• 한국환경보건학회지
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• 제50권4호
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• pp.257-266
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• 2024

Background: Exposure to fine particulate matter (PM_2.5) and ozone (O₃) poses potential health risks. The Indoor-to-Outdoor ratio (I/O ratio) is a valuable tool for understanding indoor air quality and identifying potential indoor sources. Objectives: The objective of this study was to determine I/O ratios of PM_2.5 and O₃ by different microenvironments and seasons in Korea. Methods: From December 2021 to November 2023, indoor concentrations of PM_2.5 and O₃ were monitored every hour in 13 microenvironments (residential indoor, office, school, restaurant, pub, café, study café, private educational institute, PC room, billiard room, screen golf center, supermarket, and shopping mall) in Korea. Hourly outdoor concentrations of PM_2.5 and O₃ were obtained from local air quality monitoring stations, provided by airkorea.or.kr. The hourly I/O ratio was calculated by the indoor and outdoor concentrations. Results: At the pub, billiard room, and PC room, the median PM_2.5 I/O ratio exceeded 1 in all seasons, except in spring at the PC room (0.9), suggesting indoor smoking as a potential cause. The median PM_2.5 I/O ratio at the restaurant exceeded 1 in winter, autumn, and summer, except for spring (0.9), indicating significant PM_2.5 emission sources in the restaurant. The median O₃ I/O ratio was below 0.5 in all seasons and microenvironments. Conclusions: This study provided useful data on relationships between indoor and outdoor pollution in various microenvironments by seasons. These I/O ratios could be applied for more accurate exposure assessment to protect health of human.

• 한국대기환경학회지
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• 제26권5호
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• pp.567-580
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• 2010

Organic carbon (OC) and elemental carbon (EC) concentrations were determined for $PM_{10}$, $PM_{2.5}$ and $PM_{1.0}$ aerosols particles collected at Gosan Superstation on Jeju Island from August 2007 to September 2008. Aerosols were collected on quartz filters for 24 hours and then OC and EC were analyzed by TOR/IMPROVED method. Mean concentrations of OC and EC were $4.66\;{\mu}g/m^3$ and $1.69\;{\mu}g/m^3$ for $PM_{10}$, $3.95\;{\mu}g/m^3$ and $1.69\;{\mu}g/m^3$ for $PM_{2.5}$, and $3.16\;{\mu}g/m^3$ and $1.42\;{\mu}g/m^3$ for $PM_{1.0}$, respectively. The concentrations of OC and EC comprised 16.4% and 6.0% of $PM_{10}$, 22.9% and 9.8% of $PM_{2.5}$, and 23.0% and 10.0% of $PM_{1.0}$. OC and EC showed a clear seasonal variation with the highest in winter and the lowest in summer. The correlations between the two were also the best during the winter ($R^2$=0.87, 0.94, and 0.95 for $PM_{10}$, $PM_{2.5}$ and $PM_{1.0}$). The ratio of OC/EC exhibited the maximum (7.24) during an Asian dust event due to an increase of OC, which was possibly derived from soil. The mass fraction of both OC and EC was the highest in fall. When OC and EC concentrations were highly elevated, EC1 (the first EC fraction determined at $550^{\circ}C$) and pyrolyzed OC (POC) were dominant subcomponents in winter and OC3 (the third OC fraction determined at $450^{\circ}C$) and POC in spring.

• Journal of Preventive Medicine and Public Health
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• 제57권2호
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• pp.185-196
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• 2024

Objectives: Excess mortality associated with long-term exposure to fine particulate matter (PM_2.5) has been documented. However, research on the disease burden following short-term exposure is scarce. We investigated the cause-specific mortality burden of short-term exposure to PM_2.5 by considering the potential non-linear concentration-response relationship in Korea. Methods: Daily cause-specific mortality rates and PM_2.5 exposure levels from 2010 to 2019 were collected for 8 Korean cities and 9 provinces. A generalized additive mixed model was employed to estimate the non-linear relationship between PM_2.5 exposure and cause-specific mortality levels. We assumed no detrimental health effects of PM_2.5 concentrations below 15 ㎍/m³. Overall deaths attributable to short-term PM_2.5 exposure were estimated by summing the daily numbers of excess deaths associated with ambient PM_2.5 exposure. Results: Of the 2 749 704 recorded deaths, 2 453 686 (89.2%) were non-accidental, 591 267 (21.5%) were cardiovascular, and 141 066 (5.1%) were respiratory in nature. A non-linear relationship was observed between all-cause mortality and exposure to PM_2.5 at lag0, whereas linear associations were evident for cause-specific mortalities. Overall, 10 814 all-cause, 7855 non-accidental, 1642 cardiovascular, and 708 respiratory deaths were attributed to short-term exposure to PM_2.5. The estimated number of all-cause excess deaths due to short-term PM_2.5 exposure in 2019 was 1039 (95% confidence interval, 604 to 1472). Conclusions: Our findings indicate an association between short-term PM_2.5 exposure and various mortality rates (all-cause, non-accidental, cardiovascular, and respiratory) in Korea over the period from 2010 to 2019. Consequently, action plans should be developed to reduce deaths attributable to short-term exposure to PM_2.5.

