• Journal of Environmental Health Sciences
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• v.49 no.3
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• pp.149-158
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• 2023

Background: Injury is one of the major health problems in South Korea. Few studies have evaluated both intentional and unintentional injury when investigating the association between exposure to air pollutants and injury. Objectives: We aimed to explore the association between short-term exposure to ambient air pollution and years of life lost (YLLs) due to injury. Methods: Data on daily YLLs for 2002~2019 were obtained from the the Death Statistics Database of the Korean National Statistical Office. This study estimated short-term exposure to particulate matter with an aerodynamic diameter of <10 ㎛ (PM₁₀), particulate matter with an aerodynamic diameter of <2.5 ㎛ (PM_2.5), sulfur dioxide (SO₂), nitrogen dioxide (NO₂), carbon monoxide (CO), and ozone (O₃). This time series study was conducted using a generalized additive model (GAM) assuming a Gaussian distribution. We also evaluated a delayed effect of ambient air pollution by constructing a lag structure up to seven days. The best-fitting lag was selected based on smallest generalized cross validation (GCV) value. To explore effect modification by intentionality of injury (i.e., intentional injury [self-harm, assault] and unintentional injury), we conducted stratified subgroup analyses. Additionally, we stratified unintentional injury by mechanism (traffic accident, fall, etc.). Results: During the study period, the average daily YLLs due to injury was 307.5 years. In the intentional injury, YLLs due to self-harm and assault showed positive association with air pollutants. In the unintentional injury, YLLs due to fall, electric current, fire and poisoning showed positive association with air pollutants, whereas YLLs due to traffic accident, mechanical force and drowning/submersion showed negative associations with air pollutants. Conclusions: Injury is recognized as preventable, and effective strategies to create a safe society are important. Therefore, we need to establish strategies to prevent injury and consider air pollutants in this regard.

• Journal of Korean Society for Atmospheric Environment
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• v.28 no.5
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• pp.571-580
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• 2012

Epidemiologic studies of air pollution need accurate exposure assessments at unmonitored locations. A land use regression (LUR) model has been used successfully for predicting traffic-related pollutants, although its application has been limited to Europe, North America, and a few Asian region. Therefore, we modeled traffic-related pollutants by LUR then examined whether LUR models could be constructed using a regulatory monitoring network in Metropolitan area in Korea. We used the annual-mean nitrogen dioxide ($NO_2$) in 2010 in the study area. Geographic variables that are considered to predict traffic-related pollutants were classified into four groups: road type, traffic intensity, land use, and elevation. Using geographical variables, we then constructed a model to predict the monitored levels of $NO_2$. The mean concentration of $NO_2$ was 30.71 ppb (standard deviation of 5.95) respectively. The final regression model for the $NO_2$ concentration included five independent variables. The LUR models resulted in $R^2$ of 0.59. The mean concentration of $NO_2$ of elementary schools was 34.04 ppb (standard deviation of 5.22) respectively. The present study showed that even if we used regulatory monitoring air quality data, we could estimate $NO_2$ moderately well. These analyses confirm the validity of land use regression modeling to assign exposures in epidemiological studies, and these models may be useful tools for assessing health effects of long-term exposure to traffic related pollution.

• Journal of Preventive Medicine and Public Health
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• v.23 no.1 s.29
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• pp.43-56
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• 1990

To evaluate the difference of concentration and mutagenicity of organic pollutants between residential and traffic area of Seoul, air samples were collected in Bulkwang (residential) and Shinchon (traffic) area. Samples were analyzed to measure the concentration of extractable organic matters (EOM) and their subfractions and mutagenicities were tested using Salmonella typhimurium TA 98. The concentrations of polycyclic aromatic hydrocarbons (PAHs) were also measured by gas-chromatography and compared between two areas. The results were as follows ; 1. While the concentration of total suspended particulate (TSP) in residential area was below the environmental standard in annual average, the concentration in traffic area was above the standard and was up to its maximum $256{\mu}g/m^3$ in November. The difference of TSP concentrations in both areas of each month was statistically significant (P<0.05). 2. The concentration of fine particle in traffic area was significantly higher compare to that in residential area and showed statistically significant monthly difference in both areas (P<0.05). The proportion of concentration of fine particle to TSP was 55-68%. 3. Mean concentrations of EOM in residential and traffic areas were $4.3{\mu}g/m^3\;and\;5.3{\mu}g/m^3$ respectively. The proportion of amount of EOM from fine particle to EOM from TSP was 70-88%. 4. While the percentage of polar neutral organic compounds (POCN) of fine particle in Bulkwang's sample was higher compare to Shinchon's sample, the percentage of aliphatic compounds of fine particle in Shinchon's sample was higher compare to Bulkwang's sample. The percentages of PAH fraction were as low as 6-10% in both areas. 5. The mutagenic activity of nit concentration of organic matters extracted from fine particle was higher compare to that of coarse particle and was increased when metabolically activated with S9. Mutagenicities with metabolic activation calculated by unit air volume were significantly different between residential and traffic area, $17\;revertants/m^3$\;and\;22\;revertants/m^3$ respectively. 6. The concentrations of benzo(a)pyrene in fine particle of traffic and residential areas were $3.10ng/m^3\;and\;2.02ng/m^3$ respectively. Sixteen PAHs were higher in samples of traffic area compare to residential area and also concentrations of PAHs in fine particle were higher compare to coarse particle.

