• Title/Summary/Keyword: Exposure Measures

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Derivation of Green Infrastructure Planning Factors for Reducing Particulate Matter - Using Text Mining - (미세먼지 저감을 위한 그린인프라 계획요소 도출 - 텍스트 마이닝을 활용하여 -)

  • Seok, Youngsun;Song, Kihwan;Han, Hyojoo;Lee, Junga
    • Journal of the Korean Institute of Landscape Architecture
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    • v.49 no.5
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    • pp.79-96
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    • 2021
  • Green infrastructure planning represents landscape planning measures to reduce particulate matter. This study aimed to derive factors that may be used in planning green infrastructure for particulate matter reduction using text mining techniques. A range of analyses were carried out by focusing on keywords such as 'particulate matter reduction plan' and 'green infrastructure planning elements'. The analyses included Term Frequency-Inverse Document Frequency (TF-IDF) analysis, centrality analysis, related word analysis, and topic modeling analysis. These analyses were carried out via text mining by collecting information on previous related research, policy reports, and laws. Initially, TF-IDF analysis results were used to classify major keywords relating to particulate matter and green infrastructure into three groups: (1) environmental issues (e.g., particulate matter, environment, carbon, and atmosphere), target spaces (e.g., urban, park, and local green space), and application methods (e.g., analysis, planning, evaluation, development, ecological aspect, policy management, technology, and resilience). Second, the centrality analysis results were found to be similar to those of TF-IDF; it was confirmed that the central connectors to the major keywords were 'Green New Deal' and 'Vacant land'. The results from the analysis of related words verified that planning green infrastructure for particulate matter reduction required planning forests and ventilation corridors. Additionally, moisture must be considered for microclimate control. It was also confirmed that utilizing vacant space, establishing mixed forests, introducing particulate matter reduction technology, and understanding the system may be important for the effective planning of green infrastructure. Topic analysis was used to classify the planning elements of green infrastructure based on ecological, technological, and social functions. The planning elements of ecological function were classified into morphological (e.g., urban forest, green space, wall greening) and functional aspects (e.g., climate control, carbon storage and absorption, provision of habitats, and biodiversity for wildlife). The planning elements of technical function were classified into various themes, including the disaster prevention functions of green infrastructure, buffer effects, stormwater management, water purification, and energy reduction. The planning elements of the social function were classified into themes such as community function, improving the health of users, and scenery improvement. These results suggest that green infrastructure planning for particulate matter reduction requires approaches related to key concepts, such as resilience and sustainability. In particular, there is a need to apply green infrastructure planning elements in order to reduce exposure to particulate matter.

Study on Standardization of the Environmental Impact Evaluation Method of Extremely Low Frequency Magnetic Fields near High Voltage Overhead Transmission Lines (고압 가공송전선로의 극저주파자기장 환경영향평가 방법 표준화에 관한 연구)

  • Park, Sung-Ae;Jung, Joonsig;Choi, Taebong;Jeong, Minjoo;Kim, Bu-Kyung;Lee, Jongchun
    • Journal of Environmental Impact Assessment
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    • v.27 no.6
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    • pp.658-673
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    • 2018
  • Social conflicts with extremely low frequency magnetic field(ELF-MF) exposures are expected to exacerbate due to continued increase in electric power demand and construction of high voltage transmission lines(HVTL). However, in current environmental impact assessment(EIA) act, specific guidelines have not been included concretely about EIA of ELF-MF. Therefore, this study conducted a standardization study on EIA method through case analysis, field measurement, and expert consultation of the EIA for the ELF-MF near HVTL which is the main cause of exposures. The status of the EIA of the ELF-MF and the problem to be improved are derived and the EIA method which can solve it is suggested. The main contents of the study is that the physical characteristics of the ELF-MF affected by distance and powerload should be considered at all stages of EIA(survey of the current situation - Prediction of the impacts - preparation of mitigation plan ? post EIA planning). Based on this study, we also suggested the 'Measurement method for extremely low frequency magnetic field on transmission line' and 'Table for extremely low frequency magnetic field measurement record on transmission line'. The results of this study can be applied to the EIA that minimizes the damage and conflict to the construction of transmission line and derives rational measures at the present time when the human hazard to long term exposure of the ELF-MF is unclear.

Changes in State Curiosity and State Anxiety in Science Learning Depending on Confronting Violation of Expectation (과학 학습에서 불일치 현상 대면 여부에 따른 상태호기심 및 상태불안의 변화)

  • Kang, Jihoon;Kim, Jina
    • Journal of Korean Elementary Science Education
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    • v.41 no.3
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    • pp.521-537
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    • 2022
  • State curiosity and state anxiety in the science learning have a great influence on academic performance and achievement. Since the levels of state curiosity and anxiety can change at any moment, it is essential to identify the levels of student's state curiosity and state anxiety throughout the course of science learning. Accordingly, we assessed the changes in state curiosity and anxiety levels sensed by 5th- and 6th-grade elementary school students depending on their exposure to the violation of expectation. To this end, we classified science learning into three situations: confronting a scientific task, checking the result, and learning science concepts. As a result, there was no significant difference in state curiosity level of the nVOE group who confronting the result consistent with their expectations in checking the result after confronting a scientific task, but the state curiosity level of the VOE group who facing violation of their expectation increased. In the VOE groups, there was no significant change in the state curiosity level of the VOE-R group who correctly inferred the reason for the result, but that of the VOE-FR group who could not correctly inferred increased. The state anxiety levels of the VOE and nVOE groups decreased after checking the result of the task. The state anxiety level also declined in the VOE-R group. In contrast, there was no significant change in state anxiety level of the VOE-FR group. In learning science concepts of the result after checking the result, the state curiosity of the VOE, nVOE, and VOE-FR group all faded. No significant change was observed in the state anxiety level of the nVOE group, whereas the VOE, VOE-R, and VOE-FR group presented a decreased state anxiety. This study discusses the educational implication of these findings and its outcomes are expected to broaden the understanding of emotional states of students in science learning.