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Urban Street Planting Scenarios Simulation for Micro-scale Urban Heat Island Effect Mitigation in Seoul

미시적 열섬현상 저감을 위한 도시 가로수 식재 시나리오별 분석 - 서울시를 대상으로 -

  • Kwon, You Jin (Interdisciplinary Program in Landscape Architecture, Seoul National University) ;
  • Lee, Dong Kun (Department of Landscape Architecture and Rural System Engineering, Seoul National University) ;
  • Ahn, Saekyul (Graduate School, Seoul National University)
  • 권유진 (서울대학교 협동조경학과) ;
  • 이동근 (서울대학교 조경시스템공학부) ;
  • 안새결 (서울대학교 조경시스템공학)
  • Received : 2018.09.22
  • Accepted : 2019.01.22
  • Published : 2019.02.28

Abstract

Global warming becomes a serious issue that poses subsidiary issues like a sea level rise or a capricious climate over the world. Because of severe heat-wave of the summer in Korea in 2016, a big attention has been focused on urban heat island since then. Not just about heat-wave itself, many researches have been concentrated on how to adapt in this trendy warming climate and weather in a small scope. A big part of existing studies is mitigating "Urban Heat Island effect" and that is because of huge impervious surface in urban area where highly populated areas do diverse activities. It is a serious problem that this thermal context has a high possibility causing mortality by heat vulnerability. However, there have been many articles of a green infrastructures' cooling impact in summer. This research pays attention to measure cooling effect of a street planting considering urban canyon and type of green infrastructures in neighborhood scale. This quantitative approach was proceeded by ENVI-met simulation with a spatial scope of a commercial block in Seoul, Korea. We found the dense double-row planting is more sensitive to change in temperature than that of the single-row. Among the double-row planting scenarios, shrubs which have narrow space between the plant and the land surface were found to store heat inside during the daytime and prevent emitting heat so as to have a higher temperature at night. The quantifying an amount of vegetated spaces' cooling effect research is expected to contribute to a study of the cost and benefit for the planting scenarios' assessment in the future.

지구온난화는 해수면 상승이나 전 세계의 변덕스러운 기후와 같은 심각하면서 부차적인 문제를 야기한다. 2015년 여름에 심각한 폭염이 있은 이래로, 도시열섬에 대한 큰 관심이 모아졌다. 폭염 자체에 대한 연구뿐만이 아니라, 많은 연구가 온난화된 기후와 미시 기후에 적응하는 방법에 중점을 둔다. 기존 연구들의 상당부분은 도시열섬 효과를 완화하는 것인데, 이는 다양한 활동을 하고 있는 인구가 많은 도시 지역에 거대한 불침투성 표면이 존재하고 있기 때문이다. 또한 이 열 환경이 열 취약성에 의한 사망을 초래할 가능성이 높다는 것은 심각한 문제이다. 여름철 그린인프라의 냉각효과에 대한 논문이 많이 있어왔지만, 본 연구는 도시 협곡과 인접한 그린인프라 유형을 고려하여 가로수의 냉각 효과를 측정하는 데에 집중했다. 이 정량적 접근은 ENVI-met 시뮬레이션을 통해 서울의 상업지역 블록에서 진행되었다. 연구결과로 밀도가 높은 2열 식재가 단열식재보다 온도 변화에 더 민감하다는 것을 발견했다. 2열 식재 시나리오 중 가로수와 지표면 사이의 공간이 좁은 관목은 주간에 열을 저장하여 야간에 저장열 방출을 막아 더 높은 온도를 유지하는 것으로 밝혀졌다. 식생 공간의 냉각 효과를 정량화하면 미래의 비용 및 편익 평가 연구에 기여할 것으로 기대된다.

Keywords

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Figure 1. Study area street views (a, b, c) & Key map plan (d) (photos : Naver.com map street view)

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Figure 2. (a) Seasonal mean temperature, (b) location of CBD in Seoul (Seo 2014; Seoul Institute 2016)

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Figure 3. A: a domain of 3D view and B: a schematic plan for ENVI-met simulation

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Figure 4. Seven scenarios a. VS (Single-row tree), b. VM (Straight single-row shrub), c. TT (Twisted double-row tree), d. SDT (Straight doublerow tree), e. TM (Twisted double-row tree and shrub), f. TS (Twisted double-row shrub), g. VSD (Straight doublerow shrub), profiles and sections of AA’~GG’

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Figure 5. ENVI-met Simulation flow chart for seven scenarios (a process from input data using DATABASE to output data)

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Figure 6. Hourly temperature shift of 7 scenarios presenting a different gap between day and night

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Figure 7. Temperature shift in 6 scenarios (VM, VSD, SDT, TS, TM, TT), a. Temperature shift in day time (15h), b. Temperature shift in night time (23h)

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Figure 8. Heat flux diagram of TS & TT : At night TS and TT indicate that the storage heat is released from the surface of the earth and there is a difference in the numerical value of the emission heat under shrubs and trees.

Table 1. Input parameters for a scenarios’ at ENVI-met simulation

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Table 2. Temperature shift & standard deviation on each scenario at day & night (unit: ℃)

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Table 3. TT & TS significance test

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