Sensitivity Analysis And Comparison Of The Factors Affecting Vehicle Emission Based On MOBILE

Chinese vehicle industry has grown rapidly and the number of vehicle increases rapidly with the rapid development of economy. The rapid development of vehicle industry promotes the development of economic, but also brings serious air pollution. We need a proper understanding of relationship between vehicle's emission characteristics and vehicle emission factors. It is tremendous essential to make transportation decision on improving the exhaust pollution. Sensitivity analysis provides an effective tool for the study of vehicle emission models.The factors influencing vehicle emission are very complicated and they mainly contain speed, ambient temperature, operating condition, inspection and maintenance and so on. The main job of this paper is to get large amounts of initial data meeting Chinese emission condition from the MOBILE model, analyze and contrast the influence factors through data processing. Simultaneously, I have established one and multiple variables linear regression emission models, and have processed sensitivity analysis by applying the sampling-based method.Firstly, I have get large amounts of initial data from the MOBILE model, then have contrasted and analyzed the influence level of roadway types, vehicle speed, temperature, fuel RVP to the emission rates of NOx, CO and HC. The emission rates of different vehicle types under different influence factors are complicated and have more large difference.Secondly, I have proposed the prediction models of emission rates based on the speed of a single vehicle type.In these models, the input variable is the vehicle speed and vehicle's emission rate are considered as the output. Therefore, the models are simple and easy to use. Applying regression analysis, the prediction models of emission rates involve the power function models, polynomial function models, exponential models, which mainly contain the polynomial models. We can respectively calculate the three pollutants'emission rates through the established models for a random speed value in any given range.Lastly, as there are many factors impacting vehicle emission on the actual roadway, single-factor models have their limitation and therefore I consider the establishment of multi-factors models of the emission rates, then multiple regression emission rate models based on two independent variables on speed and fuel RVP are established. These models are more realistic and have more accurate results. The key factors impacting models are obtained from the quantitative point of view under certain condition through sensitivity analysis applying based on Latin Hypercube sampling on the factors of models. The speed is more sensitive for CO, NOx emission rate within the considered variable range, however, the fuel RVP is even more sensitive in HC emission rate models as the vehicle speed increases.