우리나라 지역별 초미세먼지(PM_2.5) 농도 추이와 고농도 발생 현황

여민주,김용표,Yeo, Minju,Kim, Yongpyo 한국입자에어로졸학회 2019 Particle and Aerosol Research Vol.15 No.2

The public's concern on ambient $PM_{2.5}$ has been increasing in Korea. We have estimated (1) the annual and monthly mean $PM_{2.5}$ concentrations, (2) the frequency by the $PM_{2.5}$ concentration interval, and (3) the high concentration occurrence duration time between 2015 and 2018 at 16 administration regions. We found that there have been differences in all three above parameters' trends among the studied 16 regions in Korea. Still, Jeonbuk showed the highest rank in all three parameters' trends. In Jeonbuk, the average $PM_{2.5}$ concentration and the sum of the frequency fraction when the $PM_{2.5}$ concentration being over $75{\mu}g/m^3$ between 2016 and 2018 was $28.4{\mu}g/m^3$ and 9.0%, respectively. And the days when the $PM_{2.5}$ concentration is over $50{\mu}g/m^3$ between 2015 and 2018 were 149. Chungbuk was the only region with the increasing trend of $PM_{2.5}$ concentration between 2016 and 2018. And in Seoul and Gyeonggi, the average $PM_{2.5}$ concentrations decreased whereas the high concentration frequency fraction increased between 2016 and 2018. Also, it is found that there have been differences in the trends of the frequency by the $PM_{2.5}$ concentration interval and the high concentration occurrence duration time between $PM_{10}$ and $PM_{2.5}$.

시·공간적 풍계에 따른 부산지역 고농도 PM_2.5의 일변화 특성

김부경,이동인,김정창,이준호 한국지구과학회 2012 한국지구과학회지 Vol.33 No.6

This study was to analyze the characteristics of diurnal variation of high PM_2.5 concentration, PM_2.5/PM_10 concentration ratio by spatio-temporal wind system (wind speed and wind direction) for high PM_2.5 concentration (over the 24 hr environmental standard of PM_2.5, 50 μg/㎥) in the air quality observation sites (Jangrimdong: Industrial area, Jwadong: Residential area) that were measured for 3 years (2005. 12. 1-2008. 11. 30) in Busan. The observation days of high PM_2.5 concentration were 182 at Jangrimdong and 27 at Jwadong. The seasonal diurnal variation of hourly mean of high PM_2.5 concentration and of PM_2.5/PM_10 concentration ratio showed a similar pattern that had higher variation at dawn, and night and in the morning than in the afternoon. Durning daytime in summer at Jwadong, the PM_2.5/PM_10 concentration ratio increased because a secondary particulate matter, which was created by photochemical reaction, decreased the coarse particles of PM_10 more than the fine particles of PM_2.5 concentrations in ocean condition. We did an analysis of spatio-temporal wind system (wind speed range and wind direction) in each time zone. The result showed that high PM_2.5 concentration at Jangrimdong occurred due to the congestion of pollutants emissions from the industrial complex in Jangrimdong area and the transportation of pollutants from places nearby Jangrimdong. It also showed that high PM_2.5 concentration occurred at Jwadong because of a number of local residential and commercial activities that caused the congestion of pollutants. 본 연구는 3년(2005. 12. 1-2008. 11. 30) 동안 부산의 PM_2.5 대기오염자동관측소(장림동: 공업지역, 좌동: 주거지역) 측정자료 중 고농도 PM_2.5(24시간 환경기준 50 μg/㎥)에 대한 PM_2.5 및 PM_2.5/PM_10 농도비의 일변화 특성과 함께 시·공간적 풍계(풍향 및 풍속)에 따른 특성을 분석하고자 하였다. 고농도 PM2.5는 장림동과 좌동 각각 182일 및 27일이었다. 장림동에서 고농도 PM_2.5의 시간평균농도 및 PM_2.5/PM_10 농도비의 일변화는 모든 계절에서 오후에 비해 새벽과 오전 및 야간에 높은 비슷한 패턴을 나타내었다. 좌동의 여름 주간에 PM_2.5/PM_10 농도비가 증가하는 것은 해양조건에서 광화학반응에 의해 생성되는 이차 입자상물질 중 PM10의 거대입자 농도가 미세입자인 PM_2.5 농도보다 더 감소하기 때문이다. 시간대별로 시·공간적 풍계(풍향 및 풍속등급) 특성을 분석하였다. 그 결과, 고농도 PM_2.5는 장림동에서 공업단지의 산업활동에 의한 오염물질 정체와 주변지역의 오염물질 이동에 의해 발생되었다. 좌동에서는 주로 주거와 상업활동으로 인한 지역적 오염물질 정체로 발생하는 것으로 나타났다.

