• Journal of Korean Society for Atmospheric Environment
• /
• v.29 no.4
• /
• pp.369-377
• /
• 2013

The trends of the criteria air pollutants' concentrations over Seoul are reviewed, relative contributions of major sources are discussd, and directions for future air quality management are suggested. It was shown that the yearly average concentrations of the criteria air pollutants except nitrogen dioxide and ozone have decreased significantly over the last three decades. Though the concentration of nitrogen dioxide has not decreased, the concentration of $NO_x$ has decreased significantly. The major reason for the reduction of the criteria air pollutants has been strict government regulations such as establishment of strict emission standards and switch to cleaner fuels. However, it is not clear the major reason (s) for the reduction of the $PM_{10}$ concentration. It is suggested that to further reduce the concentrations of secondary air pollutants such as ozone and $PM_{2.5}$, understanding the major chemical pathways for them is essential. In addition, influence from outside Seoul should be quantified and effectively controlled.

• Proceedings of the Korea Air Pollution Research Association Conference
• /
• 2005.11a
• /
• pp.162-164
• /
• 2005

• Journal of Korean Society of societal Security
• /
• v.2 no.1
• /
• pp.65-74
• /
• 2009

In this study, the air pollution management system based GIS has been developed to estimate the emission rate and air pollution modeling of air pollutants, effectively. This system is able to estimate emission rate of air pollutant and to analyze the emission characteristics with high spatial and temporal resolution. air pollution modeling. The air pollution management system was applied to Gwangyang Bay including large industry complex with a large number of emission sources. The air pollution management system was constructed using the spatial database of emission sources in Gwangyang Bay. It was found that the estimated emission rates of air pollutants is similar to the emission characteristics in Gwangyang Bay. Also, the spatial distribution of pollutants was similar to the location of emission sources. The predicted results of air pollution model was showed a good correlation coefficient (0.75) for TSP. The air pollution management system is expected to be effective tool (database system (GIS)) for the management and the control of air pollution.

• Journal of Environmental Science International
• /
• v.28 no.4
• /
• pp.455-464
• /
• 2019

BAT-AEL(Best Available Techniques Associate Emission Level) is the basis for establishing permissible emission standards for the workplace. Therefore, it is necessary to formulate a regulated BAT-AEL setting methodology that is generally applicable to all relevant industries. For the BAT-AEL settings, various factors should be considered such as the pollutants item, whether the workplace is subject to integrated pollution prevention and control, whether BAT is applicable, the basic data type, the emission classification system, and the suitability of the collected data. Among these factors, it is the most important factor to establish the classification system for the emitting facilities such that the emission characteristics of an industrial facility and its pollutants can be effectively reflected. Furthermore the target of the survey workplace should adhere to the BAT guidelines, even if it is a workplace that is subject to an the integrated environmental system. Certified data (SEMS, TMS, cleanSYS, WEMS, etc.) can be used to prioritize the classification system for the emission facility and the emission levels of pollutants. However, the self-measured data, daily logs, and questionnaire data from the workplace can also be used upon agreement of the relevant TWG. The collected data should only be used only when the facility is operating normally. Data that have been determined to be outliers or inappropriate validation methods should also be excluded. The BAT-AEL can be establish by adhering to the following procedure: 1) investigate all relevant workplaces with in the industry, 2)select workplaces for integrated management, 3)Identify BAT application, 4)identify whether BAT is generally applicable, 5)establish a classification system for emitting facilities, 6)collection available data, 7)verify conformity, 8)remove of outliers, 9)prepare the BAT-AEL draft, 10)deliberate, and 11) perform the confirmation procedure.

• Korean Journal of Remote Sensing
• /
• v.38 no.1
• /
• pp.1-20
• /
• 2022

As unmanned aerial vehicle (UAV) technology grew in popularity over the years, it was introduced for air quality monitoring. This can easily be used to estimate the sidewalk emission concentration by calculating road traffic emission factors of different vehicle types. These calculations require a simulation of the spread of pollutants from one or more sources given for estimation. For this purpose, a Gaussian plume dispersion model was developed based on the US EPA Motor Vehicle Emissions Simulator (MOVES), which provides an accurate estimate of fuel consumption and pollutant emissions from vehicles under a wide range of user-defined conditions. This paper describes a methodology for estimating emission concentration on the sidewalk emitted by different types of vehicles. This line source considers vehicle parameters, wind speed and direction, and pollutant concentration using a UAV equipped with a monocular camera. All were sampled over an hourly interval. In this article, the YOLOv5 deep learning model is developed, vehicle tracking is used through Deep SORT (Simple Online and Realtime Tracking), vehicle localization using a homography transformation matrix to locate each vehicle and calculate the parameters of speed and acceleration, and ultimately a Gaussian plume dispersion model was developed to estimate the CO, NOx concentrations at a sidewalk point. The results demonstrate that these estimated pollutants values are good to give a fast and reasonable indication for any near road receptor point using a cheap UAV without installing air monitoring stations along the road.

• Journal of the Korean Society of Marine Environment & Safety
• /
• v.28 no.6
• /
• pp.1063-1069
• /
• 2022

According to domestic air pollutant emission statistics, a considerable amount of air pollutants is generated by ships. Therefore, various policies are being implemented to limit air pollutant emissions from ships and improve the air quality in ports. In addition, international conventions are carried out for the prevention of marine pollution by ships. However, because few studies and experiments have been conducted on the measurement of air pollutants emitted from actually operating ships, this study presented a method and possibility for evaluating air pollutant emissions from a 9,196GT ship actually operating using a portable emission measurement system (PEMS). A difference in emission occurred depending on the RPM and load, and the emission of NO_X was 497-2,060ppm, CO₂ was 1.55-6.9%, and CO was 0.002-0.14%. The emission specified in the shop test provided by the engine manufacturer differed from the actual emission measured. This study proved that the maximum emission of each air pollutant generated in the entire sailing section of the ship was included in the PEMS measurement range, and the possibility of using PEMS for ships within 10,000GT was verified.

