Influence of landscape layout on microclimate in residential area based on ENVI-met simulation
-
摘要:目的
利用数值模拟不同绿化布局方案对居住区微气候的影响，以期获取最优绿化方案。
方法以广州某老旧小区为研究对象，选取典型湿热天气条件，对研究区的室外微气候要素进行测量；利用模拟软件ENVI-met构建实况数值模拟模型，将模拟结果与实测值进行对比分析，验证模型精度和质量；对研究区预设的3种绿化方案微气候特征进行模拟分析。
结果清理灌木后温度较现状平均升高0.1 ℃，湿度平均降低0.51%，可适当改善低处通风情况；去除乔木后温度升高近0.4 ℃，湿度降低1.18%，整体风速明显增大；屋顶简单式绿化具有一定的降温增湿效果，温度降低0.16 ℃，湿度增加1.17%，风速较现有绿况变化不大。
结论ENVI-met能够较好地预测温度和湿度的日变化趋势，能有效地评估老旧小区空间的营造与绿化改善效果。
Abstract:ObjectiveThe effects of different landscape layout schemes on microclimate of residential area were numerically simulated to obtain the optimal scheme.
MethodTaking an old residential area in Guangzhou as the research site, we measured key characteristics of the outdoor microclimate under typical humid and hot weather condition. A numerical simulation model was built using ENVI-met software. The accuracy and quality of the model were validated by comparing the simulation results with the measured values. The microclimate characteristics of three landscape layout schemes were simulated and analyzed.
ResultComparing with the current landscape condition, after clearing shrubs from the landscape layout, the mean temperature increased 0.1 ℃ and the mean humidity decreased 0.51%, and ventilation near the ground was moderately improved. After removing trees from the landscape layout, the mean temperature increased 0.4 ℃, the mean humidity increased 1.18%, and the overall wind speed evidently increased. After the roof was simply landscaped with green plants, the mean temperature decreased 0.16 ℃, the mean humidity increased 1.17%, and the wind speed did not obviously change.
ConclusionENVI-met model can be used to well predict the diurnal variation trend of temperature and humidity, to effectively evaluate the influence of landscape planning and improvement in old residential areas.
-
Keywords:
- microclimate /
- ENVI-met /
- old community /
- numerical simulation /
- landscape layout
-
-
![]()
图 1 研究区遥感影像图和模型示意图
Figure 1. Remote sensing image and schematic diagram of the research area
![]()
图 2 空气温度、相对湿度和风速实测结果
Figure 2. Measured air temperature, relative humidity and wind speed
![]()
图 3 不同时间点空气温度、相对湿度和风速实测与模拟结果
Figure 3. Measurement and simulation results of air temperature, relative humidity and wind speed at different time
![]()
图 4 不同实测点空气温度、相对湿度和风速实测与模拟结果
Figure 4. Measurement and simulation results of air temperature, relative humidity and wind speed at different measured points
![]()
图 5 不同绿化方案情景下的空气温度模拟分布图
Figure 5. Simulated distribution of air temperature in different greening layout
![]()
图 6 不同绿化方案情景下的相对湿度模拟分布图
Figure 6. Simulated distribution of relative humidiy in different greening layout
![]()
图 7 不同绿化方案情景下风速模拟分布图
Figure 7. Simulated distribution of wind speed in different greening layout
-
[1] 秦文翠, 胡聃, 李元征. 基于ENVI-met的北京典型住宅区微气候数值模拟分析[J]. 气象与环境学报, 2015, 31(3): 56-62. [2] SU X, CAI H, CHEN Z, et al. Influence of the ground greening configuration on the outdoor thermal environment in residential areas under different underground space overburden thicknesses[J]. Sustainability, 2017, 9(9): 1656-1679. doi: 10.3390/su9091656
[3] 陈卓伦, 赵立华, 孟庆林. 广州典型住宅小区微气候实测与分析[J]. 建筑学报, 2008, 55(11): 24-27. doi: 10.3969/j.issn.0529-1399.2008.11.007 [4] 林满, 王宝民, 刘辉志. 广州典型小区微气候特征观测与数值模拟研究[J]. 中山大学学报(自然科学版), 2015, 54(1): 124-129. [5] 章莉, 詹庆明, 蓝玉良. 武汉市居住用地绿地降温效应研究[J]. 中国园林, 2018, 34(4): 47-53. doi: 10.3969/j.issn.1000-6664.2018.04.009 [6] ALI-TOUDERT F, MAYER H. Numerical study on the effects of aspect ratio and orientation of an urban street canyon on outdoor thermal comfort in hot and dry climate[J]. Build Environ, 2006, 41(2): 94-108. doi: 10.1016/j.buildenv.2005.01.013
[7] MIDDEL A, HÄB K, BRAZEL A J, et al. Impact of urban form and design on mid-afternoon microclimate in Phoenix local climate zones[J]. Landscape Urban Plan, 2014, 122: 16-28. doi: 10.1016/j.landurbplan.2013.11.004
[8] 郑子豪, 陈颖彪, 千庆兰. 基于三维模型的城市局地微气候模拟[J]. 地球信息科学学报, 2016, 21(9): 1199-1208. [9] 方小山. 亚热带湿热地区郊野公园气候适应性规划设计策略研究[D]. 广州: 华南理工大学, 2014. [10] Department of Atmospheric Science, University of Wyoming. 59280 Qing Yuan Observations at 00Z 1 Apr 2018[DB/OL]. (2018-04-01)[2018-10-01]. http://weather.uwyo.edu/upperair/sounding.html.
[11] 广东省建设厅. 《夏热冬暖地区居住建筑节能设计标准》广东省实施细则: DBJ15-50—2006[S]. 北京: 中国建筑工业出版社, 2006: 47. [12] 詹慧娟, 解潍嘉, 孙浩, 等. 应用ENVI-met模型模拟三维植被场景温度分布[J]. 北京林业大学学报, 2014, 36(4): 64-74. [13] 杨小山. 室外微气候对建筑空调能耗影响的模拟方法研究[D]. 广州: 华南理工大学, 2012. [14] Z LCH T, MADERSPACHER J, WAMSLER C, et al. Using green infrastructure for urban climate-proofing: An evaluation of heat mitigation measures at the micro-scale[J]. Urban For Urban Gree, 2016, 20: 305-316. doi: 10.1016/j.ufug.2016.09.011
[15] CHOW W T L, POPE R L, MARTIN C A, et al. Observing and modeling the nocturnal park cool island of an arid city: Horizontal and vertical impacts[J]. Theor Appl Climatol, 2011, 103(1): 197-211.
[16] PASTORE L, CORRAO R, HEISELBERG P K. The effects of vegetation on indoor thermal comfort: The application of a multi-scale simulation methodology on a residential neighborhood renovation case study[J]. Enegr Buildings, 2017, 146: 1-11. doi: 10.1016/j.enbuild.2017.04.022
[17] LEE H, MAYER H, CHEN L. Contribution of trees and grasslands to the mitigation of human heat stress in a residential district of Freiburg, Southwest Germany[J]. Landscape Urban Plan, 2016, 148: 37-50. doi: 10.1016/j.landurbplan.2015.12.004
[18] MORAKINYO T E, DAHANAYAKE K W D K, NG E, et al. Temperature and cooling demand reduction by green-roof types in different climates and urban densities: A co-simulation parametric study[J]. Energ Buildings, 2017, 145: 226-237. doi: 10.1016/j.enbuild.2017.03.066
下载:
