• Title/Summary/Keyword: Evaluation Area

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Evaluation of urban regeneration projects in accordance with the type of declining area - Focusing on the declining area in Daejeon - (쇠퇴지역의 유형에 따른 도시재생사업의 평가 - 대전광역시 쇠퇴지역을 중심으로 -)

  • Park, So-Yeon;Oh, Deog-Seong
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.16 no.7
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    • pp.4984-4991
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    • 2015

  • This study derives the city's declining area by the type, and evaluates urban regeneration projects to sustainable urban regeneration planning factors. And assess whether urban regeneration projects are suitable for declining aspect of area. Application of sustainable urban regeneration plan factors of 19 declining areas is found to be less than 'normal'. This showed that urban regeneration projects not being actively enforced. All areas except hoedeokdong have been estimated that urban regeneration projects did not enforce the corresponding type on the decline, it still showed that concentrated on the physical regeneration projects. Excavation of social, economic regeneration projects that can respond to the type of decline and integrated, ongoing urban regeneration efforts are needed.

  • https://doi.org/10.5762/KAIS.2015.16.7.4984 인용 PDF KSCI

Evaluation and Complement of the Representativeness of Air Quality Monitoring Stations Using Passive Air Samplers (수동측정기에 의한 대기오염 자동측정망의 지역대표성 조사 및 보완방완에 대한 기초연구)

  • 우정현;김선태;김정욱
    • Journal of Korean Society for Atmospheric Environment
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    • v.13 no.6
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    • pp.415-426
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    • 1997

  • Some arguments have been about over the representativeness of government-run air quality monitoring stations among scholars and non-governmental organizations (NGOs). However, it is not a simple problem to move monitoring stations because of continuity of data and high cost. So it is necessary to complement the monitoring data if it do not represent the ambient air quality properly. The purpose of this study was to evaluate the representativeness of some monitoring stations using passive $NO_2$ samplers and to find a complementary method from linear regression. Two stations were chosen for the evaluation: Shinlim Station was one of the most controversial stations in Seoul and Banpo Station had the best reputation. Air qualities were surveyed at seven points around each monitoring station with consideration of land use and distance. The ratios of the average $NO_2$ levels of the areas to these at the monitoring stations were 1.59 for Shinlim Station and 1.03 for Banpo Station. The differences between the average $NO_2$ levels and those at the monitoring stations were 10.75 ppb for Shilim Station and 0.34 ppb for Banpo Station. The correlation coefficients between the two levels were 0.7668 for Shinlim and 0.7662 for Banpo. The average coefficients of determination $(R^2)$ were 0.61 for Shinlim and 0.61 for Banpo. The Shinlim Station could not represent the air quality of Shinlim-Dong good because it is located in a green area at an outskirt of Shinlim-Dong. But the Banpo Station located in a central residential area of Banpo-Dong showed a fair representativeness. However, air quality turned out to be different with land use such as residential area, green area or road: the air quality data from a monitoring station located at a certain land use should not be interpreted as representing the air quality at any sites around the station. Equations to predict the average $NO_2$ levels of each area from the data from the monitoring stations were presented based on linear regression.

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