• 한국대기환경학회지
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• 제27권4호
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• pp.460-471
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• 2011

A port has been regarded as a significant contributor to air pollution in the surrounding areas. Port-related air pollutants are released from not only marine vessels, but also various land-side sources at ports, which include cargo handling equipment, vehicles, locomotives, and fugitive dust sources by port activities such as bulk handling and vehicle movements. However, most studies in Korea have only focused on vessel emissions and there is a lack of information on the emissions from other sources at port. In this study, in order to establish the port-related emission inventory and evaluate the relative contribution of these sources to air emissions from the Port of Incheon, the emissions from land-side sources were estimated and the CAPSS (Clean Air Policy Support System) data for vessel emissions were used. In particular, the detailed information and activity data for the cargo handling equipment source were collected and the emission factors and emissions by equipment types were calculated using U.S. EPA methodologies. Total HC, CO, $NO_x$, $PM_{10}$, and $SO_2$ emissions from port-related sources including the vessel in 2007 were calculated as 229 ton/year, 638 ton/year, 4,861 ton/year, 307 ton/year, and 3,995 ton/year, respectively. It was found that the vessel was the largest contributor to air pollutant emissions from the port, the cargo handling equipment was responsible for about from 8% to 13% of HC, CO, and $NO_x$ emissions and the resuspended road dust contributed about 39% for $PM_{10}$ emissions. The results of this study will be used to establish the management and reduction strategies of air pollution in the port.

• 한국환경과학회지
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• 제17권10호
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• pp.1169-1182
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• 2008

The chemical and meteorological effects on the concentration variations of air pollutants ($O_3$ and its precursors) were evaluated based on ground observation data in coastal and inland regions, Busan during springs and summers of 2005-2006. For the purpose of this study, study areas were classified into 5 categories: coastal area (CA), industrial area (IA), downtown area (DA), residential area (RA), and suburban area (SA). Two sites of Dongsam (DS) and Yeonsan (YS) were selected for the comparison purpose between the coastal and inland regions. $O_3$ concentrations in CA and SA were observed to be highest during spring (e.g., 40 ppb), whereas those in DA and RA were relatively low during summer (e.g., $22\sim24$ ppb). It was found that $O_3$ concentrations in IA were not significantly high although high VOCs (especially toluene of about 40 ppb) and $NO_x$ ($\geq$ 35 ppb) were observed. On the other hand, the concentration levels of $O_3$ and $PM_{10}$ at the DS site were significantly higher than those at the YS site, but $NO_x$ was slightly lower than that at the YS site. This might be caused by the photochemical activity and meteorological conditions (e.g., sea-land breeze and atmospheric stagnance). When maximum $O_3$ (an index of photochemical activity) exceeds 100 ppb, the contribution of secondary $PM_{10}\;((PM_{10})_{SEC})$ to total observed $PM_{10}$ concentrations was estimated up to 32% and 17% at the DS and YS sites, respectively. In addition, the diurnal variations of $(PM_{10})_{SEC}$ at the DS site were similar to those of $O_3$ regardless of season, which suggests that they are mostly secondary $PM_{10}$ produced from photochemical reactions.

• 한국환경보건학회지
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• 제35권6호
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• pp.454-460
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• 2009

The subway is the major public transportation system in Seoul with 2.2 million people using it everyday. Indoor air pollution in the subway can be a significant part of population exposure because of the number of people using the subway, time spent in transit and potentially high exposure for certain pollutants. The Korea Ministry of Environment has established the level 2 of recommended standards of $PM_{10}$ and $CO_2$ in subway trains. The aims of this study were to determine the airborne levels of $PM_{10}$, $CO_2$ and any correlation between pollutant levels and number of passenger in a subway train. The airborne $PM_{10}$ and $CO_2$ were measured on the inside of trains on line #4 for 4 different days from October to November in 2008. Average $PM_{10}$ and $CO_2$ levels were $113{\pm}25{\mu}g/m^3$ and $1402{\pm}442$ ppm, respectively. These levels did not exceed the level 2 of recommended standards of $250{\mu}g/m^3$ for $PM_{10}$ and 3500 ppm for $CO_2$. $PM_{10}$ level was not correlated with the number of passengers, while $CO_2$ levels were positively correlated with the number of passengers. The findings suggested that $PM_{10}$ in subway trains may have sources other than those directly associated with the number of passengers.

