Journal articles on the topic 'Low carbon- Transportation- Vishakhapatna'

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1

Chen, Rong Hua. "China’s Urban Low-Carbon Transportation." Advanced Materials Research 962-965 (June 2014): 1697–700. http://dx.doi.org/10.4028/www.scientific.net/amr.962-965.1697.

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At present, the development of China’s urban low-carbon transportation is lagging. This paper analyzed the status of carbon emissions of China's urban transportation, and pointed out that the main problems of China's urban low-carbon transportation were: high carbonation of the urban transportation structure, the unreasonableness of urban layout, the lagging management of low-carbon transportation, the lagging technology innovation of low-carbon transportation. Finally, based on the analysis of the problems, this paper put forward some measures for the development of China's urban low carbon transportation.
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2

Anita, Ratnasari Rakhmatulloh, Zuleika Islamey Talitha, and Intan Kusumo Dewi Diah. "Can online transportation support low carbon?" E3S Web of Conferences 73 (2018): 08001. http://dx.doi.org/10.1051/e3sconf/20187308001.

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The existence of online transportation is one of the alternative priority modes in transportation. Online transportation has the concept of car sharing, mainly by the uses of vehicles together. The function of car-sharing is expected to reduce the number of vehicles use. Through the concept of car sharing, it can help to realize the concept of a low-carbon city. In previous studies, people prefer to choose private cars than public transportation, because of their easiness in mobility and short travel time. Online Transportation is also efficient same as private vehicles, regarding mobility and travel time. Thus, Online Transportation is expected to reduce the usage of private vehicles and create more environmentally friendly. Based on this phenomenon, researchers want to explore the purpose of the preference for online transportation. The result finds out that the variables could influence the choices of online transportation. This research was conducted using the utility of transportation mode selection model.
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3

Huang, Ling, and Han Qing Zhou. "Research on Urban Low-Carbon Transportation." Applied Mechanics and Materials 409-410 (September 2013): 1273–76. http://dx.doi.org/10.4028/www.scientific.net/amm.409-410.1273.

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In order to achieve sustainable development of the economy, resources and environment, developing low-carbon economy is the only way, and urban low-carbon transportation is one of the key areas. The paper analyzes the important significance, characteristics and strategies of developing low-carbon transportation.
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4

Brömmelstroet, Marco te. "Moving Towards Low Carbon Mobility." Transport Reviews 34, no. 1 (January 2, 2014): 122–23. http://dx.doi.org/10.1080/01441647.2013.879236.

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Yu, Bin, Feng Guan, Lin Zhang, Hanbing Zhu, Chao Zhang, Zixuan Peng, and Baozhen Yao. "Waterbus system optimisation for low-carbon transportation." Proceedings of the Institution of Civil Engineers - Transport 168, no. 5 (October 2015): 434–41. http://dx.doi.org/10.1680/jtran.13.00080.

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6

Yu, Bin, Zixuan Peng, Baozhen Yao, Feng Guan, Lin Zhang, Hanbing Zhu, and Chao Zhang. "Waterbus system optimisation for low-carbon transportation." Proceedings of the ICE - Transport 168, no. 5 (October 1, 2015): 434–41. http://dx.doi.org/10.1680/tran.13.00080.

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7

Maheshwari, Hariom. "Low Carbon Transportation System for Indian Cities." International Journal of Scientific Research 3, no. 7 (June 1, 2012): 174–76. http://dx.doi.org/10.15373/22778179/july2014/55.

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8

Xiao, Hong. "Study on Low-Carbon Transportation Plan in China." Advanced Materials Research 598 (November 2012): 121–24. http://dx.doi.org/10.4028/www.scientific.net/amr.598.121.

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The urban motorization has enhanced along with economy development in China, but the environment question and the energy question which brings by the transportation is more serious on urban , I analyzed urban problems along with high density construction by large population, and put forward that the key to low-carbon urban planning under the motorized issues is to deal with relationships between centralization and decentralization .
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9

Cao, Xinyu (Jason), Marlon G. Boarnet, and Xiaoshu Cao. "Low carbon cities: Land use and transportation interventions." Journal of Regional Science 57, no. 3 (June 2017): 467–69. http://dx.doi.org/10.1111/jors.12343.

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10

Creutzig, Felix. "Evolving Narratives of Low-Carbon Futures in Transportation." Transport Reviews 36, no. 3 (September 7, 2015): 341–60. http://dx.doi.org/10.1080/01441647.2015.1079277.

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11

Xin, Linglai. "Current Status and Future Trend of Urban Low-Carbon Transportation in China." Urban Transportation & Construction 6, no. 2 (September 14, 2020): 25. http://dx.doi.org/10.18686/utc.v6i2.85.

