• Title/Summary/Keyword: 풍향 측정

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Characteristics of Diurnal Variation of High PM2.5 Concentration by Spatio-Temporal Wind System in Busan, Korea (시·공간적 풍계에 따른 부산지역 고농도 PM2.5의 일변화 특성)

  • Kim, Bu-Kyung;Lee, Dong-In;Kim, Jeong-Chang;Lee, Jun-Ho
    • Journal of the Korean earth science society
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    • v.33 no.6
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    • pp.469-480
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    • 2012
  • This study was to analyze the characteristics of diurnal variation of high $PM_{2.5}$ concentration, $PM_{2.5}/PM_{10}$ concentration ratio by spatio-temporal wind system (wind speed and wind direction) for high $PM_{2.5}$ concentration (over the 24 hr environmental standard of $PM_{2.5}$, $50{\mu}g/m^3$) in the air quality observation sites (Jangrimdong: Industrial area, Jwadong: Residential area) that were measured for 3 years (2005. 12. 1-2008. 11. 30) in Busan. The observation days of high $PM_{2.5}$ concentration were 182 at Jangrimdong and 27 at Jwadong. The seasonal diurnal variation of hourly mean of high $PM_{2.5}$ concentration and of $PM_{2.5}/PM_{10}$ concentration ratio showed a similar pattern that had higher variation at dawn, and night and in the morning than in the afternoon. Durning daytime in summer at Jwadong, the $PM_{2.5}/PM_{10}$ concentration ratio increased because a secondary particulate matter, which was created by photochemical reaction, decreased the coarse particles of $PM_{10}$ more than the fine particles of $PM_{2.5}$ concentrations in ocean condition. We did an analysis of spatio-temporal wind system (wind speed range and wind direction) in each time zone. The result showed that high $PM_{2.5}$ concentration at Jangrimdong occurred due to the congestion of pollutants emissions from the industrial complex in Jangrimdong area and the transportation of pollutants from places nearby Jangrimdong. It also showed that high $PM_{2.5}$ concentration occurred at Jwadong because of a number of local residential and commercial activities that caused the congestion of pollutants.

A Numerical Study on the Characteristics of Flows and Fine Particulate Matter (PM2.5) Distributions in an Urban Area Using a Multi-scale Model: Part II - Effects of Road Emission (다중규모 모델을 이용한 도시 지역 흐름과 초미세먼지(PM2.5) 분포 특성 연구: Part II - 도로 배출 영향)

  • Park, Soo-Jin;Choi, Wonsik;Kim, Jae-Jin
    • Korean Journal of Remote Sensing
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    • v.36 no.6_3
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    • pp.1653-1667
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    • 2020
  • In this study, we coupled a computation fluid dynamics (CFD) model to the local data assimilation and prediction system (LDAPS), a current operational numerical weather prediction model of the Korea Meteorological Administration. We investigated the characteristics of fine particulate matter (PM2.5) distributions in a building-congested district. To analyze the effects of road emission on the PM2.5 concentrations, we calculated road emissions based on the monthly, daily, and hourly emission factors and the total amount of PM2.5 emissions established from the Clean Air Policy Support System (CAPSS) of the Ministry of Environment. We validated the simulated PM2.5 concentrations against those measured at the PKNU-AQ Sensor stations. In the cases of no road emission, the LDAPS-CFD model underestimated the PM2.5 concentrations measured at the PKNU-AQ Sensor stations. The LDAPS-CFD model improved the PM2.5 concentration predictions by considering road emission. At 07 and 19 LST on 22 June 2020, the southerly wind was dominant at the target area. The PM2.5 distribution at 07 LST were similar to that at 19 LST. The simulated PM2.5 concentrations were significantly affected by the road emissions at the roadside but not significantly at the building roof. In the road-emission case, the PM2.5 concentration was high at the north (wind speeds were weak) and west roads (a long street canyon). The PM2.5 concentration was low in the east road where the building density was relatively low.

