• Journal of environmental and Sanitary engineering
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• v.24 no.4
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• pp.1-26
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• 2009

We conclude the following with air pollution data measured from city measurement net administered and managed in Gwangju for the last 7 years from January in 2001 to December in 2007. In addition, some major statistics governed by Gwangju city and data administered by Gwangju as national official statistics obtained by estimating the amount of national air pollutant emission from National Institute of Environmental Research were used. The results are as follows ; 1. The distribution by main managements of air emission factory is the following ; Gwangju City Hall(67.8%) > Gwangsan District Office(13.6%) > Buk District Office(9.8%) > Seo District Office(5.5%) > Nam District Office(3.0%) > Dong District Office(0.3%) and the distribution by districts of air emission factory ; Buk District(32.8%) > Gwangsan District(22.4%) > Seo District(21.8%) > Nam District(14.9%) > Dong District(8.1%). That by types(Year 2004~2007 average) is also following ; Type 5(45.2%) > Type 4(40.7%) > Type 3(8.6%) > Type 2(3.2%) > Type 1(2.2%) and the most of them are small size of factory, Type 4 and 5. 2. The distribution by districts of the number of car registrations is the following ; Buk District(32.8%) > Gwangsan District(22.4%) > Seo District(21.8%) > Nam District(14.9%) > Dong District(8.1%) and the distribution by use of car fuel in 2001 ; Gasoline(56.3%) > Diesel(30.3%) > LPG(13.4%) > etc.(0.2%). In 2007, there was no ranking change ; Gasoline(47.8%) > Diesel(35.6%) > LPG(16.2%) >etc.(0.4%). The number of gasoline cars increased slightly, but that of diesel and LPG cars increased remarkably. 3. The distribution by items of the amount of air pollutant emission in Gwangju is the following; CO(36.7%) > NOx(32.7%) > VOC(26.7%) > SOx(2.3%) > PM-10(1.5%). The amount of CO and NOx, which are generally generated from cars, is very large percentage among them. 4. The distribution by mean of air pollutant emission(SOx, NOx, CO, VOC, PM-10) of each county for 5 years(2001~2005) is the following ; Buk District(31.0%) > Gwangsan District(28.2%) > Seo District(20.4%) > Nam District(12.5%) > Dong District(7.9%). The amount of air pollutant emission in Buk District, which has the most population, car registrations, and air pollutant emission businesses, was the highest. On the other hand, that of air pollutant emission in Dong District, which has the least population, car registrations, and air pollutant emission businesses, was the least. 5. The average rates of SOx for 5 years(2001~2005) in Gwangju is the following ; Non industrial combustion(59.5%) > Combustion in manufacturing industry(20.4%) > Road transportation(11.4%) > Non-road transportation(3.8%) > Waste disposal(3.7%) > Production process(1.1%). And the distribution of average amount of SOx emission of each county is shown as Gwangsan District(33.3%) > Buk District(28.0%) > Seo District(19.3%) > Nam District(10.2%) > Dong District(9.1%). 6. The distribution of the amount of NOx emission in Gwangju is shown as Road transportation(59.1%) > Non-road transportation(18.9%) > Non industrial combustion(13.3%) > Combustion in manufacturing industry(6.9%) > Waste disposal(1.6%) > Production process(0.1%). And the distribution of the amount of NOx emission from each county is the following ; Buk District(30.7%) > Gwangsan District(28.8%) > Seo District(20.5%) > Nam District(12.2%) > Dong District(7.8%). 7. The distribution of the amount of carbon monoxide emission in Gwangju is shown as Road transportation(82.0%) > Non industrial combustion(10.6%) > Non-road transportation(5.4%) > Combustion in manufacturing industry(1.7%) > Waste disposal(0.3%). And the distribution of the amount of carbon monoxide emission from each county is the following ; Buk District(33.0%) > Seo District(22.3%) > Gwangsan District(21.3%) > Nam District(14.3%) > Dong District(9.1%). 8. The distribution of the amount of Volatile Organic Compound emission in Gwangju is shown as Solvent utilization(69.5%) > Road transportation(19.8%) > Energy storage & transport(4.4%) > Non-road transportation(2.8%) > Waste disposal(2.4%) > Non industrial combustion(0.5%) > Production process(0.4%) > Combustion in manufacturing industry(0.3%). And the distribution of the amount of Volatile Organic Compound emission from each county is the following ; Gwangsan District(36.8%) > Buk District(28.7%) > Seo District(17.8%) > Nam District(10.4%) > Dong District(6.3%). 9. The distribution of the amount of minute dust emission in Gwangju is shown as Road transportation(76.7%) > Non-road transportation(16.3%) > Non industrial combustion(6.1%) > Combustion in manufacturing industry(0.7%) > Waste disposal(0.2%) > Production process(0.1%). And the distribution of the amount of minute dust emission from each county is the following ; Buk District(32.8%) > Gwangsan District(26.0%) > Seo District(19.5%) > Nam District(13.2%) > Dong District(8.5%). 10. According to the major source of emission of each items, that of oxides of sulfur is Non industrial combustion, heating of residence, business and agriculture and stockbreeding. And that of NOx, carbon monoxide, minute dust is Road transportation, emission of cars and two-wheeled vehicles. Also, that of VOC is Solvent utilization emission facilities due to Solvent utilization. 11. The concentration of sulfurous acid gas has been 0.004ppm since 2001 and there has not been no concentration change year by year. It is considered that the use of sulfurous acid gas is now reaching to the stabilization stage. This is found by the facts that the use of fuel is steadily changing from solid or liquid fuel to low sulfur liquid fuel containing very little amount of sulfur element or gas, so that nearly no change in concentration has been shown regularly. 12. Concerning changes of the concentration of throughout time, the concentration of NO has been shown relatively higher than that of $NO_2$ between 6AM~1PM and the concentration of $NO_2$ higher during the other time. The concentration of NOx(NO, $NO_2$) has been relatively high during weekday evenings. This result shows that there is correlation between the concentration of NOx and car traffics as we can see the Road transportation which accounts for 59.1% among the amount of NOx emission. 13. 49.1~61.2% of PM-10 shows PM-2.5 concerning the relationship between PM-10 and PM-2.5 and PM-2.5 among dust accounts for 45.4%~44.5% of PM-10 during March and April which is the lowest rates. This proves that particles of yellow sand that are bigger than the size $2.5\;{\mu}m$ are sent more than those that are smaller from China. This result shows that particles smaller than $2.5\;{\mu}m$ among dust exist much during July~August and December~January and 76.7% of minute dust is proved to be road transportation in Gwangju.

