• 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 Cadastre & Land InformatiX
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• v.51 no.2
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• pp.141-150
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• 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.

• Journal of Environmental Science International
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• v.29 no.6
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• pp.623-631
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• 2020

This study analyzes the effect of negative air ions on the concentration of airborne particulate matter and evaluates the expected purification efficiency of open spaces for particulate matter by investigating the amount of negative air ions generated by plants. This study establishes a negative air ion generation treatment environment, plant environment, and control environment to measure the purification efficiency of particulate matter under the conditions of each, analyzing the expected purification efficiency by designing a particulate matter purification model. Results show that the amount of generated negative air ion according to environment was negative air ion generation treatment environment > plant environment > control environment; this order also applies to the particulate matter purification efficiency. Moreover, it took 65 min for the negative ion generation treatment environment, 90 min for the plant environment, and 240 min for the control environment to reach the standard expected purification efficiency of particulate matter concentration of 960 mg/㎥ for PM₁₀. For PM_2.5, with the designated maximum concentration of 700 mg/㎥, it took 60 min for the negative ion generation treatment environment, 80 min for the plant environment, and more than 240 min for the control environment. Based on these results, the expected purification efficiency compared to the control environment was quadrupled in the negative ion generation treatment environment and tripled in the plant environment on average.

• The Journal of the Convergence on Culture Technology
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• v.4 no.1
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• pp.325-329
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• 2018

There are many pollutants in the residential space due to building materials, ventilation, cooking, etc. Among them, particulate matter is a primary carcinogen and very harmfull to the human body, it occurs mostly in cooking. Therefore, in order to manage the indoor air quality well, it is necessary to evaluate the relationship between the concentration of particulate matter generated during cooking and ventilation method. In this study, we propose a management method and particulate matte which occurs during the kitchen cooking by measuring and analyzing the concenteation change of particulate matter(PM2.5) according to the type of food and the ventilation method.

• Resources Recycling
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• v.29 no.1
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• pp.62-69
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• 2020

Manufacturing processes in industrial complexes produce NOx, SOx, VOCs, which cause particulate matter (PM). Therefore, this study analyzed the characteristics of each industrial complex by using scattered public data, matched the existing particulate matter(PM) reduction technology, and proposed an optimized reduction plan. The application of matching technologies and facilities by industrial complexes based on data is able to mitigate NOx, SOx, and VOCs which cause particulate matter in the process in advance. This way can be an effective alternative in order to reduce PM in the manufacturing processes as well as industrial complexes.

• Journal of the Korean Institute of Landscape Architecture
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• v.47 no.6
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• pp.67-77
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• 2019

The purpose of this study is to analyze how much particulate matter at the center of the urban park is reduced compared to the entrance of the park, where the particulate matter problem is serious. It also endeavored to analyze the relationship between the space closure rate and particulate matter reduction rate in the center of the park through the collection and analysis of experimental data. Seven flat land type urban neighborhood parks in Suseong-gu, Daegu were measured at the same place for three days. The research results are as follows. First, the center of the urban neighborhood park had an average temperature 1.05℃ lower than at the entrance and an average humidity of 2.57% higher. Second, the rate of fine dust reduction was PM1- 17.09%, PM2.5- 17.65%, PM10- 14.99%. As for the reduction rate of particulate matter, the smaller the size of the park, the greater the reduction rate. In addition, the reduction rate at the center of the park was lower on days when particulate matter concentration based on the weather reports was low. The higher the concentration at the park entrance, the higher the reduction rate was. Third, a higher the rate of space closures at the center of the park resulted in a higher effect of particulate matter reduction. Noting this, the relationship between particulate matter reduction and the space closure rate in urban neighborhood parks was clearly shown. We hope to be the basis for more extensive experimental data collection.

• Communications for Statistical Applications and Methods
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• v.25 no.6
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• pp.619-631
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• 2018

Functional data analysis continues to attract interest because advances in technology across many fields have increasingly permitted measurements to be made from continuous processes on a discretized scale. Particulate matter is among the most harmful air pollutants affecting public health and the environment, and levels of PM10 (particles less than 10 micrometers in diameter) for regions of California remain among the highest in the United States. The relatively high frequency of particulate matter sampling enables us to regard the data as functional data. In this work, we investigate the dominant modes of variation of PM10 using functional data analysis methodologies. Our analysis provides insight into the underlying data structure of PM10, and it captures the size and temporal variation of this underlying data structure. In addition, our study shows that certain aspects of size and temporal variation of the underlying PM10 structure are associated with changes in large-scale climate indices that quantify variations of sea surface temperature and atmospheric circulation patterns.

