Time-Varying Dynamics and Socioeconomic Determinants of Energy Consumption and Truck Emissions in Cold Regions
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 es...
Saved in:
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-07-01
|
| Series: | Energies |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1996-1073/18/13/3527 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849319902756732928 |
|---|---|
| author | Ge Zhou Wenhui Zhang Xiaotian Qiao Wenjie Lv Ziwen Song |
| author_facet | Ge Zhou Wenhui Zhang Xiaotian Qiao Wenjie Lv Ziwen Song |
| author_sort | Ge Zhou |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-e4a9fec935af4df5a81be18991b0d523 |
| institution | Kabale University |
| issn | 1996-1073 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj-art-e4a9fec935af4df5a81be18991b0d5232025-08-20T03:50:17ZengMDPI AGEnergies1996-10732025-07-011813352710.3390/en18133527Time-Varying Dynamics and Socioeconomic Determinants of Energy Consumption and Truck Emissions in Cold RegionsGe Zhou0Wenhui Zhang1Xiaotian Qiao2Wenjie Lv3Ziwen Song4School of Civil Engineering and Transportation, Northeast Forestry University, 26 Hexing Str., Harbin 150040, ChinaSchool of Civil Engineering and Transportation, Northeast Forestry University, 26 Hexing Str., Harbin 150040, ChinaSchool of Civil Engineering and Transportation, Northeast Forestry University, 26 Hexing Str., Harbin 150040, ChinaSchool of Civil Engineering and Transportation, Northeast Forestry University, 26 Hexing Str., Harbin 150040, ChinaSchool of Civil Engineering and Transportation, Northeast Forestry University, 26 Hexing Str., Harbin 150040, ChinaFacing 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.https://www.mdpi.com/1996-1073/18/13/3527road transporttruckscarbon emissionsinfluencing factorsenergy intensity |
| spellingShingle | Ge Zhou Wenhui Zhang Xiaotian Qiao Wenjie Lv Ziwen Song Time-Varying Dynamics and Socioeconomic Determinants of Energy Consumption and Truck Emissions in Cold Regions Energies road transport trucks carbon emissions influencing factors energy intensity |
| title | Time-Varying Dynamics and Socioeconomic Determinants of Energy Consumption and Truck Emissions in Cold Regions |
| title_full | Time-Varying Dynamics and Socioeconomic Determinants of Energy Consumption and Truck Emissions in Cold Regions |
| title_fullStr | Time-Varying Dynamics and Socioeconomic Determinants of Energy Consumption and Truck Emissions in Cold Regions |
| title_full_unstemmed | Time-Varying Dynamics and Socioeconomic Determinants of Energy Consumption and Truck Emissions in Cold Regions |
| title_short | Time-Varying Dynamics and Socioeconomic Determinants of Energy Consumption and Truck Emissions in Cold Regions |
| title_sort | time varying dynamics and socioeconomic determinants of energy consumption and truck emissions in cold regions |
| topic | road transport trucks carbon emissions influencing factors energy intensity |
| url | https://www.mdpi.com/1996-1073/18/13/3527 |
| work_keys_str_mv | AT gezhou timevaryingdynamicsandsocioeconomicdeterminantsofenergyconsumptionandtruckemissionsincoldregions AT wenhuizhang timevaryingdynamicsandsocioeconomicdeterminantsofenergyconsumptionandtruckemissionsincoldregions AT xiaotianqiao timevaryingdynamicsandsocioeconomicdeterminantsofenergyconsumptionandtruckemissionsincoldregions AT wenjielv timevaryingdynamicsandsocioeconomicdeterminantsofenergyconsumptionandtruckemissionsincoldregions AT ziwensong timevaryingdynamicsandsocioeconomicdeterminantsofenergyconsumptionandtruckemissionsincoldregions |