- Main
Development of an Aggregate Forecasting and Impact Evaluation Modeling Framework for China’s Passenger and Freight Fleets
- Zhang, Xiuli
- Advisor(s): Jaller, Miguel
Abstract
China's road transportation contributed about 8% of the country’s GHG emissions in 2020. Chinese government has made the commitment of reaching “carbon peak in 2030 and carbon neutrality in 2060”. Among all the sectors, transportation is one of the most challenging and essential ones to mitigate GHG emissions. The experienced economic development and improvement in people's living standards have increased vehicle ownership for both passenger vehicles and freight trucks. For the road transportation sector, electrification of the fleet represents one of the most important measures to reduce criteria pollutants and GHG emissions.By modeling passenger and freight vehicle fleets, this study projects the vehicle growth based on economic projections and the changes in demographic characteristics of the population during 2010 to 2050. The study developed a stock and sales model considering vehicle survival rates by vehicle types to reflect the different vehicle retirement and replacement schedules. Moreover, the study designed three sets of fleet electrification scenarios considering different technology penetration and deployment levels for different vehicle type. The scenario analysis extensively explored the energy consumption and GHG emission trajectories for the different vehicle growth scenarios, electrification pathways and renewable energy penetration rates in the grid. The scenarios also considered, as mentioned, changes in the demographics. For instance, in aging society scenario (considering an aging and decreasing fertility demographic), fleet growth rates slow down in the following three decades. This scenario results in a reduction of energy consumption and GHG emission from the road transportation sector. The scenario analysis extensively explored the energy consumption and GHG emission trajectories of the different vehicle growth scenarios, electrification pathways, and renewable energy penetration rates in the grid. From the scenarios analysis, in the aging society vehicle growth scenario, the decelerate vehicle ownership growth rates would bring down the energy consumption and GHG emission from road transportation sector. With the electrification pace stated in the NEV Development Technology Roadmap, the scenarios with truck electrification could bring down the GHG emission 26.6 to 30.4% than the electrification targets solely met through light-duty vehicles electrification, which highlight the need electrify both light-, and medium- and heavy-duty vehicles to achieve the larger reductions. Concentrating on light-duty will be enough to achieve reductions as needed by the country’s reduction targets. However, at present, most of the electrified vehicles are small private light duty passenger vehicles, and the current trends of increased vehicle sizes, would make it impossible to reach the carbon neutrality target. Consequently, a faster electrification and more deployment in the trucking sector would help to significantly bring down the energy consumption and GHG emissions. Furthermore, vehicle electrification must be accompanied by a rapid renewable energy penetration in the power grid to achieve GHG emissions reduction. The models show that if the electricity grid significantly phases out coal fired electricity down to 30% by 2030, GHG emissions from the cleaner fleet could reach carbon neutrality by 2050. To provide some context on the potential feasibility of the scenarios, the study conducted a case study in Shenzhen, which has been able to achieve a very large penetration of the electric vehicles in its transit fleet. The case study included a total cost of ownership analysis of the electric bus fleet, and compare it to the traditional diesel bus. Battery electric bus reached cost parity with the diesel bus with the support of governmental subsidies, and when environmental cost are considered, these buses are preferable to diesel ones.
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