• 대한조선학회논문집
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• 제61권2호
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• pp.135-142
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• 2024

There is a lot of concern around the world about air pollution from ships. The majority of air pollution from ships comes from fuel combustion. The combustion process produces various air pollutants such as carbon monoxide (CO), carbon dioxide (CO₂), nitrogen oxides (NOx), sulfur oxides (SOx), and particulate matter (PM), each of which has adverse effects on people and is a major environmental problem. To prevent this, the International Maritime Organization (IMO) has strengthened the regulation of pollutant emissions through the Convention for the Prevention of Marine Pollution. This paper discusses the types of air pollutants emitted by ships, their current status, and the latest technologies to reduce emissions of NOx and SOx.

• 한국습지학회지
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• 제22권1호
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• pp.24-30
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• 2020

본 연구에서는 습지 조성 및 습지 내 식물에 따른 미세먼지 저감 능력 규명을 통해 습지생태계의 가치에 대하여 새로운 시각의 해석을 제공하고자 하였다. 소형 간이온실(70cm W × 70cm L × 60cm H)로 닫힌계를 형성하였으며, 간이온실 내 메조코즘에 일정 수위가 유지되는 습지(W) 혹은 건조 상태를 유지하는 육상(L) 조건을 조성하였다. 육상과 습지 조건 각각에 식물종 미식재, 단일종 식재 그리고 두 종 혼합 식재의 총 8가지 조건을 4반복씩 조성하였다. 열린계의 메조코즘에서 초기 대기질과 닫힌계로의 전환 1시간 경과한 후의 대기질을 측정하여 공기 정화능을 확인하였다. 각 실험구의 대기질로서 PM2.5, PM10농도를 중점적으로 측정하였으며, 2차 실험에서는 식물체의 건중량을 측정하였다. 닫힌계 형성 1시간 후 습지 환경에서의 PM2.5와 PM10의 감소량은 1차 실험에서 각각 13.7±1.3, 15.0±1.4 ㎍·m^-3hr^-1로 나타났으며, 2차 실험에서는 각각 10.5±2.1, 11.2±2.2 ㎍·m^-3hr^-1로 나타났다. 육지 환경에서의 미세먼지 감소량은 1차 실험에서 각각 13.2±1.3, 13.8±1.5 ㎍·m^-3hr^-1로 나타났으며, 2차 실험에서는 각각 9.2±1.5, 8.8±1.4 ㎍·m^-3hr^-1로 나타났다. 이는 습지의 높은 생산성으로 인한 식물의 생장으로 식물의 조직에 미세먼지 흡착을 통한 저감이나 증산작용을 통한 수분, 또 습지 자체의 수생태계적 특성을 통한 미세먼지 저감 효과가 드러난 것으로 여겨진다. 따라서 습지의 미세먼지 저감 능력은 습지의 또 다른 가치로 볼 수 있으며 이는 미세먼지 문제에 대한 해결방안 중의 하나로 제시될 수 있을 것이다.

• 한국해양학회지:바다
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• 제19권4호
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• pp.302-307
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• 2014

2008년 4월에서 2009년 1월 사이에 진동만 미더덕의 섭식 생태를 설명하기 위하여 $20{\mu}m$ 이상(coarse particulate organic matter, CPOM) 그리고 $0.7{\mu}m$ 이상 $20{\mu}m$ 이하(fine POM)의 크기가 나누어진 각각의 부유입자유기물과 미더덕에 대한 ${\delta}^{13}C$ 과 ${\delta}^{15}N$ 값의 월별 변동을 비교 분석하였다. CPOM과 FPOM의 ${\delta}^{13}C$ 및 ${\delta}^{15}N$을 월별로 비교한 결과 전체적으로 CPOM(평균 $-18.5{\pm}1.2$‰, $9.3{\pm}0.7$‰)이 FPOM(평균 $-20.5{\pm}1.5$‰, $8.4{\pm}0.5$‰)에 비해 유의하게 높은 값을 나타내었다. 미더덕의 ${\delta}^{13}C$과 ${\delta}^{15}N$ 값은 각각 평균 $-18.9({\pm}1.7)$‰과 $11.6({\pm}0.7)$‰로 나타났는데, 이와 같은 비값들은 CPOM 보다는 FPOM의 월별 변동과 비슷한 경향을 보여 이들이 CPOM에 비하여 상대적으로 FPOM에 더 높은 영양 의존도를 가진다는 것을 강하게 시사해 주었다. 그러나 미더덕의 먹이원으로서 CPOM과 FPOM의 상대적인 중요성은 시기에 따른 각 요소의 가용성(availability)에 크게 의존하는 것으로 나타났는데, 이와 같은 결과는 부유입자물질의 크기에 관계없이 미더덕에 의한 비선택적 먹이 섭식을 잘 반영하는 듯 하였다. 본 연구 결과는 미더덕의 지속적인 양식생산을 유지하기 위해 가용 먹이원으로서 식물플랑크톤과 함께 미소 부유입자유기물의 유용성을 고려해야함을 잘 나타내 주었다.

