The impacts of residential buildings’ energy compliance standards on Iran’s GHG emissions toward achieving the Paris Agreement

Abstract

Countries have been driven to undertake energy conservation measures to lessen their negative environmental effects due to rising CO2 emissions worldwide. To effectively forecast the future status and evaluate the efficacy of energy-saving and mitigation scenarios, estimating energy consumption and the associated CO2 emissions from fossil fuels is essential. The domestic sector in Iran, liable for using around 30% of the total energy consumption, is the focus of this research. The research has developed a model for future energy consumption and greenhouse gas emissions distinctive to the features of the Iranian residential building stock by considering climate change and using statistical data. To assess prospective results, the Business-As-Usual and energy conservation scenarios are compared. The research also evaluates the potential of energy savings and CO2 reduction across several provinces. The fulfillment of the energy compliance requirements confined in the National Building Regulations by considering the impact of climate change on energy consumption in dwellings of different climate regions has been prioritized. The results show that under different mitigation scenarios, CO2 emissions in the household sector are projected to decrease by 15.7%, 18.4%, 26.8%, and 31.8% by 2030 and 2050. According to the Paris Agreement, these reductions are consistent with Iran's Intended Nationally Determined Contribution. The study emphasizes the significance of targeted measures and policy implementations to lower CO2 emissions in the domestic sector substantially, supporting global efforts to mitigate climate change. The methodology described here addresses energy-related challenges within the constraints of available data on the residential building stock statistic. While acknowledging the potential for further refinement, the country's development of a detailed typology of residential buildings holds promise for enhancing the precision of the modeling in future studies and enabling more robust assessments of energy-saving strategies.