• Annals of Occupational and Environmental Medicine
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• v.34
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• pp.21.1-21.13
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• 2022

Background: Because particulate matter (PM) and asthma are closely related, the prevalence of school absence among adolescents with asthma can be affected by the concentration of PM. We aimed to investigate the relationship between school absences due to asthma and the total number of days that the PM concentration exceeded the standard. Methods: We used the data from the 16th Korea Youth Risk Behavior Survey and the PM levels of 17 metropolitan cities and provinces gathered from the AirKorea. Information on the characteristics of asthmatic adolescents and the prevalence of school absence was obtained using a questionnaire, while the PM levels based on the total number of days with poor and very poor PM grades were collected from the AirKorea website. Both χ² test and logistic regression analysis were performed using the weights presented in the original dataset. Results: In the case of particulate matter of 10 microns in diameter or smaller (PM₁₀), the odds ratio (OR) after adjusting for confounders (sex, school year, body mass index, smoking history, diagnosis of allergic rhinitis, diagnosis of atopic dermatitis and city size) was 1.07 (95% confidence interval [CI]: 1.01-1.13) for absents due to asthma when the total days of poor and very poor grades of PM₁₀ (81 ㎍/m³ or higher) increased by 1 day. In the analysis of particulate matter of 2.5 microns in diameter or smaller (PM_2.5), the OR after adjusting for confounders was 1.01 (95% CI: 1.00-1.03) for absents due to asthma when the total number of days with poor and very poor PM_2.5 grades (36 ㎍/m³ or higher) increased by 1 day. Conclusions: A significant association was observed between the total number of days of poor and very poor PM₁₀ and PM_2.5 grades and school absence due to asthma; PM can cause asthma exacerbation and affect the academic life.

• Annals of Occupational and Environmental Medicine
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• v.35
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• pp.51.1-51.15
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• 2023

Background: Recently, there has been increasing worldwide concern about outdoor air pollution, especially particulate matter (PM), which has been extensively researched for its harmful effects on the respiratory system. However, sufficient research on its effects on cardiovascular diseases, such as hypertension, remains lacking. In this study, we examine the associations between PM levels and hypertension and hypothesize that higher PM concentrations are associated with elevated blood pressure. Methods: A total of 133,935 adults aged ≥ 40 years who participated in the Korean Genome and Epidemiology Study were analyzed. Multiple linear regression analyses were conducted to investigate the short- (1-14 days), medium- (1 and 3 months), and long-term (1 and 2 years) impacts of PM on blood pressure. Logistic regression analyses were conducted to evaluate the medium- and long-term effects of PM on blood pressure elevation after adjusting for sex, age, body mass index, health-related lifestyle behaviors, and geographic areas. Results: Using multiple linear regression analyses, both crude and adjusted models generated positive estimates, indicating an association with increased blood pressure, with all results being statistically significant, with the exception of PM levels over the long-term period (1 and 2 years) in non-hypertensive participants. In the logistic regression analyses on non-hypertensive participants, moderate PM₁₀ (particulate matter with diameters < 10 ㎛) and PM_2.5 (particulate matter with diameters < 2.5 ㎛) levels over the long-term period and all high PM₁₀ and PM_2.5 levels were statistically significant after adjusting for various covariates. Notably, high PM_2.5 levels of the 1 year exhibited the highest odds ratio of 1.23 (95% confidence interval: 1.19-1.28) after adjustment. Conclusions: These findings suggest that both short- and long-term exposure to PM is associated with blood pressure elevation.

• BMB Reports
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• v.56 no.2
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• pp.96-101
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• 2023

Particulate matter is an air pollutant composed of various components, and has adverse effects on the human body. Particulate matter is known to induce cell death by generating an imbalance in the antioxidant system; however, the underlying mechanism has not been elucidated. In the present study, we demonstrated the cytotoxic effects of the size and composition of particulate matter on small intestine cells. We found that particulate matter 2.5 (PM_2.5) with extraction ion (EI) components (PM_2.5 EI), is more cytotoxic than PM containing only polycyclic aromatic hydrocarbons (PAHs). Additionally, PM-induced cell death is characteristic of ferroptosis, and includes iron accumulation, lipid peroxidation, and reactive oxygen species (ROS) generation. Furthermore, ferroptosis inhibitor as liproxstatin-1 and iron-chelator as deferiprone attenuated cell mortality, lipid peroxidation, iron accumulation, and ROS production after PM_2.5 EI treatment in human small intestinal cells. These results suggest that PM_2.5 EI may increase ferroptotic-cell death by iron accumulation and ROS generation, and offer a potential therapeutic clue for inflammatory bowel diseases in human small intestinal cells.