• 한국환경과학회지
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• 제4권1호
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• pp.63-70
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• 1995

1993년 7월부터 1994년 6월까지 1년간 시골지역에서 지면 부근의 오존을 연속적으로 측정하여 5분 평균치를 연구에 이용하였다. 이 관측은 북위 $37.4{\circ}$, 동경 $127.6{\circ}$ 에 위치한 충북 청원군 강내에서 실시되었으며, 1년 평균값은 17ppbㅠ이고 월평균은6-47ppb이다. 여름에 최대값이 발생하고 겨울에 최소값이 나타나며, 이들은 인위적인 배출물 및 광화학 반응과 관련이 있따. 오존으 일변화는 15:00~16:00시에 최대치와 07:00~08:00시에 최소치가 발생한다. 오존이 80ppb이상 발생하는 기간에는 북-북서풍의 안정한 기류가 유입할때 발생하는 반면, 여름에 오존이 매우 낮게 발생하는 기간에는 북태평양에서 유입되는 기류와 함꼐 발생하였다. 그러므로 장거리에 근원을 둔 인위적인 대기오염의 이동(LRTAP)이 시골지역의 국지적인 오존의 발생보다 더 큰 기여를 하고 있음을 시사한다.

• 지역연구
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• 제33권4호
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• pp.29-42
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• 2017

이 연구는 중국 지방정부 역량이 대기오염 개선에 미치는 영향을 실증적으로 분석하는 것을 목적으로 한다. 이를 위해 2007년부터 2014년까지 중국 성급 행정단위를 대상으로 $SO_2$, $CO_2$, 분진 등 대기오염 물질과 지방정부 역량에 관한 자료를 이용하여 동적패널모형을 구축하였다. 분석 결과는 지방정부의 역량 중에서 환경인력, 환경예산, 환경기관 평균규모 등 조직역량이 가장 중요하고, 제도역량이나 사회역량은 대기오염 개선에 대한 영향이 미미함을 보여준다. 조직역량 이외의 지방정부 역량 중에서는 사회역량인 환경단체의 활동성만이 부분적으로 대기오염 개선에 영향을 미치고 있다. 지역 여건과 관련해서는 재정의 수직적 의존도 및 1인당 GDP, 인구 밀도 등이 대기오염 개선에 부정정적인 영향을 미친다. 이러한 연구결과는 대기오염 개선을 위해 중국 지방정부들이 어떤 역량을 특히 강화해야 하는지에 대한 시사점을 제공한다.

• 한국대기환경학회지
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• 제27권5호
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• pp.545-557
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• 2011

The objective of this study was to estimate the trends of each pollutant using the air pollution monitoring networks data from January 2005 to December 2008 in Daegu area. Also, the spatial characteristics of each pollutant were determined using the Pearson correlation coefficients and COD (coefficients of divergence). In this study, the trends of hourly, monthly, seasonal, and total average concentrations of each pollutant for the 10 sites were analyzed. The Ihyeon site showed highest concentration for the $SO_2$, $NO_2$, and PM10}. In the case of $O_3$, the Jisan site showed highest concentration among the other sites. Also, industrial area presented highest concentration for the $SO_2$, CO, and PM10. On the other hand, $NO_2$ showed highest in commercial area. The IDW (inverse distance weighting) method was used to estimate characteristics of spatial distribution. The results provide identify spatial distribution for each pollutant. Also, the Pearson correlation coefficients and COD values provide spatial variability among the monitoring sites. The COD of each pollutant showed very low values for all of the sites pairs. On the other hand, the Pearson correlation coefficients showed high values for all of the sites pairs. Finally, analysis of spatial variability can be used to characterize the spatial uniformity and similarity of concentrations from each pollutant.

• 한국환경보건학회지
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• 제41권4호
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• pp.223-230
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• 2015

Objectives: There is considerable evidence that polluted ambient air contributes to the risk of cardiovascular morbidity and mortality. Heart rate variability (HRV) is defined as the variation in heartbeat intervals and has been reported as a biological marker of cardiovascular disease. This article reviews the existing literature in order to examine the association between air pollution and HRV. Methods: Literature was searched using Web of Science with the key words of "air pollution", "heart rate variability" and other related terms. A total of 156 articles were listed. For review, 21 of those listed publications were chosen after excluding studies regarding chamber studies, occupational environment, secondhand smoke and automobile exhaust. Results: Research methods employed in the publications were classified by type of participants (elderly/adult), air pollution monitoring (ambient/personal) and HRV monitoring (continuous/spot). Among HRV parameters, power in the low frequency range (LF), power in the high frequency range (HF) and standard deviation of all NN intervals (SDNN) were all associated with air pollutants. The chosen studies were mostly based on elderly populations. In studies based on continuous HRV monitoring, LF and SDNN significantly decreased when $PM_{2.5}$ exposure increased. Conclusion: Continuous HRV monitoring combined with personal exposure monitoring has been one of the most common study methods in recent publications. We expect that this review will be useful for the study of the association between air pollution and cardiovascular effects using HRV.

