• Title/Summary/Keyword: Particulate Matters

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The Implementation of the Fine Dust Measuring System based on Internet of Things(IoT) (사물인터넷기반 미세먼지 측정 시스템 구현)

  • Noh, Jin-Ho;Tack, Han-Ho
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.21 no.4
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    • pp.829-835
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    • 2017
  • Recently, the health issues triggered by fine dust matters occurred in higher frequency. Having adverse effects on health, particulate matters affect the human body indoors as well as outdoors. There is thus a need for a system to measure the concentration of particulate matters and control harmful particulate matters for human health in the indoor spaces where people live. The present study applied Internet of Things(IoT) technologies in order to increase the efficiency of the conventional fine dust measurement system. Especially, for the bidirectional communication environment, directly construct a separate server and applied to the system instead of a free cloud server also we used it directly in the school lab and home. When the proposed system is used in schools and homes, it can recognize the indoor environment quickly and it is expected that this will gradually contribute to the health of the individual. Users can also check the server data outside and deal with the current indoor situations.

The Forest Experience on Kindergarten Children's Mother's Analysis of Differences in Perception Between Forest and Fine Particulate Matter (유치원 아동 어머니들의 숲체험에 따른 숲과 미세먼지에 대한 인식의 차이 분석)

  • Do, Hyun-Jin;Koo, Chang-Duck
    • Korean Journal of Environment and Ecology
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    • v.32 no.5
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    • pp.541-552
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    • 2018
  • This study investigated for perception about particulate matter in daily lives of mothers who have children aged from three to five years old and the difference of perception after participating in forest experience programs. The data were compiled from 122 mothers of preschoolers composed by 61 mothers who participated in the forest experience and those who did not. 82.8 percent of 122 mothers were concerned with particulate matters, and 84.4 percent frequently checked information on particulate matters. However, they lacked knowledge, countermeasures, and active practice to reduce it. Awareness of forest and fine particulate matter was high among mothers who had participated in the forest experience, with a high positive perception of forest role and forest environment. Therefore, expanding the opportunity for mothers to actively experience forest will contribute not only the forest experience in infants being activated but also to improve harmful environment such as fine particulate matter.

Design and Implementation of an Indoor Particulate Matter and Noise Monitoring System (실내 미세먼지 및 소음 모니터링 시스템 설계 및 구현)

  • Cho, Hyuntae
    • IEMEK Journal of Embedded Systems and Applications
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    • v.17 no.1
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    • pp.9-17
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    • 2022
  • As the COVID-19 pandemic situation worsens, the time spent indoors increases, and the exposure to indoor environmental pollution such as indoor air pollution and noise also increases, causing problems such as deterioration of human health, stress, and discord between neighbors. This paper designs and implements a system that measures and monitors indoor air quality and noise, which are representative evaluation criteria of the indoor environment. The system proposed in this paper consists of a particulate matter measurement subsystem that measures and corrects the concentration of particulate matters to monitor indoor air quality, and a noise measurement subsystem that detects changes in sound and converts it to a sound pressure level. The concentration of indoor particulate matters is measured using a laser-based light scattering method, and an error caused by temperature and humidity is compensated in this paper. For indoor noise measurement, the voltage measured through a microphone is basically measured, Fourier transform is performed to classify it by frequency, and then A-weighting is performed to correct loudness equality. Then, the RMS value is obtained, high-frequency noise is removed by performing time-weighting, and then SPL is obtained. Finally, the equivalent noise level for 1 minute and 5 minutes are calculated to show the indoor noise level. In order to classify noise into direct impact sound and air transmission noise, a piezo vibration sensors is mounted to determine the presence or absence of direct impact transmitted through the wall. For performance evaluation, the error of particulate matter measurement is analyzed through TSI's AM510 instrument. and compare the noise error with CEM's noise measurement system.

A Study on the treatment efficiency of A2O Process coupled with Mesh Screening Reactor (Mesh Screening Reactor와 결합된 A2O 공정의 처리효율에 관한 연구)

