基于多尺度模拟的寒地滨海城市室外热舒适影响机制

Influence Mechanism of Outdoor Thermal Comfort in Cold Coastal Cities Based on Multiscale Simulation

摘要

【目的】针对寒地滨海城市夏季热暴露与冬季冷应激并存、现有研究对多季节多尺度下城市形态作用机制认识不足的问题，探讨街道—街区空间形态对室外热舒适的季节与尺度响应及非线性作用机制。【方法】通过多尺度模拟评价城市室外热舒适，并采用机器学习方法揭示滨海城市室外热环境与空间形态之间的复杂关联。【结果】研究区热舒适呈显著的空间异质性与季节差异，夏季典型气象日14时平均PET为41.24℃，冬季为11.56℃。街道尺度下，主导走向由夏季E-W转变为冬季NE-SW；街区尺度下，夏季容积率贡献最高，平均绝对SHAP值约为0.70，冬季则以SVF贡献最高，约为0.52。街道与街区空间形态通过影响辐射暴露、局部通风和热量交换调节热舒适，街道走向、SVF、容积率和绿地率等指标在不同季节与尺度下表现出差异化影响。【结论】寒地滨海城市室外热舒适受季节背景、空间尺度与形态组合共同影响。空间优化应由单一指标控制转向多要素协同调节，夏季侧重遮阳与通风，冬季兼顾日照利用与风寒削弱，以实现全年热舒适的季节适应性提升。

Abstract

【Objective】Given the coexistence of summer heat exposure and winter cold stress in cold-region coastal cities, as well as the limited understanding of how urban morphology affects outdoor thermal comfort across multiple seasons and spatial scales, this study investigates the seasonal and scale-dependent responses of outdoor thermal comfort to street-and block-scale urban morphology, with particular attention to nonlinear mechanisms. This study investigates the relationship between urban spatial form and outdoor thermal comfort in Xi'an Road, Dalian, a typical cold-region coastal district. 【Method】Taking Xi'an Road in Dalian City as an example, the study evaluates urban outdoor thermal comfort through multiscale simulation and employs the machine learning method to reveal the complex associations between the urban outdoor thermal environment and urban form in coastal cities. 【Result】There are clear spatial heterogeneity and seasonal variations in the study area. At 14:00 on typical meteorological days, the mean PET is 41.24℃ in summer and 11.56℃ in winter. At the street scale, the dominant orientation shifts from E-W in summer to NE-SW in winter. At the block scale, floor area ratio has the highest contribution in summer, with a mean absolute SHAP value of about 0.70, while SVF dominates in winter at about 0.52. Urban form at street and block scales influences thermal comfort mainly through radiation exposure, local ventilation and heat exchange, and key indicators such as street orientation, SVF, floor area ratio and green space ratio present differentiated effects across seasons and spatial scales. 【Conclusion】Outdoor thermal comfort in cold-region coastal cities is jointly influenced by seasonal climatic conditions, spatial scale, and morphological configurations. Spatial optimization should therefore shift from the control of individual indicators toward the coordinated regulation of multiple morphological factors. Summer strategies should prioritize shading and ventilation, while winter strategies should balance solar access and wind-chill mitigation, thereby improving year-round thermal comfort through seasonally adaptive design.

关键词

室外热舒适 / 微气候 / 城市形态 / 影响机制 / 寒地滨海城市

Key words

outdoor thermal comfort / microclimate / urban form / impact mechanism / cold coastal city

参考文献

[1] 王旭, 付学成, 徐文甜, 等 . 2000—2020年中国城乡热舒适度特征及其驱动因素[J]. 地理学报, 2024, 79(5): 1318-1336.

[2] 袁敬诚, 韩腾瑞, 李海滨 . 寒地街区蓝绿空间对热环境的影响研究:以沈阳市过渡季节为例[J]. 西部人居环境学刊, 2025, 40(3): 117-123.

[3] 冷红, 鲁钰雯, 袁青 . 寒地城市冬季公共开放空间步行可达性研究[J]. 建筑学报, 2017(增刊1): 38-42.

[4] 郑开雄, 运迎霞, 常玮 . 滨海城市“气候承载—空间适应”方法研究:厦门气候承载空间模拟分析[J]. 城市发展研究, 2018, 25(8): 51-58,82.

