Spatio-temporal evolution and projection of urban heat island in China under the shared socioeconomic pathways

doi:10.12006/j.issn.1673-1719.2022.266

Abstract

Abstract:

Human activities have been thought as the key factors for the urban heat island effect. However, the impacts of anthropogenic factors on the intensity of the urban heat island effect at the city scale are still unclear. The intensity of daytime surface urban heat island (SUHI) at the city scale in China from 2012 to 2018 was calculated based on multi-source geographic data. Then the spatial and temporal patterns at the city scale were analyzed, following which the relationship between the driving factors and SUHI was discovered. Coupled with the shared socioeconomic pathways (SSPs) proposed by IPCC, the intensity of human activities under different scenarios were used to project the SUHI from 2020 to 2100. The spatial distribution of the annual mean SUHI at the city scale in 2012-2018 showed an obvious positive spatial autocorrelation. The southern China experienced higher SUHI than the northern China in general, and the strongest SUHI occurred in the southeast coast, with the weakest SUHI occurring in the northwest during 2012-2018. The mean value of SUHI slightly increased from 2012 to 2018 by 0.08℃ and was influenced by both anthropogenic and natural factors, among which GDP and ΔNDVI presented the largest contributions. From 2020 to 2100, the SUHI in most Chinese cities under the five SSPs scenarios will increase significantly, with the mean value of SUHI under the SSP5 scenario increasing by 0.67℃. In addition, the future SUHI in large cities varies largely under different scenarios. In terms of driving factors, the GDP will be the main anthropogenic driver of SUHI growth for most cities. Meanwhile, the comparative analysis for typical cities suggests that the fluctuations of SUHI in Shanghai urban agglomeration, Tianjin city, Urumqi and Nanning city may reach 4.83-8.98℃, 3.24-4.95℃, 1.11-1.55℃ and 2.61-4.05℃ at the end of the 21st century, respectively. The results of this study reveal the possible temporal and spatial changing trend of SUHI under the SSPs in future. The conclusions are important for achieving healthy development of urban ecological environment.

Key words: Surface urban heat island, Spatial and temporal pattern, Driving factors, The shared socioeconomic pathways (SSPs)

GAO Yun-Xiang, LI Ke-Ke, ZHANG Wen-Ting, WANG Tian-Wei, LI Shan. Spatio-temporal evolution and projection of urban heat island in China under the shared socioeconomic pathways[J]. Climate Change Research, 2023, 19(4): 431-445.

Figures/Tables 13

Table 1 Information of research data

Fig. 1 Spatial distribution of annual average surface urban heat island intensity (SUHI) in China from 2012 to 2018. (a) 7-year mean, (b) 7-year difference, (c) box plot. (Data of Hong Kong, Macao and Taiwan are not included. IQR stands for interquartile range, the same below)

Table 2 Result of global Moran’s index

Table 3 Results of ULR model

Fig. 2 Spatial distribution of R2 (a) and residual (b) in the GWR model

Fig. 3 Comparison of actual and simulated SUHI values in 2018

Table 4 Growth rate of SUHI in China during 2020-2100 and 2012-2018 under different SSPs

Fig. 4 Plot of variation of mean value of SUHI in China from 2020 to 2100 under different SSPs

Fig. 5 Spatial distribution of mean and difference of SUHI in China from 2020 to 2100 under SSP1 and SSP5

Fig. 6 Time series changes of SUHI, population and GDP in Shanghai urban agglomeration from 2020 to 2100 under different SSPs

Fig. 7 Time series changes of SUHI, population and GDP in Tianjin from 2020 to 2100 under different SSPs

Fig. 8 Time series changes of SUHI, population and GDP in Urumqi from 2020 to 2100 under different SSPs

Fig. 9 Time series changes of SUHI, population and GDP in Nanning from 2020 to 2100 under different SSPs

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