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<p>The concept and connotation of urban low-carbon transportation are put forward and expounded. The status of energy consumption and carbon emission of urban transportation since 2000 in China is analyzed. The analysis shows that the total energy consumption and CO2 emission of urban transportation has increased rapidly, and public transportation has the lowest carbon emission intensity among all kinds of motor vehicles. The construction of urban low-carbon transportation in China faces the following problems: the development speed of public transportation lags behind; the non-motorization degree of residents’ travel structure has decreased greatly; the lack of effective demand management, weak awareness of energy conservation and emission reduction; and the urban transportation management system is incompatible with the construction of urban low-carbon transportation Based on the analysis of the present situation, this article puts forward three strategic directions and five main measures for the construction of low-carbon transportation in Chinese cities. Transportation industry is a basic service industry and a key area of urban energy conservation and emission reduction. Effective measures should be taken to accelerate the development of urban low-carbon transportation from the aspects of urban transportation planning, construction and operation.</p>
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12

Miao, Pan, and Xia Guo. "Study on Low-Carbon Development Status Quo and Countermeasures of Transportation in Shandong Province." Applied Mechanics and Materials 291-294 (February 2013): 1389–94. http://dx.doi.org/10.4028/www.scientific.net/amm.291-294.1389.

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The rapid development of the transportation industry in Shandong Province provides a fundamental guarantee for the economic and social development, but also brings a lot of energy consumption and pollutant emissions, directly affecting the construction of ecological Shandong. By investigating low-carbon development of the transportation industry in Shandong Province, this article analyzes the status of low-carbon development and identifies the problems: transportation structure is irrational; low-carbon development lacks corporate body; regulation of transportation energy saving needs to be strengthened. Put forward countermeasures for low-carbon development of the transportation in Shandong Province: speed up the construction of the integrated transport system; optimize transport organization; improve regulation of transportation energy; give full play to the leading role of science and technology to a low-carbon economy; strengthen low-carbon economic subject consciousness of transportation enterprises; develop public low carbon transport consciousness.
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13

Li, Meiyan, and Xiaoni Sun. "Path Optimization of Low-Carbon Container Multimodal Transport under Uncertain Conditions." Sustainability 14, no. 21 (October 28, 2022): 14098. http://dx.doi.org/10.3390/su142114098.

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The development of multimodal transport has had a significant impact on China’s transportation industry. Due to the variability of the market environment, in this study, based on the context of the official launch of the national carbon emission trading market, the uncertainty of the demand and the randomness of carbon trading prices were considered. Taking minimum total transportation cost as the objective function, a robust stochastic optimization model of container multimodal transport was constructed, and a hybrid fireworks algorithm with gravitational search operator (FAGSO) was designed to solve and verify the effectiveness of the algorithm. Using a 35-node multimodal transportation network as an example, the multimodal transportation costs and schemes under three different modes were compared and analyzed, and the influence of parameter uncertainty was determined. The results show that the randomness of carbon trading prices will lead to an increase or decrease in the total transport cost, while robust optimization with uncertain demand will be affected by the regret value constraint, resulting in an increase in the total transport cost. Multimodal carriers can reduce transportation costs, reduce carbon emissions, and improve the transportation efficiency of multimodal transportation by comprehensively weighing the randomness of carbon trading prices, the nondeterminism of demand, and the relationship between the selection of maximum regret values and transportation costs.
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14

Feng, Fenling, Chengguang Liu, Haihong Liu, and Zhizhou Ji. "Research on Price of Railway Freight Based on Low-Carbon Economy." Mathematical Problems in Engineering 2016 (2016): 1–7. http://dx.doi.org/10.1155/2016/6209618.

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Transportation is one of the major energy consumption and carbon emission industries. Railway transport is a typical low-carbon transport. To accelerate the green low-carbon transportation development and improve the railway market share, this paper defines the concept of carbon saving profit to study the price of railway freight after the government functions were separated from railway enterprise management. First, taking full account of market factors and on the principle of utility maximization and maximum likelihood method, the sharing ratio model of transportation modes is established. Then consideration is given to both the profit of railway enterprises and social benefits, and income maximization model of railway freight based on low-carbon economy is established. The model can scientifically guide the transportation users who prefer to use resource-saving and environmental-friendly transportation modes, optimize transportation structure, and comprehensively improve the efficiency of transportation system. Finally, case analysis is conducted to verify the rationality and validity of the model, and reference for the rail freight pricing is provided.
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15

Qiu, Li Xin, and Yan Lei Song. "Path Selection of Low-Carbon Traffic Development in Qingdao." Advanced Materials Research 869-870 (December 2013): 976–79. http://dx.doi.org/10.4028/www.scientific.net/amr.869-870.976.

