• Transactions of the Korean Society of Automotive Engineers
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• v.16 no.3
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• pp.94-101
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• 2008

Since regulations of exhaust emissions are continuously reinforced, studies to reduce harmful emissions during the cold start period of SI engines have been carried out very extensively worldwide. During the cold start period, raising the temperature of cold exhaust gas is a key strategy to minimize the light-off time of three way catalysts. In this study, a synthetic gas containing a large amount of hydrogen was injected into the exhaust manifold to raise the exhaust gas temperature and to reduce harmful emissions. The authors tried to evaluate changes in exhaust gas temperature and harmful emissions through controlling the engine operating parameters such as ignition timings and lambda values. Also the authors investigated both combustion stability and reduction of harmful emissions. Experimental results showed that combustion of the synthetic gas in the exhaust manifold is a very effective way for solving the problems of harmful emissions and light-off time. The results also showed that the strategy of retarded ignition timings and increased air/fuel ratios with ESGI is effective in raising exhaust gas temperature and reducing harmful emissions. Futhermore, the results showed that engine operating parameters ought to be controlled to lambda = 1.2 and ignition timing = $0{\sim}3^{\circ}$ conditions to reduce harmful emissions effectively under stable combustion conditions.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.7
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• pp.1302-1308
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• 2010

In this study, Zigbee Sensor Node to transmit harmful gases CO and $CO_2$ information using wireless communication within the ground and underground structures were developed. Wireless communication protocol was used Zigbee Stack included IEEE 802. 15.4 MAC protocol. For wireless transmission of detected harmful gas signal from ADC of MCU was implemented Zigbee Sensor Node that was developed protocol using Serial-Port-Profile(SPP) here. The proposed Zigbee Sensor Node was verified transmission distance from experiments. Transmission distance was into 90m in experiments. Distance experiments were measured at 10m intervals using sine & pulse wave input signal at indoors. The proposed Route Sensor Node was applied mesh routing protocol. When built up USN(Ubiquitous Sensor Network)using Route Sensor Node, transmission distance was not limited. On the experimental results, harmful gas values between direct measurements and USN measurements were consistent. The semiconductor CO sensor and N-DIR $CO_2$ sensor module as a harmful sensor was used. Therefore, the proposed Zigbee Sensor Node was verified about reliability and validity to build USN for transmission of harmful gas information.

• Journal of the Korea Safety Management & Science
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• v.16 no.2
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• pp.237-246
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• 2014

Researches on the elimination of sulfur and nitrogen oxides with catalysts and absorbents reported many problems related with elimination efficiency and complex devices. In this study, decomposition efficiency of harmful gases was investigated. It was found that the efficiency rate can be increased by moving the harmful gases together with SPCP reactor and the catalysis reactor. Calcium hydroxide($Ca(OH)_2$), CaO, and $TiO_2$ were used as catalysts. Harmful air polluting gases such as $SO_2$ were measured for the analysis of decomposition efficiency, power consumption, and voltage according to changes to the process variables including frequency, concentration, electrode material, thickness of electrode, number of electrode winding, and additives to obtain optimal process conditions and the highest decomposition efficiency. The standard sample was sulfur oxide($SO_2$). Harmful gases were eliminated by moving them through the plasma generated in the SPCP reactor and the $Ca(OH)_2$ catalysis reactor. The elimination rate and products were analyzed with the gas analyzer (Ecom-AC,Germany), FT-IR(Nicolet, Magna-IR560), and GC-(Shimazu). The results of the experiment conducted to decompose and eliminate the harmful gas $SO_2$ with the $Ca(OH)_2$ catalysis reactor and SPCP reactor show 96% decomposition efficiency at the frequency of 10 kHz. The conductivity of the standard gas increased at the frequencies higher than 20 kHz. There was a partial flow of current along the surface. As a result, the decomposition efficiency decreased. The decomposition efficiency of harmful gas $SO_2$ by the $Ca(OH)_2$ catalysis reactor and SPCP reactor was 96.0% under 300 ppm concentration, 10 kHz frequency, and decomposition power of 20 W. It was 4% higher than the application of the SPCP reactor alone. The highest decomposition efficiency, 98.0% was achieved at the concentration of 100 ppm.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.30 no.12 s.255
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• pp.1181-1187
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• 2006

Stringent regulations of exhaust emission from vehicles become a major issue in automotive industries. In SI engines, it is one of the crucial factor to reduce exhaust emissions during cold start in order to meet stringent regulations such as SULEV or EURO-4, because SI engines emit a large portion of total harmful exhaust compounds when they are cold. At early stages of cold start in gasoline engines, exhaust gas temperature plays a key role to improve three way catalyst by virtue of fast warmup. Therefore, this study focused on the increase of exhaust gas temperature under controls of engine operating parameters such as spark ignition timing, valve overlap by virtue of intake VVT and catalyst heating function. Furthermore, effects on harmful emission due to these parameters are also investigated. Experiments showed that retarded spark ignition timings and increased valve overlap may be helpful to increase exhaust gas temperature. It was also found that $NO_x$ was decreased with increased valve overlap. This study also showed that sudden changes in ISA and amount of fuel due to the deactivation of catalyst heating function cause temporal increase of harmful emissions.

