Pub Date : 2024-11-21DOI: 10.1016/j.tranpol.2024.11.017
Wenqian Zou , Zhanshuo Zhang , Shengguo Gao , Lei Wang , Yonglei Jiang
This study analyzes the impact of the temporary flight subsidy policy on the operational performance of China's domestic air transport market. Using panel data from 42 days between May 7 and June 17, 2022, and applying a dynamic panel model with time-invariant variables, the study explores the factors influencing average load factor and average ticket price under short-term basic air service conditions. The results reveal that, during the pandemic, load factors exhibited weak dependence on historical data, with airlines adjusting to real-time demand fluctuations. Additionally, the flight subsidy policy failed to meet its intended goals, leading to a reduction in overall load factors, particularly for China Southern, China Eastern, and Hainan Airlines, while Air China demonstrated more flexibility in adapting to the policy. The study also identifies the significant influence of route distance and airport size on both load factors and ticket prices, with longer routes and major hub airports commanding higher prices. These findings suggest that future subsidy policies should be more flexible and tailored to specific market conditions to effectively support the recovery and long-term sustainability of the aviation industry.
{"title":"Drivers of short-term essential air service operations: Load factor, pricing, and subsidy policies in China's domestic air market","authors":"Wenqian Zou , Zhanshuo Zhang , Shengguo Gao , Lei Wang , Yonglei Jiang","doi":"10.1016/j.tranpol.2024.11.017","DOIUrl":"10.1016/j.tranpol.2024.11.017","url":null,"abstract":"<div><div>This study analyzes the impact of the temporary flight subsidy policy on the operational performance of China's domestic air transport market. Using panel data from 42 days between May 7 and June 17, 2022, and applying a dynamic panel model with time-invariant variables, the study explores the factors influencing average load factor and average ticket price under short-term basic air service conditions. The results reveal that, during the pandemic, load factors exhibited weak dependence on historical data, with airlines adjusting to real-time demand fluctuations. Additionally, the flight subsidy policy failed to meet its intended goals, leading to a reduction in overall load factors, particularly for China Southern, China Eastern, and Hainan Airlines, while Air China demonstrated more flexibility in adapting to the policy. The study also identifies the significant influence of route distance and airport size on both load factors and ticket prices, with longer routes and major hub airports commanding higher prices. These findings suggest that future subsidy policies should be more flexible and tailored to specific market conditions to effectively support the recovery and long-term sustainability of the aviation industry.</div></div>","PeriodicalId":48378,"journal":{"name":"Transport Policy","volume":"161 ","pages":"Pages 44-58"},"PeriodicalIF":6.3,"publicationDate":"2024-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142747090","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Methanol dual-fuel (DF) liners can simultaneously use traditional fuel oil and methanol as blended fuels, which can address environmental protection requirements while ensuring economy. This paper presents an optimization model for the speed and refueling strategy of methanol DF liners. A decision-making tool is introduced for shipping companies to develop liner operation plans. A mixed-integer 0–1 planning model is constructed with the objective of minimizing the operating cost of a single voyage of a methanol DF liner, and the optimal solutions for the voyage speed in each segment and the fuel oil and methanol refueling strategy at each port are computed considering the dual-fuel mixing of fuel oil and methanol. In this paper, the validity of the model and algorithm are verified with the AEU3 route of COSCO Shipping as an example, and the results show that installing a scrubber on liners and mixing heavy fuel oil (HFO) and methanol is more economical than mixing very low-sulfur fuel oil (VLSFO) and methanol, considering the existing emission standards. The studied liner should increase its speed in emission control areas (ECAs) and refuel at ports with low prices for fuel oil and methanol. Although the above conclusions are not influenced by changes in the price of methanol, the price difference between HFO and VLSFO, or the carbon allowance price, changes in sulfur emission standards will have a significant effect on the speed and refueling strategy of liners and carbon emissions. This paper provides a theoretical reference for operational decision-making for shipping companies operating methanol DF liners and is of practical value for improving the scientific management of methanol DF liners, enhancing the energy efficiency of ships, and reducing the emission of pollutants from ships.
