基于ENVI-met的广州市街区夏季热环境和热舒适度变化数值模拟

李海燕; 孙家仁; 李江波; 潘蔚娟; 吴晓绚; 翟志宏

doi:10.16032/j.issn.1004-4965.2025.004

基于ENVI-met的广州市街区夏季热环境和热舒适度变化数值模拟

doi: 10.16032/j.issn.1004-4965.2025.004

1.
广州市生态与农业气象中心，广东广州 511430
2.
生态环境部华南环境科学研究所/广东省大气污染控制工程实验室，广东广州 510655
3.
广州大学土木工程学院，广东广州 510006

基金项目:

广东省气象局科学技术研究项目 GRMC2022M21

广州市气象学会科研项目 M202218

广东省自然科学基金重点项目 2016A030311007

广东省自然科学基金面上项目 2023A1515012240

详细信息

通讯作者:
孙家仁，男，黑龙江省人，研究员，主要从事气候与环境研究。E-mail：sunjiaren@scies.org

中图分类号: P435
计量
- 文章访问数: 22
- HTML全文浏览量: 8
- PDF下载量: 5
- 被引次数: 0
出版历程
- 收稿日期: 2023-09-28
- 修回日期: 2024-11-28
- 网络出版日期: 2025-05-17
- 刊出日期: 2025-02-20

ENVI-met Simulation of Summer Thermal Environment and Thermal Comfort Changes in Guangzhou Urban Blocks

1.
Guangzhou Ecological and Agricultural Meteorological Center, Guangzhou 511430, China
2.
Guangdong Province Engineering Laboratory for Air Pollution Control, South China Institute of Environmental Sciences, MEE, Guangzhou 510655, China
3.
School of Civil Engineering, Guangzhou University, Guangzhou 510006, China

摘要

摘要: 基于微气候数值模式ENVI-met，模拟分析夏季高温环境下广州市街区的热环境特征及其舒适度响应。结果表明：模式能较好地再现区域温度和湿度的日变化特征(均方根误差分别为0.99 ℃、6.1%)。研究区域内下垫面绿化覆盖对行人活动高度处的温度影响很大，气象观测场硬化地面区域形成局部热岛现象温度接近38 ℃，建筑和植被遮挡形成的阴影区域出现局部降温现象；极度热区域面积(PET＞41 ℃)占比为66.82%，主要出现在硬化地面区。无植被时，研究区域内温度整体升高，区域平均温度升高2.0 ℃，高温面积增加了34.4%，植被降温效应在垂直方向上可延伸至13 m；风速增幅最大1.0 m · s^-1，温度较高区域面积(Mean Rediant Temperature，MRT＞58 ℃)增加了36.96%；极度热区域增加了23.13%。因此，良好的风环境、有效的阴影利用、良好的绿化布局都可以优化街区室外热舒适度。
- 数值模式ENVI-met /
- 广州市街区 /
- 热环境 /
- 热舒适度
Abstract: Based on the ENVI-met microclimate numerical model, this study simulated and analyzed the thermal environment and comfort responses within Guangzhou urban blocks during periods of high temperature in summer. The results showed that the model accurately reproduced the daily variations in regional temperature and humidity, with root mean square errors of 0.99 ℃ and 6.1%, respectively. The green coverage of the underlying surface within the study area significantly impacted the temperature at pedestrian height. The temperature of local heat island in the hardened ground area of meteorological observation field was close to 38 ℃, while areas shaded by buildings and vegetation experienced localized cooling. Extremely hot areas (with a physiological equivalent temperature exceeding 41 ℃) accounted for 66.82% of the study area, primarily observed at hardened ground. In the absence of vegetation, the overall temperature within the study area increased, with the average regional temperature rising by 2.0 ℃, the high-temperature area expanding by 34.4%, and the cooling effect of vegetation extending up to 13 m vertically. The maximum wind speed increase was 1.0 m·s^-1, the area with higher mean radiant temperature (MRT, MRT > 58 ℃) expanded by 36.96%, and the extremely hot areas increased by 23.13%. Therefore, a favorable wind environment, effective use of shade, and well-planned greenery may help optimize outdoor thermal comfort within urban blocks.
- Guangzhou model /
- Guangzhou urban streets /
- thermal environment /
- thermal comfort

HTML全文

图 1 ENVI-met模拟的区域地理位置及其土地利用类型

下载: 全尺寸图片幻灯片

图 2 研究区的卫星图(a)及其ENVI-met的3D建模效果图(b)

