Estimates of China's national and regional transport sector CO2 emissions in 2007

Cai, Bofeng; Yang, Weishan; Dong, Can; Liu, Lan-Cui; Zhou, Ying; Zhang, Zhansheng

doi:10.1016/j.enpol.2011.11.008

Cited by 81 publications

(34 citation statements)

References 4 publications

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“…Moreover, in most cases, any effort on carbon emissions caused by changes in the road transport sector's energy consumption lasts longer than effects brought about due to economic growth. In addition, many scholars have also studied the CO 2 reduction potential in the transport sector at the national level [2,33,[38][39][40][41][42][43][44][45][46][47][48][49][50]. For instance, Xu et al [46,51] introduced the vector auto-regression model and the dynamic non-parametric additive regression model as a means to analyze the factors that influenced the CO 2 emissions of China's transportation sector.…”

Section: Introductionmentioning

confidence: 99%

Moving Low-Carbon Transportation in Xinjiang: Evidence from STIRPAT and Rigid Regression Models

Dong

Deng

et al. 2016

Sustainability

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Abstract:With the rapid economic development of the Xinjiang Uygur Autonomous Region, the area's transport sector has witnessed significant growth, which in turn has led to a large increase in carbon dioxide emissions. As such, calculating of the carbon footprint of Xinjiang's transportation sector and probing the driving factors of carbon dioxide emissions are of great significance to the region's energy conservation and environmental protection. This paper provides an account of the growth in the carbon emissions of Xinjiang's transportation sector during the period from 1989 to 2012. We also analyze the transportation sector's trends and historical evolution. Combined with the STIRPAT (Stochastic Impacts by Regression on Population, Affluence and Technology) model and ridge regression, this study further quantitatively analyzes the factors that influence the carbon emissions of Xinjiang's transportation sector. The results indicate the following: (1) the total carbon emissions and per capita carbon emissions of Xinjiang's transportation sector both continued to rise rapidly during this period; their average annual growth rates were 10.8% and 9.1%, respectively; (2) the carbon emissions of the transportation sector come mainly from the consumption of diesel and gasoline, which accounted for an average of 36.2% and 2.6% of carbon emissions, respectively; in addition, the overall carbon emission intensity of the transportation sector showed an "S"-pattern trend within the study period; (3) population density plays a dominant role in increasing carbon dioxide emissions. Population is then followed by per capita GDP and, finally, energy intensity. Cargo turnover has a more significant potential impact on and role in emission reduction than do private vehicles. This is because road freight is the primary form of transportation used across Xinjiang, and this form of transportation has low energy efficiency. These findings have important implications for future efforts to reduce the growth of transportation-based carbon dioxide emissions in Xinjiang and for any effort to construct low-carbon and sustainable environments.

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Section: Introductionmentioning

confidence: 99%

Moving Low-Carbon Transportation in Xinjiang: Evidence from STIRPAT and Rigid Regression Models

Dong

Deng

et al. 2016

Sustainability

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show abstract

“…Many previous studies concentrated on CO 2 emissions and the future growth of gases from general aspects of the transport sector: vehicles, railways, waterways, aviation [13][14][15][16][17]. In terms of research on specific modes of transport, the road and railway transport sectors have been more popular owing to their significant roles in daily life [18][19][20][21][22][23].…”

Section: Literature Reviewmentioning

confidence: 99%

Trends in CO2 Emissions from China-Oriented International Marine Transportation Activities and Policy Implications

Yang

Xing

2017

Energies

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Abstract:The demand for marine transportation and its associated CO 2 emissions are growing rapidly as a result of increasing international trade and economic growth. An activity-based approach is developed for forecasting CO 2 emissions from the China-oriented international seaborne trade sector. To accurately estimate the aggregated emissions, CO 2 emissions are calculated individually for five categories of vessels: crude oil tanker, product tanker, chemical tanker, bulk carrier, and container. A business-as-usual (BAU) scenario was developed to describe the current situation without additional mitigation policies, whilst three alternative scenarios were developed to describe scenarios with various accelerated improvements of the key factors. The aggregated CO 2 emissions are predicted to reach 419.97 Mt under the BAU scenario, and 258.47 Mt under the optimal case, AD3. These predictions are 4.5 times and 2.8 times that of the aggregated emissions in 2007. Our analysis suggests that regulations for monitoring, reporting, and verifying the activities of vessels should be proposed, in order to quantify the CO 2 emissions of marine transportation activities in Chinese territorial waters. In the long-term future, mitigation policies should be employed to reduce CO 2 emissions from the marine trade sector and to address the climatic impact of shipping.

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“…Carbon emissions from transport due to the travel activities from buildings can be estimated according to the following eqn (1) [19]: …”

Section: Carbon Emissions From Transport Activities Due To Buildings'mentioning

confidence: 99%

Operational Energy/Carbon Dioxide Emissions Analysis Combing Building Cluster and Transport Demand of Buildings’ Users at the Street Level: A Case Study of Hankou Railway Station Surroundings in China

Ji¹,

Jones²

2017

WIT Transactions on Ecology and the Environment

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Rapidly growing energy consumption and associated carbon emissions from building clusters and transport activities have raised concerns. Predicting carbon emissions combing building clusters and transport activities due to buildings' users is an effective way to getting a better understanding of their energy use and carbon emissions, and thus to control carbon emissions for low carbon development. The purpose of this paper is to quantify and compare operational energy consumption and associated carbon dioxide emissions from building cluster and transport activities due to the buildings' occupants. The energy consumption and carbon emission features on building cluster and transport activities are then presented and analysed. Finally, relevant low-carbon development strategies in the built environment from building cluster and transport activities are outlined and discussed. The results of the case study have shown that: (1) Energy consumption and carbon emissions from building clusters are almost four times higher than transport carbon emissions due to buildings' users in the unit of the square metre per year. Therefore, more focus on energy-saving should be emphasised on the buildings sector compared to the transport sector. (2) Different building types significantly varied in energy demands. Specifically, residential buildings have the highest heating demands, while public buildings in term of commercial, office and hotel buildings consumed more energy on cooling demands. (3) Transport-related carbon emissions due to mobility from buildings' users by car and taxi are the primary sources of carbon emissions. The highest average carbon emissions come from private cars/ taxis. By contrast, public transport has the lowest average transport carbon emissions due to their per capita low carbon emission factor. Transit modes are the preferred low carbon travel modes, so these should be promoted.

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Estimates of China's national and regional transport sector CO2 emissions in 2007

Cited by 81 publications

References 4 publications

Moving Low-Carbon Transportation in Xinjiang: Evidence from STIRPAT and Rigid Regression Models

Moving Low-Carbon Transportation in Xinjiang: Evidence from STIRPAT and Rigid Regression Models

Trends in CO2 Emissions from China-Oriented International Marine Transportation Activities and Policy Implications

Operational Energy/Carbon Dioxide Emissions Analysis Combing Building Cluster and Transport Demand of Buildings’ Users at the Street Level: A Case Study of Hankou Railway Station Surroundings in China

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