• 한국환경과학회지
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• 제30권10호
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• pp.845-861
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• 2021

This study investigated the variations in monthly PM_2.5 concentrations and their characteristics at the sampling site (35.075°N, 129.080°E) around the Busan seaport area for six months (from August 2020 to January 2021). Monthly PM_2.5 concentrations in the filtered samples ranged from 8.4 to 42.3 ㎍/m³ (average=19.6±8.2 ㎍/m³, n=50) and were generally high in August, December, and January, and low in September, October, and November. The variations of monthly PM_2.5 concentrations showed similar patterns to those of the neighboring national air quality monitoring sites. The contents of Total Carbon (TC), Organic Carbon (OC), Elemental Carbon (EC), and OC/EC ratios in PM_2.5 showed large variability during the study period. The OC/EC ratios ranged from 4.2 to 34.4, suggesting that the relative contributions of OC and EC to the PM_2.5 concentrations changed temporally and might be related to their formation sources. Variations in the chemical components of and particle size distributions in PM_2.5 showed that high PM_2.5 concentrations were affected by various sources, such as sea salt and ship emission. The precursor gas concentrations were discussed in terms of monthly variations and their contributions to PM_2.5 concentrations. However, further research is needed to understand the characteristics and behaviors of PM_2.5 concentrations around the Busan seaport area.

• 한국산학기술학회논문지
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• 제13권1호
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• pp.445-450
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• 2012

2015년 대기환경기준에 추가되는 PM2.5의 천안시 대기 중 오염도를 조사하기 위해, 2010년 2월부터 2011년 1월까지 천안시 상명대학교에 광산란방식의 Dust Monitor를 설치하여 대기 중 연간 PM2.5 농도 특성을 PM10 농도와 같이 조사하였다. 측정 기간 중 연평균 PM2.5 농도는 $40.45{\mu}g/m^3$으로 시행예정인 연평균 기준인 $25{\mu}g/m^3$을 초과하였다. 일평균 PM2.5 농도는 $2.43{\sim}174.84{\mu}g/m^3$으로, 전체 측정 기간 중 약 26%의 측정일이 일평균 기준치인 $50{\mu}g/m^3$을 초과하였다. 같은 기간 중 일평균 PM10 농도 기준을 초과하는 측정일 수는 11%로 나타나, PM2.5의 오염도가 PM10에 비해 상대적으로 심각함을 나타냈다. 계절별로는 봄과 겨울철에 높은 PM2.5 농도를 보였으며, 강우의 영향을 많이 받는 여름철의 PM2.5 오염도가 다른 계절에 비해 상대적으로 낮았다. 일 중 PM2.5의 농도 분포는 출퇴근 시간대에 높은 농도를 나타내는 전형적인 도시형 특성을 나타냈으며, 이는 인위적 배출원 중 이동오염원에 의해 생성되는 미세 입자가 PM2.5의 주요 성분임을 시사한다.

• 한국대기환경학회지
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• 제23권1호
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• pp.132-140
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• 2007

Concentrations of atmospheric fine particles in Chungnam were measured at 7 sampling sites during 2005. The daily average concentrations of PM 10, PM2.5, and PM1 ranged from 14.9 to $136.5{\mu}g/m^3$, 8.2 to $113.2{\mu}g/m^3$, and 5.7 to $107.5{\mu}g/m^3$, respectively, and the highest levels were observed at Yeongi site. The lowest concentrations for the all size fractions of particulate were observed at Taean located at the west end of the peninsula. The daily average PM10 concentrations were below the current National Standard at all sites, while the daily average PM2.5 concentrations frequently exceeded the US Standard at Cheonan, Dangjin, Boryeong, and Yeongi sites. The frequencies of PM2.5 concentrations exceeding the US standard at Cheonan, Dangjin, Boryeong, and Yeongi were 10.8%, 6.7%, 6.7%, and 26.7%, respectively. In addition, $68{\sim}80%$ of PM10 was in the PM2.5 fraction indicating that fine particles were the major component of atmospheric particles in Chungnam.