• 한국환경보건학회지
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• 제41권1호
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• pp.11-16
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• 2015

Objectives: This study assessed the impact of the smoke-free law on secondhand smoke exposure in computer game rooms by measuring concentrations of particulate matter smaller than $2.5{\mu}m$($PM_{2.5}$). Methods: Indoor $PM_{2.5}$ concentrations were measured in 56 (during the smoke-free guidance period) and 118 computer game rooms (after the law went into effect) in four cities (Seoul, Cheonan, Daegu and Kunsan) in Korea. The number of smokers in the computer game rooms was also counted every five minutes. Results: Although a smoking ban had been implemented nationally, smoking was observed in 47% of the computer game rooms. Smoking density decreased from 1.62 persons per $100m^3$ during the guidance period to 0.32 persons per $100m^3$ after the smoke-free law. There is no statistically significant difference of $PM_{2.5}$ concentrations before and after the smoking ban. The $PM_{2.5}$ concentration was two times higher than the US NAAQS of $35{\mu}g/m^3$. The $PM_{2.5}$ concentration in computer game rooms without smokers was two times higher than the outdoor concentration. Conclusion: The smoke-free law in computer game rooms was complied with, even after the guidance period, in Korea. Indoor $PM_{2.5}$ concentration after smoke-free law implementation was high due to this non-compliance. High $PM_{2.5}$ concentration in computer game rooms without smokers might be due to smoking booths. The complete prohibition of smoking in computer game rooms should be implemented to protect patrons from secondhand smoke exposure.

• Asian Journal of Atmospheric Environment
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• 제9권1호
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• pp.66-77
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• 2015

In order to survey the seasonal variation of the chemical composition of particulate matter of $2.5{\mu}m$ or less ($PM_{2.5}$), $PM_{2.5}$ was sampled from 8 February 2013 to 31 March 2014 in an industrial area of Chiba Prefecture, Japan. Chemical measurements of the sample included: ionic components ($Na^+$, $NH_4{^+}$, $Ca^{2+}$, $Mg^{2+}$, $K^+$, $Cl^-$, $NO_3{^-}$ and $SO_4{^{2-}}$), carbonaceous components - organic carbon (OC) and elemental carbon (EC), and water-soluble organic carbon (WSOC). Also, secondary organic carbon (SOC) was measured based using the EC tracer method, and char-EC and soot-EC were calculated from the analytical results. The data obtained were interpreted in terms of temporal variation. Of the overall mean value of $PM_{2.5}$ mass concentration obtained during the study period, ionic components, OC and EC accounted for 45.3%, 19.7%, and 8.0%, respectively. $NO_3{^-}$ showed a unique seasonal distribution pattern due to a dependence on temperature and absolute humidity. It was estimated that an approximate temperature of $14^{\circ}C$, and absolute humidity of $7g/m^3$ were critical for the reversible reaction of $NH_4NO_3(p){\leftrightharpoons}NH_3(g)+HNO_3(g)$. The amount of OC and EC contributing to the monthly $PM_{2.5}$ mass concentration was higher in autumn and winter compared to spring and summer. This result could be attributed to the impact of burning biomass, since WSOC and the ratio of char-EC/soot-EC showed a similar pattern during the corresponding period. From the comparison of monthly WSOC/OC values, a maximum ratio of 83% was obtained in August (summer). The WSOC and estimated SOC levels derived from the EC tracer method correlated (R=0.77) in summer. The high occurrence of WSOC during summer was mainly due to the formation of SOC by photochemical reactions. Through long-term observation of $PM_{2.5}$ chemical components, we established that the degree to which the above-mentioned factors influence $PM_{2.5}$ composition, fluctuates with seasonal changes.

