[Energy-saving and Emission Reduction Path for Road Traffic in Key Coastal Cities of Guangdong, Fujian and Zhejiang].

The rapid development of society and economy has resulted in a substantial increase in energy consumption, consequently exacerbating pollution issues. Current research predominantly focuses on energy-saving and emission reduction in road transportation within individual cities or the three major economic regions of China:the Yangtze River Delta, the Pearl River Delta, and the Beijing-Tianjin-Hebei Region. However, there is a dearth of studies addressing the southeastern coastal economic region. Located at the heart of China's southeastern coastal economic development, the provinces of Guangdong, Fujian, and Zhejiang unavoidably face challenges associated with energy consumption and emissions while pursuing economic growth. To address these challenges, this study employed a LEAP model to construct various scenarios for road transportation in the key coastal cities of Guangdong, Fujian, and Zhejiang from 2015 to 2035. These scenarios included a baseline scenario (BAU), an existing policy scenario (EPS), and an improved policy scenario (MPS). The MPS and EPS encompassed vehicle structure optimization (VSO), improved fuel economy (IFE), and reduced annual average mileage (RDM). By simulating and evaluating these scenarios, the energy-saving and emission reduction potentials of road transportation in the key coastal cities were assessed. The results indicated that, in the primary scenario, the MPS exhibited the most significant improvements in energy-saving, carbon reduction, and pollutant reduction effects. By 2035, the MPS achieved a remarkable 75% energy-saving rate compared to that in the baseline scenario, accompanied by reductions of 68%, 59%, 66%, 70%, and 64% in CO2 , CO, NO x , PM2.5 , and SO2 emissions, respectively. In the secondary scenario, the improved scenario of enhancing fuel economy achieved a notable 30% reduction in energy consumption. Additionally, the scenarios involving vehicle structure adjustment (yielding reductions of 36%, 30%, 36%, 26%, and 40%) and annual average mileage reduction (resulting in reductions of 37%, 37%, 36%, 37%, and 36%) demonstrated significant reductions in CO2 , CO, NO x , PM2.5 , and SO2 emissions.