Abstract Cities comprising more than half of the global population and consuming 75% of total energy are critical starting points for urban planners aiming to improve energy efficiency and mitigate climate change. Research in this field has predominantly focused on countries and cities, mostly located in temperate or cold regions, while arid areas are less studied. In this regard, this paper intends to address this gap by modeling Residential Electricity Consumption (REC) in an arid region and examining the impact of urban form variables on reducing electricity consumption intensity, particularly during the summer months in Tehran, where households experience prolonged daily blackouts. With this intention, a multi-level modeling approach is employed, accounting for the hierarchical data structure (individual households nested within their neighborhoods) to separately model annual and cooling electricity demand per household in 2021. The results show that among the various urban form variables considered in this study, building orientation, the average number of floors, and its standard deviation within a neighborhood are significant predictors of REC. Notably, the model explains 47.4% of the variance in annual REC using only fixed effects, of which 7.4% is attributable to urban form variables. In contrast to previous studies conducted primarily in temperate and cold regions, no negative correlations are observed between population density, floor area ratio, or building coverage ratio and REC in Tehran located in an arid area. Therefore, since shading and ventilation are critical factors in reducing electricity demand, the findings do not support compact urban development.
Abar et al. (Thu,) studied this question.