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环境科学  2012 

Dynamic Road Vehicle Emission Inventory Simulation Study Based on Real Time Traffic Information
基于实时交通信息的道路机动车动态排放清单模拟研究

Keywords: emission inventory,vehicle emission,emission simulation,traffic information,real time
排放清单
,机动车排放,排放模拟,交通信息,实时

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Abstract:

The vehicle activity survey, including traffic flow distribution, driving condition, and vehicle technologies, were conducted in Shanghai. The databases of vehicle flow, VSP distribution and vehicle categories were established according to the surveyed data. Based on this, a dynamic vehicle emission inventory simulation method was designed by using the real time traffic information data, such as traffic flow and average speed. Some roads in Shanghai city were selected to conduct the hourly vehicle emission simulation as a case study. The survey results show that light duty passenger car and taxi are major vehicles on the roads of Shanghai city, accounting for 48%-72% and 15%-43% of the total flow in each hour, respectively. VSP distribution has a good relationship with the average speed. The peak of VSP distribution tends to move to high load section and become lower with the increase of average speed. Vehicles achieved Euro 2 and Euro 3 standards are majorities of current vehicle population in Shanghai. Based on the calibration of vehicle travel mileage data, the proportions of Euro 2 and Euro 3 standard vehicles take up 11%-70% and 17%-51% in the real-world situation, respectively. The emission simulation results indicate that the ratios of emission peak and valley for the pollutants of CO, VOC, NOx and PM are 3.7, 4.6, 9.6 and 19.8, respectively. CO and VOC emissions mainly come from light-duty passenger car and taxi, which has a good relationship with the traffic flow. NOx and PM emissions are mainly from heavy-duty bus and public buses and mainly concentrate in the morning and evening peak hours. The established dynamic vehicle emission simulation method can reflect the change of actual road emission and output high emission road sectors and hours in real time. The method can provide an important technical means and decision-making basis for transportation environment management.

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