• 한국대기환경학회지
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• 제33권5호
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• pp.445-457
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• 2017

In this study, we developed an approach to better account for uncertainties in estimated contributions from fine particulate matter ($PM_{2.5}$) modeling. Our approach computes a Concentration Correction Factor (CCF) which is a ratio of observed concentrations to baseline model concentrations. We multiply modeled direct contribution estimates with CCF to obtain revised contributions. Overall, the modeling system showed reasonably good performance, correlation coefficient R of 0.82 and normalized mean bias of 2%, although the model underestimated some PM species concentrations. We also noticed that model biases vary seasonally. We compared contribution estimates of major source sectors before and after applying CCFs. We observed that different source sectors showed variable magnitudes of sensitivities to the CCF application. For example, the total primary $PM_{2.5}$ contribution was increased $2.4{\mu}g/m^3$ or 63% after the CCF application. Out of a $2.4{\mu}g/m^3$ increment, line sources and area source made up $1.3{\mu}g/m^3$ and $0.9{\mu}g/m^3$ which is 92% of the total contribution changes. We postulated two major reasons for variations in estimated contributions after the CCF application: (1) monthly variability of unadjusted contributions due to emission source characteristics and (2) physico-chemical differences in environmental conditions that emitted precursors undergo. Since emissions-to-$PM_{2.5}$ concentration conversion rate is an important piece of information to prioritize control strategy, we examined the effects of CCF application on the estimated conversion rates. We found that the application of CCFs can alter the rank of conversion efficiencies of source sectors. Finally, we discussed caveats of our current approach such as no consideration of ion neutralization which warrants further studies.

• Korean Chemical Engineering Research
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• 제48권1호
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• pp.20-26
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• 2010

수용성 유기 및 무기성분은 대기 에어로졸 입자의 중요한 구성성분들이며 간접적으로 기후에 영향을 미치는 구름응결핵으로 작용한다. 유기 및 원소탄소(organic and elemental carbon, OC 및 EC) 및 수용성 유기탄소(water soluble OC, WSOC) 및 이온성분농도를 조사하기 위하여 광주지역에서 24시간 기준의 미세입자($PM_{2.5}$)를 측정하였다. 측정기간 중 $PM_{2.5}$ 수용성 분율의 주요성분인 WSOC, $NO_3^-$, $SO_4^{2-}$ 및 $NH_4^+$의 평균농도는 각각 2.11, 5.73, 3.51 및 $3.31{\mu}g/m^3$ 이었으며, $PM_{2.5}$ 농도의 12.0(2.9~23.9%), 21.0(12.9~37.6%), 11.6(2.5~25.9%), 및 11.7%(3.8~18.6%)를 차지하였다. 총 수용성 성분(유기+무기) 중 WSOC 화합물이 차지하는 분율은 평균 17.6%(5.4~35.9%)이었다. EC 추적자 기법을 이용해 평가한 2차 OC 및 WSOC 농도는 각각 평균적으로 0.78 및 $0.34{\mu}g/m^3$이었으며, 전체 OC 및 WSOC 중의 평균 17.9%(범위: 0~44.4%) 및 평균 11.2%(범위: 0~51.4%)를 차지하였다. 광주지역 겨울철에 측정한 $SO_4^{2-}$ 입자는 국지적인 기상산화반응보다는 장거리 이동 또는 수용액 변환과정에 의한 영향, 구름 내 변환과정 등이 황산염 입자 생성에 중요하게 작용했을 것으로 판단한다.

• 한국산업보건학회지
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• 제24권1호
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• pp.65-73
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• 2014

