• 한국환경과학회지
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• 제25권5호
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• pp.715-726
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• 2016

This study investigates the characteristics of metallic and ionic elements concentration, concentration according to transport path, and factor analysis in $PM_{10}$ at Guducsan in Busan in the springtime of 2015. $PM_{10}$ concentration in Guducsan and Gwaebeopdong were $59.5{\pm}9.04{\mu}g/m^3$ and $87.5{\pm}20.2{\mu}g/m^3$, respectively. Contribution rate of water-soluble ions and secondary ion in $PM_{10}$ concentration in Guducsan were 37.0% and 27.8% respectively. [$NO_3{^-}/SO{_4}^{2-}$] ratio and contribution rate of sea salt of $PM_{10}$ in Guducsan and Gwaebeopdong were 0.91 and 1.12, 7.0% and 5.3%, respectively. The results of the backward trajectory analysis indicates that $PM_{10}$ concentration, total inorganic water-soluble ions and total secondary ions were high when the air parcels moved from Sandong region in China than non-Sandong and northen China to Busan area. The results of the factor analysis at Guducsan indicates that factor 1 was anthropogenic source effects such as automobile emissions and industrial combustion processes, factor 2 was marine sources such as sea salts from sea, and factor 3 was soil component sources.

• 분석과학
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• 제24권4호
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• pp.310-318
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• 2011

제주도 고산지역에서 $PM_{10}$과 $PM_{2.5}$ 미세먼지 시료를 채취하여 주요 성분의 화학 조성, 오염 정도, 배출원 특성 등을 조사하였다. 연구기간의 $PM_{10}$과 $PM_{2.5}$ 미세먼지의 질량농도는 각각 $37.6{\pm}20.1{\mu}g/m^3$, $22.9{\pm}14.3{\mu}g/m^3$로 $PM_{2.5}$ 질량농도는 $PM_{10}$의 약 61%를 차지하였다. $PM_{2.5}/PM_{10}$ 농도비를 조사해 본 결과, 인위적 기원의 nss-$SO_4^{2-}$, $NO_3$, $NH_4^+$은 주로 미세입자에, 그리고 nss-$Ca^{2+}$과 $Na^+$, $Cl^-$, $Mg^{2+}$ 성분들은 대부분 조대입자에 많이 분포하였다. 또 미세먼지 조성은 대체적으로 인위적 오염원의 영향이 가장 크고, 다음으로 토양 또는 해양의 영향을 많이 받는 것으로 나타났다. 역궤적 분석법으로 미세먼지 성분들의 유입경로를 조사해 본 결과, nss-$SO_4^{2-}$, $NO_3^-$, $NH_4^+$, nss-$Ca^{2+}$, Pb 성분들은 대체적으로 기류가 중국대륙과 한반도로부터 유입되었을 때 농도가 높게 나타났다. 반면에 북태평양이나 동해를 통해 유입되었을 때는 상대적으로 낮은 경향을 보였다.

• 자원환경지질
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• 제55권6호
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• pp.701-716
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• 2022

This study investigated the distribution behaviors of PM2.5 and PM10 at two air quality monitoring sites, Go-eup (GO) and Backseokeup (BS), located in Yangju City, South Korea. The amounts of emissions sources of pollutants were analyzed based on the Clean Air Policy Support System (CAPSS), and the contribution rates of neighboring cities were enumerated in Yangju. Yangju has a geological basin structure, and it is a city with mixed urban and rural characteristics. The emission concentration of particulate matter was affected by geological and seasonal factors for all sites observed in this study. Therefore, these factors should be considered when establishing policies related to particulate matter. Because the official GO and BS station sites in Yangju are both situated in the southern part of the city, the representativeness of both stations was checked using correlation analysis for the measurement of PM2.5 and PM10 by considering two more sites-those of Bongyang-dong (BY) and the Gumjun (GJ) industrial complex. The data included discharge amounts for business types 4 and 5, which were not sufficiently considered in the CAPSS estimates. Because the 4 and 5 types of businesses represent over 92.6% of businesses in this city, they are workplaces in Yangju that have a significant effect on the total air pollutant emission. These types of businesses should be re-inspected as the main discharge sources in industry, and basic data accumulation should be carried out. Moreover, to manage the emission of particulate matter, attainable countermeasures for the main sources of these emissions should be prepared in a prioritized fashion; such countermeasures include prohibition of backyard burning, supervision of charcoal kilns, and management of livestock excretions and fugitive dust in construction sites and on roads. The contribution rates by neighboring cities was enumerated between 6.3% and 10.9% for PM2.5. Cooperation policies are thought to be required with neighboring cites to reduce particulate matter.