{"title":"A model for speed and fuel refueling strategy of methanol dual-fuel liners with emission control areas","authors":"Tianhang Gao, Jia Tian, Changjian Liu, Chuan Huang, Hongyu Wu, Ziwen Yuan","doi":"10.1016/j.tranpol.2024.11.015","DOIUrl":"10.1016/j.tranpol.2024.11.015","url":null,"abstract":"<div><div>Methanol dual-fuel (DF) liners can simultaneously use traditional fuel oil and methanol as blended fuels, which can address environmental protection requirements while ensuring economy. This paper presents an optimization model for the speed and refueling strategy of methanol DF liners. A decision-making tool is introduced for shipping companies to develop liner operation plans. A mixed-integer 0–1 planning model is constructed with the objective of minimizing the operating cost of a single voyage of a methanol DF liner, and the optimal solutions for the voyage speed in each segment and the fuel oil and methanol refueling strategy at each port are computed considering the dual-fuel mixing of fuel oil and methanol. In this paper, the validity of the model and algorithm are verified with the AEU3 route of COSCO Shipping as an example, and the results show that installing a scrubber on liners and mixing heavy fuel oil (HFO) and methanol is more economical than mixing very low-sulfur fuel oil (VLSFO) and methanol, considering the existing emission standards. The studied liner should increase its speed in emission control areas (ECAs) and refuel at ports with low prices for fuel oil and methanol. Although the above conclusions are not influenced by changes in the price of methanol, the price difference between HFO and VLSFO, or the carbon allowance price, changes in sulfur emission standards will have a significant effect on the speed and refueling strategy of liners and carbon emissions. This paper provides a theoretical reference for operational decision-making for shipping companies operating methanol DF liners and is of practical value for improving the scientific management of methanol DF liners, enhancing the energy efficiency of ships, and reducing the emission of pollutants from ships.</div></div>","PeriodicalId":48378,"journal":{"name":"Transport Policy","volume":"161 ","pages":"Pages 1-16"},"PeriodicalIF":6.3,"publicationDate":"2024-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142707291","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-11-20DOI: 10.1016/j.tranpol.2024.11.016
Yudan Kong , Xinyu Tian , Jinghui Sun , Huan Zhou
The global economy's rapid expansion highlights the need for sustainable development in ports. However, existing research has overlooked the crucial aspect of social sustainability. To address this gap, this paper evaluates ports' sustainability using a novel framework that combines cross-hierarchical data envelopment analysis and cross-efficiency. Examining 18 ports in China from 2017 to 2020, we assess their internal and external sustainability dimensions. Results show that most ports demonstrate commendable efficiency in internal sustainability, though room for improvement remains. In terms of external sustainability, some ports excel economically and socially, but environmental indicators require more attention. Overall, sustainability performance shows an encouraging upward trend, with southern ports leading in sustainability practices. However, economic factors pose challenges to port development, emphasizing the need for heightened focus on environmental and social dimensions. By filling a knowledge gap and offering valuable recommendations, this study introduces a fresh perspective on sustainable port development.
