Investigating the efficacy of a fast urban climate model for spatial planning of green and blue spaces for heat mitigation

城市热岛 绿色基础设施 环境科学 城市规划 空间规划 气候变化 环境规划 城市气候 环境资源管理 气象学 地理 土木工程 地质学 工程类 海洋学
作者
Jiayu Chen,Peter M. Bach,Kerry A. Nice,João P. Leitão
出处
期刊:Science of The Total Environment [Elsevier]
卷期号:: 176925-176925
标识
DOI:10.1016/j.scitotenv.2024.176925
摘要

Problems caused by urban heat have prompted the exploration of urban greenery and blue spaces for heat mitigation. Various numerical models can simulate heat-related processes, but their use as support-tools to urban planners remains underexplored, particularly at the city-scale, due to high computational demand and complexity of such models. This study investigates the spatial relationships between urban heat, urban form and urban green and blue spaces with the fast climate model TARGET (The Air-temperature Response to Green/blue-infrastructure Evaluation Tool), which only requires minimal inputs of standard meteorological data, land cover and building geometry data. Using the City of Zurich as our case study, we: (i) validated the TARGET model against air temperature measurements from private sensor networks, (ii) performed a sensitivity analysis to identify key variables affecting urban heat, and (iii) investigated urban heat relationships with blue-green cover at locations frequented by pedestrians. Presence of urban green and blue spaces across the region shows potential for reducing local air temperatures by up to 5.2 °C (with urban forest). Investigating this relationship at different locations in the city revealed key districts that should potentially be targeted for reduction of pedestrian heat-impacts, due to their high pedestrian traffic, fewer green and blue spaces and high daytime air temperatures. Our results not only provide insights into the cooling effect of different amounts of green and blue features in the urban environment, but also demonstrates the application and integration potential of simplified models like TARGET to support the planning of more liveable future cities.
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