下载: 全尺寸图片幻灯片

图 3 ENVI-met模拟值与自动气象站观测值对比

a、b. 2022年7月25日的气温变化曲线对比及散点图；c、d. 相对湿度的结果。

下载: 全尺寸图片幻灯片

图 4 实际方案(a)、无植被方案(b)行人活动高度处的温度分布

单位：℃。

下载: 全尺寸图片幻灯片

图 5 同图 4，但为相对湿度分布

单位：%。

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图 6 两种方案下气温随高度的变化趋势

单位: ℃。

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图 7 同图 4，但为风速分布

单位：m·s^-1。

下载: 全尺寸图片幻灯片

图 8 实际方案(a)、无植被方案(b)行人活动高度的平均辐射温度分布

单位：℃。

下载: 全尺寸图片幻灯片

图 9 实际方案(a)、无植被方案(b)行人活动高度的PET分布

单位：℃。

下载: 全尺寸图片幻灯片

图 10 2022年7月25日14:00 PET＞41 ℃面积百分比随高度变化

下载: 全尺寸图片幻灯片

表 1 ENVI-met模型输入参数

气象参数	自动气象站逐时空气温度、相对湿度、风速、风向、云量高空(2 500 m高度)空气比湿为10.73 g·kg^-1 气象观测站地面粗糙度默认为0.1 m
植物	树高5 m，简单落叶型树高10 m，简单落叶型树高15 m，简单落叶型草高0.5 m，LAD=0.3 m²·m^-3
建筑	墙：K=1.5 W·m^-2·℃^-1 屋顶：K=1.5 W·m^-2·℃^-1
地面构造及热物性	砖路(KK)粗糙度：0.01，反照率：0.5，发射率：0.9 沥青路(ST)：10 cm沥青-土壤，粗糙度：0.01，反照率：0.2，发射率：0.9
土壤初始状态(温度/湿度)	0~20 cm：293 K/65%；20~50 cm：293 K/70%；50~200 cm：292 K/75%；200 cm以下：291 K/75%

下载: 导出CSV

参考文献(41)

