山东交通学院学报

为量化CO₂排放因子、燃料消耗量与交通运行状况对机动车碳排放的影响，以济南市为研究区，在MOVES模型本地化的基础上，构建基于车速的CO₂排放因子模型，建立CO₂排放因子、燃料消耗量与车速的关系式，分析不同交通运行状况对济南市机动车CO₂排放的影响。结果表明：不同类型机动车的CO₂排放因子差异显著，但随平均车速的变化趋势基本一致，当平均车速小于10 km/h时，各车型的CO₂排放因子处于较高水平，平均车速升至10～<50 km/h时，CO₂排放因子迅速减小，平均车速为50～<100 km/h时，CO₂排放因子逐渐稳定并处于较低水平，平均车速为100～120 km/h时，大部分车型的CO₂排放因子有增大趋势；2017年至2022年，济南市核心区的高峰期平均车速由20.18 km/h增至31.72 km/h,拥堵缓解使汽油小型客车、汽油轻型货车、柴油轻型货车、柴油重型货车的CO₂排放因子分别降低21.71%、21.23%、18.84%、15.35%,仅汽油小型客车每年汽油消耗量减少约93.6万t, CO₂排放量减少约312.0万t;将本文模型与基于车辆比功率的CO₂排放因子模型进行对比，二者的CO₂排放因子随平均车速的变化趋势基本一致，在平均车速为15～60 km/h时，所构建模型能较好地拟合CO₂排放因子与平均车速的关系，适用于城市道路交通CO₂排放研究。提高城市交通运行效率是降低机动车碳排放的重要途径。

To quantify the impacts of the CO₂ emission factor, fuel consumption, and traffic operating conditions on vehicle CO₂ emissions, this study takes Jinan City as the research area. Based on a localized MOVES model, a speed-based CO₂ emission factor model is constructed, and the relationship among the CO₂ emission factor, fuel consumption, and vehicle speed is established to analyze the influence of different traffic conditions on vehicle CO₂ emissions in Jinan. The results show that the CO₂ emission factors of different vehicle types differ significantly but follow generally consistent trends with changes in average speed. When the average speed is below 10 km/h, the CO₂ emission factors of all vehicle types remain at a high level. As the average speed increases to 10-50 km/h, the CO₂ emission factors decrease rapidly. When the average speed reaches 50-100 km/h, the CO₂ emission factors gradually stabilize and remain at a relatively low level. At speeds between 100 km/h and 120 km/h, most vehicle types show an increasing trend in CO₂ emission factors. From 2017 to 2022, the average peak-hour speed in the core area of Jinan increased from 20.18 km/h to 31.72 km/h. The alleviation of traffic congestion reduced the CO₂ emission factors of gasoline passenger cars, gasoline light-duty trucks, diesel light-duty trucks, and diesel heavy-duty trucks by 21.71%, 21.23%, 18.84%, and 15.35%, respectively. For gasoline passenger cars alone, this translates to an annual reduction in gasoline consumption of approximately 936 000 tons and a reduction in CO₂ emissions of about 3.12 million tons. The proposed model is compared with the CO₂ emissions factor model based on vehicle specific power, and both show generally consistent trends of CO₂ emission factors with vehicle speed. Within the speed range of 15-60 km/h, the constructed model fits the relationship between CO₂ emission factors and average speed well, demonstrating its applicability to the study of CO₂ emissions from urban road traffic. Improving urban traffic operational efficiency is an important pathway to reducing vehicle CO₂ emissions.