Analysis of influencing factors of CO2 emissions in Xinjiang under the context of different policies

Huo, Jinwei; Yang, Degang; Zhang, Wenbiao; Wang, Fei; Wang, Guiling; Fu, Qing

doi:10.1016/j.envsci.2014.09.006

Cited by 27 publications

(20 citation statements)

References 16 publications

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“…During the same phase, the per capita carbon emissions increased from 0.29 t to 0.74 t, or a total growth of 260% and an average annual growth rate of 9.1%. The enormous differences between the two phases in terms of growth rate can be explained by the implementation by the central government of the Western Development Strategy in 2001 [4]. The implementation of this strategy has promoted the construction of transportation infrastructure and thus facilitated the development of the logistics sector.…”

Section: Macro-level: Total Energy-related Carbon Emissionsmentioning

confidence: 99%

“…To be specific, the intensity of carbon emissions reached 6.48 t/10 4 yuan in 2008. The implementation of the Western Development Strategy [4] and China's accession to the World Trade Organization (WTO) may be the main causes for this rise. According to XSY [5], during this period, the level of cargo turnover increased sharply, with an annual growth rate of 12.76%.…”

Section: Micro-level: Carbon Emissions Structure and Intensitymentioning

confidence: 99%

“…In addition, Xinjiang is also an important channel for economic exchanges between China and Central Asia. Since the implementation of the Western Development Strategy in 2001 and the Jumping Development Strategy in 2010 [4], Xinjiang's transportation sector has witnessed rapid and sustained development. The total output value of the transportation sector increased from USD 305.8 million in 1990 to USD 748.5 million in 2012.…”

Section: Introductionmentioning

confidence: 99%

“…Furthermore, with regard to the research methods, two approaches are widely used at present. They are the index decomposition method [6][7][8]11,20,23,53] and the econometric method [2,4,6,24,28,54,55]. Due to the constraints of the Kaya identity, the factors that are considered in the index decomposition method are limited.…”

Section: Introductionmentioning

confidence: 99%

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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: Macro-level: Total Energy-related Carbon Emissionsmentioning

confidence: 99%

Section: Micro-level: Carbon Emissions Structure and Intensitymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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

Dong

Deng

et al. 2016

Sustainability

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“…It is a recurrent problem in nowadays cities. (Chiesa et al, 2014;Yang et al, 2015;Berrittella et al, 2008). o Noise (NOI).…”

Section: First Questionnaire and Decision Hierarchy Structurementioning

confidence: 99%

Prioritization by consensus of enhancements for sustainable mobility in urban areas

Curiel-Esparza

Mazario-Diez

Canto-Perello

et al. 2016

Environmental Science & Policy

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ElsevierCuriel Esparza, J.; Mazario-Diez, JL.; Canto-Perello, J.; Martín Utrillas, MG. (2016). Prioritization by consensus of enhancements for sustainable mobility in urban areas. Environmental Science and Policy. 55 (1) ABSTRACTNowadays the European cities usually present important problems at economic, social and environmental levels. The European Union has published policies to ease this issue, and several European cities are creating sustainable mobility urban plans with the measures which can be taken to improve the mobility system. Transport decisions have direct impact on transit times, urban connectivity, and have also effects in the environment, public health and society. Choosing the best enhancement to implement is a complex decision, depending on tangible and intangible criteria, which have to be taken into account together. A compromise solution that weighs travel quality, cost and sustainability inputs has to be achieved. This research work presents a decision support system to select the optimal sustainability enhancement integrating the Delphi technique with the Analytic Hierarchy Process and the VIKOR method. GRAPHICAL ABSTRACT HIGHLIGHTSSelect optimal strategies in achieving sustainable mobility.Analytic Hierarchy Process combined with a Delphi technique and the VIKOR method.Framework to achieve consensus decision-making in urban mobility.Applying tangible and intangible criteria in sustainable urban transport.

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The Influencing Factors of CO2 Emissions and the Role of Biomass Energy Consumption: Statistical Experience from G-7 Countries

Shahbaz

Balsalobre

Shahzad

2018

Environ Model Assess

132

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This paper examines the impact of biomass energy consumption on CO2 emissions and the environmental Kuznets curve (EKC) hypothesis in G-7 countries. We also incorporate capitalization, financial development and globalization measures (economic, social and political) as additional determinants of CO2 emissions. This study covers the period of 1980-2014. We apply the generalized moments method (GMM) for empirical analysis. The empirical results reveal that biomass energy consumption contributes to CO2 emissions. The EKC hypothesis is valid in G-7 countries. Capitalization is inversely linked with CO2 emissions. Financial development deteriorates environmental quality. Foreign direct investment (FDI) and trade openness improve environmental quality. Globalization increases CO2 emissions. Institutional quality improves environmental quality through effective economic and environmental policies. Urbanization impedes environmental quality. These results provide new insights for policy makers in designing comprehensive environmental policy by considering biomass energy as an economic tool for sustainable economic development and to improve environmental quality.

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Analysis of influencing factors of CO2 emissions in Xinjiang under the context of different policies

Cited by 27 publications

References 16 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

Prioritization by consensus of enhancements for sustainable mobility in urban areas

The Influencing Factors of CO2 Emissions and the Role of Biomass Energy Consumption: Statistical Experience from G-7 Countries

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