인공지능을 이용한 수도권 학교 미세먼지 취약성 평가: Part I - 미세먼지 예측 모델링

손상훈 ( Sanghun Son ),김진수 ( Jinsoo Kim ) 대한원격탐사학회 2021 大韓遠隔探査學會誌 Vol.37 No.6

미세먼지는 인체에는 물론 생태계, 날씨 등에도 많은 영향을 끼치며, 인구와 건물, 차량 등이 밀집된 대도시에서의 미세먼지의 예측과 모니터링은 중요하다. 특히 자동차, 연소 등에서 발생하는 PM_2.5 농도는 독성 물질을 포함할 수 있어 체계적인 관리가 필요하다. 따라서 본 연구는 화학 인자, 위성 기반의 aerosol optical depth (AOD), 기상 인자 등을 입력 자료로 하여 수도권PM_2.5 농도를 예측하고자 한다. PM_2.5 농도 예측을 위해 기계 학습 모델 중 PM 농도 예측에 우수한 성능을 보이는 random forest (RF) 모델을 선정하였으며, 모델 평가를 위해 통계 지표인 R², RMSE, MAE, MAPE를 산출하였다. RF 모델의 모델 정확도는 R², RMSE, MAE, MAPE는 각각 0.97, 3.09, 2.18, 13.31로 나타났으며, 예측 정확도는 각각 0.82, 6.03, 4.36, 25.79로 본 연구에서 사용한 인자들을 이용하여 PM_2.5를 예측 시 높은 정확도와 상관성을 나타내었다. 따라서 향후 학교 미세먼지 예측 및 범주화를 위해 본 연구에서 사용한 인자들을 RF 모델에 적용하였을 때 신뢰할만한 결과를 도출할 수 있을 것으로 기대된다. Particulate matter (PM) affects the human, ecosystems, and weather. Motorized vehicles and combustion generate fine particulate matter (PM_2.5), which can contain toxic substances and, therefore, requires systematic management. Consequently, it is important to monitor and predict PM_2.5 concentrations, especially in large cities with dense populations and infrastructures. This study aimed to predict PM_2.5 concentrations in large cities using meteorological and chemical variables as well as satellite-based aerosol optical depth. For PM_2.5 concentrations prediction, a random forest (RF) model showing excellent performance in PM concentrations prediction among machine learning models was selected. Based on the performance indicators R², RMSE, MAE, and MAPE with training accuracies of 0.97, 3.09, 2.18, and 13.31 and testing accuracies of 0.82, 6.03, 4.36, and 25.79 for R², RMSE, MAE, and MAPE, respectively. The variables used in this study showed high correlation to PM_2.5 concentrations. Therefore, we conclude that these variables can be used in a random forest model to generate reliable PM_2.5 concentrations predictions, which can then be used to assess the vulnerability of schools to PM_2.5.