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By the use of the low-carbon traffic model, quantitatively analyzed the current situation of carbon emissions in different modes of urban traffic, this paper emphasized on studying the low-carbon development paths of Qingdao transportation. The results show that, the proportion of CO2 from private cars is the most highest; the increasing number of private cars, and the reduce use of public transport, is the main reason for the increase urban traffic emissions. Through the study of traffic structure, transportation and energy consumption characteristics of Qingdao, low-carbon development paths of Qingdao transportation are proposed from the aspects of urban space, traffic structure, residents travel mode and energy-saving technology.
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16

Jia, Jian Min, and Ru Hua Zhang. "Evaluation on Urban Low-Carbon and Ecological Transportation System." Applied Mechanics and Materials 361-363 (August 2013): 1967–72. http://dx.doi.org/10.4028/www.scientific.net/amm.361-363.1967.

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With the Fast Development of Economy, Urban Transportation Problems, such as Traffic Congestion, Energy Consumption and Pollution Emission, is Becoming more and more Serious. to Deal with this, Low-Carbon and Ecological Become Significant for Urban Development, and they are the Evaluation Criterions for Urban Transportation Development. Based on the Former Research on Transportation Evaluation, we Add Evaluation Indexes about Pedestrian and Bicycle, which Completes the Evaluation System. Whats more, we Combine the AHP and Coefficient of Variation Method while make Evaluation, which is Different from the Traditional Evaluation Method. Finally, in Order to Test the Evaluation System and Evaluation Method in the Paper, we Choose Jinan as the Example.
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17

Zheng, Yi, Xue Yang, and Wen Jiang. "The Impact of Transport Mode and Carbon Policy on Low-Carbon Retailer." Discrete Dynamics in Nature and Society 2015 (2015): 1–12. http://dx.doi.org/10.1155/2015/964305.

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Low-carbon retail has become a strategic target for many developed and developing economies. This study discusses the impact of transport mode and carbon policy on achieving this objective. We investigated the retailer transportation mode, pricing, and ordering strategy, which all consider carbon-sensitive demand under the carbon cap-and-trade policy. We analyzed the optimal decision of retailer and their maximum profit affected by transport mode and cap-and-trade policy parameters. Results show that the two elements (cap-and-trade policy and consumer low-carbon awareness) could encourage the retailer to choose low-carbon transportation. The two elements also influence the profit and optimal decision of retailer. Finally, a numerical example is presented to illustrate the applicability of the model.
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18

Zhang, Kun, and Guo Qiang Cai. "Construction Strategy on Low-Carbon Transportation System in New District of Lanzhou." Applied Mechanics and Materials 505-506 (January 2014): 537–41. http://dx.doi.org/10.4028/www.scientific.net/amm.505-506.537.

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For low-carbon transportation is important to the construction in a city, as a new city, New District of Lanzhou has more advantages to construct low-carbon transportation system, compared with the completed cities. Combining with planning features of it, the article proposes some targeted measures to low-carbon transportation system construction in New District of Lanzhou, from the transverse dimensions, like software, hardware, and vertical dimensions, like inner of the district, the connection between main and new district. Result of carbon emission calculation demonstrates the importance of low-carbon transportation in New District of Lanzhou.
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19

Senin, S. N., M. Fahmy-Abdullah, and M. A. N. Masrom. "The implementation of green transportation towards low carbon city." IOP Conference Series: Earth and Environmental Science 736, no. 1 (April 1, 2021): 012063. http://dx.doi.org/10.1088/1755-1315/736/1/012063.

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20

MACHADO-FILHO, HAROLDO. "Brazilian low-carbon transportation policies: opportunities for international support." Climate Policy 9, no. 5 (January 2009): 495–507. http://dx.doi.org/10.3763/cpol.2009.0638.

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21

Gao, Kai, Xin Guo, Tingting Liu, and Rui Han. "Government Low-Carbon Policies Optimization for Smart Transportation Enterprises." Discrete Dynamics in Nature and Society 2022 (January 31, 2022): 1–14. http://dx.doi.org/10.1155/2022/1099147.

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As an important part of energy saving and carbon reduction, the low-carbon development of the transportation industry is imperative. It is the responsibility of smart transportation enterprises to closely combine their own digital technology with the governments’ policies to achieve green innovation. In this study, we conducted an evolutionary game model of the interaction between the governments and smart transportation enterprises, which depended on innovation subsidies and punitive taxes. Besides, we derived the evolutionarily stable strategy of the governments and enterprises and used a simulation to analyze the impact of various policy tools on green innovation strategy. The results showed that the behavior of the governments relies on the benefits of supervision and the costs of supporting green technology innovation. The enterprises’ behavior depends on the benefits of green innovation and the loss of no green innovation. Moreover, different policy tools provided by the governments can accelerate the implementation of enterprises’ green innovation.
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22

OHNO, Eishi. "Car Technologies and Transportation Systems for Low-Carbon Society." Journal of The Institute of Electrical Engineers of Japan 129, no. 1 (2009): 20–23. http://dx.doi.org/10.1541/ieejjournal.129.20.