[5] 冷红, 郑春宇, 鲁钰雯 . 老龄人口健身出行视角下的寒地城市公共空间可步行性研究[J]. 国际城市规划, 2019, 34(5): 27-32.

[6] LI J J, MAO Y, OUYANG J Y, et al. A review of urban microclimate research based on CiteSpace and VOSviewer analysis[J]. International Journal of Environmental Research and Public Health, 2022, 19(8): 4741.

[7] ZHOU Y C, AN N, YAO J W. Characteristics, progress and trends of urban microclimate research: a systematic literature review and bibliometric analysis[J]. Buildings, 2022, 12(7): 877.

[8] ROY T B, MIDDEY A, KRUPADAM R J. Unveiling the microclimate: a comprehensive review of tools, techniques, and future directions for sustainable cities[J]. Building and Environment, 2025, 274: 112726.

[9] LI B, ZHANG B L, YIN L, et al. Assessing heat risk for residents of complex urban areas from an accessibility—based perspective[J]. Sustainable Cities and Society, 2023, 88: 104278.

[10] ZHOU Y, ZHAO H L, MAO S C, et al. Exploring surface urban heat island (SUHI) intensity and its implications based on urban 3D neighborhood metrics: an investigation of 57 Chinese cities[J]. Science of the Total Environment, 2022, 847: 157662.

[11] ZOU M, ZHANG H. Cooling strategies for thermal comfort in cities: a review of key methods in landscape design[J]. Environmental Science and Pollution Research, 2021, 28(44): 62640-62650.

[12] NASROLLAHI N, GHOSOURI A, KHODAKARAMI J, et al. Heat—mitigation strategies to improve pedestrian thermal comfort in urban environments: a review[J]. Sustainability, 2020, 12(23): 10000.

[13] BARROS MOREIRA DE CARVALHO G, BUENO DA SILVA L. The microclimate implications of urban form applying computer simulation: systematic literature review[J]. Environment, Development and Sustainability, 2024, 26(10): 24687-24726.

[14] SHISHEGAR N. Street design and urban microclimate: analyzing the effects of street geometry and orientation on airflow and solar access in urban canyons[J]. Journal of Clean Energy Technologies, 2013, 1(1): 52-56.

[15] CHEN Y, WANG Y P, ZHOU D. Knowledge map of urban morphology and thermal comfort: a bibliometric analysis based on CiteSpace[J]. Buildings, 2021, 11(10): 427.

[16] LYU T, BUCCOLIERI R, GAO Z. A numerical study on the correlation between sky view factor and summer microclimate of local climate zones[J]. Atmosphere, 2019, 10(8): 438.

[17] ZHAO B L, ZHAO Y H, XU Y T, et al. Refining adaptive models for overheating evaluation: Evidence—driven comparative analysis of residential buildings in China's cold and severe cold regions[J]. Building and Environment, 2024, 263: 111896.

[18] XI T Y, WANG M, CAO E J, et al. Preliminary research on outdoor thermal comfort evaluation in severe cold regions by machine learning[J]. Buildings, 2024, 14(1): 284.

[19] NIE T, LAI D Y, LIU K X, et al. Discussion on inapplicability of Universal Thermal Climate Index (UTCI) for outdoor thermal comfort in cold region[J]. Urban Climate, 2022, 46: 101304.

[20] WU X, YUAN C P, XUE H R, et al. Comprehensive effects of thermal and acoustic environments on overall comfort in urban parks of cold regions in China[J]. Energy and Buildings, 2025, 347: 116329.

[21] HE X Y, AN L, HONG B, et al. Cross—cultural differences in thermal comfort in campus open spaces: a longitudinal field survey in China's cold region[J]. Building and Environment, 2020, 172: 106739.

[22] 卢新潮, 徐苏宁, 刘羿伯, 等 . 寒地城市滨河区生态规划研究:以哈尔滨市为例[J]. 现代城市研究, 2017(12): 70-78.

[23] 陈飞, 曹诗茵, 蔡军, 等 . 纽约滨海韧性规划研究进展与实践综述[J]. 西部人居环境学刊, 2025, 40(3): 188-195.

