before and after the outbreak of COVID-19 decreased by about 18% on average. Conclusions: Comparing before and after the outbreak of COVID-19, the population exposures to PM_2.5 decreased by about 40%. This can be explained to suggest that changes in people's activity patterns due to the outbreak of COVID-19 resulted in a decrease in exposure to PM_2.5.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1191-1205
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• 2022

Particulate matter(PM) among air pollutants with complex and widespread causes is classified according to particle size. Among them, PM_2.5 is very small in size and can cause diseases in the human respiratory tract or cardiovascular system if inhaled by humans. In order to prepare for these risks, state-centered management and preventable monitoring and forecasting are important. This study tried to predict PM_2.5 in Seoul, where high concentrations of fine dust occur frequently, using two ensemble models, random forest (RF) and extreme gradient boosting (XGB) using 15 local data assimilation and prediction system (LDAPS) weather-related factors, aerosol optical depth (AOD) and 4 chemical factors as independent variables. Performance evaluation and factor importance evaluation of the two models used for prediction were performed, and seasonal model analysis was also performed. As a result of prediction accuracy, RF showed high prediction accuracy of R² = 0.85 and XGB R² = 0.91, and it was confirmed that XGB was a more suitable model for PM_2.5 prediction than RF. As a result of the seasonal model analysis, it can be said that the prediction performance was good compared to the observed values with high concentrations in spring. In this study, PM_2.5 of Seoul was predicted using various factors, and an ensemble-based PM_2.5 prediction model showing good performance was constructed.

• Economic and Environmental Geology
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• v.55 no.3
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• pp.281-293
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• 2022

We examined degradation characteristics of lead based pigments(white lead, Red lead, Litharge) according to atmospheric environmet condition, for example atmospheric gas(CO₂, NO₂) and soluble salt. Painted samples not changed material compositions but were occured the color change(𝚫E 4~31) after exposed UV irradiation. All sample were not affected by CO₂ gas not only color but chemical composition. However, samples were remakably changed color exposed NO₂ gas and it was formed secondary product like as lead nitrate. Such as red lead and white lead samples' color difference were 𝚫E 2 and 𝚫 10 respectively and became dark, along with litharge became bright and color difference was 𝚫E 5 after react with NO₂ gas. It confirm that NO₂ was influential factor than CO₂ in the case of same concentration. Furthermore salt spray test was taken to figure out soluble salt influence in fine dust. The result showed noticeable color change and secondary product was formed on samples' surface. The glue film peeled off or hole, and color changed around the secondary products. After salt spray, XRD pattern showed decrease peak intensity and lower crystalinity. As a result of salt spray test, white lead was formed new product litharge and litharge was formed litharge and minium. According to the results, influential atmospheric factors for conservation of paint pigments were UV, NO₂, soluble salt, and litharge was most weakness throughout lead base pigments.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.2
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• pp.108-116
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• 2023

Recently, the concentration of fine dust causative substances (NOx, VOC, etc.) in the atmosphere has increased, resulting in high concentrations of tropospheric ozone (O3) and increased damage to crops. This study aimed to analyze the impact of high concentrations of ozone gas on the initial growth of rice plants and investigate the relationship between ozone damage resistance and anthocyanin biosynthesis. To achieve this, rice plants were exposed to elevated levels of ozone g as using an ozone chamber, and subsequent measurements were taken to assess changes in growth, the percentage of damaged leaves, and the anthocyanin content. The results revealed that varieties with a higher proportion of damaged leaves exhibited a relative increase in anthocyanin biosynthesis following ozone exposure. Notably, detrimental effects on growth, such as decreased biomass, were mitigated. Additionally, Anthocyanin biosynthesis genes in rice were listed by selecting homologous genes from Arabidopsis and Maize. The expression of OsF3H2, OsFLS1 and OsLDOX3 was induced during ozone treatment. This result is expected to contribute to the study of the protection mechanism of plants from ozone damage.

• Korean Chemical Engineering Research
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• v.59 no.1
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• pp.127-137
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• 2021

Air emission charge for nitrogen oxide as a precursor of fine dust has been introduced and implemented within the country from 2020. Therefore, the development of economical combustion technology for NOx reduction has got more needed urgently. This study investigated the air-staging effect as a way to reduce the NOx during combustion of domestic unused forest biomass, recently possible to secure REC (Renewable Energy Certification) as a substitute for overseas wood pellets in a 0.1 MWth circulating fluidized bed combustion test-rig. Operating conditions were comparison with and without air-staging, the supply position of tertiary air (6.4 m, 8.1 m, 9.4 m in the combustor) and variation of air-staging ratio (Primary air:Secondary air:Tertiary air=91%:9%:0%, 82%:9%:9%, 73%:9%:18%). NO and CO concentrations in flue gas, profiles of temperature and pressure at the height of the combustion, unburned carbon in sampled fly ash and combustion efficiency on operating conditions were evaluated. As notable results, NO concentration with air-staging application under tertiary air supply at 9.4 m in the combustor reduced 100.7 ppm compared to 148.8 ppm without air-staging while, CO concentration increased from 52.2 ppm without air-staging to 99.8 ppm with air-staging. However, among air-staging runs, when tertiary air supply amount at 6.4 m in the combustor increased by air-staging ratio (Primary air:Secondary air:Tertiary air=73%:9%:18%), NO and CO concentrations decreased the lowest 90.8 ppm and 66.1 ppm, respectively. Furthermore, combustion efficiency at this condition was improved to 99.3%, higher than that (98.3%) of run without air-staging.

• Journal of Service Research and Studies
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• v.13 no.1
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• pp.63-75
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• 2023

Due to the development of industry, interest in air pollutants has increased. Air pollutants have affected various fields such as environmental pollution and global warming. Among them, environmental diseases are one of the fields affected by air pollutants. Air pollutants can affect the human body's skin or respiratory tract due to their small molecular size. As a result, various studies on air pollutants and environmental diseases have been conducted. Asthma, part of an environmental disease, can be life-threatening if symptoms worsen and cause asthma attacks, and in the case of adult asthma, it is difficult to cure once it occurs. Factors that worsen asthma include particulate matter and air pollution. Asthma is an increasing prevalence worldwide. In this paper, we study how air pollutants correlate with the number of emergency room admissions in asthma patients and predict the number of future asthma emergency patients using highly correlated air pollutants. Air pollutants used concentrations of five pollutants: sulfur dioxide(SO₂), carbon monoxide(CO), ozone(O₃), nitrogen dioxide(NO₂), and fine dust(PM₁₀), and environmental diseases used data on the number of hospitalizations of asthma patients in the emergency room. Data on the number of emergency patients of air pollutants and asthma were used for a total of 5 years from January 1, 2013 to December 31, 2017. The model made predictions using two models, Informer and LTSF-Linear, and performance indicators of MAE, MAPE, and RMSE were used to measure the performance of the model. The results were compared by making predictions for both cases including and not including the number of emergency patients. This paper presents air pollutants that improve the model's performance in predicting the number of asthma emergency patients using Informer and LTSF-Linear models.