• Title/Summary/Keyword: lidar ratio

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The Study of PM10, PM2.5 Mass Extinction Efficiency Characteristics Using LIDAR Data (라이다 데이터를 이용한 PM10, PM2.5 질량소산효율 특성 연구)

  • Kim, TaeGyeong;Joo, Sohee;Kim, Gahyeong;Noh, Youngmin
    • Korean Journal of Remote Sensing
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    • v.37 no.6_2
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    • pp.1793-1801
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    • 2021
  • From 2015 to June 2020, the backscattering coefficients of 532 and 1064 nm measured using LIDAR and the depolarization ratio at 532 nm were used to separate the backscattering coefficient at 532 nm as three types as PM10, PM2.5-10, PM2.5 according to particle size. The mass extinction efficiency (MEE) of three types was calculated using the mass concentration measured on the ground. The overall mean values of the calculated MEE were 5.1 ± 2.5, 1.7 ± 3.7, and 9.3 ± 6.3 m2/g in PM10, PM2.5-10, and PM2.5, respectively. When the mass concentration of PM10 and PM2.5 was low, higher than average MEE was calculated, and it was confirmed that the MEE decreased as the mass concentration increased. When the MEE was calculated for each type according to the mixing degree of Asian dust, PM2.5-10 was twice at pollution aerosol as high as 2.1 ± 2.8 m2/g, compare to pollution-dominated mixture, dust-dominated mixture, and pure dust of 1.1 ± 1.8, 1.4 ± 3.3, 1.1 ± 1.5 m2/g, respectively. However, PM2.5 MEE showed similar values irrespective of type: 9.4 ± 6.5, 9.0 ± 5.8, 10.3 ± 7.5, and 9.1 ± 9.0 m2/g. The MEE of PM10 was 5.6 ± 2.9, 4.4 ± 2.0, 3.6 ± 2.9, and 2.8 ± 2.4 m2/g in pollution aerosol (PA), pollution-dominated mixture (PDM), dust-dominated mixture (DDM), and pure dust (PD), respectively, and increased as the dust ratio value decreased. Even if the same type according to the same mass concentration or Asian dust mixture was shown, as the PM2.5/PM10 ratio decreased, the MEE of PM2.5-10 decreased and the MEE of PM2.5 showed a tendency to increase.

The Study on the Quantitative Dust Index Using Geostationary Satellite (정지기상위성 자료를 이용한 정량적 황사지수 개발 연구)

  • Kim, Mee-Ja;Kim, Yoonjae;Sohn, Eun-Ha;Kim, Kum-Lan;Ahn, Myung-Hwan
    • Atmosphere
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    • v.18 no.4
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    • pp.267-277
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    • 2008
  • The occurrence and strength of the Asian Dust over the Korea Peninsular have been increased by the expansion of the desert area. For the continuous monitoring of the Asian Dust event, the geostationary satellites provide useful information by detecting the outbreak of the event as well as the long-range transportation of dust. The Infrared Optical Depth Index (IODI) derived from the MTSAT-1R data, indicating a quantitative index of the dust intensity, has been produced in real-time at Korea Meteorological Administration (KMA) since spring of 2007 for the forecast of Asian dust. The data processing algorithm for IODI consists of mainly two steps. The first step is to detect dust area by using brightness temperature difference between two thermal window channels which are influenced with different extinction coefficients by dust. Here we use dynamic threshold values based on the change of surface temperature. In the second step, the IODI is calculated using the ratio between current IR1 brightness temperature and the maximum brightness temperature of the last 10 days which we assume the clear sky. Validation with AOD retrieved from MODIS shows a good agreement over the ocean. Comparison of IODI with the ground based PM10 observation network in Korea shows distinct characteristics depending on the altitude of dust layer estimated from the Lidar data. In the case that the altitude of dust layer is relatively high, the intensity of IODI is larger than that of PM10. On the other hand, when the altitude of dust layer is lower, IODI seems to be relatively small comparing with PM10 measurement.

Aerosol-extinction Retrieval Method at Three Effective RGB Wavelengths Using a Commercial Digital Camera (상용 디지털 카메라를 이용한 3가지 유효 RGB 파장에서의 미세먼지 소산계수 산출법)

  • Park, Sunho;Kim, Dukhyeon
    • Korean Journal of Optics and Photonics
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    • v.31 no.2
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    • pp.71-80
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    • 2020
  • In this article, we suggest a new method for measuring an aerosol's extinction coefficient using a commercial camera. For a given image, we choose three pixel-points that are imaged for the same kinds of objects located in similar directions. We suggest and calculate aerosol extinction coefficients from these RGB gray levels and the different distances of the three objects. To compare our measurement results, we also measure extinction coefficients using lidar. Finally, we find that there are meaningful and sensible correlations between these two measurements, with a correlation coefficient of 0.86. We measure the aerosol extinction coefficient at three different RGB wavelengths using the same method. From these aerosol extinction coefficients at three different wavelengths, we find that the Angstrom exponent ranges from 0.7 to 1.6 over a full daytime period. We believe that these Angstrom exponents can give important information about the size of the fine particles.

A Study of Hazard Analysis and Monitoring Concepts of Autonomous Vehicles Based on V2V Communication System at Non-signalized Intersections (비신호 교차로 상황에서 V2V 기반 자율주행차의 위험성 분석 및 모니터링 컨셉 연구)

  • Baek, Yun-soek;Shin, Seong-geun;Ahn, Dae-ryong;Lee, Hyuck-kee;Moon, Byoung-joon;Kim, Sung-sub;Cho, Seong-woo
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.19 no.6
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    • pp.222-234
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    • 2020
  • Autonomous vehicles are equipped with a wide rage of sensors such as GPS, RADAR, LIDAR, camera, IMU, etc. and are driven by recognizing and judging various transportation systems at intersections in the city. The accident ratio of the intersection of the autonomous vehicles is 88% of all accidents due to the limitation of prediction and judgment of an area outside the sensing distance. Not only research on non-signalized intersection collision avoidance strategies through V2V and V2I is underway, but also research on safe intersection driving in failure situations is underway, but verification and fragments through simple intersection scenarios Only typical V2V failures are presented. In this paper, we analyzed the architecture of the V2V module, analyzed the causal factors for each V2V module, and defined the failure mode. We presented intersection scenarios for various road conditions and traffic volumes. we used the ISO-26262 Part3 Process and performed HARA (Hazard Analysis and Risk Assessment) to analyze the risk of autonomous vehicle based on the simulation. We presented ASIL, which is the result of risk analysis, proposed a monitoring concept for each component of the V2V module, and presented monitoring coverage.