부산지역 PM10과 PM2.5 중의 금속 농도와 이온농도 특성

전병일 ( Byung Il Jeon ),황용식 ( Yong Sik Hwang ) 한국환경과학회 2014 한국환경과학회지 Vol.23 No.5

This study analyzes the chemical composition of metallic elements and water-soluble ions in PM10 and PM2.5. PM10 and PM2.5 concentrations in Busan during 2010-2012 were 97.2±67.5 and 67.5±32.8 ㎍/㎥, respectively, and the mean PM2.5/PM10 concentration ratio was 0.73. The contribution rate of water-soluble ions to PM10 ranged from 29.0% to 58.6%(a mean of 38.6%) and that to PM2.5 ranged from 33.9% to 58.4%(a mean of 43.1%). The contribution rate of sea salt to PM10 was 13.9% for 2011 and 9.7% for 2012, while that to PM2.5 was 17.4% for 2011 and 10.1% for 2012. PM10 concentration during Asian dust events was 334.3 ㎍/㎥ and 113.3 ㎍/㎥ during non-Asian dust events, and the PM10 concentration ratio of Asian Dust/Non Asian dust was 2.95. On the other hand, the PM2.5 concentration in Asian dust was 157.4 ㎍/㎥ and 83.2㎍/㎥ in Non Asian dust, and the PM2.5 concentration ratio of Asian Dust/Non Asian dust was 1.89, which was lower than that of PM10.

2006-2008년 봄철 부산 지역 PM10과 PM2.5의 질량농도 및 금속성분의 화학적 특성

전병일,황용식 한국지구과학회 2010 한국지구과학회지 Vol.31 No.3

본 연구에서는 2006년부터 2008년까지 3년간 봄철에 PM10과 PM2.5를 채취하여 질량농도와 금속원소의 화학적특성, 기상인자와의 관계 분석, 황사 및 비황사시의 미세먼지 특성 그리고 이동경로에 따른 농도의 특성을 고찰하였다. 연구기간동안의 PM10, PM2.5, PM10-2.5 평균농도는 각각 126.2±89.8, 85.5±41.6, 40.7±54.9 μg/㎥이었으며 PM2.5/PM10 및PM10-2.5/PM2.5 비는 각각 0.70, 0.48이었다. 우리나라의 북서쪽인 북경을 포함한 지역과 서쪽인 상해를 포함한 지역에서공기덩어리가 이류 할 때 가장 높은 미세먼지농도를 나타내었다. Twenty-four hour integrated PM10 and PM2.5 samples were measured during springtime (March, April, and May) in Busan for three years from 2006 to 2008, and mass concentrations and metallic elements of measurement were analyzed to investigate temporal, spatial, chemical characteristics of the mass concentration and metallic elements in association with meteorological conditions including Asian Dust (AD) vs. non Asian Dust (NAD) seasons, and other air mass transport patterns. The result showed that PM10, PM2.5 and PM10-2.5 concentrations were on average of 126.2±89.8,85.5±41.6, and 40.7±54.9 μg/㎥, respectively, and the PM2.5/PM10 and PM10-2.5/PM2.5 ratios were 0.70 and 0.48,respectively. The highest concentrations of PM were observed when air parcels were originated from both northwest sector covering Beijing and west sector including Shanghai areas.