{"title":"Charting sustainable vistas: Analysis of internal and external sustainability performance of Chinese ports","authors":"Yudan Kong , Xinyu Tian , Jinghui Sun , Huan Zhou","doi":"10.1016/j.tranpol.2024.11.016","DOIUrl":"10.1016/j.tranpol.2024.11.016","url":null,"abstract":"<div><div>The global economy's rapid expansion highlights the need for sustainable development in ports. However, existing research has overlooked the crucial aspect of social sustainability. To address this gap, this paper evaluates ports' sustainability using a novel framework that combines cross-hierarchical data envelopment analysis and cross-efficiency. Examining 18 ports in China from 2017 to 2020, we assess their internal and external sustainability dimensions. Results show that most ports demonstrate commendable efficiency in internal sustainability, though room for improvement remains. In terms of external sustainability, some ports excel economically and socially, but environmental indicators require more attention. Overall, sustainability performance shows an encouraging upward trend, with southern ports leading in sustainability practices. However, economic factors pose challenges to port development, emphasizing the need for heightened focus on environmental and social dimensions. By filling a knowledge gap and offering valuable recommendations, this study introduces a fresh perspective on sustainable port development.</div></div>","PeriodicalId":48378,"journal":{"name":"Transport Policy","volume":"161 ","pages":"Pages 31-43"},"PeriodicalIF":6.3,"publicationDate":"2024-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142747089","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-11-17DOI: 10.1016/j.tranpol.2024.11.011
Qi Wang , Jianing Mao , Xin Wen , Stein W. Wallace , Muhammet Deveci
Airline schedules are easily affected by disruptions, leading to flight delays or (and) cancellations, causing significant financial losses to airline companies and inconvenience for passengers. When making recovery decisions, airlines need to simultaneously consider various entities, including flights, aircraft, and crew. This paper examines the integrated recovery policies for airlines to help re-schedule flights, re-route aircraft, and reassign crew members. To realize quick responses upon the occurrence of disruptions, an attention-based end-to-end deep reinforcement learning approach is proposed to learn a parameterized stochastic policy for the integrated airline recovery problem. Numerical experiments based on randomly generated disruption instances demonstrate that the proposed method outperforms the existing approaches and is applicable in realistic situations. The key insights obtained from our analyses are summarized as follows: (1) traditionally, among all disruption sources, it is most challenging and time-consuming to determine the recovery policies in reaction to aircraft delays and airport closures. However, the new approach developed in this study overcomes this difficulty and can provide high-quality recovery policies for aircraft delays and airport closures quickly. Thus, our work is especially valuable for airports and regions that suffer from frequent flight delays and closures, and can significantly improve their operational efficiency and service quality; (2) when traditional approaches are applied, the adoption of the well-known schedule robustness enhancement strategy ‘crew follow aircraft’ generally leads to high operations costs. Differently, our proposed approach can apply this strategy without encountering a significant cost growth. Therefore, airlines can fully leverage this strategy to gain additional advantages; (3) our developed new approach demonstrates high generality to accommodate various disruptions, which can benefit airlines and airports in the highly-volatile environment with various unpredictable events.
{"title":"Flight, aircraft, and crew integrated recovery policies for airlines - A deep reinforcement learning approach","authors":"Qi Wang , Jianing Mao , Xin Wen , Stein W. Wallace , Muhammet Deveci","doi":"10.1016/j.tranpol.2024.11.011","DOIUrl":"10.1016/j.tranpol.2024.11.011","url":null,"abstract":"<div><div>Airline schedules are easily affected by disruptions, leading to flight delays or (and) cancellations, causing significant financial losses to airline companies and inconvenience for passengers. When making recovery decisions, airlines need to simultaneously consider various entities, including flights, aircraft, and crew. This paper examines the integrated recovery policies for airlines to help re-schedule flights, re-route aircraft, and reassign crew members. To realize quick responses upon the occurrence of disruptions, an attention-based end-to-end deep reinforcement learning approach is proposed to learn a parameterized stochastic policy for the integrated airline recovery problem. Numerical experiments based on randomly generated disruption instances demonstrate that the proposed method outperforms the existing approaches and is applicable in realistic situations. The key insights obtained from our analyses are summarized as follows: (1) traditionally, among all disruption sources, it is most challenging and time-consuming to determine the recovery policies in reaction to aircraft delays and airport closures. However, the new approach developed in this study overcomes this difficulty and can provide high-quality recovery policies for aircraft delays and airport closures quickly. Thus, our work is especially valuable for airports and regions that suffer from frequent flight delays and closures, and can significantly improve their operational efficiency and service quality; (2) when traditional approaches are applied, the adoption of the well-known schedule robustness enhancement strategy ‘crew follow aircraft’ generally leads to high operations costs. Differently, our proposed approach can apply this strategy without encountering a significant cost growth. Therefore, airlines can fully leverage this strategy to gain additional advantages; (3) our developed new approach demonstrates high generality to accommodate various disruptions, which can benefit airlines and airports in the highly-volatile environment with various unpredictable events.</div></div>","PeriodicalId":48378,"journal":{"name":"Transport Policy","volume":"160 ","pages":"Pages 245-258"},"PeriodicalIF":6.3,"publicationDate":"2024-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142705135","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-11-15DOI: 10.1016/j.tranpol.2024.11.009
Lingxiao Yang , Jianfeng Zheng , Jian Wang
For the design of feeder lines within a region, previous studies assume that the hub port is given in advance. It is necessary to investigate locating hub port together with designing feeder lines for a region. This paper proposes a hub port location and routing problem for a single-hub feeder network, which addresses feeder line design and hub port location. The proposed problem also considers liner shipping network connectivity (the connection between feeder lines and main lines via container transshipment at hub ports). It is described by a mixed integer linear program, which is solved by a genetic algorithm devised. Numerical experiments show that: i) the devised algorithm can efficiently solve our model; ii) due to considering liner shipping network connectivity, the optimal solution of hub port location and feeder line design becomes more rational, as compared with that without considering liner shipping network connectivity.
