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Evaluating the Effect of Roadside Parking on a Dual-Direction Urban Street

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[Dynamic road vehicle emission inventory simulation study based on real time traffic information].

Cheng Huang¹, Juan Liu, Chang-Hong Chen

¹Shanghai Academy of Environmental Sciences, Shanghai 200233, China. huangc@saes.sh.cn

Huan Jing Ke Xue= Huanjing Kexue

|January 18, 2013

Summary

A new dynamic vehicle emission simulation method accurately models Shanghai

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Area of Science:

Environmental Science
Transportation Engineering
Atmospheric Chemistry

Background:

Vehicle emissions significantly impact urban air quality.
Accurate emission inventories are crucial for effective environmental management.
Previous methods lacked real-time dynamic simulation capabilities.

Purpose of the Study:

To develop and validate a dynamic vehicle emission inventory simulation method.
To analyze vehicle activity, driving conditions, and emission patterns in Shanghai.
To provide a decision-making basis for transportation environment management.

Main Methods:

Conducted a vehicle activity survey in Shanghai, collecting data on traffic flow, driving conditions, and vehicle technologies.
Established databases for vehicle flow, Vehicle Specific Power (VSP) distribution, and vehicle categories.
Designed a dynamic emission simulation method using real-time traffic data (flow, average speed).

Main Results:

Light-duty passenger cars and taxis are dominant vehicle types in Shanghai.
Vehicle Specific Power (VSP) distribution correlates with average speed.
Euro 2 and Euro 3 vehicles constitute the majority of the vehicle population.
Emission peaks for CO, VOC, NOx, and PM were 3.7, 4.6, 9.6, and 19.8 times higher than valleys, respectively.
CO and VOC emissions are linked to traffic flow, primarily from passenger cars and taxis.
NOx and PM emissions originate mainly from heavy-duty and public buses during peak hours.

Conclusions:

The dynamic simulation method accurately reflects real-world road emissions.
The method can identify high-emission road sectors and times in real-time.
This approach offers a valuable tool for transportation and environmental management.