• Transactions of the Korean Society of Automotive Engineers
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• v.24 no.5
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• pp.556-565
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• 2016

As a result of the enforced control of emission, many devices, including the diesel particulate filter, have been installed in diesel cars to reduce the emission of particulate matters. In this study, a car fire case has been investigated and analyzed. A car fire broke out after the vehicle traveled a distance of 1.4 km from a car service center. The car was provided with DPF cleaning when the DPF warning light came on. After being dismantled in the engine room, the car's engine and gearbox were investigated. The findings showed that the rear part of the DPF metal case was melted and punctured, while the honeycomb filter of the DPF was damaged. The car fire was caused by an overheated DPF associated with inaccurate maintenance practice. Therefore, the responsibility of the fire rested on the car service center that performed the DPF cleaning.

• International Journal of Automotive Technology
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• v.6 no.2
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• pp.95-105
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• 2005

Diesel engines have low specific fuel consumption, but high particulate emissions, mainly soot. Diesel soot is suspected to have significant effects on the health of living beings and might also affect global warming. Hence stringent measures have been put in place in a number of countries and will be even stronger in the near future. Diesel engines require either advanced integrated exhaust after treatment systems or modified engine models to meet the statutory norms. Experimental analysis to study the emission characteristics is a time consuming affair. In such situations, the real picture of engine control can be obtained by the modeling of trend prediction. In this article, an effort has been made to predict emissions smoke and NO$_{x}$ using cylinder combustion derived parameters and diesel particulate filter data, with artificial neural network techniques in MATLAB environment. The model is based on three layer neural network with a back propagation learning algorithm. The training and test data of emissions were collected from experimental set up in the laboratory for different loads. The network is trained to predict the values of emission with training values. Regression analysis between test and predicted value from neural network shows least error. This approach helps in the reduction of the experimentation required to determine the smoke and NO$_{x}$ for the catalyst coated filters.

• Journal of The Korean Society of Agricultural Engineers
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• v.64 no.1
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• pp.99-110
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• 2022

In this study, the generation and emission characteristics of particulate matter and gaseous matter in a mechanically ventilated layer house were evaluated. Each concentration of PM₁₀, PM_2.5, inhalable dust, respirable dust, and NH₃ was measured and compared with occupational limit considering seasons and respiratory disorder. CAPPS (Clean Air Policy Support System) of the Ministry of Environment proposes the emission factors of PM₁₀, PM_2.5, and NH₃ for a layer houses however, emission factors are still calculated from foreign factors such as CONINAIR values. As a result, it is urgent to develop national emission factors for domestic layer house. Emission coefficients of the studied mechanically-ventilated layer house in a summer season were calculated as 0.052 kg/head/year for PM₁₀, about 12% lower than that of CAPSS, and 0.0068±0.0038 kg/head/year for PM_2.5, showing no significant difference. Emission factor of NH₃ was calculated as 0.159±0.031 kg/head/year, about 51% lower than that of CAPSS.

• 한국연소학회:학술대회논문집
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• 2015.12a
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• pp.41-44
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• 2015

Experimental study was conducted to investigate the effect of ultra-high injection pressure on combustion and emission characteristics in a single-cylinder diesel engine. Electronically controlled ultra-high pressure fuel injection system consistently supplied the fuel of ultra-high pressure up to 250 MPa. Various injection pressures, 40 to 250 MPa, were applied and compared. A injector with eight identical nozzle holes which have diameter of $105{\mu}m$ was used. The results showed high potential to improve the nitrogen oxide (NOx) and particulate matter (PM) trade-off relationship with an ultra-high injection pressure and the exhaust gas recirculation (EGR).

• Korean Journal of Environmental Agriculture
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• v.40 no.3
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• pp.211-218
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• 2021

BACKGROUND: Fine particulate matter (PM_2.5) is produced by chemical reactions between various precursors. PM_2.5 has been found to create greater human risk than particulate matter (PM₁₀), with diameters that are generally 10 micrometers and smaller. Ammonia (NH₃) and nitrogen oxides (NOx) are the sources of secondary generation of PM_2.5. These substances generate PM_2.5 through some chemical reactions in the atmosphere. Through chemical reactions in the atmosphere, NH₃ generates PM_2.5. It is the causative agent of PM_2.5. In 2017 the annual ammonia emission recorded from the agricultural sector was 244,335 tons, which accounted for about 79.3% of the total ammonia emission in Korea in that year. To address this issue, the agricultural sector announced the inclusion of reducing fine particulate matter and ammonia emissions by 30% in its targets for the year 2022. This may be achieved through analyses of its emission characteristics by monitoring the PM_2.5 and NH₃. METHODS AND RESULTS: In this study, the PM_2.5 concentration was measured real-time (every 1 hour) by using beta radiation from the particle dust measuring device (Spirant BAM). NH₃ concentration was analyzed real-time by Cavity Ring-Down Spectroscopy (CRDS). The concentrations of ozone (O₃) and nitrogen dioxide (NO₂) were continuously measured and analyzed for the masses collected on filter papers by ultraviolet photometry and chemiluminescence. CONCLUSION: This study established air pollutant monitoring system in agricultural areas to analyze the NH₃ emission characteristics. The amount of PM_2.5 and NH₃ emission in agriculture was measured. Scientific evidence in agricultural areas was obtained by identifying the emission concentration and characteristics per season (monthly) and per hour.

