Surface anthropogenic heat islands in six megacities: An assessment based on a triple-source surface energy balance model

Abstract

Anthropogenic heat flux (AHF) is a main contributor to the formation of surface urban heat islands (SUHI). Megacities in particular are facing severe problems due to excessive population growth, urban area expansion, human activity, increased energy consumption, and increased anthropogenic heat. In this study, a physical modeling approach based on a triple-source surface energy balance (triple-SEB) model was developed to uncover the effect of AHF on land surface temperature (LST) and surface anthropogenic heat island (SAHI) intensity. For this purpose, satellite imagery along with climatic and meteorological data from 1985 to 2019 were studied for six selected megacities: Los Angeles, Atlanta, Athens, Istanbul, Tehran, and Beijing. First, LST and the fraction of different surface covers were calculated by using a single-channel algorithm and a normalized spectral mixture analysis model, respectively. In the second step, impervious surface cover (ISC) and the urban main boundary area (UMBA) of each city were extracted based on the biophysical composite index and city clustering algorithm, respectively. In the third step, anthropogenic LST (ALST) was modeled using a triple-SEB model. In the fourth step, the ALST and UMBA were used together to model SAHI intensity at different dates. Finally, the relationship between the estimated ALST and ISC, as well as between SAHI and ISC, was examined. Results show that the average value of estimated ALST for the megacities increased from 2.02, 0.55, 0.61, 0.64, 0.58, and 0.72 to 2.99, 1.73, 1.66, 1.19, 2.32, and 2.76 °C, respectively. The coefficient of determination between the mean value of ISC and the estimated ALST for all megacities yielded 0.8, which was higher than that between ISC and satellite-derived LST. Moreover, the SAHI intensity for these megacities was found to have increased to 0.73, 0.92, 0.95, 0.98, 0.95 and 1.32 °C, respectively, which can be predicted by ISC with a coefficient of determination of 0.78, 0.79, 0.79, 0.73, 0.71 and 0.52, respectively. This suggests that the triple-SEB model proposed by this study allowed for independent modeling of AHF's influence on SUHI and a better determination of the effect of ISC on LST and SUHI intensity. This approach facilitated comparative analysis of LST and SAHI for a city at different times as well as SAHIs in different cities with different geographic and climate settings.