A Study on Variable Speed Limit Considering Wind Resistance on Off-Shore Bridge (해상교량의 풍하중을 고려한 제한 속도 도출 방안)

  • Lee, Seon-Ha;Kang, Hee-Chan
    • Journal of Korean Society of Transportation
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    • v.22 no.5
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    • pp.75-87
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    • 2004
  • Along the seashore regions in Korea, though strong winds with very large strength are frequently witnessed, no system which can provide appropriate speed information for driving vehicle has been introduced. The driving against strong winds could be very dangerous because of the high possibility of accidents such as rollover and collision. These accidents usually resulted from driver's forced driving try even in difficult situation for steering vehicle, and sometimes overspeed without consideration of wind impact to the vehicles. To reduce accident caused by strong winds, it is important to inform drivers of appropriate driving speeds by perceiving strong winds. By setting up WIS at the main points where strong winds frequently appear and using the variable message sign(VMS) connected to the on-line whether information system, it tis possible to provide desired speed information, which can maintain vehicles' tractive force and maximum running resistance. The case study is conducted on the case of Mokpo-Big-Bridge, which is under construction at Mokpo city. The result show that in case the annual average direction of wind is South and the wind speed is over 8m/hr, the desired speed, which is required in order for vehicles running to South direction to maintain the marginal driving power, is 60km/hr. In addition, for the case of a typhoon such as Memi generated in 2003 year, if wind speed had been 18m/sec in Mokpo city at that time, the running resistance at the speed of 40km/hr is calculated as 1131N. This resistance can not be overcome at the 4th gear(1054N) level, therefore, the gear of vehicles should be reduced down to the 3rd level. In this case, the appropriate speed is 40km/h, and at this point the biggest difference between running resistance and tractive force is generated.

A Case Study on the Impact of Ground-based Glaciogenic Seeding on Winter Orographic Clouds at Daegwallyeong (겨울철 대관령지역 지형성 구름에 대한 지상기반 구름씨뿌리기 영향 사례연구)

  • Yang, Ha-Young;Chae, Sanghee;Jeong, Jin-Yim;Seo, Seong-Kyu;Park, Young-San;Kim, Baek-Jo
    • Journal of the Korean earth science society
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    • v.36 no.4
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    • pp.301-314
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    • 2015
  • The purpose of this study was to investigate the impact of ground-based glaciogenic seeding on orographic clouds in the Daegwallyeong area on 13 March, 2013. The experiments was conducted by releasing silver iodide (AgI) under following conditions: surface temperature below $-4^{\circ}C$, wind direction between 45 and $130^{\circ}$, and wind speed less than $5ms^{-1}$. Two seeding rates, $38gh^{-1}$ (SR1) and $113gh^{-1}$ (SR2), were tested to obtain an appropriate AgI ratio for snowfall enhancement in the Daegwallyeong area. Numerical simulations were carried out by using the WRF (Weather Research and Forecast) model with AgI point-source module which predicted dispersion fields of AgI particles. The results indicated that the target orographic clouds contained adequate amount of supercooled liquid water and that the dispersion of AgI particles tended to move along the prevailing wind direction. To validate the seeding effects, the observation data from FM-120 and MPS as well as PARSIVEL disdrometer were analyzed. In this case study, glaciogenic seeding significantly increased the concentration of small ice particles below 1 mm in diameter. The observation results suggest that SR1 seeding be reasonable to use the ground-based seeding in the Daegwallyeong area.