• Journal of Korean Society for Atmospheric Environment
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• v.9 no.4
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• pp.320-328
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• 1993

Gaseous pollutants in Namsan Nos. 1, 2, and 3 tunnels and Pukak tunnel were measured along the road by an air-monitoring van from the evening of February 9 to the morning of February 12 in 1993. Average concentrations of pollutants in Namsan tunnels were 9.2-13.5 ppm CO and 0.037-0.047 ppm SO$_{2}$. Average concentrations of SO$_{2}$ in Pukak tunnel was 0.79 ppm, higher than those in Namsan tunnels, due to the traffic of heavy-duty buses and trucks. The pollutant concentrations in Namsan tunnesl could be explained by emission of passenger cars using unleaded gasolin and LPG taxies. Average concentration of NO$_{x}$ in Namsan tunnels was at least 1.1 ppm, estimated from the emission factor of pasenger cars using unleaded gasoline. Pollutant concentrations in Namsan No. 3 tunnel were higher at the exit because of the piston action of air mass in the tunnel provided by the traffic. Fans installed at Namsan and Pukak tunnes could be useful, but their flushing action of ambient air in the tunnel was not clearly observed.d.

• Journal of ILASS-Korea
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• v.23 no.2
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• pp.81-89
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• 2018

The objective of this study is to estimate the level of exposure of traffic-related air pollutants (TRAPs) on the pedestrians in Seoul area. The road network's link-based pollutant emission was calculated by using a set of mobile source emission factor package and associated activity information. The population information, which is the number of pedestrian, was analyzed in conjunction with the link-based traffic emissions in order to quantify exposure level by selected 23 spots. We proposed the Exposure Intensity, which is defined by the amount of traffic emission and the population, to quantify the probability of exposure of pedestrian. Link-based traffic NOx and PM emissions vary by up to four times depending on the location of each spot. The Hot-spots is estimated to be around 1.8 times higher Exposure Intensity than the average of the 23 selected spots. The information of Exposure Intensity of each spot allows us to develop localized policies for air quality and health. Even in the same area, the Exposure Intensity over time also shows a large fluctuation, which gives suggestions for establishing site-specific counter-measures.

• Asian Journal of Atmospheric Environment
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• v.6 no.2
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• pp.96-103
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• 2012

Ambient particulate matter (PM) and particle-bound polycyclic aromatic hydrocarbon (PAH) concentrations were measured continuously for 70 days at a Korean elementary school located near a highway. The $PM_{10}$, $PM_{2.5}$, and $PM_1$ values were measured with a light-scattering, multi-channel, aerosol spectrometer (Grimm, Model 1.107). The number concentrations of the particles were measured using a scanning mobility particle sizer and counter (SMPS+C) which counted particles from 11.1 to 1083.3 nm classified in 44 channels. Particle-bound PAHs were measured with a direct reading, photoelectric aerosol sensor. The daily $NO_2$, $SO_2$, and CO concentrations were obtained from a national air-monitoring station located near the school. The average concentrations of $PM_{10}$, $PM_{2.5}$, and $PM_1$ were 75.3, 59.3, and $52.1{\mu}g/m^3$, respectively. The average number concentration of the ultrafine particles (UFPs) was $46,307/cm^3$, and the averaged particle-bound PAHs concentration was $17.9ng/cm^3$ during the study period. The ambient UFP variation was strongly associated with traffic intensity, particularly peak concentrations during the traffic rush hours. Particles <100 nm corresponded to traffic-related pollutants, including PAHs. Additional longterm monitoring of ambient UFPs and high-resolution traffic measurements should be carried out in future studies. In addition, transient variations in the ambient particle concentration should be taken into consideration in epidemiology studies in order to examine the short-term health effects of urban UFPs.