• Asian Journal of Atmospheric Environment
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• v.8 no.1
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• pp.35-47
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• 2014

The purpose of the study is to evaluate the pollution level (gaseous and particle phase) in the public facilities for the PAHs, non-regulated materials, forecast the risk level by the health risk assessment (HRA) and propose the guideline level. PAH assessments through sampling of particulate matter of diameter < 2.5 ${\mu}m$ ($PM_{2.5}$). The user and worker exposure scenario for the PAHs consists of 24-hour exposure scenario (WIES) assuming the worst case and the normal exposure scenario (MIES) based on the survey. This study investigated 20 PAH substances selected out of 32 substances known to be carcinogenic or potentially carcinogenic. The risk assessment applies major toxic equivalency factor (TEF) proposed from existing studies and estaimates individual Excess Cancer Risk (ECR). The study assesses the fine dusts ($PM_{2.5}$) and the exposure levels of the gaseous and particle PAH materials for 6 spots in each 8 facility, e.g. underground subway stations, child-care facilities, elderly care facilities, super market, indoor parking lot, terminal waiting room, internet caf$\acute{e}$ (PC-rooms), movie theater. For internet caf$\acute{e}$ (PC-rooms) in particular, that marks the highest $PM_{2.5}$ concentration and the average concentration of 10 spots (2 spots for each cafe) is 73.3 ${\mu}g/m^3$ (range: 6.8-185.2 ${\mu}g/m^3$). The high level of $PM_{2.5}$ seen in internet cafes was likely due to indoor smoking in most cases. For the gaseous PAHs, the detection frequency for 4-5 rings shows high and the elements with 6 rings shows low frequency. For the particle PAHs, the detection frequency for 2-3 rings shows low and the elements with 6 rings show high frequency. As a result, it is investigated that the most important PAHs are the naphthalene, acenaphthene and phenanthrene from the study of Kim et al. (2013) and this annual study. The health risk assessment demonstrates that each facility shows the level of $10^{-6}-10^{-4}$. Considering standards and local source of pollution levels, it is judged that the management standard of the benzo (a)pyrene, one of the PAHs, shall be managed with the range of 0.5-1.2 $ng/m^3$. Smoking and ventilation were considered as the most important PAHs exposure associated with public facility $PM_{2.5}$. This study only estimated for inhalation health risk of PAHs and focused on the associated cancer risk, while multiple measurements would be necessary for public health and policy.