• Proceedings of the Korea Air Pollution Research Association Conference
• /
• 2003.11a
• /
• pp.221-222
• /
• 2003

잔류성유기오염물질(Persistent Organic Pollutants, 이하 POPs)은 환경에 노출되면 장기간 잔류하면서 인체 및 생태계에 악영향을 끼치며 또한 장거리 이동하는 특징으로 인하여 전지구적인 규제ㆍ관리의 필요성이 제기되고 있다. 이러한 필요에 부응하여 UNEP를 중심으로 국제적인 관리를 위한 논의가 이루어져 2001년 5월 스톡홀름협약(Stockholm convention for Persistent Organic Pollutants)이 당사국회의에서 채택되었고, 우리나라는 외교적 서명을 함으로써 협약가입의사를 분명히 하였다. (중략)

• Journal of Korean Society for Atmospheric Environment
• /
• v.30 no.3
• /
• pp.251-260
• /
• 2014

Biomass burning is one of the significant emission source of PM and CO, but a few studies are reported in Korea. Air pollutants emission from biomass burning such as wood stove and boiler, and wood-pellet stove and boiler were estimated in this study. Activity levels related to biomass burning such as fuel types, amount of fuel loading, and location and temporal variation were investigated by field survey over Korea. Fuel loadings were 14.9 kg/day for wood stove, 31.3 kg/day for wood boiler, 12.8 kg/day for wood-pellet stove, 32.5 kg/day for wood-pellet boiler during the season of active use. These were mostly burned in winter season from october to april of next year. Estimated annual emissions from wood stove & boiler were CO 76,677, $NO_x$ 710, $SO_x$ 70, VOC 20,941, TSP 6,605, PM10 2,921, PM2.5 1,851, and NH3 7 ton/yr, respectively. Emissions from wood-pellet stove and boiler were CO 32,798, $NO_x$ 1,830, $SO_x$ 25, VOCs 5,673, TSP 629, PM10 457, PM2.5 344, and $NH_3$ 2 ton/yr, respectively. When the emission estimates are compared with total emissions of the national emission inventory (CAPSS: Clean Air Policy Support System), Those occupy 12.5%, 2.8% of total national emission for CO and PM10, respectively. These results show wood and wood-pellet burning appliances were one of the major source of air pollution in Korea. In future, these types of heaters need to be regulated to reduce air pollution, especially in suburb area.

• Environmental Analysis Health and Toxicology
• /
• v.24 no.2
• /
• pp.137-148
• /
• 2009

This study quantitatively investigated the emissions of indoor air pollutants associated with the utilization of air fresheners indoors, and evaluated individual exposure to five specified indoor air pollutants, which were chosen on the basis of selection criteria. An electrically-polished stainless steel chamber (50L) was employed to achieve this purpose. Test air fresheners were selected through three steps: first, on the basis of market sales; second, on the basis on a preliminary head-space study; and lastly, on the basis of emissions of toxic compounds (benzene, ethyl benzene, limonene, toluene, and xylene). The empirical mathematical model fitted well with the time-series concentrations in the environmental chamber (in most cases, determination coefficient, $R^2{\gtrsim}$0.9), thereby suggesting that the empirical model was suitable for testing emissions. The concentration equilibrium appeared 180 min after the introduction of sample air fresheners into the chamber. Both the chamber concentrations of emission rates or factors varied greatly according to air freshener type. It is noteworthy that although benzene, ethyl benzene, toluene, and xylene were emitted from all test air fresheners, their exposure levels were not significant enough to result in any significant health risk. However, certain type of air fresheners were observed to emit significant amount of limonene, which is potentially reactive with ozone to generate secondary pollutants with oxidants such as ozone, hydroxyl radicals, and nitrogen oxides. The exposure levels to limonene associated with the utilization of three air fresheners were estimated to be 13 to 175 times higher than that of other air fresheners. This information can help consumers to select low-pollutant-emitting air fresheners.

• Journal of Climate Change Research
• /
• v.6 no.2
• /
• pp.113-119
• /
• 2015

Emission from the traditional Korean fireplace, or the under-floor heating and cooking device, can contribute significantly to airborne pollutants inventories. This study has systematically measured emissions of airborne pollutants from the fireplace when used different fuels such as firewood, agricultural crop residuals, household wastes. The results show that emission factors of airborne pollutants through the primary combustion of firewood were 3.22 g/kg for TSP, 2.93 g/kg for $PM_{10}$, 2.65 g/kg for $PM_{2.5}$, 174.19 g/kg for CO, 7.77 g/kg for NO, 0.15 g/kg for $SO_2$, 40.53 g/kg for TVOC and 0.03 g/kg for $NH_3$; from burning of agricultural crop residues, 2.85 g/kg for TSP, 1.38 g/kg for $PM_{10}$, 1.14 g/kg for $PM_{2.5}$, 126.47 g/kg for CO, 12.60 g/kg for NO, 0.20 g/kg for $SO_2$, 33.73 g/kg for TVOC and 0.02 g/kg for $NH_3$; and for household wastes, 10.52 g/kg for TSP, 8.52 g/kg for $PM_{10}$, 6.23 g/kg for $PM_{2.5}$, 72.86 g/kg for CO, 11.73 g/kg for NO, 0.20 g/kg for $SO_2$, 47.10 g/kg for TVOC and 0.20 g/kg for $NH_3$.