• 한국대기환경학회지
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• 제26권1호
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• pp.21-33
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• 2010

The objective of this study was to estimate the $PM_{2.5}$ source apportionment at the Pinnacles National Monument IMPROVE site in western coastal USA. The PMF was applied to identify the existing sources and apportion the $PM_{2.5}$ mass to each source. To analyze local source impacts from various wind directions, the NPR analysis was performed using source contribution results with the wind direction values measured at the site. Also, PSCF was applied to identify the locations by point sources relative to the back trajectories. A total of 1,634 samples were collected from March 1988 to May 2004 by IMPROVE sampler and 32 chemical species were analyzed by PIXE, PESA, XRF, IC, and TOR methods. The PMF modeling identified seven sources and the average mass was apportioned to gasoline vehicle, secondary sulfate, aged sea salt, secondary nitrate, wood/field burning, diesel emission, and soil, respectively. In this study, the average mass was apportioned to gasoline vehicle (33.0%), secondary sulfate (25.7%), aged sea salt (17.8%), and secondary nitrate (10.1%). Also, this study suggests the possible role for source apportionment study of $PM_{2.5}$ at similar areas such as wildness, national park, and coastal areas in Korea.

• 한국대기환경학회지
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• 제25권2호
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• pp.154-166
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• 2009

In this study, 1-hour integrated $PM_{2.5}$ mass and chemical composition concentrations were monitored at the St. Louis-Midwest Supersite in Illinois. Time-resolved samples were collected one week in each of June 2001 (22 June to 28 June), November 2001 (7 November to 13 November), and March 2002 (19 March to 25 March). A total of 427 samples were collected by CAMM (continuous ambient mass monitor) and 15 compounds were analyzed by AAS, PILS (particle-into-liquid sampler), and TOT (thermal optical transmittance) method. PMF was applied to identify the sources and apportion the $PM_{2.5}$ mass to each source for highly time resolved data. In addition, the nonparametric regression (NPR) was applied to identify the predominant directions of local sources relative to wind direction. Also, this study performed compare the NPR analysis and location of actual local point sources at the St. Louis area. The PMF modeling identified nine sources and the average mass was apportioned to gasoline vehicle, road dust, zinc smelter, copper production, secondary sulfate, diesel emission, secondary nitrate, iron+steel, and lead smelter, respectively. These results suggested that this study results will be help for $PM_{2.5}$ source apportionment studies at similar metropolitan area, establish $PM_{2.5}$ standard, and establish effective emissions reduction strategies in Korea.

• 한국대기환경학회지
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• 제16권5호
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• pp.469-476
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• 2000

This study was performed to understand the behavior and source characteristics of particulate trace metals in Daegu area. To do this, total of 84 samples had been collected from January to December 1999. TSP (total suspended particulate matter) and PM-10(particulate matter with aerodynamic diameters less 10${\mu}{\textrm}{m}$) were collected by filters on portable air sampler, and in TSP and PM-10 were analyzed by ICP(Inductively Coupled Plasma Spectrometer) after preliminary treatment. The results were follow as: first, annul means of TSP and PM-10 concentration were 123 and 69$\mu\textrm{g}$/㎤ respectively. The concentration of TSP adn PM-10 were highest in winter season compared to other seasons. Second, the concentration of Al, Fe, Mn were higher in TSP than in PM-10, indicating that these metals are generally associate with natural contributions. Third, a hierarchical clustering technique was used to group 9 metals. The results from the cluster analysis of TSP and PM-10 shows a similar clustering pattern : Fe, Al in a group and the rest of the metals such as Ni, Cr, As, Mn, Cd, Pb, Zn in the other group. One group of metal such as Fe, Al is associated with natural sources such as soil and dust. The other is closely related to urban anthropogenic sources such as fuel combustion, incineration, and refuse burning, Finally, using Al as a reference element, enrichment factors were used for identifying the major particulate contributors. The enrichment factors of Al. Fe<10 (standard value of enrichment factor) were considered to have a significant dust and soil source and termed nonenriched. Ni, Cr, As, Mn, Cd, Pb, Zn》10 is enriched and has a significant which is contributed by athropogenic sources.