• Korean Journal of Ecology and Environment
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• v.38 no.3 s.113
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• pp.372-381
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• 2005

This study was conducted to test the efficiency of water quality improvement using the dissolved air flotation (DAF) technique in a shallow eutrophic reservoir. The application of DAF was followed by the addition of a chemical coagulant (poly aluminum chloride; PAC). The experiment was conducted in the mesocosm scale (wide ${\times}$ length ${\times}$ depth: 6 m ${\times}$ 6 m ${\times}$ 3 m). Suspended solids (SS) and volatile SS (VSS) concentration decreased by 54 ${\sim}$ 71% and 57 ${\sim}$ 79% of the initial concentrations, respectively. Total phosphorus and Chl- a concentration also decreased by 74 ${\sim}$ 92% and 54 ${\sim}$ 98%, respectively. BOD decreased by>86% while COD decrease ranged 29 ${\sim}$ 63%. Dissolved inorganic P (DIP) and dissolved total P (DTP) concentration decreased by 34 ${\sim}$ 88% and 62 ${\sim}$ 88%, respectively. After DAF application further onto the sediment, DIP-release rates from the sediment decreased by 17% (0.82 ${\to}$ 0.68 mg $m^{-2}$$day^{-1}$ in the oxic condition and 23% (2.27 ${\to}$ 1.76 mg $m^{-2}$$day^{-1}$) in the anoxic condition, compared to the release rate from the untreated sediment. DTP-release rate from both the oxic and anoxic sediments also decreased by 33% (5.62 ${\to}$ 3.78 mg $m^{-2}$$day^{-1}$) and 20% (6.23 ${\to}$ 4.99 mg $m^{-2}$$day^{-1}$), respectively. These results suggest that the DAF application both to the water column and onto the sediment be effective to improve water quality by removing particulate matters in the water column as well as reducing P-release from the sediment.

• Journal of Korean Society of Transportation
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• v.34 no.5
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• pp.377-393
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• 2016

Vehicle emissions have been known as a critical factor to give a negative impact on the public health. In particular, particulate matters(PM) and NOx are highly related with respiratory diseases such as asthma. This study aimed at analyzing spatio-temporal patterns of PM and NOx generated from urban freeway traffic. MOVES, which is a well-known emission analysis tool presented by US Environmental Protection Agency(EPA), was applied to estimate PM and NOx based on traffic volume and speed data obtained from Seoul Outer Ring Expressway during January~June, 2012. K-means clustering analysis was used for categorizing the Level of Vehicle Emissions(LOVE) to support more systematical identification of the significance of emissions. Then, spatio-temporal analyses of estimated emissions were conducted by LOVE. Finally, this study proposed a set of strategies to reduce both PM and NOx to enhance public health based on analysis results.

