Urban climate changes during the COVID-19 pandemic: integration of urban-building-energy model with social big data

Abstract

The changes in human behaviour associated with the spread of COVID-19 infections have changed the urban environment. However, little is known about the extent to which they have changed the urban climate, especially in air temperature (T), anthropogenic heat emission (QF) and electricity consumption (EC). We quantitatively evaluated these effects using a unique method that integrates real-time human population data (social big data) with an urban climate model. The results showed that in an office district in the city centre of Tokyo, the biggest metropolis in the world, under a significantly reduced population, EC (CO2 emissions) would be 30% and QF would be 33% of pre-COVID levels (without the stay-at-home advisories). This resulted in a T decrease of about 0.2 °C, representing about 20% of the past greenhouse gas-induced warming (about 1.0 °C) in Tokyo. This method can be benchmarked and then applied to worldwide. The results suggest that changes in human behaviour can represent an adaptation and decarbonising strategies to climate change in cities.