Modeling impacts of highway circular curve elements on heavy-duty diesel trucks’ CO2 emissions

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Abstract

Heavy-duty trucks contribute a significant component of all transportation in cargo terminals, such as Shaanxi Province, China. The emissions from these vehicles are the primary source of carbon emissions during highway operations. While several studies have attempted to address emission issues by improving traffic operations, a few focused on the relationship between emissions and highway geometric design, especially for heavy-duty trucks. The primary goal of this research was to understand the impact of circular curve on carbon dioxide (CO2) emissions produced by heavy-duty diesel trucks. Firstly, appropriate parameters were specified in MOVES (motor vehicle emission simulator) model according to the geometrical characteristics. Fuel consumption, speed and location data were collected by hiring five skilled drivers on the automotive proving ground located at Chang’an University, Shaanxi Province. The associated carbon emission data were derived from fuel consumption data by applying the IPCC (Intergovernmental Panel on Climate Change) method. After this, the applicability of MOVES model was verified by the field experiment. Moreover, a multiple regression model for CO2 emissions incorporated with roadway segment radius, circular curve length, and initial vehicle speed was established with data generated by the MOVES model. The proposed CO2 emission model was also verified by field experiment with relative error of 6.17%. It was found that CO2 emission had monotone decreasing property with radius increasing, and the minimum radius that influenced diesel CO2 emission was 550 m. The proposed quantitative CO2 emission model can provide a reference for low-carbon highway design, leading to environment-friendly transportation construction.

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CITATION STYLE

APA

Zhang, X., Xu, J., Li, M., Li, Q., & Yang, L. (2019). Modeling impacts of highway circular curve elements on heavy-duty diesel trucks’ CO2 emissions. International Journal of Environmental Research and Public Health, 16(14). https://doi.org/10.3390/ijerph16142514

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