The Impact of Urban Form and Density on Residential Energy Use: A Systematic Review

Abstract

The first step for reducing residential energy use is identifying the effective variables in this sector. This review paper extracts 10 urban form variables and discusses their correlations, interpretations, and frequencies alongside methodologies used to quantify their impacts. This review also identifies the parameters that cause mixed effects of density on residential energy use in different studies. Multinomial logistic regression is used to quantify the odds of obtaining a positive or non-significant association rather than a negative correlation. The model can predict the impact of density on residential energy consumption in almost 80% of the cases based on the identified parameters, namely the number of indicators considered in the model as the proxy of density, type of energy, unit of measurement, methodology, data reliability, published year, relevancy, geographical location of case studies and their climate classifications. The result shows that while density correlates negatively with residential energy use in cold climates, its impact could be considered positive in temperate regions.