{"title":"Hub port location and routing for a single-hub feeder network: Effect of liner shipping network connectivity","authors":"Lingxiao Yang , Jianfeng Zheng , Jian Wang","doi":"10.1016/j.tranpol.2024.11.009","DOIUrl":"10.1016/j.tranpol.2024.11.009","url":null,"abstract":"<div><div>For the design of feeder lines within a region, previous studies assume that the hub port is given in advance. It is necessary to investigate locating hub port together with designing feeder lines for a region. This paper proposes a hub port location and routing problem for a single-hub feeder network, which addresses feeder line design and hub port location. The proposed problem also considers liner shipping network connectivity (the connection between feeder lines and main lines via container transshipment at hub ports). It is described by a mixed integer linear program, which is solved by a genetic algorithm devised. Numerical experiments show that: i) the devised algorithm can efficiently solve our model; ii) due to considering liner shipping network connectivity, the optimal solution of hub port location and feeder line design becomes more rational, as compared with that without considering liner shipping network connectivity.</div></div>","PeriodicalId":48378,"journal":{"name":"Transport Policy","volume":"160 ","pages":"Pages 212-227"},"PeriodicalIF":6.3,"publicationDate":"2024-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142705132","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-11-15DOI: 10.1016/j.tranpol.2024.11.010
Shuang Cui , Lijun Tian , Yue Bao , Zhichao Zhang
Prior negative congestion experiences can influence public acceptance of congestion charging policies; however, this area remains underexplored in both academic and practical contexts. This study investigates this issue by integrating the norm activation model (NAM) and the theory of planned behavior (TPB), focusing on public acceptance of tradable credits schemes (TCS). Specifically, acceptance is measured via attitudes toward TCS and behavioral intentions to reduce car use under TCS. Using latent profile analysis, 426 participants were categorized into three distinct groups based on their prior negative congestion experiences. The findings indicate that those with high reactions exhibit stronger behavioral intentions to reduce car use. Chain mediation analysis demonstrates that prior negative congestion experiences causally impact these behavioral intentions. Moderated mediation analysis further reveals that such experiences (e.g., anxiety and bodily reactions) moderate behavioral intentions under TCS. High levels of anxiety and bodily reactions weaken the impact of personal norms on attitudes toward TCS, suggesting that individuals with intense reactions to congestion are more likely to directly support TCS. Conversely, enhancing personal norms among individuals with lower anxiety or bodily reactions tend to increase their support for TCS. Furthermore, personal norms are found to be more influential than social norms, offering greater explanatory power.
