Provincial energy and environmental efficiency analysis of Chinese transportation industry with the fixed-sum carbon emission constraint

Feng, Li; Ye, Shiqi; Chevalier, J.; Zhang, Jinyu; Kou, Gang

doi:10.1016/j.cie.2023.109393

Cited by 11 publications

(2 citation statements)

References 57 publications

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“…By introducing the non-discretionary input DEA eco-efficiency evaluation method (Song [16], 2022), a new double-boundary DEA common weight model (Kiani [17], 2019) was established. From the perspective of spatial characteristics and spatial spillover of transportation green efficiency, researchers used the Global Moran's I index to verify the spatial autocorrelation of factors affecting transportation carbon emissions (Li [18], 2023) and LISA (Local Indications of Spatial As-sociation, LISA) (Yuan [11], 2017). The Dagum Gini coefficient is utilized to examine the spatial non-equilibrium of comprehensive transportation green efficiency (Ma [5], 2022).…”

Section: Introductionmentioning

confidence: 99%

Study on Transportation Green Efficiency and Spatial Correlation in the Yangtze River Economic Belt

Li,

Feng

2024

Sustainability

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The Yangtze River Economic Belt (YREB), a crucial transportation corridor spanning China’s east and west and linking coastal and inland regions, is not only pivotal in the nation’s strategic development but also drives regional economic and social progress through its transportation industry. Despite rapid growth, the industry faces challenges such as low efficiency, resource supply–demand imbalances, and environmental issues. To advance green and sustainable progress, this study establishes a regional transportation green efficiency evaluation system. Using principal component analysis (PCA) to refine input data, the undesirable super-SBM model quantitatively assesses green transportation efficiency (GTE) in YREB provinces and cities, revealing regional disparities. The study also explores spatial correlations and distribution characteristics of GTE. Results indicate that ① YREB’s GTE shows a U-shaped trend, with significant differences between upper, middle, and lower reaches, being stronger in the east and weaker in the west (lower > middle > upper reaches); ② GTE exhibits spatial correlation in YREB regions, with clear clustering; and ③ cold and hot spots of GTE in the middle reaches are relatively stable, with upstream areas generally cold or sub-cold, and hot spots mainly downstream.

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Section: Introductionmentioning

confidence: 99%

Study on Transportation Green Efficiency and Spatial Correlation in the Yangtze River Economic Belt

Li,

Feng

2024

Sustainability

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“…Despite the implementation of low-carbon development strategies focused on green travel in major cities, carbon emissions from the transport sector continue to contribute over 10% to the national total. Road transport alone accounts for approximately 80% of these emissions and is increasing [3][4][5] . Consequently, urban rail transit, as a public transportation mode characterized by low emissions and high energy efficiency, is receiving increasing attention 6 .…”

Section: Introductionmentioning

confidence: 99%

Quantitative Assessment of the Environmental Impact of Urban Rail Transits through Carbon Emission Reduction—A Case Study of Beijing Municipality

Jia,

Wang,

Qian

et al. 2024

Preprint

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Urban rail transit, as an efficient and eco-friendly mode of transportation, plays a pivotal role in mitigating traffic congestion and lowering urban carbon emissions. Despite the significant contributions by scholars in this area, debates surrounding the quantification of carbon emissions during the operational phase of urban rail transit persist, particularly in assessing its impact on reducing ground traffic congestion. This study focuses on the passenger flows in Beijing during peak morning and evening hours, postulating a shift from urban rail transit to alternative modes, such as buses and taxis. A model predicting traffic congestion states based on passenger flow and other relevant parameters was developed. Through this model, the study calculates the potential congestion times across various scenarios, employing a bottom-up approach to carbon emission estimation to analyze the impact on carbon emissions. Results spanning 2015 to 2021 suggest that substituting urban rail transit with buses could increase congestion by 76–169 minutes and 101–162 minutes during morning and evening peaks, respectively, leading to a 27%-51% and 31%-55% surge in carbon emissions. Conversely, a shift to taxis could result in a 271–291 minutes and 252–312 minutes increment in congestion times, with carbon emissions spiking by 130%-222% and 142%-236%, respectively. These outcomes emphasize the substantial efficacy of urban rail transit in curbing traffic congestion and carbon emissions.

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Assessing the performance of industrial water resource systems in China with total constraints on water consumption and pollution emissions

Qin,

Wang

2023

Environ Sci Pollut Res

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Provincial energy and environmental efficiency analysis of Chinese transportation industry with the fixed-sum carbon emission constraint

Cited by 11 publications

References 57 publications

Study on Transportation Green Efficiency and Spatial Correlation in the Yangtze River Economic Belt

Study on Transportation Green Efficiency and Spatial Correlation in the Yangtze River Economic Belt

Quantitative Assessment of the Environmental Impact of Urban Rail Transits through Carbon Emission Reduction—A Case Study of Beijing Municipality

Assessing the performance of industrial water resource systems in China with total constraints on water consumption and pollution emissions

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