서울에서 채취한 고농도 PM<SUB>2.5</SUB>와 황산이온, 유기성 탄소물질과의 상관관계 분석

서영화(Young-Hwa Seo) 한국환경관리학회 2014 環境管理學會誌 Vol.20 No.3

서울시 8지점 대기 측정소에서 초미세먼지(PM2.5)를 채취 분석한 자료를 가지고 PM2.5의 고농도 발생 원인을 분석하였다. 2008년 가을부터 2010년 3월까지 PM2.5의 평균 농도는 30.5μg/m³으로 나타났으며, 도로변 채취지점인 동대문과 신사동에서 33.5μg/m³과 26.9μg/m³로 가장 높았으며, 도시 채취지점인 강서, 구로, 구의, 도봉, 종로에서는 33.3∼27.2μg/m³, 서울시 배경 측정지점인 북한산 지점에서 가장 낮은 25.4μg/m³로 관측되었다. 고농도 PM2.5가 발생한 날에 황산이온 중량이 PM2.5 중량에 23.4%를 차지하였는데 PM2.5가 낮을 때는 10.9%에 불과하여 고농도 PM2.5 발생에 황산이온의 발생이나 유입이 매우 큰 원인임을 확인하였다. PM2.5와 황산이온농도, PM2.5와 OC농도의 상관관계 분포 비교만 가지고 고농도 발생의 원인을 찾아본 결과 PM10과 달리 모든 측정지점의 상관관계가 비슷한 반면 상관계수는 0.68∼0.80으로 높았다. 모든 측정지점에서 PM2.5과 OC 농도와의 상관관계 계수가 PM2.5과 OC 농도와의 상관관계 계수보다 약간 높게 나타났는데 PM2.5가 증가할 때 OC의 증가와 좀 더 관련이 있음을 알 수 있었다. Correlation analysis between PM2.5 and sulfate anion, organic carbon was carried out to identify the cause and occurrence of high levels of PM2.5. Average concentration of PM2.5 during sampling period from 2008 and 2010 was 30.5 μg/m³. PM2.5 concentration of was the highest at the dongdamun roadside sampling point with 33.5μg/m³, ranged from 33.3∼27.2μg/m³ at inside sampling points, and was the lowest at bukansan Seoul background sampling point. Wt.% of sulfate anion was 23.4% of PM2.5 at the day of the highest PM2.5 occurrence, while it was only 10.9% at the lowest PM2.5 occurrence, indicating that inflow or production of sulfate anions was the biggest cause of high levels of PM2.5. The correlation coefficients between PM2.5, sulfate and OC were much better than those of PM10, showing that the fine particulates with sulfate and OC were more packed together. Correlations of PM2.5 and OC were slightly higher than those of PM2.5 and sulfate at most sampling site.

High Time-resolution Characterization of PM2.5 Sulfate Measured in a Japanese Urban Site

마창진,강공언,김기현 한국대기환경학회 2015 Asian Journal of Atmospheric Environment (AJAE) Vol.9 No.4

The high time-resolution monitoring data are essential to estimate rapid changes in chemical compositions, concentrations, formation mechanisms, and likely sources of atmospheric particulate matter (PM). In this study, PM2.5 sulfate, PM2.5, PM10, and the number concentration of size-resolved PMs were monitored in Fukuoka, Japan by good time-resolved methods during the springtime. The highest monthly average PM2.5 sulfate was found in May (8.85 μg m-3), followed by April (8.36 μg m-3), March (8.13 μg m-3), and June (7.22 μg m-3). The cases exceed the Japanese central government’s safety standard for PM2.5 (35 μg m-3) reached 10.11% during four months campaign. The fraction of PM2.5 sulfate to PM2.5 varied from 12.05% to 68.11% with average value of 35.49% throughout the entire period of monitoring. This high proportion of sulfate in PM2.5 is an obvious characteristic of the ambient PM2.5 in Fukuoka during the springtime. However, the average fraction of PM2.5 sulfate to PM2.5 in three rain events occurred during our intensive campaign fell right down to 15.53%. Unusually high PM2.5 sulfate (>30 μg m-3) marked on three days were probably affected by the air parcels coming from the Chinese continent, the natural sulfur in the remote marine atmosphere, and a large number of ships sailing on the nearby sea. The theoretical number concentration of (NH4)2SO4 in PM0.5-0.3 was originally calculated and then compared to PM2.5 sulfate. A close resemblance between the diurnal variations of the theoretically calculated number concentration of (NH4)2SO4 in PM0.5-0.3 and PM2.5 sulfate concentration indicates that the secondary formed (NH4)2SO4 was the primary form of sulfate in PM2.5 during our monitoring period.

ORIGINAL ARTICLE : Comparison of the Number Concentration and the Chemical Composition of the Atmospheric PM2.5 in Jeju Area

