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Assessment of surface urban heat island across China’s three main urban agglomerations

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This article proposes a method for estimating the surface urban heat island intensity (SUHI) of urban areas, which addresses prior difficulties in the determination of rural contexts that may be… Click to show full abstract

This article proposes a method for estimating the surface urban heat island intensity (SUHI) of urban areas, which addresses prior difficulties in the determination of rural contexts that may be used as a point of comparison. Based on indexes produced using this method, as well as remotely sensed datasets, the article compares the temporal and spatial characteristics of SUHIs within three major urban agglomerations (the Beijing-Tianjin-Hebei, the Yangtze River Delta, and the Pearl River Delta) and six typical metropolises. The article also examines the influence of socioeconomic factors on SUHI. The study revealed that this method is able to objectively monitor regional-scale SUHIs. The climate of the area studied is probably a determining factor in the seasonal variation of SUHIs. Research from the last 5 years (2010–2014) demonstrates that the urban heat island effect within the three urban agglomerations and five metropolises is serious. From 1994 to 2014, the average SUHI value for central urban areas rose from 0.4 to 2.3 K, while the total area where the SUHI value was >3.0 K increased from 1938 to 29,690 km2. The morphology of heat islands is significantly influenced by urbanization, meaning that heat islands within the areas studied will only continue to grow. Urban population and electricity consumption are the socioeconomic factors that exerted the greatest influence on the size of heat islands in China’s major urban agglomerations. However, it is likely that economic measures designed to mitigate the UHI effect will differ in effectiveness from one urban agglomeration to another.

Keywords: urban heat; surface urban; urban agglomerations; heat island; heat

Journal Title: Theoretical and Applied Climatology
Year Published: 2017

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