Drivers of the decoupling indicator between the economic growth and energy-related CO2 in China: A revisit from the perspectives of decomposition and spatiotemporal heterogeneity

Dong, Feng; Li, Jingyun; Wang, Yue; Zhang, Xiaoyun; Zhang, Shengnan; Zhang, Shuaiqing

doi:10.1016/j.scitotenv.2019.05.269

Cited by 94 publications

(38 citation statements)

References 80 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…As the world's largest greenhouse gas emitter, China is also under great pressure to reduce emissions [3]. In recent years, with the increase of disposable household incomes [4,5] and the acceleration of urbanization [6,7] in China, the carbon emissions from households has increased since more high-carbon lifestyles have been adopted by residents, which attracts attention [8][9][10]. Moreover, analysis of households and lifestyles might promote an understanding of family business [11], and even building industry [12] towards sustainability.…”

Section: Introductionmentioning

confidence: 99%

A Study on the Factors Affecting China’s Direct Household Carbon Emission and Comparison of Regional Differences

Fan

Ran

2019

Sustainability

View full text Add to dashboard Cite

As the world’s largest emitter of greenhouse gases, China has been attracting attention. In the global carbon emission structure, the proportion of household carbon emissions continues to increase, and it is necessary to focus on the issue of household emissions. Based on the perspective of the family sector and the comparison of urban–rural and interprovincial differences, this study makes a thorough and systematic analysis of the factors affecting direct household carbon emissions. The average carbon emission of urban households is higher than that of rural households. Both personal background and household energy consumption facility use have important impacts on household carbon emissions, and the degree of impact varies between urban and rural areas and between provinces. Reducing household carbon emissions and achieving a harmonious coexistence between man and nature are the common goals of the government and society. The government should explore the model of green sustainable development on the basis of ensuring the energy needs of residents. Residents should also further establish a low-carbon life concept and focus on the cultivation of low-carbon lifestyles.

show abstract

Section: Introductionmentioning

confidence: 99%

A Study on the Factors Affecting China’s Direct Household Carbon Emission and Comparison of Regional Differences

Fan

Ran

2019

Sustainability

View full text Add to dashboard Cite

show abstract

“…Li et al [18] predicted that the decoupling relationship between China's CO 2 emissions and economic development would become stronger between 2015 and 2030. Dong et al [19] examined Chinese economic growth and energy-related CO 2 emission decoupling driver forces from the perspective of spatial and temporal heterogeneity, and the results indicated that the influences of energy structure, energy intensity, industrial structure and technological progress in most regions were positive in the decoupling index, and are prompting weak decoupling to develop in most parts of China to develop.…”

Section: Literature Reviewmentioning

confidence: 99%

Decoupling Elasticity and Driving Factors of Energy Consumption and Economic Development in the Qinghai-Tibet Plateau

Fan

Meng

et al. 2020

Sustainability

View full text Add to dashboard Cite

Decoupling of energy consumption and economic development is a key factor in achieving sustainable regional development. The decoupling relationship between energy consumption and economic development in the Qinghai-Tibet Plateau region is still unclear. This paper uses the logarithmic mean Divisia index (LMDI) decomposition method and Tapio elastic index model to analyze the decoupling degree and driving factors of energy consumption and economic development, and evaluates the decoupling effort level in Qinghai-Tibet Plateau from 2006 to 2016. The results indicate that the Qinghai-Tibet Plateau region showed a weak decoupling as a whole, and that only Tibet experienced expanding negative decoupling in 2006–2007 and an expansion link in 2007–2008. Economic scale is a primary factor that hinders the decoupling of energy consumption, followed by investment intensity and industrial energy structure. The cumulative promotion effect of research and development (R&D) efficiency and intensity and the inhibition effect of investment intensity cancel each other out. With the exception of Tibet and Xinjiang, all provinces in the Qinghai-Tibet plateau have made decoupling efforts. Decoupling efforts made by R&D efficiency contributed the most, followed by energy intensity and R&D intensity. This paper provides policy recommendations for the decoupling of energy consumption experience for underdeveloped regions.

show abstract

“…The traditional econometric model can only reflect the statistical relationship among variables as a whole, but cannot reflect the regional effect among variables, while the spatial econometric model can make up for the shortcomings of the traditional econometric model and fully reflect the differences in spatial geographical impact among variables, and especially can show all variables' coefficients of the smart city in the sample [33][34][35]. Therefore, the geographical weighted regression (GWR) model was used to analyze the spatial differences of the influence of various factors on resilience capacity of smart cities.…”

Section: The Geographical Weight Regression Modelmentioning

confidence: 99%

Temporal and Spatial Differences in the Resilience of Smart Cities and Their Influencing Factors: Evidence from Non-Provincial Cities in China

et al. 2020

View full text Add to dashboard Cite

Based on the sample data of 81 non-provincial smart cities in China in 2017, the comprehensive evaluation index of the resilience of sample cities is calculated by using the entropy method, and the spatial differences of different factors on the resiliency are analyzed by using the geographical weighted regression (GWR) model. The conclusions are as follows: Firstly, the comprehensive evaluation index of the resilience of smart cities presents a spatial distribution characteristic of decreasing from the east to the west. At the same time, the resilience comprehensive index, the public infrastructure resilience capacity index, the economic development resilience index, the social security resilience index, and the ecological environment resilience index of smart cities have obvious agglomeration effects on their geographical spaces. Secondly, the public infrastructure resilience capacity index and the ecological environment resilience index are both low with a discrete distribution, while the economic development resilience index and the social security resilience index are both high with a concentrated distribution. Thirdly, different factors have significantly positive effects on the resilience of smart cities. In particular, the public infrastructure capacity resilience index decreases from the north to the south with the spatial distribution pattern of concentration, the economic development resilience index and the ecological environment resilience index of smart cities decrease from the east to the west with a concentrated spatial distribution pattern, and the social security resilience index of smart cities decreases from the southwest to the northeast with a concentrated spatial distribution pattern. Therefore, it is necessary to enhance awareness of smart cities, strengthen the driving force of science and technology innovation, strengthen public infrastructure and service construction, and continuously improve the rapid resilience of smart cities.

show abstract

Drivers of the decoupling indicator between the economic growth and energy-related CO2 in China: A revisit from the perspectives of decomposition and spatiotemporal heterogeneity

Cited by 94 publications

References 80 publications

A Study on the Factors Affecting China’s Direct Household Carbon Emission and Comparison of Regional Differences

A Study on the Factors Affecting China’s Direct Household Carbon Emission and Comparison of Regional Differences

Decoupling Elasticity and Driving Factors of Energy Consumption and Economic Development in the Qinghai-Tibet Plateau

Temporal and Spatial Differences in the Resilience of Smart Cities and Their Influencing Factors: Evidence from Non-Provincial Cities in China

Contact Info

Product

Resources

About