Multivariate analysis of the influence between building design and energy performance, socio-demographic metrics, and the intra-urban environment

Through advancements of direct and remote sensing technologies, we have recently learned that urban microclimate and air quality gradients can often be more significant than city to rural differences. However, the urban design parameters that are most critical to improve environmental health and reduce building energy consumption, are yet to be identified. This research makes use of air quality datasets collected through a dense stationary sensing network in New York City, remote sensing datasets for land surface temperature and normalized difference vegetation index, building usage metrics, building and urban design metrics, and socio-demographic datasets including population and health metrics. Through a neighbourhood-scale footprint-based regression analysis, the correlation between the air quality, land surface temperature, building usage and urban metrics has been studied. Highest correlations have been observed between air quality and land surface temperature and urban design and socio-economic metrics. The results show that building usage metrics such as the energy use intensity or electricity purchase, are mainly affected by building design characteristics. On the other hand, significant correlations have been observed between the urban design, socio-demographic and contaminant concentration gradients, addressing the critical role the planning and design of our cities plays in the environmental well-being of citizens.