A Submodel as a Plug-in for the Assessment of Energy Consumption and CO2 Emissions in Urban Mobility Plans

Abstract

This study provides a comprehensive view of energy consumption and CO2 emissions for different vehicle technologies in real driving cycles. Universal correlation functions have been proposed for different vehicle technologies, associating fuel consumption and CO2 emissions with speed. A submodel was developed, calibrated for the city of Brasília, Brazil, and later used to simulate future scenarios with a higher prevalence of cleaner vehicle technologies, such as ethanol, hybrid, and electric vehicles. The use of the submodel can serve as a valuable tool for decision making in transport planning, allowing for a more realistic determination of energy consumption and CO2 emissions in different traffic conditions, i.e., in real driving cycles. The results obtained using the developed submodel showed that with the increased participation of more efficient vehicles, such as BEV and HEV, and an even greater participation of ethanol-powered vehicles, there is a significant reduction in CO2 emissions. Finally, the use of the developed tool allows managers and specialists in transport planning, through the generation of future scenarios, to propose and implement more effective policies to reduce CO2 emissions, thus contributing to more sustainable mobility.