• 한국대기환경학회지
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• 제23권1호
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• pp.110-124
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• 2007

In this study, the control efficiency of odorous compounds was measured from diverse control process units of 14 individual companies located within the Ban-Wall industrial complex of Ansan city, Korea (January to July 2005), To quantify the control efficiency levels of major odorous compounds, we collected odor samples from both the front and rear side of 17 control process units ($N=17{\times}2=34$). If the control efficiency is compared for each of 32 compounds between different process units, wet scrubber (WS) was found to be the most effective unit in terms of the sum of pollutants showing the positive control signals. Although the WS system shows generally a good control pattern for VOC, it is not the case for most index odorous pollutants; only 3 out of 12 index compounds were found to show positive control efficiencies. The results of the study also indicated that the control efficiency differ greatly between different industrial sectors and/or control process types. In the case of leather industry, carbonyl compounds were found to exhibit the highest control efficiency with its values varying from 19 to 90%. On the other hand, in the case of metal production sector, VOC recorded the maximum control efficiency with values varying from 18 to 79%. According to this study, most air pollution control facilities operated in most companies show fairly poor control efficiencies for most malodor compounds. Hence, to obtain best control efficiency of odorous pollutant emission, acquisition of better information on source characteristics and establishment of effective control technologies are highly demanding.

• 대기
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• 제29권4호
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• pp.429-438
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• 2019

Organic carbon (OC) and elemental carbon (EC) in PM_2.5 were measured with Sunset Laboratory Model-5 Semi-Continuous OC/EC Field Analyzer by NIOSH/TOT method at Anmyeondo Global Atmosphere Watch (GAW) Regional Station (37°32'N, 127°19'E) in July and August, 2017. The mean values of OC and EC were 3.7 ㎍ m^-3 and 0.7 ㎍ m^-3, respectively. During the study period, the concentrations of reactive gases and aerosol compositions were evidently lower than those of other seasons. It is mostly due to meteorological setting of the northeast Asia, where the influence of continental outflow is at its minimum during this season under southwesterly wind. While the diurnal variation of OC and EC were not clear, the concentrations of O₃, CO, NOx, EC, and OC were evidently enhanced under easterly wind at night from 20:00 to 8:00. However, the high concentration of EC was observed concurrently with CO and NOx under northerly wind during 20:00~24:00. It indicates the influence of thermal power plant and industrial facilities, which was recognized as a major emission source during KORUS-AQ campaign. The diurnal variations of pollutants clearly showed the influence of land-sea breeze, in which OC showed good correlation between EC and O₃ in seabreeze. It is estimated to be the recirculation of pollutants in land-sea breeze cycle. This study suggests that in general, Anmyeondo station serves well as a background monitoring station. However, the variation in meteorological condition is so dynamic that it is primary factor to determine the concentrations of secondary species as well as primary pollutants at Anmyeondo station.

• 한국환경보건학회지
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• 제43권2호
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• pp.157-166
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• 2017

Objectives: Exposure to hazardous air pollutants could be affected by sociodemographic factors such as age, gender and more. Information on time spent in microenvironments has a critical role in exposure assessment. The purpose of this study was to analyze the exposure pathways which influence personal exposure through time-activity patterns and sociodemographic factors. Methods: A total of 379 subjects were collected from the second term of the Korean National Environmental Health Survey. A questionnaire survey in relation to sociodemographic factors and a time-activity diary were carried out for personal exposure to toluene. Focusing on personal exposure to toluene, factors affecting personal exposure were analyzed using multiple regression analysis. Results: Participants spent their time in an indoor house for $16.8{\pm}4.0hr$, workplace or school $2.3{\pm}3.5hr$, and other indoor $2.1{\pm}2.2hr$. Sociodemographic factors were significantly different among each personal exposure and microenvironment. Time of staying at an office turned out to be a main factor from point of exposure in exposure pathway using multiple regression analysis. As a result, this means that exposure may be different according to the time of staying in each microenvironment. Conclusions: Personal exposure to air pollutants might be decided by time-activity pattern indicating when, where, and which activities people pursue, as well as individual sociodemographic factors.