The increasing vehicle usage has brought about a sharp increase in greenhouse gas (GHG) emissions of vehicles, which brings severe challenges to the sustainable development of road transportation in Chinese counties. Low-carbon transportation planning is an essential strategy for carbon control from the source of carbon emissions and is crucial to the full transition to a low-carbon future. For transportation planning designers, a quick and accurate estimation of carbon emissions under different transportation planning schemes is a prerequisite to determine the optimal low-carbon transportation development plan. To address this issue, a novel prediction method of hourly GHG emissions over the urban roads network was constructed in this paper. A case study was conducted in Changxing county, and the results indicate the effectiveness of our proposed method. Furthermore, we applied the same approach to 30 other counties in China to analyze the influencing factors of emissions from urban road networks in Chinese counties. The analysis results indicate that the urban road mileage and arterial road ratio are the two most important factors affecting road network GHG emissions in road traffic planning process. Moreover, the method was employed to derive peak hour emission coefficients that can be used to quickly estimate daily or annual GHG emissions. The peak hour emission of CO2, CH4, and N2O accounts for approximately 9–10%, 8.5–10.5%, 5.5–7.5% of daily emissions, respectively. It is expected that the findings from this study would be helpful for establishing effective carbon control strategies in the transportation planning stage to reduce road traffic GHG emissions in counties.


  • In 2015, 17 Sustainable Development Goals (SDGs) were adopted by 193 countries for sustainable development over the coming years

  • This paper focuses on the research and application of greenhouse gas (GHG) emission estimation for low-carbon road transportation planning, which can lay the foundation for the implementation of low-carbon strategies and is a critical technology to achieve structural emission reduction

  • Motivated by the conception of design-hour volume (DHV) in road traffic planning, in this paper we propose the concept of peak hour GHG emission coefficient, which can be calculated as: APHE = ADE ∗ K 100 (8)

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In 2015, 17 Sustainable Development Goals (SDGs) were adopted by 193 countries for sustainable development over the coming years. The methodology is applicable to the prediction of the GHG emissions from road traffic in planning year and suitable for the evaluation of carbon emissions of existing road network if current road network indicator data are available This method is new to the field of GHG emissions prediction from road transportation and helped in identifying key factors and their changes to influence the sustainability of road transportation in any Chinese county. The main contribution of this study lies in applying only urban road planning indicators to evaluate GHG emissions in the planning year that could be potentially employed by transportation planners or government policy-makers to implement effective carbon control measures and promote low-carbon transportation development

Calibration of MOVES
Estimation of Traffic Activity Data
Hourly Traffic Volume Estimation
Prediction of Average Speed Distribution on Different Road Types
Case Study
Application to GHG Driving Factors Analysis
Application to Peak Hour Emission Coefficient

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