Zhang Ying, Wang Xu-Hong, Feng Zi-Hao, Yuan Jia-Xin, Yu Meng-Qian-Xi
College of Urban and Environmental Sciences, Northwest University, Xi'an 710127, China.
Shaanxi Key Laboratory of Earth Surface System and Environmental Carrying Capacity, Northwest University, Xi'an 710127, China.
Huan Jing Ke Xue. 2024 Jun 8;45(6):3734-3745. doi: 10.13227/j.hjkx.202307151.
The urban thermal environment is an important indicator for evaluating the ecological environment of a city. It directly affects the health of residents and the sustainable development of the urban economy. However, there is currently a lack of analysis on the impact pathways of the thermal environment considering both natural and human factors. Based on the MODIS MYD11A2 land surface temperature data, meteorological data, and human activity data of Xi'an metropolitan area in 2020, ArcGIS spatial geostatistical analysis was used to study the temporal and spatial distribution pattern of the thermal environment in different seasons, and redundancy analysis was utilized to select the main factors affecting the thermal environment. Then, structural equation modeling was used to quantify the direct and indirect effects of the dominant factors on the urban thermal environment. The results showed that:① The surface temperature in the Xi'an urban area showed a spatial pattern of higher temperatures in the north and lower temperatures in the south, with a decrease in temperature from the city center to the surrounding areas. The most severe heat environment pollution occurred in the summer. ② The redundancy analysis (RDA) results indicated that the main factors that affected the thermal environment were air temperature, impermeable surfaces, vegetation, and precipitation. ③ The results of the structural equation modeling (SEM) indicated that meteorological, surface, and anthropogenic factors affected the urban thermal environment mainly through direct pathways, which were much more important than all indirect pathways. Factors such as temperature, impervious surfaces, and point of interest density had a significant positive effect on the thermal environment (0.10 and 0.33). On the other hand, factors such as water bodies, precipitation, and vegetation had a significant negative effect on the thermal environment (-0.29 and -0.25). Human activities had a greater direct impact on nocturnal surface temperatures than surface and meteorological factors. Increasing economic efficiency is beneficial for mitigating the urban heat island effect. The results of the study can provide a reference for studying local climate change in urban heat islands and for the construction of green and ecologically livable urban environments.
城市热环境是评估城市生态环境的重要指标。它直接影响居民健康和城市经济的可持续发展。然而,目前缺乏对同时考虑自然和人为因素的热环境影响路径的分析。基于2020年西安大都市区的MODIS MYD11A2地表温度数据、气象数据和人类活动数据,利用ArcGIS空间地统计分析研究不同季节热环境的时空分布格局,并利用冗余分析筛选影响热环境的主要因素。然后,采用结构方程模型量化主导因素对城市热环境的直接和间接影响。结果表明:①西安市区地表温度呈现北高南低的空间格局,从市中心向周边地区温度逐渐降低。夏季热环境污染最为严重。②冗余分析(RDA)结果表明,影响热环境的主要因素是气温、不透水表面、植被和降水。③结构方程模型(SEM)结果表明,气象、地表和人为因素主要通过直接路径影响城市热环境,这些直接路径比所有间接路径都重要得多。温度、不透水表面和兴趣点密度等因素对热环境有显著正向影响(分别为0.10和0.33)。另一方面,水体、降水和植被等因素对热环境有显著负向影响(分别为-0.29和-0.25)。人类活动对夜间地表温度的直接影响大于地表和气象因素。提高经济效率有利于缓解城市热岛效应。研究结果可为研究城市热岛局部气候变化及绿色生态宜居城市环境建设提供参考。