• Journal of Animal Science and Technology
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• v.66 no.2
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• pp.237-250
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• 2024

The emission of noxious gases is a significant problem in pig production, as it can lead to poor production, welfare concerns, and environmental pollution. The noxious gases are the gasses emitted from the pig manure that contribute to air pollution. The increased concentration of various harmful gasses can pose health risks to both animals and humans. The major gases produced in the pig farm include methane, hydrogen sulfide, carbon dioxide, ammonia, sulfur dioxide and volatile fatty acids, which are mainly derived from the fermentation of undigested or poorly digested nutrients. Nowadays research has focused on more holistic approaches to obtain a healthy farm environment that helps animal production. The use of probiotics, prebiotics, dietary enzymes, and medicinal plants in animal diets has been explored as a means of reducing harmful gas emissions. This review paper focuses on the harmful gas emissions from pig farm, the mechanisms of gas production, and strategies for reducing these emissions. Additionally, various methods for reducing gas in pigs, including probiotic interventions; prebiotic interventions, dietary enzymes supplementation, and use of medicinal plants and organic acids are discussed. Overall, this paper provides a comprehensive review of the current state of knowledge on reducing noxious gas in pigs and offers valuable insights for pig producers, nutritionists, and researchers working in this area.

• Proceedings of the KIEE Conference
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• 2007.04a
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• pp.439-441
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• 2007

The seoul metropolitan subway has installed 8 lines and about 500 stations to transport 5 million passengers everyday. The underground air pollution level in the subway stations is very severe status, which is very harmful to the commutators and its personals. Although subway roles as such a massive and huge transportation system, the subway doesn't adapt yet any real-time air monitoring system. They have only some hand-held type detector equipments for monitoring air pollution. Therefore subway passengers are exposed to the harmful air pollution environment. The most harmful environmental parameters among the air pollution are known as the dust and sound noise dB level in the subway station. Because the dust is consisted of very small particles, we can't see them easily in dark condition on the platform, but it is very harmful. The monitoring system for air pollution is developed using embedded system attached with 6 different environmental sensors. This system monitors air pollution of dust sound noise, gas, temperature, humidity, inflammable gas, toxic gas in the subway ?station. The sensor unit of the ARM-CPU board and sensor transmits real time environmental data to the main server using Zigbee wireless communication module and TCP/IP network. The main control server receives and displays the real-time environmental data, and it send alarms to the personals when high level value.

• Special Issue of the Society of Naval Architects of Korea
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• 2011.09a
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• pp.63-69
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• 2011

Exhaust gases of a vessel from a main engine, a diesel generator and an incinerator contain very harmful substances like soot, $SO_2$ and NOx. Careful design of funnel shape is required to prevent those harmful exhaust gases from influencing on accommodation and a fan room. Meanwhile, the exhaust gases are also hot enough to damage electronic devices like radar. Therefore the funnel design should be considered so that electronic devices are not directly exposed to the exhaust gas in the strong stern wind. This study may propose guidelines of optimum design criterion for the anti-thermal damage design of the electronic devices and anti-recirculating design of harmful exhaust gas near the accommodation. From CFD analyses, we can understand that the major factors affecting the exhaust gas dispersion are the large scale mixing by separation vortices and the sluggish flow in the recirculation region. We hope that the funnel flow analysis around ship's funnel is used for practical optimum funnel design to minimize the exhaust gas dispersion by adjusting the funnel shape, the position of the exhaust pipe, the shape of bulwark, the exhaust direction of air ventilated an engine room and the angle of the exhaust pipe.

• Journal of Sensor Science and Technology
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• v.17 no.6
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• pp.406-413
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• 2008

We have been implemented simple statistical pattern recognition methods for harmful gases classification using gas sensors array fabricated by MEMS (Micro Electro Mechanical System) technology. The performance of pattern recognition method as a gas classifier is highly dependent on the choice of pre-processing techniques for sensor and sensors array signals and optimal classification algorithms among the various classification techniques. We carried out pre-processing for each sensor's signal as well as sensors array signals to extract features for each gas. We adapted simple statistical pattern recognition algorithms, which were PCA (Principal Component Analysis) for visualization of patterns clustering and MLR (Multi-Linear Regression) for real-time system implementation, to classify harmful gases. Experimental results of adapted pattern recognition methods with pre-processing techniques have been shown good clustering performance and expected easy implementation for real-time sensing system.

• Journal of the Korean Society of Industry Convergence
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• v.24 no.3
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• pp.323-331
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• 2021

With global warming and pollution problems, accurate forecasting of the harmful gases would be an essential alarm in our life. In this paper, we forecast the emission of the five gases(SOx, NO₂, NH₃, H₂S, CH₄) using the time series model of ARIMA, the learning algorithms of Random forest, and LSTM. We find that the gas emission data depends on the short-term memory and behaves like a random walk. As a result, we compare the RMSE, MAE, and MAPE as the measure of the prediction performance under the same conditions given to three models. We find that ARIMA forecasts the gas emissions more precisely than the other two learning-based methods. Besides, the ARIMA model is more suitable for the real-time forecasts of gas emissions because it is faster for modeling than the two learning algorithms.

• Proceedings of the Korea Institute of Fire Science and Engineering Conference
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• 2008.04a
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• pp.337-340
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• 2008

Smoke composed of harmful gases such as carbon monocide and carbon dioxide is reconized as the major killer in fire situation. Especailly it is said that smoke movement is related to the panic phenomenon which threatens the life seriously. The purpose of this study is to investgate and analyse the reaction mechanism of harmful gas caused by fire effects on the human psychology and panic phenomenon.