关键词: 城市交通；碳排放；偏最小二乘回归模型：影响因素；减排措施

Abstract: In the context of achieving "peak carbon" by 2023, the urban transportion sector has become a major contributor to carbon emissions. In order to alleviate the environmental impact of urban transportation carbon emissions, this paper uses the "down-top method" to measure the carbon emissions of urban transportation in Lhasa from 2013 to 2022, and selects the factors that have a high impact on carbon emissions, such as the total population, gross domestic product (GDP), motor vehicle ownership, and passenger and freight turnover of Lhasa, and analyzes the influencing factors by using the partial least squares regression analysis model. Therefore, it is concluded that freight turnover, motor vehicle ownership, passenger turnover, and gross national product have a promoting effect on carbon emissions, while the impact of local tourists, total population, and public transport passenger volume is relatively low. Therefore, energy conservation and emission reduction measures are proposed accordingly, which provides a favorable reference for the influencing factors of urban transportation carbon emissions in other regions.

Key words: Urban transportation; Carbon emissions; Partial least squares regression model; Influencing factors; Emissions reduction measures