[1]	NG E, CHEN L, WANG Y, et al. A study on the cooling effects of greening in a high-density city: An experience from Hong Kong[J]. Building and Environment, 2012, 47(1): 256-271.
[2]	LIN B S, LIN C T. Cooling effect of shade trees with different characteristics in a subtropical urban park[J]. HortScience, 2010, 45(1): 83- 86.
[3]	FRÖHLICH D, MATZARAKIS A. Modeling of changes in thermal bioclimate: examples based on urban spaces in Freiburg Germany[J]. Theoretical and Applied Climatology, 2013, 111(3-4): 547-558.
[4]	CHANDRAMATHI S, SURESH K, ANITA Z B, et al. Comparison of STEVE and ENVI-met as temperature prediction models for Singapore context[J]. International Journal of Sustainable Building Technology & Urban Development, 2012, 3(3): 197-209.
[5]	ZAKHOUR S. The impact of urban geometry on outdoor thermal comfort conditions in Hot-arid region[J]. Journal of Civil Engineering and Architecture Research, 2015, 2(8): 862-875.
[6]	SALATA F, GOLASI I, VOLLARO R, et al. Urban microclimate and outdoor thermal comfort. A proper procedure to fit ENVI-met simulation outputs to experimental data[J]. Sustainable Cities and Society, 2016, 5(7): 318-343.
[7]	SOFLAEI F, MEHDI S, SEYED M. Traditional Iranian courtyards as microclimate modifiers by considering orientation, dimensions, and proportions[J]. Frontiers of Architectural Research, 2016, 2(5): 225-238.
[8]	MARTIN M P, SIMMONS C, ASHTON M S. Survival is not enough: The effects of microclimate on the growth and health of three common urban tree species in San Francisco, California[J]. Urban Forestry & Urban Greening, 2016, 19: 1-6.
[9]	TSITOURA M, MICHAILIDOU M, TSOUTSOS T. Achieving sustainability through the management of microclimate parameters in Mediterranean ur-ban environments during summer[J]. Sustainable Cities and Society, 2016, 26(1): 48-64.
[10]	TALEB D, ABU H B. Urban heat islands: potential effect of organic and structured urban configurations on temperature variations in Dubai, UAE[J]. Renewable Energy, 2013, 50: 747-762.
[11]	KETTERER C, MATZARAKIS A. Human-biometeorological assessment of the urban heat island in a city with complex topography-The case of stuttgart, Germany[J]. Urban Climate, 2014, 10(3): 573-584.
[12]	TALEGHANI M, KLEEREKOPER L, TENPIERIK M, et al. Outdoor thermal comfort within five different urban forms in the Netherlands [J]. Building and Environment, 2015, 83: 65-78.
[13]	杨阳, 唐晓岚, 吉倩妘, 等. 基于ENVI-met模拟的南京典型历史街区微气候数值分析[J]. 苏州科技大学学报: 工程技术版, 2018, 31(3): 33-40.
[14]	吴思佳, 董丽, 贾培义, 等. 基于计算流体力学数值模拟的城市绿地温湿效应及室外热舒适评价研究进展[J]. 风景园林, 2019, 26(2): 79-84.
[15]	秦文翠, 胡聃, 李元征, 等. 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.
[16]	李英男, 韩依纹. 基于ENVI-met的城市绿地微气候模拟研究进展[J]. 中国城市林业, 2021, 19(3): 61-66.
[17]	李舟雅, 杨婷, 戈晓宇. 基于ENVI-met微气候情景模拟的避暑山庄环境分析[J]. 中国城市林业, 2019, 17(6): 75-81.
[18]	戴俭, 闫晓光. 基于ENVI-met模拟的传统村落理想山水格局主山高度变化微气候研究[J]. 城市住宅, 2021, 28(9): 4.
[19]	HAIHUA W, YUE C, WEIFEN D, et al. The effects of tree canopy structure and tree coverage ratios on urban air temperature based on ENVI-Met[J]. Forests, 2023, 14(1): 80.
[20]	GEORGE T, JOBIN T, MARIYA G M, et al. Assessment of the potential of green wall on modification of local urban microclimate in humid tropical climate using ENVI-met model[J]. Ecological Engineering, 2023, 187: 106868.
[21]	林波荣. 绿化对室外热环境影响的研究[D]. 北京: 清华大学, 2004.
[22]	张伟. 居住小区绿地布局对微气候影响的模拟研究[D]. 南京: 南京大学, 2015.
[23]	劳钊明, 李颖敏, 邓雪娇, 等. 基于ENVI-met的中山市街区室外热环境数值模拟[J]. 中国环境科学, 2017, 37(9): 3 523-3 531.
[24]	孙铁钢, 肖荣波, 蔡云楠, 等. 城市热环境定量评价技术研究进展及发展趋势[J]. 应用生态学报, 2016, 27(8): 2 717-2 728.
[25]	王婷, 陈小芮, 章家恩, 等. 不同绿化改造方案对小区微气候环境影响的ENVI-met模拟研究[J]. 华南农业大学学报, 2019, 40(4): 61-68.
[26]	杨诗敏, 易慧琳, 吴友炉, 等. 基于ENVI-met的二沙岛公园植物群落空间微气候模拟研究[J]. 热带农业科学, 2023, 43(6): 68-76.
[27]	张仲雅, 王燕飞, 吴泽心, 等. 基于ENVI-met绿地布局形态对热环境的影响研究——以洛阳高层居住区为例[J]. 城市建筑, 2023, 20 (12): 26-30.
[28]	李浩宇, 张秦英, 王穗. 基于ENVI-met的夏季儿童热舒适调节效应树种研究[J]. 绿色科技, 2023, 25(7): 22-28.
[29]	谭兴, 廖建军, 王志远, 等. 住区不同绿化组合比率的绿地热环境模拟[J]. 中国城市林业, 2022, 20(4): 37-42.
[30]	张桂欣, 刘祎, 祝善友. 城市建筑布局要素对区域热环境影响的ENVI-met模拟与分析——以南京江北新区部分区域为例[J]. 气候与环境研究, 2022, 27(4): 513-522.
[31]	庄莉娟, 蔡芫镔, 祁娟娟. 基于ENVI-met的福州大学校区冬季热环境模拟与热舒适度变化分析[J]. 气象与环境学报, 2021, 37(6): 44- 52.
[32]	MORAKINYO T E, DAHANAYAKE K W, ADEGUN O B, et al. Modelling the effect of tree-shading on summer indoor and outdoor thermal condition of two similar buildings in a Nigerian university[J]. Energy and Buildings, 2016, 130: 721-732.
[33]	HOPPE P. The physiological equivalent temperature-Auniversal index for the biometeorological assessment of the thermal environment[J]. International Journal of Biometeorology, 1999, 43(2): 71-75.
[34]	HOPPE P. Different aspects of assessing indoor and outdoor thermal comfor[J]. Energy and Buildings, 2002, 34(6): 661-665.
[35]	BRUSE M, FLEER H. Simulating surface-plant-air interactions inside urban environments with a three dimensional numerical model[J]. Environmental Modelling & Software, 1998, 13(3): 373-384.
[36]	陈卓伦. 绿化体系对湿热地区建筑组团室外热环境影响研究[D]. 广州: 华南理工大学, 2010.
[37]	ZHANG L, ZHAN Q M, LAN Y L. Effects of the tree distribution and species on outdoor environment conditions in a hot summer and cold winter zone: A case study in Wuhan residential quarters[J]. Building and environment, 2018, 130: 27-39.
[38]	TSOKA S, LEDUC T, RODLER A. Assessing the effects of urban street trees on building cooling energy needs: The role of foliage density and planting pattern[J]. Sustainable Cities and Society, 2021, 65: 102633.
[39]	刘之欣, 郑森林, 方小山, 等. ENVI-met乔木模型对亚热带湿热地区细叶榕的模拟验证[J]. 北京林业大学学报, 2018, 40(3): 1-12.
[40]	徐新良, 刘纪远, 张树文, 等. 中国多时期土地利用土地覆被遥感监测数据集(CNLUCC)[OB]. 资源环境科学数据注册与出版系统(https://www.resdc.cn/DOI/DOI.aspx?DOIID=54), 2018.
[41]	YANG X, ZHAO L, BRUSE M, et al. Evaluation of a microclimate model for predicting the thermal behavior of different ground surfaces [J]. Building and environment, 2013, 60: 93-104.