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23

Li, Zhenyu. "Development Mode and Strategy of Low-Carbon Urban Transportation." JOURNAL OF ENGINEERING STUDIES 3, no. 2 (June 30, 2011): 105–12. http://dx.doi.org/10.3724/sp.j.1224.2011.00105.

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24

Li, Nan, and Wenying Chen. "Modeling China’s interprovincial coal transportation under low carbon transition." Applied Energy 222 (July 2018): 267–79. http://dx.doi.org/10.1016/j.apenergy.2018.03.103.

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25

Guan, ChengHe, Sumeeta Srinivasan, and Chris P. Nielsen. "Does neighborhood form influence low-carbon transportation in China?" Transportation Research Part D: Transport and Environment 67 (February 2019): 406–20. http://dx.doi.org/10.1016/j.trd.2018.12.015.

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26

Cao, Hong Yan, and Zhi Hua Song. "The Study on Transportation Planning for Historic Cities Based on Low Carbon Concept." Applied Mechanics and Materials 178-181 (May 2012): 1829–33. http://dx.doi.org/10.4028/www.scientific.net/amm.178-181.1829.

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With the rapid development of urbanization and motorization, contradiction between transportation development and historical features protection becomes prominent. Transportation planning is crucial for the future development of a city; therefore, active strategies must be adopted on account of the characteristics of historic cities. This paper argues that for historic cities, the principle of transportation planning should be low carbon, low pollution and low energy. Taking Penglai city as an example, the author analyzes its traffic features first, and then with the guidance of low carbon principle, the author probes into issues such as public transportation, road network, parking facilities and transportation supervision of the transportation planning.
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Li, Ya Fan, Juan Wang, and Xin Tian. "Research on Green Low-Carbon Management Measures of Integrated Passenger Transportation Hub." Advanced Materials Research 962-965 (June 2014): 2445–51. http://dx.doi.org/10.4028/www.scientific.net/amr.962-965.2445.

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This paper firstly analyzed the current situation of integrated passenger transportation hub, putting forward the integrated passenger transportation hub had a strong advantage on developing green low-carbon economy. And then based on the energy consumption analysis of integrated passenger transportation hub, energy saving and emission reduction management measures were proposed.
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Arya, B., and S. Chaturvedi. "Psychological predictors of Sustainable Transportation Behaviour: Implications for Low Carbon Economy and Society." IOP Conference Series: Earth and Environmental Science 1084, no. 1 (October 1, 2022): 012045. http://dx.doi.org/10.1088/1755-1315/1084/1/012045.

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Abstract There’s been a consistent increase in carbon emissions globally in the recent decades, primarily because of a consistent increase in personal transportation needs. Thus sustainable transportation behaviour has become a pertinent variable for investigation. The current study thus aimed to study the impact of environmental consciousness, green identity, values (biospheric, altruistic, egoistic), and consideration of future consequences on sustainable transportation behaviour such as usage of public transport and carpooling. The study employed a quantitative survey design with 351 participants in total and (M=67% F=33%) who were daily commuters to offices or universities. Results indicated that environmental consciousness, green identity and consideration of future consequences to be positively correlated with sustainable transportation behaviour. Biospheric and altruistic values were also found to have a positive correlation with sustainable transportation behaviour while egoistic values had a negative correlation with sustainable transportation behaviour. These findings have implications for a low carbon economy and society since they highlight important psychological variables that can promote sustainable transportation behaviour at an individual level and reduce overall carbon emissions.
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Hua, Hong, and Yu Han Xiong. "Research on Assessment of Urban Transportation Low-Carbonization Development." Advanced Materials Research 779-780 (September 2013): 872–77. http://dx.doi.org/10.4028/www.scientific.net/amr.779-780.872.

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Five influence factors of urban transportation low-carbonization development are analyzed which includes low-carbon transportation planning, road network construction, green travel, energy utilization and transportation management. The assessment indicator system and the assessment method of urban transportation low-carbonization development are set up. A case of assessment in Chengyang District is studied.
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Guo, Xuemeng, Bingyao Chen, and Yuting Feng. "Public-Private Partnership Transportation Investment and Low-Carbon Economic Development: An Empirical Study Based on Spatial Spillover and Project Characteristics in China." Sustainability 14, no. 15 (August 4, 2022): 9574. http://dx.doi.org/10.3390/su14159574.