• Journal of Korean Society for Atmospheric Environment
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• v.3 no.1
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• pp.55-64
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• 1987

Actual driving pattern of each motor vehicle type was measured and analyzed in Seoul area and vehicle emission rate was measured and traffic data were used to estimate vehicular emission factor and motor vehicle-related air pollutant emission. The analysis of contribution ratio of each vehicle type showed that LPG taxi's took 38.1% of total vehicular CO, gasoline passenger cars 37.5%, therefore, these cars are major sources of CO, gasoline passenger cars took 45.4% of total vehicular HC, motorcycles 25.3%, LPG taxi's 16.2%, so motorcycles can be said to play an important role in HC emission. For NOx, buses and trucks were thought to be major sources as buses took 36.8% and truck 26.4%. Diesel vehicles, on the other hand, took most $SO_2$ and particulate matter emission. Total emission from motor vehicles in Seoul was estimated to be 547 t/day of CO, 68t/day of HC, 163t/day of NOx, 18t/day of $SO_2$ and 19t/day of paticulate matter.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.30 no.2
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• pp.236-248
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• 2020

Objectives: The purpose of this study was to evaluate the concentrations of particulate matter generated during coffee roasting and to study various factors affecting the concentrations. Methods: Differences in concentration levels were investigated based on various factors to understand the emission rates of particulate matter over time and to compare the mass and number concentrations according to their size. Sampling was performed in closed laboratories without the operation of air conditioning or ventilation. Optical Particle Sizer(OPS) was used as a measuring device. An OPS measures using a light-scattering method. Sampling was performed for sixty minutes at one-minute intervals. The background concentration was measured for about 30 minutes before starting of coffee roasting. The concentrations of particulate matter generated during coffee roasting were monitored until roasted coffee beans were removed from the roaster and cooled down. Several factors affecting the concentrations of particulate matter were investigated, which includes the origins of green beans, the roasting level, and the input amount of green beans. Results: The results of this study may be summarized as follows: 1) There was no difference in particulate matter concentration levels by the origin of the green beans, but a statistically significant difference in concentration levels by roasting level and the input amount of green beans; The higher the roasting level, the higher was the particulate matter concentration. The more green beans we put in the roaster, the higher were the concentrations; 2) The PM10 mass concentrations increased over time. The average concentration after roasting was higher than the average concentration during roasting; 3) In the distribution of mass and number concentration by particle diameter, the majority of particles was below 2.5 ㎛. Conclusions: Persons who work in roastery cafes can be exposed to high concentrations of particulate matter. Therefore, personal exposure and risk assessment should be conducted for roastery cafe workers.

• Transactions of the Korean Society of Automotive Engineers
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• v.16 no.5
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• pp.84-91
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• 2008

Due to increasing need for better emission characteristics and lower fuel consumption rate in automotive engines, alternative fuels are drawing more attentions recently. The GTL (gas to liquid) is the one of most favored candidates. In this study, emission characteristics are compared between diesel and GTL fuel in commercial 2.0 liter diesel engine and vehicle with CRDi(Common Rail Direct injection) system. The effects of injection timings on emission and fuel consumption rate are compared at various engine speeds and loads. Noticeable reduction in HC, CO and PM emissions are observed due to higher cetane number and low sulfur and aromatic contents in GTL. On the trade-off curve of NOx and PM(Particulate matter) GTL showed much more benefits than diesel, where about 30% of PM mass decreased at the same operating conditions. On CVS 75 mode test in vehicle, GTL showed an excellent emission enhancement, in which 50% of HC, 21% of PM, and 12% of NOx engine-out emissions are decreased compared to ULSD(Ultra low sulfur diesel) fuel.

• KEPCO Journal on Electric Power and Energy
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• v.6 no.4
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• pp.455-460
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• 2020

In order to identify the characteristics of fine particle emissions from thermal power plants, this study conducted measurement of the primary emission concentration of TPM, PM₁₀ and PM_2.5 according to Korea standard test method (ES 01301.1) and ISO 23210 method (KS I ISO 23210). Particulate matters were sampled in total 74 units of power plants such as 59 units of coal-fired power plants, 7 units of heavy oil power plants, 2 units of biomass power plant, and 6 units of liquid natural gas power plants. The average concentration of TPM, PM₁₀, PM_2.5 by fuel are 3.33 mg/m³, 3.01 mg/m³, 2.70 mg/m³ in coal-fired plant, 3.02 mg/m³, 2.99 mg/m³, 2.93 mg/m³ in heavy oil plant, 0.114 mg/m³, 0.046 mg/m³, 0.036 mg/m³ in LNG plant, respectively. These results of TPM, PM₁₀ and PM_2.5 were satisfied with the standards of fine dust emission allowance in all units of power plants, respectively. Also, this study evaluated the characteristics of fine particle emissions by conditions of power plants including generation sources, boiler types and operation years and calculated emission factors and then evaluated fine particle emissions by sources of electricity generation.

• Transactions of the Korean Society of Automotive Engineers
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• v.17 no.5
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• pp.91-96
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• 2009

The number of vehicles applied diesel engine are rapidly rising for fuel economy. Accompanying this trend, application of an after-treatment system is strictly required as a result of reinforced emission regulation. The Diesel Particulate Filter (DPF) system is considered as the most efficient method to reduce particulate matter by car makers but also in retrofit market. In this paper we discussed the optimization of active regeneration timing by comparing the fuel consumption from back pressure caused by PM loading and from active regeneration. The effects of back pressure of DPFs during PM loading, active regeneration condition and engine emission(PM) on additional fuel consumption are experimentally investigated and the proper regeneration timings according to DPF systems and fuel loss for 160,000km are determined.