Households energy consumption and carbon dioxide emissions of Mahabad City, Iran

Abstract

This study seeks to find a method to identify the dominant pattern of energy choice and consumption in households, centring on demographic factors affecting the use of home appliances. To this aim, this research dealt with a variety of energy sources that were widely used by households, namely LPG, electricity, and kerosene for cooking, heating and cooling, lighting, and home appliances. Additionally, significant associations for household energy choice and consumption were identified for demographic variables, including household size, gender, age of household head, educational level, and income group. A binary logistic regression was performed to obtain quantitative data provided by a survey from 821 households across residential districts of urban and rural areas in Mahabad Region, northwest of Iran. Collected data were analyzed within a proposed three-energy dimensions model (3-ED). The results showed that if the other variables remain constant, income may lead to variation in LPG and electricity consumption. Unlike other independent variables, the household-head age failed to have a significant impact. The findings can contribute to a better understanding of effective factors on household energy choice and consumption in other cities and be useful for the support of policymakers in their consumption patterns. This research explores the impact of different household demographic characteristics on energy-saving behaviours and carbon dioxide (CO2) emissions in Mahabad city located in the northwest of Iran. The structural model adopted was composed of six variables, including household age, household size, educational qualification, income quintile, gender, and energy conservation behaviour concerning demographic features, energy sources, and consumptions. To compare the predictability power of these variables' effects on households' energy conservation and CO2 emissions, a crisp instruction on how to evolve a statistical technique for analyzing data was provided by Partial Least Squares Structural Equation Modelling (PLS-SEM). It was revealed that households consume approximately 89.71% on liquefied petroleum gas (LPG), 9.87% on electricity, and the rest 0.43% on kerosene, petrol, and diesel on a monthly basis. Eventually, the results of this research showed that age, family size, and carbon dioxide emissions, except education background and income level, are significantly correlated with energy-saving behaviour.