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As the most widely used investment mode of transportation infrastructure in China, PPP has been regarded as an effective institutional tool by the Chinese government for the construction of efficient and sustainable transportation infrastructure, promoting high-quality economic development. In order to evaluate the economic sustainability of PPP, this paper innovatively takes the low-carbon economy as the research perspective and uses 276 cities of China from 2006 to 2018 as samples to comprehensively investigate the impact of transportation PPP investment on the low-carbon economy from the diversified dimensions of the overall effect, spatial effect, mediating effect, heterogeneous effect, lagged effect, and PPP project-level characteristics. The results show that: (1) transportation PPP investment markedly promotes low-carbon economic development in China, which is manifested as the dual improvement effects of benefits and efficiency; (2) transportation PPP investment has a positive spatial spillover effect that can promote the low-carbon economic development of neighboring cities; (3) transportation PPP investment can promote low-carbon economic development by promoting the upgrading of industrial structures, and furthermore has a spatial transmission mechanism; (4) impacts of transportation PPP investment in different subsectors are significantly heterogeneous; (5) transportation PPP investment has a continuous and stable impact on promoting the low-carbon economy in China; (6) the participation of state-owned enterprises and listed companies in PPP projects has a significant positive impact, and state-owned capital is more effective in projects with relatively large scale. All these provide reliable evidence for the far-reaching significance and practical value of transportation PPP investment on sustainable low-carbon economic development.
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Wang, Tao, Kai Zhang, Keliang Liu, Keke Ding, and Wenwen Qin. "Spatial Heterogeneity and Scale Effects of Transportation Carbon Emission-Influencing Factors—An Empirical Analysis Based on 286 Cities in China." International Journal of Environmental Research and Public Health 20, no. 3 (January 28, 2023): 2307. http://dx.doi.org/10.3390/ijerph20032307.

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In order to scientifically evaluate the characteristics and impact outcomes of transportation carbon emissions, this paper uses the panel statistics of 286 cities to measure transportation carbon emissions and analyze their spatial correlation characteristics. Afterwards, primarily based on the current research, a system of indicators for the impact factors of transportation carbon emissions was established. After that, ordinary least squares regression, geographically weighted regression, and multiscale geographically weighted regression models were used to evaluate and analyze the data, and the outcomes of the multiscale geographically weighted regression model were selected to analyze the spatial heterogeneity of the elements influencing transportation carbon emissions. The effects exhibit that: (1) The spatial characteristics of China’s transportation carbon emissions demonstrate that emissions are high in the east, low in the west, high in the north, and low in the south, with high-value areas concentrated in the central cities of Beijing-Tianjin-Hebei, the Yangtze River Delta, the Guangdong-Hong Kong-Macao region, and the Chengdu-Chongqing regions, and the low values concentrated in the Western Sichuan region, Yunnan, Guizhou, Qinghai, and Gansu. (2) The spatial heterogeneity of transportation carbon emissions is on the rise, but the patten of local agglomeration is obvious, showing a clear high-high clustering, and the spatial distribution of high-high agglomeration and low-low agglomeration is positively correlated, with high-high agglomeration concentrated in the eastern region and low-low agglomeration concentrated in the western region. (3) The effects of three variables—namely, GDP per capita, vehicle ownership, and road mileage—have a predominantly positive effect on transportation carbon emissions within the study area, while another three variables—namely, constant term, population density, and number of people employed in transportation industry—have different mechanisms of influence in different regions. Constant term, vehicle ownership, and road mileage have greater impacts on transportation carbon emissions.
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32

Zhang, Xu, Fei-Yu Jin, Xu-Mei Yuan, and Hai-Yan Zhang. "Low-Carbon Multimodal Transportation Path Optimization under Dual Uncertainty of Demand and Time." Sustainability 13, no. 15 (July 22, 2021): 8180. http://dx.doi.org/10.3390/su13158180.

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The research on the optimization of a low-carbon multimodal transportation path under uncertainty can have an important theoretical and practical significance in the high-quality development situation. This paper investigates the low-carbon path optimization problem under dual uncertainty. A hybrid robust stochastic optimization (HRSO) model is established considering the transportation cost, time cost and carbon emission cost. In order to solve this problem, a catastrophic adaptive genetic algorithm (CA-GA) based on Monte Carlo sampling is designed and tested for validity. The multimodal transportation schemes and costs under different modes are compared, and the impacts of uncertain parameters are analyzed by a 15-node multimodal transportation network numerical example. The results show that: (1) the uncertain mode will affect the decision-making of multimodal transportation, including the route and mode; (2) robust optimization with uncertain demand will increase the total cost of low-carbon multimodal transportation due to the pursuit of stability; (3) the influence of time uncertainty on the total cost is significant and fuzzy, showing the trend of an irregular wave-shaped change, like the ups and downs of the mountains. The model and algorithm we proposed can provide a theoretical basis for the administrative department and logistic services providers to optimize the transportation scheme under uncertainty.
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33

Li, Jian, Hong Yuan Liu, and Xin Teng. "Research on the Driving Force Factors of Development of Low Carbon of Urban Transportation: Taking Tianjin as an Example." Advanced Materials Research 798-799 (September 2013): 1115–18. http://dx.doi.org/10.4028/www.scientific.net/amr.798-799.1115.