• 한국환경과학회지
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• 제31권7호
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• pp.637-652
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• 2022

In this study, the contributions of emissions (foreign and domestic) and atmospheric physical and chemical processes to PM_2.5 concentrations were evaluated during a high PM_2.5 episode (March 24-26, 2018) observed on the Jeju Island in the spring of 2018. These analyses were performed using the community multi-scale air quality (CMAQ) modeling system using the brute-force method and integrated process rate (IPR) analysis, respectively. The contributions of domestic emissions from South Korea (41-45%) to PM_2.5 on the Jeju Island were lower than those (81-89%) of long-range transport (LRT) from China. The substantial contribution of LRT was also confirmed in conjunction with the air mass trajectory analysis, indicating that the frequency of airflow from China (58-62% of all trajectories) was higher than from other regions (28-32%) (e.g., South Korea). These results imply that compared to domestic emissions, emissions from China have a stronger impact than domestic emissions on the high PM_2.5 concentrations in the study area. From the IPR analysis, horizontal transport contributed substantially to PM_2.5 concentrations were dominant in most of the areas of the Jeju Island during the high PM_2.5 episode, while the aerosol process and vertical transport in the southern areas largely contributed to higher PM_2.5 concentrations.

• 한국지구과학회지
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• 제42권3호
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• pp.278-295
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• 2021

2020년 중국의 COVID-19 폐쇄는 한국의 풍상측에 위치한 중국의 대기오염 배출량을 감소시켰다. 몽골 북부로부터 중국 동부를 거쳐 한반도에 이르는 지역에서는 2020년 1~2월에 기온 아노말리가 양(+)으로 온난하였고, 2020년 1월에는 동서류 아노말리가 음(-)으로 정체적인 특징을 보였다. 2019년 12월~2020년 3월에 한국 중부 서쪽의 석모리와 파도리에서 중국 배출량 감소의 영향에 따라 PM10, NO₂, O₃ 농도 변동이 나타났다. 파도리에서 PM10, O₃ 월평균 농도와 최근 4년의 월평균 농도의 비는 2019년 12월과 비교하여 중국의 COVID-19 폐쇄 이후인 2020년 1~3월에 각각 0.7~4.7%, 9.2~22.8%로 감소하였다. 2020년 1월 중국의 춘절 기간에는 석모리와 파도리에서 PM10, NO₂, O₃ 농도가 최근 4년의 춘절 기간과 마찬가지로 감소하였다. 그러나 2020년 1월 평균 농도가 최근 4년 1월과 비교하여 감소한 것은 중국 춘절 전후의 기간에도 배출량이 감소하였던 것과 관련 있다. 2020년 1~3월 석모리의 PM10, NO₂, O₃ 농도의 비(${\bar{O}_s$/M)는 각각 70.8~89.7%, 70.5~87.1%, 72.5~97.1%이었고, 파도리에서도 각각 79.6~93.5%, 67.7~84.9%, 83.7~94.6%로 추정 월평균(M)보다 월평균(${\bar{O}_s$)이 감소하였다. 2020년 1월에 몽골 북부로부터 중국 동부와 한반도에 이르는 지역의 온난화로 인한 광화학 반응으로 최근 4년과 비교하여 AOD가 높게 나타났으나 2020년 3월에는 풍상측인 중국에서 2차 에어로졸을 생성하는 전구물질 배출 감소로 최근 4년과 비교하여 낮은 AOD 분포를 보였던 것으로 분석되었다.

• 대한원격탐사학회지
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• 제38권5_3호
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• pp.851-861
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• 2022

본 연구는 전산유체역학(computational fluid dynamics, CFD) 모델을 이용하여 도시 지역에서 수목이 PM_2.5 저감에 미치는 영향을 조사하였다. 현실적인 수치 모의를 위해, 기상청에서 현업으로 운영 중인 국지예보시스템(LDAPS)이 예측한 기상 자료를 CFD 모델의 초기·경계 자료로 사용하였다. CFD 모델 성능 검증은 연구 대상지 내에 구축된 6개의 센서에서 측정한 PM_2.5 농도를 이용하였다. 본 연구에서는 수목이 PM_2.5 농도 분포에 미치는 영향을 분석하기 위하여, 수목이 식재 되지 않았다고 가정한 경우, 수목이 식재되어 있지만 바람에 대한 항력 효과만 존재한다고 가정한 경우, 수목의 항력 효과와 침적 효과가 모두 존재한다고 가정한 경우에 대한 수치 실험을 수행하였다. 분석대상 기간 동안 PM_2.5 저감 효과가 뚜렷하게 나타난 세 가지 영역 중 군부대 내의 PM_2.5 평균 농도를 비교한 결과, 수목이 식재되지 않은 경우는 12.8 ㎍ m^-3, 수목의 항력 효과만 고려한 경우는 12.5 ㎍ m^-3이 나타났고, 수목의 항력 효과와 침적 효과가 모두 고려한 경우는 6.8 ㎍ m^-3가 나타났다. 수목에 의한 건성 침적이 PM_2.5 농도를 감소시키는 효과가 있는 것으로 확인되었다.

