A least squares regression-based approach in the investigation of the influence of density metrics of 14 distinct Toronto neighbourhoods on the roof and facade solar potential

Abstract

Introduction: This Toronto-based study explores how density metrics relate to the solar potential of rooftops and facades of buildings in neighbourhoods differentiated by their use classifications. In the context of Toronto’s 2040 Net Zero Strategy, this research contributes insight on identifying neighbourhood types in Toronto that are suitable for undergoing retrofits of active solar technologies.Methods: The methodological approach adopted in this investigation mainly entails the selection of representative neighbourhood archetypes in the city; compilation of density metrics representing the neighbourhood morphological form and conducting solar analysis and regression assessments using relevant computational tools. By identifying 14 distinct neighbourhood archetypes and examining 20 relevant density metrics, the variation of roof and façade solar potential has been evaluated through a least squares regression-based approach.Results: The findings indicate a negative correlation between certain density metrics, such as the standard deviation of height, plot density, nearest neighbour ratio, and complexity with the roof solar potential, thereby demonstrating that certain neighbourhoods such as those categorized as Employment or Institutional may be more suitable for active solar technologies retrofits. Additionally, there is no significant relationship between most density metrics and façade solar irradiance, apart from the open space ratio, which only affects it moderately. Façade solar potential is unique to building position and orientation and can vary non-uniformly across neighbourhood-use classifications based on the extent of overshadowing inherent to that configuration.Discussion: The study provides valuable insights for urban planning and neighbourhood design, specifically in terms of density metrics that need to be considered when opting for active solar technology retrofits of existing Toronto neighbourhoods. Additionally, the study’s methodological approach can be emulated as a framework for future research exploring neighbourhood archetypes in other cities and climatic conditions. The findings of this research also contribute to promoting sustainable energy transition in Toronto’s neighbourhoods.