基于正交试验的信号交叉口机动车排放影响因素分析

    Influencing Factor Analysis of Vehicle Emissions at a Signalized Intersection Based on Orthogonal Experiments

    • 摘要: 为考虑温湿度、坡度、中型车比例、公交车比例、交通需求5种因素对小汽车、中型车、公交车的NOx、CO、HC排放的影响,设计正交试验方案,利用VISSIM软件获得每种试验方案对应的交通流量、速度等数据,结合MOVES模型得到每一路段不同车型不同污染物的排放量和排放因子.采用方差分析和极差分析处理正交试验结果,对坡度与排放因子进行回归分析,还比较了进口道与非进口道上、不同排放阶段下所得排放因子的差异.结果显示,温湿度、坡度、中型车比例、公交车比例、交通需求对机动车排放量有显著影响;当交通流处于非拥挤状态时,随着下坡坡度的减小或上坡坡度的增加,各车型各污染物的排放因子均增加;机动车排放因子及其随坡度的变化率在进口道上均为在非进口道上的1.5~6.5倍;国四、国五、国六阶段的机动车排放因子相比国三阶段分别降低约27.5%、38.8%、54.9%.研究成果表明,温湿度、坡度、交通流组成、交通需求、是否处于进口道以及排放阶段都对各类机动车各种污染物的排放有重要影响.

       

      Abstract: Considering the impacts of temperature and humidity, grade, medium-size vehicle ratio, bus ratio, and traffic demand on NOx, CO and HC emissions of car, medium-size vehicle and bus, the orthogonal experiment scenarios were designed. Using the VISSIM software, the data of traffic volume, speed and the others were first obtained for each scenario. Then, the emission quantities and factors per link were estimated for different vehicle types and for different pollutants by combining the VISSIM software with the MOVES model. The analysis of variance and range analysis were carried out to process the outcomes from the orthogonal experiments, and the regression analysis was done to acquire the relationship between emission factor and grade. The emission factors at approaches and at non-approaches, and the emission factors obtained under various stages were also compared separately. The outcomes reveal that temperature and humidity, grade, medium-size vehicle ratio, bus ratio, and traffic demand all have significant impacts on vehicle emission quantities; the emission factor of each pollutant increases for each type of vehicle in non-congestion when the downhill grade declines or the uphill grade raises; the emission factors and their change rates with grade at approaches are 1.5-6.5 times higher than those at non-approaches; compared with stage three, the emission factors under stages four, five and six decrease by 27.5%, 38.8% and 54.9%, respectively. Results show that temperature and humidity, grade, vehicle composition, traffic demand, whether vehicles are at approaches, and emission stage all have important effects on traffic emissions for different vehicle types and for different pollutants.

       

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