• Journal of the Society of Naval Architects of Korea
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• v.61 no.2
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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.

• Journal of Wetlands Research
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• v.22 no.1
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• pp.24-30
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• 2020

To assess the wetland systems' capability to reduce fine dust, we used an artificial wetland module of small-sized greenhouse (70cm W × 70cm L × 60cm H) which creates a closed system. Experiment was performed twice using four species in each experiment. Non-plantation, one species, or two species condition was created in each mesocosm. We measured air quality, primarily PM2.5 and PM10 at the initial open mesocosms and 1hr later since mesocosms were closed. The dry weight of vegetation was measured at the 2nd experiment. The decreased amount of PM2.5 and PM10 was 13.7±1.3 and 13.2±1.3 ㎍·m^-3hr^-1 in wetland condition and 15.0±1.4 and 13.8±1.5 ㎍·m^-3hr^-1 in dryland condition, respectively. In 2^nd experiment, the decreased amount of PM 2.5 and PM 10 in wetland condition was 13.7±1.3 and 9.2±1.5 ㎍·m^-3hr^-1, 15.0±1.4 and 8.8±1.4 ㎍·m^-3hr^-1 in dryland condition, respectively. Wetland showed higher removal effect due to its high productivity leading to more effective absorption of particulate matter. Furthermore, the aquatic characteristics of wetland system and high humidity helped purifying the air quality. This can be seen as another value of wetlands, which can be presented as one of the solutions to the problem of fine dust.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.19 no.4
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• pp.302-307
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• 2014

To examine the trophic ecology of the ascidian Styela clava in an aquaculture system of Korea, stable carbon and nitrogen isotopes were analyzed monthly in S. clava, coarse ($>20{\mu}m$, CPOM) and fine particulate organic matters ($0.7<<20{\mu}m$, FPOM). CPOM (means: $-18.5{\pm}1.2$‰, $9.3{\pm}0.7$‰) were significantly higher ${\delta}^{13}C$ and ${\delta}^{15}N$ values than those ($-20.5{\pm}1.5$‰, $8.4{\pm}0.5$‰) of FPOM. S. clava had mean ${\delta}^{13}C$ and ${\delta}^{15}N$ values of $-18.9({\pm}1.7)$‰ and $11.6({\pm}0.7)$‰, respectively. S. clava were more similar to seasonal variations in ${\delta}^{13}C$ and ${\delta}^{15}N$ values of FPOM than those of CPOM, suggesting that they rely largely on the FPOM as a dietary source. In addition, our results displayed that the relative importance between CPOM and FPOM as dietary source for the ascidians can be changed according to the availability of each component in ambient environment, probably reflecting their feeding plasticity due to non-selective feeding irrespective of particle size. Finally, our results suggest that dynamics of pico- and nano-size plankton (i.e., FPOM) as an available nutritional source to S. clava should be effectively assessed to maintain and manage their sustainable aquaculture production.

• Journal of Environmental Health Sciences
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• v.41 no.1
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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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• v.9 no.1
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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.

• Journal of Korean Society for Atmospheric Environment
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• v.33 no.5
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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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• v.48 no.1
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• pp.20-26
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• 2010

Water soluble organic and inorganic species are important components in atmospheric aerosol particles and may act as cloud condensation nuclei to indirectly affect the climate. To characterize organic and elemental carbon(OC and EC), water-soluble organic carbon(WSOC) and inorganic ionic species contents, daily $PM_{2.5}$ measurements were made during the wintertime at an urban site of Gwangju. Average concentrations of WSOC, $NO_3^-$, $SO_4^{2-}$ and $NH_4^+$, which are major components in the water-soluble fraction in PM2.5, are 2.11, 5.73, 3.51 and $3.31{\mu}g/m^3$, respectively, representing 12.0(2.9~23.9%), 21.0(12.9~37.6%), 11.6(2.5~25.9%) and 11.7%(3.8~18.6%) of the $PM_{2.5}$, respectively. Abundance of water soluble organic compounds ranged from 5.4 to 35.9% of total water soluble organic and inorganic components with a mean of 17.6%. Even though the sampling was performed during the winter, the average contributions of secondary OC and WSOC, as deduced from primary OC/EC(or WSOC/EC) ratio, were relatively high, accounting for 17.9%(0~44.4%) of the total OC and 11.2%(0.0~51.4%) of the total WSOC, respectively. During the sampling period, low $SO_4^{2-}/(SO_4^{2-}+SO_2$) ratio of 0.14(0.03~0.32) and relative humidity condition in the winter time suggest an possibility of impact of long-range transport and/or aqueous transformation processes such as metal catalyzed oxidation of sulfur, in-cloud processes, etc.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.24 no.1
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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.

• Journal of Environmental Science International
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• v.25 no.10
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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.

• Journal of Environmental Health Sciences
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• v.47 no.5
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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.