[24] CUI P, DAI C Y, ZHANG J, et al. Assessing the effects of urban morphology parameters on PM_2.5 distribution in Northeast China based on gradient boosted regression trees method [J]. Sustainability, 2022, 14(5): 2618.

[25] GUO F, LUO M X, ZHANG C X, et al. The mechanism of street spatial form on thermal comfort from urban morphology and human—centered perspectives: a study based on multi—source data[J]. Buildings, 2024, 14(10): 3253.

[26] LI P Y, SHARMA A. Hyper—local temperature prediction using detailed urban climate informatics[J]. Journal of Advances in Modeling Earth Systems, 2024, 16(3): e2023MS003943.

[27] BRIEGEL F, WEHRLE J, SCHINDLER D, et al. High—resolution multi—scaling of outdoor human thermal comfort and its intra—urban variability based on machine learning[J]. Geoscientific Model Development, 2024, 17(4): 1667-1688.

[28] CHEN X, ZHAO H C, WANG B N, et al. Study of factors influencing thermal comfort at tram stations in Guangzhou based on machine learning[J]. Buildings, 2025, 15(6): 865.

[29] CHE Y Z, LI X C, LIU X P, et al. Building height of Asia in 3D—GloBFP[DS/OL]. Zenodo, 2024. https://zenodo.org/records/12674244.

[30] High resolution canopy height maps by WRI and meta—registry of open data on AWS[EB/OL]. [ 2024—12—23]. https://registry.opendata.aws/dataforgood—fb—forests/.

[31] 蒋玮, 彭宏欣, 袁东东, 等 . 城市道路对微区域温度场和人体热舒适性的影响规律研究[J]. 中国公路学报, 2023, 36(12): 209-221.

[32] 大连市/沙河口区基本气象资料[EB/OL]. (2023—08—09)[2025—04—19]. http://eia—data.com/大连市—沙河口区基本气象资料/.

[33] LIU Z M, LI J, XI T Y. A review of thermal comfort evaluation and improvement in urban outdoor spaces[J]. Buildings, 2023, 13(12): 3050.

[34] 姜允芳, 韩雪梅, 石铁矛, 等 . 城市道路肌理形态多维指标的微气候影响分析:上海实证研究[J]. 华东师范大学学报(自然科学版), 2020(3): 129-147.

[35] LAI D Y, LIAN Z W, LIU W W, et al. A comprehensive review of thermal comfort studies in urban open spaces[J]. Science of the Total Environment, 2020, 742: 140092.

[36] MATZARAKIS A, MAYER H, IZIOMON M G. Applications of a universal thermal index: physiological equivalent temperature[J]. International Journal of Biometeorology, 1999, 43(2): 76-84.

[37] YU Y, CHOU J S, YAO X, et al. Generation and application of typical meteorological year data for PV system potential assessment: a case study in China[J]. Journal of Building Engineering, 2024, 86: 108831.

[38] 邓寄豫 . 基于微气候分析的城市中心商业区空间形态研究:以南京为例[D]. 南京: 东南大学, 2018.

[39] 郭琳琳 . 寒冷地区平原典型城市中心区街区形态与微气候的耦合机理与优化调控[D]. 武汉: 华中科技大学, 2020.

[40] 程晴晴 . 基于景观界面测度的哈尔滨街谷群热环境整体优化模拟研究[D]. 哈尔滨: 哈尔滨工业大学, 2021.

[41] NAKANO A. Urban weather generator user interface development: towards a usable tool for integrating urban heat island effect within urban design process[D]. Cambridge: Massachusetts Institute of Technology, 2015.

[42] BUENO B, NORFORD L, HIDALGO J, et al. The urban weather generator[J]. Journal of Building Performance Simulation, 2013, 6(4): 269-281.

[43] ALI—TOUDERT F, MAYER H. Effects of asymmetry, galleries, overhanging façades and vegetation on thermal comfort in urban street canyons[J]. Solar Energy, 2007, 81(6): 742-754.

[44] VAN DEN BROECK G, LYKOVA A, SCHLEICH M, et al. On the tractability of SHAP explanations[J]. Journal of Artificial Intelligence Research, 2022, 74: 851-886.

[45] WANG M, LI Y X, YUAN H J, et al. An XGBoost—SHAP approach to quantifying morphological impact on urban flooding susceptibility[J]. Ecological Indicators, 2023, 156: 111137.