Global assessment of urban trees’ cooling efficiency based on satellite observations

环境科学 城市热岛 大气科学 相对湿度 蒸腾作用 线性回归 白天 气候学 土地覆盖 气象学 土地利用 地理 数学 统计 生态学 生物 光合作用 植物 地质学
作者
Qiquan Yang,Xin Huang,Xiaohua Tong,Changjiang Xiao,Jie Yang,Yue Liu,Yinxia Cao
出处
期刊:Environmental Research Letters [IOP Publishing]
卷期号:17 (3): 034029-034029 被引量:53
标识
DOI:10.1088/1748-9326/ac4c1c
摘要

Abstract Trees are among the most important urban land covers, and their effects on local thermal environments have been extensively evaluated by using the concept of urban trees’ cooling efficiency (CE), defined as the magnitude of land surface temperature (LST) reduction by per 1% increase in fractional tree cover (FTC). Existing studies provide quantitative knowledge of the CE at local and regional scales, but global-scale analyses are still lacking. Therefore, this study fills this research gap through investigating the spatiotemporal pattern of CE in 510 global cities. CE is quantified by the opposite value of the regression coefficient of FTC (i.e. CE =− ∂ LST/ ∂ FTC) in a multiple linear regression model, where LST is the dependent variable and FTC, surface elevation, and nighttime light intensity are the independent variables. Results show that daytime LST decreases greatly with increasing FTC in most cities, and the globally averaged annual daytime CE reaches 0.063 °C % −1 , while at night, the effect of urban trees on LST weakens a lot, with an annual average CE of only 0.007 °C % −1 across global cities. CE varies markedly among cities and tends to be higher in hot and dry cities, which can be attributed to the significant nonlinear relation between CE and climatic conditions, in that the increase in temperature and the decrease in humidity can enhance vapor pressure deficit and further promote the heat dissipation by plant transpiration. As expected, CE shows a distinct seasonal variation, generally characterized as being higher in summer and lower in winter. In addition, our results suggest that previous studies based on a bivariate linear regression model have overestimated CE, especially at night when trees’ activities are weak. This global-scale study provides new insights into the mitigation of urban thermal stress from the perspective of increasing urban greenery.
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