{"title":"Impacts of negative congestion experiences on acceptance of tradable credits schemes: Integration of NAM and TPB","authors":"Shuang Cui , Lijun Tian , Yue Bao , Zhichao Zhang","doi":"10.1016/j.tranpol.2024.11.010","DOIUrl":"10.1016/j.tranpol.2024.11.010","url":null,"abstract":"<div><div>Prior negative congestion experiences can influence public acceptance of congestion charging policies; however, this area remains underexplored in both academic and practical contexts. This study investigates this issue by integrating the norm activation model (NAM) and the theory of planned behavior (TPB), focusing on public acceptance of tradable credits schemes (TCS). Specifically, acceptance is measured via attitudes toward TCS and behavioral intentions to reduce car use under TCS. Using latent profile analysis, 426 participants were categorized into three distinct groups based on their prior negative congestion experiences. The findings indicate that those with high reactions exhibit stronger behavioral intentions to reduce car use. Chain mediation analysis demonstrates that prior negative congestion experiences causally impact these behavioral intentions. Moderated mediation analysis further reveals that such experiences (e.g., anxiety and bodily reactions) moderate behavioral intentions under TCS. High levels of anxiety and bodily reactions weaken the impact of personal norms on attitudes toward TCS, suggesting that individuals with intense reactions to congestion are more likely to directly support TCS. Conversely, enhancing personal norms among individuals with lower anxiety or bodily reactions tend to increase their support for TCS. Furthermore, personal norms are found to be more influential than social norms, offering greater explanatory power.</div></div>","PeriodicalId":48378,"journal":{"name":"Transport Policy","volume":"160 ","pages":"Pages 192-211"},"PeriodicalIF":6.3,"publicationDate":"2024-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142705131","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-11-14DOI: 10.1016/j.tranpol.2024.11.008
Lu Zhang , Jiaying Gong , Yu Yang
The COVID-19 pandemic has profoundly impacted international flights, leading to substantial economic repercussions for the global tourism industry. While existing research has explored the resilience and recovery of the air transport system during the pandemic, this analysis delves into the structural transformation of the air transportation network within “the Belt and Road” region through a quantitative analysis. The findings reveal three critical aspects: (1) The pandemic caused a marked reduction in air transport connectivity, with flight frequency and route connectivity between cities decreasing by 27.82% and 35.87%, respectively, although the basic aviation framework remained intact. This impact varied across different administrative levels, regions, and distances, due to the impact of different countries' pandemic policies. Transnational connections were particularly hard-hit, experiencing more severe disruptions than domestic routes. (2) Significant shifts occurred in the rankings of aviation hubs. For example, cities like Singapore and Doha rose in prominence, while traditional hubs such as Moscow and Beijing saw a decline in their rankings. This shift reflects a reconfiguration of key nodes within the aviation network. (3) The network structure underwent significant reorganization and decentralization, transitioning from a conventional core-periphery model to a hybrid structure that blends core-peripheries with local communities. This transformation demonstrates the network's adaptability and its capacity to develop alternative structures in response to sudden external shocks like the COVID-19 pandemic. The insights from this analysis offer valuable guidance for policy-making and the development of emergency measures to better prepare for and mitigate future disruptions in air transport. The analysis underscores the importance of flexible and adaptive strategies in managing aviation networks, particularly in the face of global challenges.
{"title":"How has the COVID-19 pandemic reshaped the aviation network? A comparative pre- and during-pandemic analysis","authors":"Lu Zhang , Jiaying Gong , Yu Yang","doi":"10.1016/j.tranpol.2024.11.008","DOIUrl":"10.1016/j.tranpol.2024.11.008","url":null,"abstract":"<div><div>The COVID-19 pandemic has profoundly impacted international flights, leading to substantial economic repercussions for the global tourism industry. While existing research has explored the resilience and recovery of the air transport system during the pandemic, this analysis delves into the structural transformation of the air transportation network within “the Belt and Road” region through a quantitative analysis. The findings reveal three critical aspects: (1) The pandemic caused a marked reduction in air transport connectivity, with flight frequency and route connectivity between cities decreasing by 27.82% and 35.87%, respectively, although the basic aviation framework remained intact. This impact varied across different administrative levels, regions, and distances, due to the impact of different countries' pandemic policies. Transnational connections were particularly hard-hit, experiencing more severe disruptions than domestic routes. (2) Significant shifts occurred in the rankings of aviation hubs. For example, cities like Singapore and Doha rose in prominence, while traditional hubs such as Moscow and Beijing saw a decline in their rankings. This shift reflects a reconfiguration of key nodes within the aviation network. (3) The network structure underwent significant reorganization and decentralization, transitioning from a conventional core-periphery model to a hybrid structure that blends core-peripheries with local communities. This transformation demonstrates the network's adaptability and its capacity to develop alternative structures in response to sudden external shocks like the COVID-19 pandemic. The insights from this analysis offer valuable guidance for policy-making and the development of emergency measures to better prepare for and mitigate future disruptions in air transport. The analysis underscores the importance of flexible and adaptive strategies in managing aviation networks, particularly in the face of global challenges.</div></div>","PeriodicalId":48378,"journal":{"name":"Transport Policy","volume":"160 ","pages":"Pages 228-244"},"PeriodicalIF":6.3,"publicationDate":"2024-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142705133","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-11-13DOI: 10.1016/j.tranpol.2024.11.005