• 대한원격탐사학회지
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• 제38권6_1호
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• pp.1191-1205
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• 2022

복잡하고 광범위한 원인을 가진 대기오염물질 중 particulate matter (PM)은 입자의 크기에 따라 분류된다. 그 중 PM_2.5는 그 크기가 매우 작아 사람이 흡입하면 인간의 호흡기나 심혈관에 질병을 유발할 수 있다. 이러한 위험에 대비하기 위해서는 국가 중심의 관리와 사전에 예방할 수 있는 모니터링 및 예측이 중요하다. 본 연구는 고농도 미세먼지의 발생이 잦은 서울시의 PM_2.5를 local data assimilation and prediction system (LDAPS) 기상 관련 인자 15가지와 aerosol optical depth (AOD), 화학인자 4가지를 독립변수로 하여 앙상블 모델 두 가지 random forest (RF)와 extreme gradient boosting (XGB)로 예측하고자 하였다. 예측에 사용된 두 모델의 성능 평가와 인자 중요도 평가를 수행하였으며, 계절별 모델 분석도 수행하였다. 예측 정확도 결과, RF가 R² = 0.85, XGB가 R² = 0.91의 높은 예측 정확도를 보이며 XGB가 RF보다 PM_2.5 예측에 적합한 모델임을 확인하였다. 계절별 모델 분석 결과, 봄에 농도가 높은 관측 값과 비교하여 예측 수행이 잘 되었다고 할 수 있다. 본 연구는 다양한 인자를 이용하여 서울시의 PM_2.5를 예측하였고, 좋은 성능을 보이는 앙상블 기반의 PM_2.5 예측 모델을 구축하였다.

• 한국농공학회논문집
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• 제62권5호
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• pp.27-37
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• 2020

As domestic meat consumption increases, the broiler production industry has been larger and denser. The concentration of particulate matter (PM) and harmful gases generated is also increasing inside livestock house. However, the current research status of PM exposed to farm workers and the health effects are in the early stage. To understand PM concentration affecting workers in the broiler house, field monitoring was conducted according to its size distributions. Concentrations of PM₁₀, PM_2.5, and TD (Total Dust) were monitored using personal air samplers with teflon filter during working and moving periods considering the ventilation systems of 6 broiler houses. The purpose of this study is to monitor the PM concentration in the experimental broiler houses operated by forced ventilation system generally used in Korea and to evaluate the regional concentrations through airflow pattern. The PM concentrations were increased from inlet to outlet vents resulting in 1,872 of TD, 1,385 of PM₁₀, and 209 ㎍/㎥ of PM_2.5, respectively. The TD and PM₁₀ concentrations were increased when the workers and broilers were moving. Among them, the particle size that occupied the largest amount of PM was 13.75 ㎛. These results suggest that personal protection equipments are important to reduce the health effect from PM inhalation.

• Annals of Occupational and Environmental Medicine
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• 제35권
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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.

• Safety and Health at Work
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• 제10권4호
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• pp.452-460
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• 2019

Background: Monitoring and control of PM_2.5 are being recognized as key to address health issues attributed to PM_2.5. Availability of low-cost PM_2.5 sensors made it possible to introduce a number of portable PM_2.5 monitors based on light scattering to the consumer market at an affordable price. Accuracy of light scatteringe-based PM_2.5 monitors significantly depends on the method of calibration. Static calibration curve is used as the most popular calibration method for low-cost PM_2.5 sensors particularly because of ease of application. Drawback in this approach is, however, the lack of accuracy. Methods: This study discussed the calibration of a low-cost PM_2.5-monitoring device (PMD) to improve the accuracy and reliability for practical use. The proposed method is based on construction of the PM_2.5 sensor network using Message Queuing Telemetry Transport (MQTT) protocol and web query of reference measurement data available at government-authorized PM monitoring station (GAMS) in the republic of Korea. Four machine learning (ML) algorithms such as support vector machine, k-nearest neighbors, random forest, and extreme gradient boosting were used as regression models to calibrate the PMD measurements of PM_2.5. Performance of each ML algorithm was evaluated using stratified K-fold cross-validation, and a linear regression model was used as a reference. Results: Based on the performance of ML algorithms used, regression of the output of the PMD to PM_2.5 concentrations data available from the GAMS through web query was effective. The extreme gradient boosting algorithm showed the best performance with a mean coefficient of determination (R²) of 0.78 and standard error of 5.0 ㎍/㎥, corresponding to 8% increase in R² and 12% decrease in root mean square error in comparison with the linear regression model. Minimum 100 hours of calibration period was found required to calibrate the PMD to its full capacity. Calibration method proposed poses a limitation on the location of the PMD being in the vicinity of the GAMS. As the number of the PMD participating in the sensor network increases, however, calibrated PMDs can be used as reference devices to nearby PMDs that require calibration, forming a calibration chain through MQTT protocol. Conclusions: Calibration of a low-cost PMD, which is based on construction of PM_2.5 sensor network using MQTT protocol and web query of reference measurement data available at a GAMS, significantly improves the accuracy and reliability of a PMD, thereby making practical use of the low-cost PMD possible.