• 한국대기환경학회:학술대회논문집
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• 한국대기환경학회 2008년도 추계학술대회 논문집
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• pp.187-189
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• 2008

• 한국대기환경학회:학술대회논문집
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• 한국대기환경학회 2010년도 춘계학술대회 논문집
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• pp.547-548
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• 2010

• 한국응용과학기술학회지
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• 제36권3호
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• pp.866-875
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• 2019

본 연구에서는 CMB(Chemical Mass Balance) 모델을 이용하여 $PM_{2.5}$에 대한 오염원 확인 및 오염원별 기여도를 분석하였다. A시의 배출원별 기여도 순위는 비산먼지(30.1%) > 생물성 연소(21.9%) > 2차 오염물질(21.1%) > 도로이동오염원(19.3%) > 면오염원(7.6%) 순이고, CMB 모델 기여도와 CAPSS(Clean Air Policy Support System) 배출자료 기여도 비교에서 증가한 배출원은 생물성 연소와 2차 오염물질이고, 감소한 배출원은 도로이동오염원, 비산먼지, 면오염원으로 분석되었다.

• 한국대기환경학회지
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• 제33권2호
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• pp.159-173
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• 2017

The Weather Research and Forecast (WRF) - Community Multiscale Air Quality (CMAQ) system was applied to investigate the influence of major point sources located in Chungcheongnam-do (CN) on surface $PM_{2.5}$ (Particulate Matter of which diameter is $2.5{\mu}m$ or less) concentrations in its surrounding areas. Uncertainties associated with contribution estimations were examined through cross-comparison of modeling results using various combinations of model inputs and setups; two meteorological datasets developed with WRF for 2010 and 2014, and two domestic emission inventories for 2010 and 2013 were used to estimate contributions of major point sources in CN. The results show that contributions of major point sources in CN to annual $PM_{2.5}$ concentrations over Seoul, Incheon, Gyeonggi, and CN ranged $0.51{\sim}1.63{\mu}g/m^3$, $0.71{\sim}1.62{\mu}g/m^3$, $0.63{\sim}1.66{\mu}g/m^3$, and $1.04{\sim}1.86{\mu}g/m^3$, respectively, depending on meteorology and emission inventory choice. It indicates that the contributions over the surrounding areas can be affected by model inputs significantly. Nitrate was the most dominant $PM_{2.5}$ component that was increased by major point sources in CN followed by sulfate, ammonium, and others. Based on the model simulations, it was estimated that primary $PM_{2.5}$ $(PPM)-to-PM_{2.5}$ conversion rates were 41.3~50.7 ($10^{-6}{\mu}g/m^3/TPY$) for CN, and 12.4~18.3 ($10^{-6}{\mu}g/m^3/TPY$) for Seoul, Incheon, and Gyeonggi, respectively. In addition, spatial gradients of PPM contributions show very steep trends. $NO_X$-to-nitrate conversion rates were 7.61~12.3 ($10^{-6}{\mu}g/m^3/TPY$) for CN, and 3.94~11.3 ($10^{-6}{\mu}g/m^3/TPY$) for the sub-regions in the SMA. $SO_2$-to-sulfate conversion rates were 4.04~5.28 ($10^{-6}{\mu}g/m^3/TPY$) for CN, and 3.73~4.43 ($10^{-6}{\mu}g/m^3/TPY$) for the SMA, respectively.