Socioeconomic determinants of public health and residential building energy use in Chicago

Limited studies on energy consumption in cities have been done to explore the effects of socioeconomic determinants of public health on urban energy use. This article examines the associations between these factors, including characteristics of occupied housing unit, household income, employment, education, dependency, poverty level, and crowded housing with urban building energy use. The available empirical data from the City of Chicago on socioeconomic indicators of public health 2008-2012 and Chicago energy benchmarking 2016 and Chicago energy Usage 2010 were used. This research applied a machine learning approach based on the Artificial Neural Network (ANN) algorithm to predict the energy use intensity across Chicago, and several explanatory methods were extended to the model to help facilitate interpreting the results. And a cross-validation technique was employed to confirm the results. Findings suggest that all these socioeconomic determinants were strongly associated with energy use of residential buildings. Household income as the highest influential variable among them has a positive relationship with residential operational energy use. Further, urban building energy use was associated with urban form and building characteristics as well as various dimensions of socioeconomic determinants. Endeavors for reducing energy consumption in cities need to consider different dimensions of urban spatial patterns and socioeconomic status of public health.

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ISBN
978-1-944214-31-9