( Chang Hee Kang ),( Chu Goo Hu ) 한국환경과학회 2014 한국환경과학회지 Vol.23 No.5

The number concentrations and the water soluble ionic concentrations of PM2.5 have measured at Gosan site in Jeju, Korea, from March 2010 to December 2010, to clarify their characteristics. PM2.5 number concentrations vary from 22.57 to 975.65 particles/㎝3 with an average value of 240.41 particles/㎝3, which have been recorded evidently high in spring season as compared with those in other season. And the concentrations in small size ranges are greatly higher than those in large size ranges, so the number concentration in the size range 0.25∼0.45 ㎛ has more than 94% of the total number concentration of PM2.5. The major ionic components in PM2.5 are SO42-, NH4+ and NO3-, which are mainly originated from anthropogenic sources, on the other hand, the concentrations of Cl-, K+, Ca2+ and Mg2+ are recorded relatively lower levels. The concentrations of the major ionic components are very high in spring season, but the concentration levels of the other components are recorded significantly high in winter season. On the other hand, in summer season, the lowest concentration levels are observed for overall components as well as the sum of them. The concentration ratios of nss-SO42-/SO42- and nss-Ca2+/Ca2+ are 98.1% and 88.9%. And the concentration ratio of SO42-/NO3-(3.64) is greatly higher than the value in urban area due to no large NOx emission sources in the measurement. In addition, the correlation and the factor analysis for the number and the ionic concentrations of PM2.5 are performed to identify their sources. From the Pearson correlation analysis and the factor analysis, it can be suggested that the smaller parts(<0.5 ㎛) of PM2.5 is contributed by anthropogenic sources, but the sources of the remaining larger parts of PM2.5 are not able to be specified sources in this study.

사업장 내 사무실의 PM2.5 노출 평가

남미란 ( Mi Ran Nam ),정종현 ( Jong Hyon Jung ),피영규 ( Young Gyu Phee ) 한국산업위생학회 2013 한국산업보건학회지 Vol.23 No.4

Objectives: This study was conducted in order to evaluate PM2.5 concentrations at 20 offices connected to the manufacturing industry from the beginning of September to the end of November 2012. Methods: A total of 20 samples were collected from 20 office buildings. Each PM2.5 sample was collected by a 37 mm PTFE filter attached to a Personal Environment Monitor. Results: The geometric mean concentrations of PM2.5 in the offices was 23.47 ㎍/㎥, and the mean PM2.5 concentrations measured in smoking offices were much higher than those of measured in non-smoking offices(24.83 ㎍/㎥and 21.55 ㎍/㎥, respectively). PM2.5 was revealed to be higher in small offices(39.52 ㎍/㎥) than in medium or large offices(22.69 ㎍/㎥and 11.04 ㎍/㎥, respectively). The mean PM2.5 concentration of offices located on the 1st floor was higher than that of those on the 2nd floor, and those of offices located in the workplace were higher than those out of the workplace. The multiple regression model showed that concentration of PM2.5 was positively associated with the method of ventilation. Conclusions: Smoking, ventilation method, location, and inflow of outdoor particulate matter are the most important factors for office PM2.5 concentrations.

주택 실내ㆍ외에서의 PM<SUB>10</SUB>, PM<SUB>2.5</SUB> 농도와 호흡기계증상과의 관련성 조사

박지연(Ji Yeon Park),서혜경(Hye Kyung Seo) 한국실내환경학회 2005 한국실내환경학회지 Vol.1 No.2

This study, conducted from April to May 2004 in the metropolitan and surrounding areas of Seoul, Korea, was performed to show the relationship between indoor and outdoor levels of PM<SUB>10</SUB> and PM<SUB>2.5</SUB> concentrations in 14 residential houses. In addition, indoor/outdoor ratios of PM<SUB>10</SUB>, PM<SUB>2.5</SUB> concentrations were calculated. The relationship between the PM<SUB>10</SUB>, PM<SUB>2.5</SUB> concentrations and respiratory symptoms by self recording questionnaire of 14 houses was investigated. In conclusion, although the results of this study failed to establish the relationship between PM<SUB>10</SUB>, PM<SUB>2.5</SUB> concentrations and respiratory symptoms among residents, the levels of indoor PM<SUB>2.5</SUB> were significantly higher than those of outdoor levels. The indoor PM<SUB>10</SUB>, PM<SUB>2.5</SUB> concentrations were increased by the amount of time spent of residents. Further research should be directed to establish the relationship between PM<SUB>10</SUB>, PM<SUB>2.5</SUB> concentration and respiratory symptoms.