• Journal of Environmental Impact Assessment
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• v.27 no.6
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• pp.717-726
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• 2018

PM(Particulate Matter) cause serious diseases of air pollution. Most of the studies have analyzed local distribution trends using satellite images or modeling techniques. However,the method using the spatial interpolation method based on the meteorological value is insufficient in Korea. In this study, monthly spatial distribution of $PM_{10}$ and $PM_{2.5}$ in January, February, March, and April of 2018 Seoul Metropolitan City were analyzed based on 39 PM monitoring networks. In addition, a distribution map showing the difference between $PM_{10}$ and $PM_{2.5}$ was based on the distribution obtained through this study. The regions of high $PM_{10}$ and $PM_{2.5}$ emissions were selected. In addition, the correlation between $PM_{10}$ and $PM_{2.5}$ was confirmed through the distribution map. This study analyzed the spatial distribution variation results of analyzing $PM_{10}$ and $PM_{2.5}$ in Seoulthrough spatial analysis technique. As a result of this study, it was confirmed that $PM_{10}$ shows high measured value on the roadside measurement station.

• The Korea Journal of Herbology
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• v.37 no.3
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• pp.29-39
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• 2022

Objective : This study is aimed to evaluate the protective effects of Rehmanniae Radix, Mori Folium, and Liriopie Tuber mixture (RML) on lung injury of Particulate matter less than 10 um in diameter and diesel exhaust particles (PM10D) mice model. Methods : To investigate the anti-inflammatory activity of RML, PM10D was diluted in aluminum hydroxide (Alum) in 7-week-old male mice and induced by Intra-Nazal-Tracheal (INT) injection method. Animal experiments were divided into 5 groups. Nor (normal mice), CTL (PM10D-induced mice with the administration of distilled water), DEXA (PM10D-induced mice with the administration of 3 mg/kg Dexamethasone), RML 100 (PM10D-induced mice treated with RML 100 mg/kg weight), and RML 200 (PM10D-induced mice treated with RML 200 mg/kg body weight). After 11 days administration, mice were sacrificed and inflammation-related immune cells in broncho-alveolar lavage fluid (BALF) were analyzed. Inflammation-related biomarkers were also analyzed in blood and lungs. Lung tissue was observed through histological examination. Results : In the PM10D induced model, the PML showed decreases in CXCL-1 and IL-17A in BALF. Expression of inflammatory cytokines and cough-related mRNA genes was significantly decreased in serum and lung tissue. The mixture treatment of RML significantly improved the immune related cells in the serum. In addition, histological observations showed a tendency to decrease the severity of lung injury. Conclusions : Overall, these results confirmed the respiratory protective effect of the RML mixture in a model of lung injury induced by air pollution (PM10+DEP), suggesting that it is a potential treatment for respiratory damage.

• Journal of Environmental Health Sciences
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• v.49 no.4
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• pp.218-227
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• 2023

Background: Since 2019, the Ministry of Environment has implemented a seasonal fine dust management system from December to March, targeting high PM_2.5 levels with the aim of reducing PM_2.5 concentrations and protecting public health. The focus of improving the seasonal management system lies in the atmospheric PM_2.5 levels. Considering the primary goal of protecting public health, it is necessary to analyze the policy effects from an exposure perspective rather than a concentration-based approach. Objectives: This study aims to quantitatively assess the improvement of indoor PM_2.5 levels and the health impacts of the seasonal management system by comparing the periods before and during its implementation in residential environments. Methods: PM_2.5 concentrations within residential environments in a metropolitan area were measured using an optical particle counter (IAQ-C7, K-weather, Ltd, Korea) at one-minute intervals during the pre-implementation period (November 21~25, 2022) and during the implementation period (December 19~23, 2022). Based on the measured PM_2.5 concentrations, a quantitative evaluation of cancer and mortality risks was conducted according to age and gender. Results: The results of comparing indoor and outdoor PM_2.5 concentrations before and during the implementation of the seasonal management system showed a decrease of approximately 56.6% and 47.9%, respectively. Health risk assessments revealed that both the safety-limit-based and safety-target-based Hazard Quotients (HQ) exceeded the threshold of 0.1 for children under 19 years of age, both before and after the implementation. The mortality risk decreased by approximately 47.9% after the implementation, with children aged 0-9 showing the highest mortality risk at 0.9%. Conclusions: The findings of this study confirmed the positive health impacts of the seasonal management system across all age groups, particularly children under 19 who are more vulnerable to fine dust exposure.