  • Whang, Gye-Dae;Lim, Dong-Min
    • Journal of Korean Society of Water and Wastewater
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    • v.22 no.6
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    • pp.705-714
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    • 2008
  • Three Mesh Screenning Reactors (MSRs) were operated in three different modes to investigate the effect of the mesh opening size and the filtrate flux on the removal of particulate matters and the production of soluble organic matters. The mesh opening size was $82{\mu}m$ (Mode 1), $61{\mu}m$ (Mode 2) and $38{\mu}m$ (Mode 3), respectively, and each mode has three different filtrate flux; $0.47m^3/m^2/d$, $0.95m^3/m^2/d$ and $1.42m^3/m^2/d$, respectively. TSS removal efficiency of mode 1, 2, and 3 fed with 191 mgTSS/L was 27%, 36%, and 60%, respectively. The SCOD concentration of 91mg/L in influent for the mode 1, 2, and 3 increased to 117 mg/L, 127 mg/L, and 155 mg/L, respectively. For the all MSRs, there was no significant effect of filtrate flux on the removal of particulate matters and the production of soluble organic matters. However, the mesh opening size greatly affected the removal of particulate matters and the production of soluble organic matters in wastewater. Three parallel A2O processes consisting of anaerobic, anoxic and aerobic reactors maintaining mixed liquor suspended solids (MLSS) of 3,000 mg/L were operated to investigate the effectiveness of MSR on the removal efficiencies of the organic matters, nitrogen, and phosphorus; MSR influent was introduced to System 1 (183 mgTSS/L, 324 mgTCOD/L, 87 mgSCOD/L, 45.2 mgTKN/L, and 6.6 mgTP/L) and MSR efluent was introduced to System 2 and 3(72 mgTSS/L, 289 mgTCOD/L, 141 mgSCOD/L, 40.2 mgTKN/L, and 4.2 mgTP/L). HRTs of the anaerobic reactors in systems 1, 2 and 3 were 1 h, 1 h and 0.6 h, respectively and anoxic reactors were 2 h in all systems. HRTs of the aerobic reactors in systems 1, 2 and 3 were 5 h, 3 h and 3 h, respectively. TSS concentration in effluent of both system 2 and 3 is about 8 mg/L and lower than that of system 1 effluent. Despite higher TCOD loading and SCOD loading, both Systems 2 and 3 had a greater TCOD and SCOD removal efficiency at 91% and 92% than System 1 was at 88% and 82%, respectively. The nitrification efficiency for system 2 was greater than observed for System 1 (99% verses 97%). The denitrification efficiency for systems 1, 2 and 3 was 78%, 88% and 87%, respectively. System 2 and 3 showed about 12% higher TN removal efficiency than system 1 (85% verses 73%). The effluent TP concentration for system 2 was less than observed for system 1 and 3.

Particulate Matter AQI Index Prediction using Multi-Layer Perceptron Network (다층 퍼셉트론 신경망을 이용한 미세먼지 AQI 지수 예측)

  • Cho, Kyoung-woo;Lee, Jong-sung;Oh, Chang-heon
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2019.05a
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    • pp.540-542
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    • 2019
  • With many announcements on air pollution and human effects from particulate matters, particulate matter forecasts are attracting a lot of public attention. As a result, various efforts have been made to increase the accuracy of particulate matter forecasting by using statistical modeling and machine learning technique. In this paper, the particulate matter AQI index prediction is performed using the multilayer perceptron neural network for particulate matter prediction. For this purpose, a prediction model is designed by using the meteorological factors and particulate matter concentration values commonly used in a number of studies, and the accuracy of the particulate matter AQI prediction is compared.

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A Study on the Performance of the Diesel Particulate Filter made of Porous Metal with Fe-based Fuel Additive (Fe 첨가제를 적용한 금속분말 필터의 포집 및 재생 특성에 관한 연구)

  • Park, S.H.;Chun, K.M.;Cho, G.B.;Jeong, Y.I.;Park, Y.L.
    • Proceedings of the KSME Conference
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    • 2001.06d
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    • pp.802-806
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    • 2001
  • Diesel particulate trap is the most reliable system to reduce the particulate matters from diesel engine. Filter is the core component of DPF and ceramic monolith type is dominantly used, which is expensive and fragile relatively at thermal shock. Porous metal filter, which has superior thermal characteristics and low cost, was tested in order to analyze the regeneration performance by using with ferrocene additive. This filter showed the 72% filtration efficiency, additives itself diminished 48% of PM from engine out emission, and final PM reduction ratio of 89% was achieved by DPF system with D-13 test mode.

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A Study on the Control Characteristics for Reduction of Particulate Material by HC Injection (HC 분사에 의한 디젤 분진 저감의 제어특성 연구)

  • Kim, Byeong-Woo;Hur, Jin
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.58 no.5
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    • pp.968-975
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    • 2009
  • The goals of this research are to understand the regeneration characteristics in diesel particulate filter using the HC injection. This research emphasized on the development of Continuously Regenerating DOC/DPF and HC technology which was the best particulate matters removing technology of current existing technology. This experimental study has been conducted with equipped a Continuously Regenerating DOC/DPF and HC injection on displacement 2.0, 3.3 $\ell$ diesel engine and compared in terms of particulate material and emission. In this study, we could constructed 3 kinds of database according to quantity of temperature to decide the HC injection quantity and develop DOC/DPF ECU algorithm.