Ge Zhou

Facing the increasingly severe challenges of global climate change, China has established clear “dual carbon” goals, with the core objective of achieving carbon peak by 2030 or earlier. However, carbon emissions from the road freight industry have remained higher for many years; understanding and estimating the characteristics of truck carbon emissions are critical for developing a low-carbon transportation system. This study takes Heilongjiang Province, a typically cold region, as a case study. By employing the growth curve method, we predicted the time for achieving carbon peak and constructed an improved STIRPAT model to identify key drivers and pathways for emission reduction in the road freight system. The research results show that only by committing to using the economy to reduce carbon emissions and improve energy intensity can the overall carbon emissions of Heilongjiang Province’s cargo transportation system achieve the “dual carbon” goals as soon as possible. If we develop according to the optimistic scenario proposed in this article, by 2030, the total quantity of trucks will reach about 933,720, and the carbon emissions per vehicle will reach about 178.14 t. If we actively increase the proportion of new energy trucks in the overall quantity of trucks, the peak time is expected to be achieved around 2030. The improvement of technological efficiency (e.g., lowering energy intensity) and the advancement of economic development have been identified as effective pathways for carbon emission reduction. Empirical studies indicate that these measures can achieve emission reduction impacts that are approximately 60 times and 10 times greater, respectively, in terms of efficiency, compared to baseline scenarios. Furthermore, energy intensity improvements and structural shifts toward low-carbon vehicles are critical to expediting peak attainment. This study provides a methodological framework for cold-region emission projections and offers actionable insights for policymakers to design tailored emission reduction pathways in the road freight transportation industry.

As the northernmost megacity in China, the long winters, large population size, and unsustainable transport structure in Harbin determine that the city will produce relatively large carbon emissions. The transportation industry is one of the three greenhouse gas emission sources; therefore, the development of low-carbon transportation is imperative. This work compares commonly used carbon emission measurement methods and chooses a mileage method to classify the carbon emissions of conventional buses of different energy types used in Harbin in 2020. A multi-factor grey prediction model was constructed to predict the population size of Harbin and the number of conventional buses. After that, a scenario analysis method was used to analyze the fuel structure of buses in Harbin from three perspectives: a pessimistic scenario, a baseline scenario, and an optimistic scenario. The carbon emissions of conventional buses were calculated for Harbin from 2023 to 2030. Finally, by combining the prediction results and factors influencing carbon emission, a regular bus path to minimize carbon emissions is proposed. The outcome of this study shows that the carbon emission environment in Harbin will be improved by reducing vehicle energy consumption, optimizing energy structure, standardizing driving behavior, building intelligent transportation, giving priority to public transportation, and improving the road network structure.