Analysis of the efficiency of natural ventilation in a multi-span greenhouse using CFD simulation (CFD 시뮬레이션을 이용한 연동형 온실 내 자연환기의 효율성 분석)

  • Short, Ted H.
    • Journal of Bio-Environment Control
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    • v.8 no.1
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    • pp.9-18
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    • 1999
  • Natural ventilation in a four and one-half span, double polyethylene commercial greenhouse was investigated with actual data collected at Quailcrest Farm near Wooster, Ohio. Moreover, a computational fluid dynamics (CFD) numerical technique, FLUENT V4.3, was used to predict natural ventilation rates, thermal conditions, and airflow distributions in the greenhouse. The collected climate data showed that the multi-span greenhouse was well ventilated by the natural ventilation system during the typical summer weather conditions. The maximum recorded air temperature difference between inside and outside the greenhouse was 3.5$^{\circ}C$ during the hottest (34.7$^{\circ}C$) recorded sunny day; the air temperatures in the greenhouse were very uniform with the maximum temperature difference between six widely dispersed locations being only 1.7$^{\circ}C$. The CFD models predicted that air exchange rates were as high as 0.9 volume per minute (A.C. .min$^{-1}$ ) with 2.5m.s$^{-1}$ winds from the west as designed.

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Observations on the Coastal Ocean Response to Typhoon Maemi at the East Sea Real-time Ocean Buoy (동해 실시간 해양관측 부이로부터 관측한 태풍 매미에 대한 연안해양의 반응 고찰)

  • Nam, Sung-Hyun;Yun, Jae-Yul;Kim, Kuh
    • The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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    • v.9 no.3
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    • pp.111-118
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    • 2004
  • An ocean buoy was deployed 10 km off Donghae city, Korea at a depth of 130 m to measure meteorological (air pressure, air temperature, wind speed, wind gust, wind direction, relative humidity) and oceanographic data (water properties and currents in the whole column) in real-time. The buoy recorded a maximum wind gust of 25 m/s (10 minutes' average speed of 20 m/s) and a minimum air pressure of 980 hPa when the eye of typhoon Maemi passed by near the Uljin city, Korea at 03:00 on 13 September 2003. The wave height reached maximum of 9 m with the significant wave height of 4 m at 04:00 (1 hour after the passage of Maemi). The currents measured near the surface reached up to about 100 cm/s at 13:00 (10 hours after the passage of Maemi). The mixed layer (high temperature and low salinity) thickness, which was accompanied by strong southward current, gradually increased from 20 m to 40 m during the 10 hours. A simple two layer model for the response to an impulsive alongshore wind over an uniformly sloping bottom developed by Csanady (1984) showed reasonable estimates of alongshore and offshore currents and interface displacement for the condition of typhoon Maemi at the buoy position (x=8.15 km) during the 10 hours.

Air-conditioning and Heating Time Prediction Based on Artificial Neural Network and Its Application in IoT System (냉난방 시간을 예측하는 인공신경망의 구축 및 IoT 시스템에서의 활용)

  • Kim, Jun-soo;Lee, Ju-ik;Kim, Dongho
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2018.05a
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    • pp.347-350
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    • 2018
  • In order for an IoT system to automatically make the house temperature pleasant for the user, the system needs to predict the optimal start-up time of air-conditioner or heater to get to the temperature that the user has set. Predicting the optimal start-up time is important because it prevents extra fee from the unnecessary operation of the air-conditioner and heater. This paper introduces an ANN(Artificial Neural Network) and an IoT system that predicts the cooling and heating time in households using air-conditioner and heater. Many variables such as house structure, house size, and external weather condition affect the cooling and heating. Out of the many variables, measurable variables such as house temperature, house humidity, outdoor temperature, outdoor humidity, wind speed, wind direction, and wind chill was used to create training data for constructing the model. After constructing the ANN model, an IoT system that uses the model was developed. The IoT system comprises of a main system powered by Raspberry Pi 3 and a mobile application powered by Android. The mobile's GPS sensor and an developed feature used to predict user's return.