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Urban transportation is the main way of carbon emission, development of low-carbon transportation has become the focus of attention of the countries all over the world. This paper analyses the influencing factors of carbon emission of Tianjin transportation based on grey correlation method, putting forward that the cost of urban resident transportation, traffic volume of urban passenger, number of private car and energy consumption of urban transportation are the most important key factors. Therefore, in order to construct low-carbon transportation system, Tianjin should design the layoff of urban space reasonably to control the demand of transportation effectively to reduce the urban transportation cost first, develop urban public transportation to optimize the urban traffic structure in response to the growing urban traffic volume of passenger second , establish a series of laws and regulations to improve the urban traffic management level to strengthen the supervision of private cars third, develop and apply new technology and new energy to adjust the energy structure of urban transportation to reduce urban transportation energy consumption at last.
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34

魏, 文义. "Strategic Envision for the Development of Low-Carbon in Transportation." Open Journal of Transportation Technologies 10, no. 03 (2021): 207–11. http://dx.doi.org/10.12677/ojtt.2021.103023.

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35

Roy, Mandira, Hamed Ghoddusi, and Jessika E. Trancik. "Evaluating Low-Carbon Transportation Technologies When Demand Responds to Price." Environmental Science & Technology 56, no. 4 (February 4, 2022): 2096–106. http://dx.doi.org/10.1021/acs.est.1c02052.

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36

肖, 红. "Study on Low-Carbon Transportation of Urbanization Process in Chongqing." Journal of Low Carbon Economy 07, no. 03 (2018): 90–96. http://dx.doi.org/10.12677/jlce.2018.73011.

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37

Jing, Mei, and Weigang Zheng. "Economic Development Advantages of Low-Carbon Economy under Waterway Transportation." IOP Conference Series: Materials Science and Engineering 780 (April 10, 2020): 062029. http://dx.doi.org/10.1088/1757-899x/780/6/062029.

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38

Gang, Zong, Yang Lijie, and Yan Hua. "Research on Development Measures of Low-carbon Transportation in Beijing." SHS Web of Conferences 7 (2014): 01002. http://dx.doi.org/10.1051/shsconf/20140701002.

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39

Chien, Yu-Chen, and Chen-Tzu Yang. "Application of APP Technology to Promote Urban Low-Carbon Transportation." IOP Conference Series: Earth and Environmental Science 581 (December 5, 2020): 012036. http://dx.doi.org/10.1088/1755-1315/581/1/012036.

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40

Mudhee, Kaled H. "Energy consumption structure model considering urban green and low-carbon transportation." Journal of Autonomous Intelligence 6, no. 2 (August 7, 2023): 879. http://dx.doi.org/10.32629/jai.v6i2.879.

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<p class="Abstract">The importance of energy conservation and emission reduction has become the consensus of the international community, and Iraq is also actively improving the urban public transportation system to control carbon emissions. This paper collects panel data of Tikrit city in Iraq in the past 3 years, constructs a random effect variable coefficient model, and studies the impact of the development of urban low-carbon transportation system on the energy consumption structure. The study finds that the government can use public transportation pricing strategies to influence consumers. In order to realize the optimization of energy consumption structure, the impact of electric vehicles on energy consumption structure will decrease with the increase of urban development. The transportation sector can increase the purchase and travel costs of traditional cars by restricting travel, purchases, and charging parking fees, which affects the number of private cars and reduces the obstacles to optimizing the energy consumption structure. The government should increase financial subsidies, improve rail transit and reasonable bus (electric) vehicle operation systems, increase investment in new energy vehicle research and development, and encourage high energy density and low power consumption technologies. development, increase residents’ demand for new energy passenger vehicles, and optimize the energy consumption structure.</p>
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Zhong, Mingchun, Linzhi Que, and Guofu Lian. "Empirical analysis of influencing factors of carbon emissions in transportation industry in Fujian Province, China." JUSTC 53, no. 1 (2023): 5. http://dx.doi.org/10.52396/justc-2022-0079.

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The transportation industry has become an important source of carbon emissions with rapid economic development and the acceleration of urbanization. Identifying the key factors of carbon emissions is crucial for energy conservation, emission reduction and green development in the transportation industry. Here, variance analysis was used to study the influencing factors of carbon emissions in the transportation industry in Fujian Province, China. The results showed that transportation efficiency have the most significant impact on carbon emissions, followed by carbon emission intensity in transportation, and then the transportation structure. Meanwhile, there was a significant interaction between transportation efficiency and structure. Therefore, innovative energy-saving and emission-reduction technologies for transportation efficiency should be studied as the focus for the green and low-carbon development of the transportation industry.
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42

Li, Mingjun, Dan Yue, Daoyuan Yang, Na Li, Rui Wu, Yuan Gao, Yahui Bai, Quansheng Huang, Hongwei Zhang, and Honglei Xu. "Study on the carbon peaking system and mechanism of the transportation industry—Lessons from Inner Mongolia." E3S Web of Conferences 360 (2022): 01040. http://dx.doi.org/10.1051/e3sconf/202236001040.

