Research on the Spatial Network Characteristics and Synergetic Abatement Effect of the Carbon Emissions in Beijing–Tianjin–Hebei Urban Agglomeration

Li, Xintao; Feng, Dong; Li, Jian; Zhang, Zaisheng

doi:10.3390/su11051444

Cited by 26 publications

(17 citation statements)

References 45 publications

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“…Second, the other category of studies employs the SNA approach to analyze the carbon emissions spatial correlation properties [34][35][36][37][38]. These studies define the spatial association between sample regions by the vector autoregression (VAR) approach or the gravity model, then create a network of spatial associations across all regions and investigate the features of CO 2 emissions spatial associations.…”

Section: Literature Reviewmentioning

confidence: 99%

Study on the Spatial Association and Influencing Factors of Carbon Emissions from the Chinese Construction Industry

You

et al. 2021

Sustainability

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As the world’s largest carbon emitter, China is under enormous pressure to decrease carbon emissions. With the economic development in recent years, China has increased its investment in infrastructure, and the construction industry has become an essential source of carbon emissions. Using the social network analysis (SNA) methodology, this article analyzes the evolutionary characteristics of the spatial correlation network for carbon emissions in the construction industry from 2003–2017 and its affecting factors. The results of the empirical analysis in this paper are: (1) the spatial association of carbon emissions in Chinese inter-provincial construction industry shows an intuitive network layout and the spatial network has gradually stabilized since 2014; (2) according to the results of degree centrality, betweenness centrality and closeness centrality, it can be concluded that the regions with higher level of association with other provinces are the central and the eastern regions (Henan, Hubei, Hunan, Guangdong, Jiangsu, etc.) and Xinjiang; the linkage of construction-related carbon emissions was mainly achieved through the regions of Henan, Anhui, Shanxi, Hebei, Guangdong, and Inner Mongolia; the regions with higher level of construction industry development (Jiangsu, Henan, Hunan, Guangdong, etc.) are more closely associated with other provinces; (3) geographical proximity and reduction of difference in energy intensity and in industrial structure have substantial positive effects on the carbon emission association of the construction industry. Finally, based on the research results, this article proposes corresponding policy recommendations.

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Section: Literature Reviewmentioning

confidence: 99%

Study on the Spatial Association and Influencing Factors of Carbon Emissions from the Chinese Construction Industry

You

et al. 2021

Sustainability

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“…Second most cited publication of Li J. explored the life cycle carbon emissions of building maintenance using a case study in Hong Kong [75]. The most reason publications of Li J. focused on the household carbon emissions of China [76] and explored the spatial correlation network structure of carbon emissions using social network analysis (SNA) [77]. These studies clearly indicate that Li J has explored different dimensions of carbon emissions through his research.…”

Section: Co-author Scientometric Analysis Rresultsmentioning

confidence: 98%

Global Research on Carbon Emissions: A Scientometric Review

2019

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Greenhouse gases such as sulfur dioxide, nitrogen dioxide, and carbon dioxide have been recognized as the prime cause of global climate change, which has received significant global attention. Among these gases, carbon dioxide is considered as the prominent gas which motivated researchers to explore carbon reduction and mitigation strategies. Research work on this domain expands from carbon emission reporting to identifying and implementing carbon mitigation and reduction strategies. A comprehensive study to map global research on carbon emissions is, however, not available. Therefore, based on a scientometric analysis method, this study reviewed the global literature on carbon emissions. A total of 2945 bibliographic records, from 1981 to 2019, were extracted from the Web of Science core collection database and analyzed using techniques such as co-author and co-citation analysis. Findings revealed an increasing trend of publications in the carbon emission research domain, which has been more visible in the past few years, especially during 2016–2018. The most significant contribution to the domain was reported from China, the United States, and England. While most prolific authors and institutions of the domain were from China, authors and institutions from the United States reported the best connection links. It was revealed that evaluating greenhouse gas emissions and estimating the carbon footprint was popular among the researchers. Moreover, climate change and environmental effects of carbon emissions were also significant points of concern in carbon emission research. The key findings of this study will be beneficial for the policymakers, academics, and institutions to determine the future research directions as well as to identify with whom they can consult to assist in developing carbon emission control policies and future carbon reduction targets.

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“…As a measure of the relationship, the gravity model originated from the formula of universal gravitation in physics, which considering the quality and geographical factors, can fully show the spatial effect of city elements attracting. The gravity model is used to measure the spatial relationship and has been widely used in urban transportation [28], commodity and energy [29,30], sustainable development [31,32], and other fields in the urban network.…”

Section: The Gravity Modelmentioning

confidence: 99%

Analysis on the Housing Price Relationship Network of Large and Medium-Sized Cities in China Based on Gravity Model

Chong

et al. 2021

Sustainability

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The relationship among cities is getting closer, so are housing prices. Based on the sale price of stocking houses in thirty-five large and medium-sized cities in China from 2010 to 2021, this study established the modified gravity model and used the method of social network analysis to explore the spatial linkage of urban housing prices. The results show that: (1) from the overall network structure, the integration degree of housing price network in China is still at a low stage, and the influence of housing price is polarized; (2) from the individual network structure, Beijing, Shanghai, Shenzhen, Nanjing, Hangzhou, and Hefei have a higher degree of centrality. Chengdu, Xining, Kunming, Urumqi, and Lanzhou stay in an isolation position every year; (3) from the results of cohesive subgroup analysis, different cities play different roles in the block each year and have different influences on other cities. (4) Emergencies, such as outbreaks of COVID-19, also have an impact on the housing price network. Structural divergence among urban housing prices has become more pronounced, and the diversity of house price network has been somewhat reduced. Based on the above findings, this paper puts forward some recommendations for the healthy development of housing market from the perspective of housing price network.

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Research on the Spatial Network Characteristics and Synergetic Abatement Effect of the Carbon Emissions in Beijing–Tianjin–Hebei Urban Agglomeration

Cited by 26 publications

References 45 publications

Study on the Spatial Association and Influencing Factors of Carbon Emissions from the Chinese Construction Industry

Study on the Spatial Association and Influencing Factors of Carbon Emissions from the Chinese Construction Industry

Global Research on Carbon Emissions: A Scientometric Review

Analysis on the Housing Price Relationship Network of Large and Medium-Sized Cities in China Based on Gravity Model

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