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Study on the Local Weather Characteristics using Observation Data at the Boseong Tall Tower (보성 종합기상탑 자료를 활용한 국지기상 특성 연구)

  • Hwang, Sung Eun;Lee, Young Tae;Shin, Seung Sook;Kim, Ki Hoon
    • Journal of the Korean earth science society
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    • v.41 no.5
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    • pp.459-468
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    • 2020
  • In this study, the selection criteria for the occurrence of sea breezes in the Boseong area during the spring season (March-May) of 2016-2017 were prepared for the analysis of vertical weather characteristics. For this purpose, wind speed values were determined using the measured precipitation, cloud volume, wind direction, the difference between the ground and sea temperature, a wind Profiler at an altitude of 1 km, and numerical model data. The dates of the sea breezes in Boseong were classified according to the selection criteria, and the spatial and temporal characteristics of the sea breezes were identified by analyzing the time and altitude of the sea breeze and the size of the wind speed. Sea breezes occurred 23 out of 183 days (12%), and in Boseong, at least 1.2 out of 10 spring days exhibited sea breezes. Sea winds ranged from 1200 to 1800 LST, mainly from ground to 700 m altitude during the day. In addition, the maximum wind speed averaged 4.9 m s-1, at an altitude of 40 m at 1600 LST, showing relatively lower values than those in a preceding study. This seems to be owing to the reduction in wind speed due to the complexity of the coastal terrain.

Optical Properties of Aerosol at Gongju Estimated by Ground-based Measurements Using Sky-radiometer (스카이라디오미터(Sky-radiometer)로 관측된 공주지역 에어로솔의 광학적 특성)

  • Kwak, Chong-Heum;Suh, Myoung-Seok;Kim, Maeng-Ki;Kwak, Seo-Youn;Lee, Tae-Hee
    • Journal of the Korean earth science society
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    • v.26 no.8
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    • pp.790-799
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    • 2005
  • We investigate the optical properties of aerosols over Gongju by an indirect method using the pound measurement, Sky-radiometer. The analysis period is from January to December, 2004. Skyrad. pack.3 is used to estimate the optical properties, such as the aerosol optical thickness (AOT), single scattering albedo (SSA), ${\AA}ngstron$ exponent $({\alpha})$ and size distribution, of aerosols from the ground measured radiance data. And qualify control is applied to minimize the cloud-contaminated data and improve the quality of analysis results. The 12-month average of AOT, ${\alpha}$, and SSA are 0.46, 1.14, and 0.91, respectively. The average volume spectra of aerosols shows a bi-modal distribution, the first peak at fine mode and the second peak at coarse mode. AOT and coarse particles clearly increases while SSA decreases during the Asian dust events. The optical properties of aerosols at Gongju vary with?seasons, but those are not influenced by the wind direction.

Evaluation and Predicting PM10 Concentration Using Multiple Linear Regression and Machine Learning (다중선형회귀와 기계학습 모델을 이용한 PM10 농도 예측 및 평가)

  • Son, Sanghun;Kim, Jinsoo
    • Korean Journal of Remote Sensing
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    • v.36 no.6_3
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    • pp.1711-1720
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    • 2020
  • Particulate matter (PM) that has been artificially generated during the recent of rapid industrialization and urbanization moves and disperses according to weather conditions, and adversely affects the human skin and respiratory systems. The purpose of this study is to predict the PM10 concentration in Seoul using meteorological factors as input dataset for multiple linear regression (MLR), support vector machine (SVM), and random forest (RF) models, and compared and evaluated the performance of the models. First, the PM10 concentration data obtained at 39 air quality monitoring sites (AQMS) in Seoul were divided into training and validation dataset (8:2 ratio). The nine meteorological factors (mean, maximum, and minimum temperature, precipitation, average and maximum wind speed, wind direction, yellow dust, and relative humidity), obtained by the automatic weather system (AWS), were composed to input dataset of models. The coefficients of determination (R2) between the observed PM10 concentration and that predicted by the MLR, SVM, and RF models was 0.260, 0.772, and 0.793, respectively, and the RF model best predicted the PM10 concentration. Among the AQMS used for model validation, Gwanak-gu and Gangnam-daero AQMS are relatively close to AWS, and the SVM and RF models were highly accurate according to the model validations. The Jongno-gu AQMS is relatively far from the AWS, but since PM10 concentration for the two adjacent AQMS were used for model training, both models presented high accuracy. By contrast, Yongsan-gu AQMS was relatively far from AQMS and AWS, both models performed poorly.