• 한국대기환경학회지
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• 제32권1호
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• pp.100-113
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• 2016

In this study, the characteristics of $PM_{2.5}$ and $PM_{2.5-10}$ concentrations were identified in two different functional areas including Chuncheon and Youngwol, Korea. Even though the anthropogenic emission rates of $PM_{2.5}$ and $PM_{10}$ are approximately four times higher in Youngwol than in Chuncheon their atmospheric concentrations were statistically higher in Chuncheon. In Chuncheon, both $PM_{2.5}$ concentrations and the ratio of $PM_{2.5}/PM_{10}$ increased as relative humidity (RH) increased possibly because the inorganic and/or organic secondary aerosols were actively formed at high RH. This result was also supported by that $PM_{2.5}$ concentration was enhanced under the fog and mist conditions in Chuncheon. On the other hand, both $PM_{2.5}$ and $PM_{2.5-10}$ concentrations clearly increased with the southerly winds blown from the cement production facility in Youngwol. In addition, high $PM_{2.5-10}$ concentrations were observed with high wind speed, low relative humidity, and high $NO_2$ concentrations in Youngwol, suggesting that $PM_{2.5-10}$ was generated through the physical process including crushing and packing procedures followed by resuspension from cement and lime factory.

• 한국대기환경학회지
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• 제27권5호
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• pp.494-503
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• 2011

Fine particles ($PM_{2.5}$) were collected and analyzed from December 2005 through December 2009 in Chuncheon, Korea to investigate the long-term trend of $PM_{2.5}$ concentrations. Also $PM_{10}$ concentrations were collected from Environmental Monitoring System operated by Ministry of Environment. Average concentrations of $PM_{2.5}$ and $PM_{10}$ were 30.5 and 58.2 ${\mu}g/m^3$, respectively. Both $PM_{2.5}$ and $PM_{10}$ were significantly affected by meteorological factors including wind speed, wind direction and precipitation. They generally decreased as wind speed increased (p=0.000), and increased when there was a prevailing westerly wind. Low concentrations of $PM_{2.5}$ were observed during rainy days while high concentrations were shown when fog, mist and/or haze occurred.

• 한국대기환경학회지
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• 제24권3호
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• pp.367-375
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• 2008

To characterize atmospheric particles in Cheonan area, 5 monitoring sites representing highway area, commercial area, residential area, and industrial areas were selected, and the mass concentrations of PM10 and PM2.5 were monitored for 14 days at each site during 2007. The daily average PM10 and PM2.5 concentrations were in the range from 18.5 to $140.9{\mu}g/m^3$ and 8.2 to $116.6{\mu}g/m^3$, respectively, showing the highest mean concentrations at the commercial area site and the lowest concentration at the residential area site. The daily average PM 10 concentrations at Shinan (Commercial area) and Bakseok (Industrial area) sites were exceeded the current National Standard for 1 and 2 days during the monitoring periods. The fractions of PM2.5 in PM10 were above 70% for all sites, indicating fine particles are the major constituent of atmospheric particles in Cheonan. The results indicate that PM10 concentrations in Cheonan are at the concerning level, and the control strategy for fine particles is necessary to address this issue.

• 한국환경과학회지
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• 제29권7호
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• pp.749-760
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• 2020

This study investigates the characteristics of diurnal, seasonal, and weekly roadside and residential concentrations of PM₁₀ and PM_2.5 in Busan, as well as relationship with meteorological phenomenon. Annual mean PM₁₀ and PM_2.5 concentrations in Busan were 44.2 ㎍/㎥ and 25.3 ㎍/㎥, respectively. The PM_2.5/PM₁₀ concentration ratio was 0.58. Diurnal variations of PM₁₀ and PM_2.5 concentrations in Busan were categorized into three types, depending on the number of peaks and times at which the peaks occurred. Roadside PM₁₀ concentration was highest on Saturday and lowest on Friday. Residential PM₁₀ concentration was highest on Monday and lowest on Friday. Residential PM_2.5 concentration was highest on Monday and Tuesday and lowest on Friday. PM₁₀ and PM_2.5 concentrations were highest on Asian dust and haze, respectively. The results indicate that understanding the spaciotemporal variation of fine particles could provide insights into establishing a strategy to control urban air quality.

• 한국대기환경학회지
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• 제34권1호
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• pp.156-165
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• 2018