• Journal of Environmental Health Sciences
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• v.18 no.2
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• pp.19-25
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• 1992

The study was carried out to investigate the correlation between the heavy metals emitted by the motor vehicles with the heavy traffic road side environment (soil, leave, bark, ambient air). The Pb, Cu, Zn contents in road side soil sand leaves, barks from Ginkgo, biloba and ambient air adjacent to the heavy traffic road side from June to August, 1992 Suwon city were analyzed by Atomic absorption spectrometry and Inductively coupled plasma emission spectrophotometry. The results were as follows: 1) The high levels of heavy metals concentration were Pb, at city-terminal in soil (186 $\mu$g/g), Cu, at city-terminal in soil (221 $\mu$g/g), Zn, at city-terminal in ambient air (252 $\mu$g/m$^{3}$). 2) The low leves of heavy metals concentration were Pb, at North-gate in ambient air (1.65$\mu$g/m$^{3}$), Cu, at North-gate in ambient air (4 $\mu$g/m$^{3}$), Zn, at North-gate in ambient air (15.31$\mu$g/m$^{3}$). 3) The regional distribution of Pb, Cu, Zn in road side soils, leaves and barks from Ginkgo, biloba, ambient air show high levels in turn, city4erminal, Guan Sean Dong, South gate, North gate. 4) The concentration of heavy metals (Pb, Cu, Zn) in soils, leaves, barks, ambient air was highly correlated with the traffic volume of the sampling sites (r=0.64~0.96). To conclude that the high levels of Pb, Cu, Zn contaminations were positively related to motor vehicles-borne pollutants and road side soils, trees, ambient air adjacent to a high density building area with low road coverage and heavy traffic volume were reflected strongly by the hazardous pollutants emitted by motor vehicles.

• Proceedings of the Korea Air Pollution Research Association Conference
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• 2000.11a
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• pp.136-138
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• 2000

The vehicle emissions of primary air pollutants are described by the emission factor (EF), defined as the emitted mass (g) of a compound per distance (km) and vehicle. The EF can be determined by exhaust measurements from single vehicles in dynamometric tests. However, the EF of a large number of vehicles has to be measured to obtain the representative results for actual road traffic emissions. Road traffic emissions can also be determined by exhaust measurements of driving vehicles or in tunnel measurements. (omitted)

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.6
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• pp.1-6
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• 2020

Road movement pollutant air environment big data is a link between real-time traffic data such as vehicle type, speed, and load using AVC, VDS, WIM, and DTG, which are always traffic volume survey equipment, and road shape (uphill, downhill, turning section) data using GIS. It consists of traffic flow data. Also, unlike general data, a lot of data per unit time is generated and has various formats. In particular, since about 7.4 million cases/hour or more of large-scale real-time data collected as detailed traffic flow information are collected, stored and processed, a system that can efficiently process data is required. Therefore, in this study, an open source-based data parallel processing performance optimization study is conducted for the visualization of big data in the air environment of road transport pollution.

• Journal of Environmental Science International
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• v.12 no.1
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• pp.23-34
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• 2003

Urban air quality is usually worse than that of rural counterpart. The contrasting atmospheric properties seem to be direct result of different urban-rural air pollutant emission. Hence, the emission estimation of air pollutants plays an important role to the atmospheric environmental management. The main purpose of this study is to find out the temporal and spatial distribution of air pollutant emission in Daegu area. For the study, the Daegu statistical yearbook and data of waste facilities and the report on traffic survey issued by Daegu metropolitan city and the statistical yearbook on the road capacity issued by the ministry of construction and transportation are used. Each item for the emission estimation is $SO_2$, CO, HC, $NO_x$, PM-10 from point, line and area source. The result were as follow; (1) The air pollutants with the highest amount of emission from the emission source is CO followed by $NO_x$, $SO_2$, PM-10, HC in descending order of magnitude. (2) The annually totaled air pollutant emission consists of 81%(73,185 ton/year) of line, 11%(9,589% ton/year) of area and 8%(7,445 ton/year) of point source in Daegu. Air polluant emission was mainly due to line sources. (3) High-emission of the air pollutants of line source appeared ariond Bukgu, Dalseonggun, Dongu and Seogu ; the areas with highway networks.