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Transportation is one of the important fields of carbon emission. Promoting the Carbon Peak in transportation industry is a key point to accelerate the green and low-carbon transformation and promote the high-quality development of the transportation industry. The transportation sector covers a wide range of fields, and there are many coordination departments. The local transportation authorities still lack a strong grasp in carrying out the Carbon Peak work. It is urgent to further improve the Carbon Peak system and mechanism in the transportation sector. This paper refines the current situation and characteristics of carbon emission in the transportation field of Inner Mongolia Autonomous Region, summarizes the progress of Carbon Peak in the transportation field, analyzes the constraints of the system and mechanism of Carbon Peak in the transportation field, and puts forward suggestions to further improve the system and mechanism of carbon emission reduction in the transportation field of Inner Mongolia Autonomous Region.
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43

Yang, Zhong Hong, Yang Yang, and Xiao Hui Chen. "Estimating Carbon Emission of Tourism Transportation and Accommodation in China." Advanced Materials Research 962-965 (June 2014): 1327–31. http://dx.doi.org/10.4028/www.scientific.net/amr.962-965.1327.

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The tourism’s growing consumption of energy, especially in transportation and accommodation, and its great demand on fossil fuels has important implications for GHG emissions. From the perspective of low carbon and emission reduction, the paper discussed the carbon emission of China’s tourism. Based on the previous studies, the paper calculated carbon emission of 31 Chinese provinces from tourism transportation and accommodation. The results show that: 1) Tourism transportation contributes most to carbon emission, accounting for 89.4% of the total, while tourism accommodation accounts for 10.6%. 2) In terms of transportation, civil aviation contributes most, accounting for 44.71% of the carbon emission of tourism transportation. 3) In terms of accommodation, three-star hotels contribute most, accounting for 45.3% of the carbon emission of tourism accommodation. 4) Cities of Guangzhou, Beijing and Shanghai make the largest contribution to the carbon emission among 31 provinces. Based on the above, it is reasonable that Tourism Sectors should make targeted policies to promote the development of low-carbon tourism according to the structure of tourism transportation and accommodation.
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44

Wei, Shu Wei, Yan Li Yang, and Zhao Wu Li. "Study on Low-Carbon Settlements Spatial Form Design Strategy - The Case of Northern China." Applied Mechanics and Materials 507 (January 2014): 599–602. http://dx.doi.org/10.4028/www.scientific.net/amm.507.599.

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Spatial form holds an important impact on carbon settlements. This paper analyzes the environmental wind, temperatures, environmental humidity, green systems and energy system of the settlements, then design requirements of low-carbon settlements spatial form are proposed from four aspects: carbon reduction from the venue, carbon conductivity by the channel, green carbon sequestration and carbon reduction in the transportation. Parameter systems of spatial form are found including five factors: venue, land, landscape, building, transportation, in order to achieve space quantization design of low-carbon settlements.
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45

Chen, Xiaoqin, Shenya Mao, Siqi Lv, and Zhong Fang. "A Study on the Non-Linear Impact of Digital Technology Innovation on Carbon Emissions in the Transportation Industry." International Journal of Environmental Research and Public Health 19, no. 19 (September 29, 2022): 12432. http://dx.doi.org/10.3390/ijerph191912432.

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Transportation is an important part of social and economic development and is also a typical high-energy and high-emissions industry. Achieving low-carbon development in the transportation industry is a much-needed requirement and the only way to achieve high-quality development. Therefore, based on the relevant data of 30 provinces in China from 2010 to 2018, this research uses the static panel model, panel threshold model and spatial Durbin model to conduct an empirical study on the impact and mechanism of digital innovation on carbon emissions in the transportation industry, and draws the following conclusions. (1) Carbon emissions in the transportation industry have dynamic and continuous adjustment characteristics. (2) There is a significant inverted U-shape non-linear relationship between the level of digital innovation and carbon emissions in the industry. In regions with a low level of digital innovation, the application of digital technology increases carbon emissions in this industry, but as the level of digital innovation continues to increase its application suppresses carbon emissions, showing an effect of carbon emission reduction. (3) The impact of digital innovation on carbon emissions in the transportation industry has a spatial spillover effect, and its level in one province significantly impacts carbon emissions in other provinces’ transportation industry through the spatial spillover effect. Therefore, it is recommended to further strengthen the exchange and cooperation of digital innovation in the transportation industry between regions, improve the scale of digitalization in this industry, and accelerate its green transformation through digital innovation, thus promoting the green, low-carbon, and sustainable development of China’s economy.
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46

Yuan, Minmin, Junfeng Mai, Xiaofei Liu, Hongfei Shen, and Jie Wang. "Current Implementation and Development Countermeasures of Green Energy in China’s Highway Transportation." Sustainability 15, no. 4 (February 7, 2023): 3024. http://dx.doi.org/10.3390/su15043024.