Long-term trend analysis on air pollutant concentrations is very important to diagnose the present status and plan for the future. In this study, the long-term trends of $PM_{2.5}$ concentrations were estimated based on the relationship between the visibility and $PM_{2.5}$ concentration regarding the effects of relative humidity in Seoul and Chuncheon. The relationships between the visibility and $PM_{2.5}$ concentration were derived from the measurement data in 2015 and 2016. Then, the annual trends of $PM_{2.5}$ concentration from 1982 to 2014 were estimated and compared to those of $PM_{10}$ concentration available in Seoul and Chuncheon. During the estimation process, four ranges of relative humidity were considered such as less than 30%, 31~50%, 51~70%, and 71~90%. In Seoul and Chuncheon, the visibility and $PM_{2.5}$ concentration generally have the inverse relationship while the visibility decreases as the relative humidity increases. The estimated $PM_{2.5}$ concentrations similarly showed the decreasing tendencies from 2006 to 2012 in Seoul and Chuncheon. However, the estimated $PM_{2.5}$ concentrations showed the increasing tendency before 2005 in Chuncheon in contrast to the decreasing tendency in Seoul. This implies that the long-term trends of $PM_{2.5}$ concentration in different cities in South Korea reflect the local influencing factors. For example, 'Special Act on the Improvement of Atmospheric Environment in the Seoul Metropolitan Area' can affect the different long-term trends in Seoul and Chuncheon. The estimated $PM_{2.5}$ concentrations were validated with the measured ones in Seoul and Chuncheon. While the general tendencies were well matched between the estimated and measured concentrations, the $PM_{2.5}$ concentration trends in 1990s and their monthly variations are needed to be improved quantitatively using more reference data for longer years.

• 한국환경과학회지
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• 제17권6호
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• pp.633-645
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• 2008

In order to investigate the variations and corelation among $PM_{10},\;PM_{2.5}\;and\;PM_1$ concentrations, the hourly concentrations of each particle sizes of 300nm to $20{\mu}m$ at a city, Gangneung in the eastern mountainous coast of Korean peninsula have been measured by GRIMM aerosol sampler-1107 from March 7 to 17, 2004. Before the influence of the Yellow Dust event from China toward the city, $PM_{10},\;PM_{2.5}\;and\;PM_1$, concentrations near the ground of the city were very low less than $35.97{\mu}g/m^3,\;22.33{\mu}g/m^3\;and\;16.77{\mu}g/m^3$, with little variations. Under the partial influence of the dust transport from the China on March 9, they increased to $87.08{\mu}g/m^3,\;56.55{\mu}g/m^3\;and\;51.62{\mu}g/m^3$. $PM_{10}$ concentration was 1.5 times higher than $PM_{2.5}$ and 1.85 times higher than $PM_1$. Ratio of $(PM_{10}-PM_{2.5})/PM_{2.5}$ had a maximum value of 1.49 with an averaged 0.5 and one of $(PM_{2.5}-PM_1)/PM_1$ had a maximum value of 0.4 with an averaged 0.25. $PM_{10}\;and\;PM_{2.5}$ concentrations were largely influenced by particles smaller than $2.5{\mu}m\;and\;1{\mu}m$ particle sizes, respectively. During the dust event from the afternoon of March 10 until 1200 LST, March 14, $PM_{10},\;PM_{2.5}\;and\;PM_1$ concentrations reached $343.53{\mu}g/m^3,\;105{\mu}g/m^3\;and\;60{\mu}g/m^3$, indicating the $PM_{10}$ concentration being 3.3 times higher than $PM_{2.5}$ and 5.97 times higher than $PM_1$. Ratio of $(PM_{10}-PM_{2.5})/PM_{2.5}$ had a maximum value of 7.82 with an averaged 3.5 and one of $(PM_{2.5}-PM_1)/PM_1$, had a maximum value of 2.8 with an averaged 1.5, showing $PM_{10}\;and\;PM_{2.5}$ concentrations largely influenced by particles greater than $2.5{\mu}m\;and\;1{\mu}m$ particle sizes, respectively. After the dust event, the most of PM concentrations became below $100{\mu}g/m^3$, except of 0900LST, March 15, showing the gradual decrease of their concentrations. Ratio of $(PM_{10}-PM_{2.5})/PM_{2.5}$ had a maximum value of 3.75 with an averaged 1.6 and one of $(PM_{2.5}-PM_1)/PM_1$ had a maximum value of 1.5 with an averaged 0.8, showing the $PM_{10}$ concentration largely influenced by corse particles than $2.5{\mu}m$ and the $PM_{2.5}$ by fine particles smaller than $1{\mu}m$, respectively. Before the dust event, correlation coefficients between $PM_{10},\;PM_{2.5}\;and\;PM_1$, were 0.89, 0.99 and 0.82, respectively, and during the dust event, the coefficients were 0.71, 0.94 and 0.44. After the dust event, the coefficients were 0.90, 0.99 and 0.85. For whole period, the coefficients were 0.54, 0.95 and 0.28, respectively.

• 대한원격탐사학회지
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• 제37권6_2호
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• pp.1881-1890
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• 2021

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.