Objectives: The purposes of this study are to investigate workers' exposures to respirable particles generated in taconite mines and to compare two metric methods for mass concentrations using direct-reading instruments. Methods: Air monitorings were conducted at six mines where subjects have been exposed primarily to particulate matters in crushing, concentrating, and pelletizing processes. Air samples were collected during 4 hours of the entire work shift for similarly exposure groups(SEGs) of nine jobs(N=37). Following instruments were employed to evaluate the workplace: a nanoparticle aerosol monitor(particle size range; 10-1000 nm, unit: ${\mu}m^2/cc$, Model 9000, TSI Inc.); DustTrak air monitors($PM_{10}$, $PM_{2.5}$, unit: $mg/m^3$, Model 8520, TSI Inc.); a condensation particle counter(size range; 20-1000 nm, unit: #/cc, P-Trak 8525, TSI Inc.); and an optical particle counter(particle number by size range $0.3-25{\mu}m$, unit: #/cc, Aerotrak 9306, TSI Inc.). Results: The highest airborne concentration among SEGs was for furnace operator followed by pelletizing maintenance workers in number of particle and surface area, but not in mass concentrations. The geometric means of $PM_{2.5}$ by the DustTrak and the Ptrak/Aerotrak were $0.04{\mu}m$(GSD 2.52) and $0.07{\mu}m$(GSD 2.60), respectively. Also, the geometric means of RPM by the DustTrak and the Ptrak/Aerotrak were $0.16{\mu}m$(GSD 2.24) and $0.32{\mu}m$(GSD 3.24), respectively. The Pearson correlation coefficient for DustTrak $PM_{2.5}$ and Ptrak/Aerotrak $PM_{2.5}$ was 0.56, and that of DustTrak RPM and Ptrak/Aerotrak RPM was 0.65, indicating a moderate positive association between the two sampling methods. Surface area and number concentration were highly correlated($R^2$ = 0.80), while $PM_{2.5}$ and RPM were also statistically correlated each other($R^2$ = 0.79). Conclusions: The results suggest that it is possible to measure airborne particulates by mass concentrations or particle number concentrations using real-time instruments instead of using the DustTrak Aerosol monitor that monitor mass concentrations only.

• 한국환경과학회지
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• 제25권10호
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• pp.1349-1368
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• 2016

Concentrations of fine particulate matter ($PM_{2.5}$) and several of its particle constituents measured outside homes in Houston, Texas, and Los Angeles, California, were characterized using multiple regression analysis with proximity to point and mobile sources and meteorological factors as the independent variables. $PM_{2.5}$ mass and the concentrations of organic carbon (OC), elemental carbon (EC), benzo-[a]-pyrene (BaP), perylene (Per), benzo-[g,h,i]-perylene (BghiP), and coronene (Cor) were examined. Negative associations of wind speed with concentrations demonstrated the effect of dilution by high wind speed. Atmospheric stability increase was associated with concentration increase. Petrochemical source proximity was included in the EC model in Houston. Area source proximity was not selected for any of the $PM_{2.5}$ constituents' regression models. When the median values of the meteorological factors were used and the proximity to sources varied, the air concentrations calculated using the models for the eleven $PM_{2.5}$ constituents outside the homes closest to influential highways were 1.5-15.8 fold higher than those outside homes furthest from the highway emission sources. When the median distance to the sources was used in the models, the concentrations of the $PM_{2.5}$ constituents varied 2 to 82 fold, as the meteorological conditions varied over the observed range. We found different relationships between the two urban areas, illustrating the unique nature of urban sources and suggesting that localized sources need to be evaluated carefully to understand their potential contributions to $PM_{2.5}$ mass and its particle constituents concentrations near residences, which influence baseline indoor air concentrations and personal exposures. The results of this study could assist in the appropriate design of monitoring networks for community-level sampling and help improve the accuracy of exposure models linking emission sources with estimated pollutant concentrations at the residential level.

• 한국환경보건학회지
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• 제47권5호
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• pp.410-424
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• 2021

Background: Subway stations have the characteristics of being located underground and are a representative public-use facility used by an unspecified number of people. As concerns about indoor air quality (IAQ) increase, various management measures are being implemented. However, there are few systematic studies and cases of long-term continuous measurement of underground station air quality. Objectives: The purpose of this study is to analyze changes and factors influencing IAQ in subway stations through real-time continuous long-term measurement using IoT-based IAQ sensing equipment, and to evaluate the IAQ improvement effect of a bio-filter system. Methods: The IAQ of a subway station in Seoul was measured using IoT-based sensing equipment. A bio-filter system was installed after collecting the background concentrations for about five months. Based on the data collected over about 21 months, changes in indoor air quality and influencing factors were analyzed and the reduction effect of the bio-filter system was evaluated. Results: As a result of the analysis, PM₁₀, PM_2.5, and CO₂ increased during rush hour according to the change in the number of passengers, and PM₁₀ and PM_2.5 concentrations were high when a PM warning/watch was issued. There was an effect of improving IAQ with the installation of the bio-filter system. The reduction rate of a new-bio-filter system with improved efficiency was higher than that of the existing bio-filter system. Factors affecting PM_2.5 in the subway station were the outdoor PM_2.5, platform PM_2.5, and the number of passengers. Conclusions: The IAQ in a subway station is affected by passengers, ventilation through the air supply and exhaust, and the spread of particulate matter generated by train operation. Based on these results, it is expected that IAQ can be efficiently improved if a bio-filter system with improved efficiency is developed in consideration of the factors affecting IAQ and proper placement.