Hang Yuan , Lei Zhao , Hangjun Yang
This study evaluates China's environmental policies, specifically the increase of carbon emission tax rates and the reduction of carbon emission intensity, by developing a New Keynesian Dynamic Stochastic General Equilibrium (NK-DSGE) model that incorporates energy consumption and carbon emissions. The production sector is segmented into manufacturing, non-manufacturing, and transportation, with transportation services acting as inputs for both manufacturing and non-manufacturing firms. We construct four cases within two scenarios, each characterized by distinct targets and policies. After calibrating and estimating the relevant parameters, we compare carbon reduction outcomes and economic fluctuations across the two scenarios. Our findings indicate that when targeting the same carbon emission tax rate increase or carbon emission intensity ratio reduction, policies that increase the carbon emission tax rate or reduce carbon emission intensity implemented in the manufacturing sector achieve greater carbon emission reductions compared to the same polices implemented in the transportation sector. Meanwhile, compared to the latter case, output experienced a greater decline, and inflation exhibited a more substantial increase in the former case. However, when the quantities of carbon emission reductions are approximately the same in the first quarter, policies that increase the carbon emission tax rate or reduce carbon emission intensity enacted in the transportation sector demonstrate superior performance relative to the same polices implemented in the manufacturing sector. This leads to smaller final output reductions and milder inflation increases. In summary, for equivalent levels of carbon emission reductions, policies implemented in the transportation sector yield more favorable economic outcomes than those applied in the manufacturing sector.
{"title":"Comparative analysis of carbon emission reduction policies in China's manufacturing and transportation sectors","authors":"Hang Yuan , Lei Zhao , Hangjun Yang","doi":"10.1016/j.tranpol.2024.11.005","DOIUrl":"10.1016/j.tranpol.2024.11.005","url":null,"abstract":"<div><div>This study evaluates China's environmental policies, specifically the increase of carbon emission tax rates and the reduction of carbon emission intensity, by developing a New Keynesian Dynamic Stochastic General Equilibrium (NK-DSGE) model that incorporates energy consumption and carbon emissions. The production sector is segmented into manufacturing, non-manufacturing, and transportation, with transportation services acting as inputs for both manufacturing and non-manufacturing firms. We construct four cases within two scenarios, each characterized by distinct targets and policies. After calibrating and estimating the relevant parameters, we compare carbon reduction outcomes and economic fluctuations across the two scenarios. Our findings indicate that when targeting the same carbon emission tax rate increase or carbon emission intensity ratio reduction, policies that increase the carbon emission tax rate or reduce carbon emission intensity implemented in the manufacturing sector achieve greater carbon emission reductions compared to the same polices implemented in the transportation sector. Meanwhile, compared to the latter case, output experienced a greater decline, and inflation exhibited a more substantial increase in the former case. However, when the quantities of carbon emission reductions are approximately the same in the first quarter, policies that increase the carbon emission tax rate or reduce carbon emission intensity enacted in the transportation sector demonstrate superior performance relative to the same polices implemented in the manufacturing sector. This leads to smaller final output reductions and milder inflation increases. In summary, for equivalent levels of carbon emission reductions, policies implemented in the transportation sector yield more favorable economic outcomes than those applied in the manufacturing sector.</div></div>","PeriodicalId":48378,"journal":{"name":"Transport Policy","volume":"160 ","pages":"Pages 159-180"},"PeriodicalIF":6.3,"publicationDate":"2024-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142705134","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-11-12DOI: 10.1016/j.tranpol.2024.11.007
M. Prussi, M. Noussan, L. Laveneziana, D. Chiaramonti
The European Union target of a net-zero economy by mid-century requires an unprecedented effort in the reduction of carbon emissions. Aviation is among the most difficult sectors to decarbonize, and since direct electrification is unlikely to become a viable option in the short-term, other alternatives are considered, including biofuels and e-fuels. The blending mandates recently approved in the ReFuelEU Aviation package (35% of e-fuels at 2050) will require devoting an important amount of renewable electricity to produce e-fuels, increasing the relative weight of aviation with respect other sectors in terms of energy consumption. Aviation accounts today for 13% of the EU27 (2019) energy consumption for transport, while in 2050 this is expected to reach the 22%. This “magnifying effect” for the energy required by the sector, due to the low overall conversion efficiency of e-fuel production, will likely foster a competition for the access to renewable energy. This shift toward the aviation sector may occur to detriment of other applications potentially most effective in decreasing carbon emissions per unit of electricity. This apparent dichotomy between GHG reduction and energy efficiency could reduce the actual effectiveness of existing policies and the possibility of fostering similar initiatives in other countries.
