  As a key energy challenge, we urgently require a better understanding of how
growing urban populations interact with municipal energy systems and the
resulting impact on energy demand across city neighborhoods, which are dense
hubs of both consumer population and CO2 emissions. Currently, the physical
characteristics of urban infrastructure are the main determinants in predictive
modeling of the demand side of energy in our rapidly growing urban areas;
overlooking influence related to fluctuating human activities. Here, we show
how applying intra-urban human mobility as an indicator for interactions of the
population with local energy systems can be translated into spatial imprints to
predict the spatial distribution of energy use in urban settings. Our findings
establish human mobility as an important element in explaining the spatial
structure underlying urban energy flux and demonstrate the utility of a human
mobility driven approach for predicting future urban energy demand with
implications for CO2 emission strategies.