• Korean Chemical Engineering Research
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• v.57 no.1
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• pp.90-104
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• 2019

In this study, CALPUFF modeling was performed, using a real surface and upper air meterological data to predict trustworthy modeling-results. Pollutant-releases from windscreen chambers of enclosed poultry farms, P1 and P2, and from a open poultry farm, P3, and their diffusing behavior were modeled by CALPUFF modeling with volume sources as well as by finally-adjusted CALPUFF modeling where a linear velocity of upward-exit gas averaged with the weight of each directional-emitting area was applied as a model-linear velocity ($u^M_y$) at a stack, with point sources. In addition, based upon the scenario of poultry farm-releasing odor and particulate matter (PM) removal efficiencies of 0, 20, 50 and 80% or their corresponding emission rates of 100, 80, 50 and 20%, respectively, CALPUFF modeling was performed and concentrations of odor and PM were predicted at the region as a discrete receptor where civil complaints had been frequently filed. The predicted concentrations of ammonia, hydrogen sulfide, $PM_{2.5}$ and $PM_{10}$ were compared with those required to meet according to the offensive odor control law or the atmospheric environmental law. Subsequently their required removal efficiencies at poultry farms of P1, P2 and P3 were estimated. As a result, a priori assumption that pollutant concentrations at their discrete receptors are reduced by the same fraction as pollutant concentrations at P1, P2 and P3 as volume source or point source, were controlled and reduced, was proven applicable in this study. In case of volume source-adopted CALPUFF modeling, its required removal efficiencies of P1 compared with those of point source-adopted CALPUFF modeling, were predicted similar each other. However, In case of volume source-adopted CALPUFF modeling, its required removal efficiencies of both ammonia and $PM_{10}$ at not only P2 but also P3 were predicted higher than those of point source-adopted CALPUFF modeling. Nonetheless, the volume source-adopted CALPUFF modeling was preferred as a safe approach to resolve civil complaints. Accordingly, the required degrees of pollution prevention against ammonia, hydrogen sulfide, $PM_{2.5}$ and $PM_{10}$ at P1 and P2, were estimated in a proper manner.

• Analytical Science and Technology
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• v.27 no.1
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• pp.1-10
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• 2014

The $PM_{10}$ and $PM_{2.5}$ samples were collected at Gosan Site of Jeju Island, and analyzed, in order to investigate the size distribution and pollution characteristics of their components. $NH{_4}{^+}$, nss-$SO{_4}^{2-}$, $K^+$, and $CH_3COO^-$ were mostly existed in fine particles. Meanwhile, $NO{_3}{^-}$ was distributed in both fine and coarse particles, and $Na^+$, $Cl^-$, $Mg^{2+}$, nss-$Ca^{2+}$ were rich in coarse particle mode. The concentrations of nss-$Ca^{2+}$ and $NO{_3}{^-}$ were increased 36.7 and 3.2 times in coarse particles, and 15.0 and 3.1 times in fine particles during the Asian Dust periods. Especially, the concentrations of crustal elemental species such as Al, Fe, Ca, K, Mg, Ti, Mn, Sr, Ba were highly increased for those periods. In the haze events, the concentrations of secondary air pollutants were increased 1.3~2.6 and 1.5~4.2 times in coarse and fine particles, respectively. Moreover, the remarkable increase of $NO{_3}{^-}$ concentration was also observed in fine particle mode. The factor analysis showed that the composition of coarse particles was influenced mainly by marine sources, followed by soil and anthropogenic sources. On the other hand, the fine particles were influenced by anthropogenic sources, followed by marine and soil sources.