{"title":"The risk of increasing energy demand while pursuing decarbonisation: the case of the e-fuels for the EU aviation sector","authors":"M. Prussi, M. Noussan, L. Laveneziana, D. Chiaramonti","doi":"10.1016/j.tranpol.2024.11.007","DOIUrl":"10.1016/j.tranpol.2024.11.007","url":null,"abstract":"<div><div>The European Union target of a net-zero economy by mid-century requires an unprecedented effort in the reduction of carbon emissions. Aviation is among the most difficult sectors to decarbonize, and since direct electrification is unlikely to become a viable option in the short-term, other alternatives are considered, including biofuels and e-fuels. The blending mandates recently approved in the ReFuelEU Aviation package (35% of e-fuels at 2050) will require devoting an important amount of renewable electricity to produce e-fuels, increasing the relative weight of aviation with respect other sectors in terms of energy consumption. Aviation accounts today for 13% of the EU27 (2019) energy consumption for transport, while in 2050 this is expected to reach the 22%. This “magnifying effect” for the energy required by the sector, due to the low overall conversion efficiency of e-fuel production, will likely foster a competition for the access to renewable energy. This shift toward the aviation sector may occur to detriment of other applications potentially most effective in decreasing carbon emissions per unit of electricity. This apparent dichotomy between GHG reduction and energy efficiency could reduce the actual effectiveness of existing policies and the possibility of fostering similar initiatives in other countries.</div></div>","PeriodicalId":48378,"journal":{"name":"Transport Policy","volume":"160 ","pages":"Pages 154-158"},"PeriodicalIF":6.3,"publicationDate":"2024-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142705123","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-11-12DOI: 10.1016/j.tranpol.2024.11.002
Tanya Sharma , Suresh Jain
This study examines the factors influencing the travel behaviour of Delhi's working population, utilizing retrospective cross-sectional data from 2005 to 2019 collected across four neighbourhoods. The research provides empirical evidence on how travel mode choices have evolved over time in response to changes in the built environment and socioeconomic conditions. GIS-based analysis was conducted to assess the impact of temporal variations in the built environment on travel behaviour. Results reveal a 21% increase in the reliance on private modes of transportation between 2005 and 2019, with the most significant rise observed in 4-wheeler usage. Conversely, bus usage declined by 32%, attributed to various factors including overcrowding, hygiene concerns, and perceived reliability issues. However, in 2019, Connaught Place reported the highest bus usage at 28%, attributed to its high bus stop density, while enhanced metro facilities across the neighbourhoods led to a 20% increase in overall metro ridership. Multinomial logistic regression analysis identified key socioeconomic determinants of travel behaviour, including age, gender, income, vehicle ownership, and commuter attitude. In 2005, two-wheeler preference over buses was primarily driven by vehicle ownership (O.R.: 620.95), gender (O.R.: 4.20), and income (O.R.: 1.28). By 2019, commuter attitude (ProPV) emerged as a significant factor, alongside vehicle ownership (O.R.: 136.72), ProPV (O.R.: 21.41), and income (O.R.: 2.14). A similar trend was observed for car usage, highlighting the increasing influence of commuter behaviour and attitudes on travel choices over time. These findings underscore critical policy implications for the development and enhancement of Delhi's transport system, offering insights that could be applicable to other cities facing similar challenges.
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