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The transportation industry is one of the largest consumers of fossil fuels and sources of carbon dioxide emission, with highway transportation accounting for more than 70% of the total. In order to promote efficient, clean, diversified, and intelligent use of energy, this study proposes an innovative application technology model for integrating highway transportation and energy to improve the utilization of clean energy and reduce the proportion of fossil energy and carbon emissions in highway transportation. This study addresses the current problems of green energy development in China’s highways, and combines green low-carbon development policies in international transportation with inspirations based on experience. Based on the principles of safety, efficiency, environmental friendliness, wisdom, and economy, this study systematically analyzes the current situation of green energy application in China’s highway transportation. It proposes one core objective, two major roles, and five major security systems of development measures for green energy application China’s highway transportation with the aim of promoting the transformation and upgrade of China’s highway transportation industry. This study can also help to achieve green and low-carbon development of highway transportation and provides a decision-making reference for the ecological civilization construction goals of the industry.
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Chen, Jin Fu, Xiao Yu Zhu, and Li Juan Ren. "Spatial Structure of Danwei Compound towards Low-Carbon - Case Study of Space Change in HUST." Advanced Materials Research 383-390 (November 2011): 3700–3706. http://dx.doi.org/10.4028/www.scientific.net/amr.383-390.3700.

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Urban transport activities have an important impact on carbon emissions. The traditional Danwei compound created a better structural condition, providing people with the way of low-carbon transportation. In this paper, we discussed the impact of HUST campus space change to the choice of transportation for the school staff, and proposed that the low-carbon urban block special structure should be encouraged in the urban planning in order to reduce carbon emissions through constructing the mixed function urban blocks.
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48

Zhang, Qiang. "Investigating the Impact of Transportation Infrastructure and Tourism on Carbon Dioxide Emissions in China." Journal of Environmental and Public Health 2022 (September 9, 2022): 1–9. http://dx.doi.org/10.1155/2022/8421756.

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In order to effectively address or eliminate the impact of CO2 emissions, it is essential to investigate the analysis of CO2 emissions under transport infrastructure and tourism. Transportation infrastructure helps to achieve carbon dioxide emission limitation, which is crucial for resource distribution, effectively summarizing the regularity and innovation in the process of carbon dioxide emission limitation. In the case of fully grasping the principles of low-carbon tourism development and related policy protection, a suitable low-carbon tourism development model is found. By constructing a data analysis model, this paper analyzes the impact of transportation infrastructure and ecotourism on carbon dioxide emission limitation. In terms of methods and systems, effective measures are given to the role of Chinese traffic settings in tourism, and the carbon emission system of the entire life cycle of traffic settings is analyzed, and the boundary of the impact of traffic carbon emissions on tourism is determined. In response to this problem, it is necessary to reform and optimize the transportation facility of the carbon emission accounting method, which has a positive effect on the green development and low-carbon development of the Chinese economy for ecotourism and transportation infrastructure.
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Guo, Liang, Shuo Yang, Qinghao Zhang, Leyu Zhou, and Hui He. "Examining the Nonlinear and Synergistic Effects of Multidimensional Elements on Commuting Carbon Emissions: A Case Study in Wuhan, China." International Journal of Environmental Research and Public Health 20, no. 2 (January 16, 2023): 1616. http://dx.doi.org/10.3390/ijerph20021616.

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Understanding the specific effects of multidimensional elements of a built environment, transportation management policies, and the socio-demographics of travelers associated with commuting carbon emissions is significant for planners in promoting low-carbon and healthy urban development through transportation and land use and urban management policies. Most of the existing studies focus on the complex mechanisms affecting commuting behavior, but the relevant elements and specific mechanisms affecting commuting carbon emissions have not received sufficient attention. This study uses a random forest approach to analyze residential travel data from Wuhan, China. The results show that built environment and transportation demand management policies are critical to commuting carbon emissions, and that there is a non-linear association between multidimensional factors and commuting carbon emissions in Chinese cities. In addition, the study examines the synergistic effects of built environment and transportation management policies on commuting carbon emissions among different built environment elements. The results of the study provide valuable insights for planners in formulating low-carbon city and transportation development policies.
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Xing, Hui, Charles Stuart, Stephen Spence, and Hua Chen. "Alternative fuel options for low carbon maritime transportation: Pathways to 2050." Journal of Cleaner Production 297 (May 2021): 126651. http://dx.doi.org/10.1016/j.jclepro.2021.126651.

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