Analysis of spatial correlation networks of carbon emissions in emerging economies

Zhang, Degang; Yao, Xiaobo

doi:10.1007/s11356-023-28384-1

Cited by 10 publications

(3 citation statements)

References 48 publications

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“…The heterogeneity of the status changes of different nodes reflects that the relative centrality of each node in the network varies over time even though the value of the degree centrality (DC) might remain unchanged. A possible reason for this is that in the process of development, some divisions have relatively more enhanced flow of production factors with central nodes, especially those related to carbon emissions such as population, investment, and technology, while others do not have such an enhanced flow level [51]. In addition, changes in the ability of each node to be unaffected by other nodes and to influence other nodes also varied across time but were consistent with the trend of decreasing dependence on a single center in the overall network.…”

Section: Land-use Carbon Emission Measurement Resultsmentioning

confidence: 99%

Unpacking the Sub-Regional Spatial Network of Land-Use Carbon Emissions: The Case of Sichuan Province in China

Zhao,

Xie,

Han

2023

Land

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Land, as an essential resource for social, economic and ecological activities, is regarded as a key factor in material production. Against the background of rapid social and economic transition, land-use carbon emissions have gradually drawn due attention. However, few studies have been conducted to explore the spatial relationship of land-use carbon emissions at the sub-regional level, especially within Sichuan Province, China. This study is aimed at unpacking the spatial network of land-use carbon emissions in Sichuan Province by employing the panel data from 2006 to 2021 and using the method of Social Network Analysis. The results indicate that the net land-use carbon emissions of various prefecture-level divisions in Sichuan generally showed an inverse and asymmetrical “V-shaped” trend. The network correlation was improved and the stability was enhanced, gradually developing into a multi-centric structure. In addition, the spatial relationship among different clusters in the network undergoes a transition from intra-regional to inter-regional spillover. Based on these findings, the carbon balance zoning policy was discussed to provide references for how to coordinate roles and positions in the network when optimizing land-use carbon emission management policies in sub-regional areas with rapid social and economic development.

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Section: Land-use Carbon Emission Measurement Resultsmentioning

confidence: 99%

Unpacking the Sub-Regional Spatial Network of Land-Use Carbon Emissions: The Case of Sichuan Province in China

Zhao,

Xie,

Han

2023

Land

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“…Quadratic Assignment Procedure (QAP) correlation analysis is often used to evaluate the correlation among multiple relational matrices. Drawing on the research achievements of scholars [15][16][17][18][19][20][21], we initially selected factors such as economic development level, urbanization rate, industrial structure, digitization level, energy intensity, investment level, external openness level, environmental regulation, and geographical spatial proximity as variables. The definition of each variable is given in Table 1.…”

Section: Qap Correlation Analysismentioning

confidence: 99%

“…To delve deeper into the driving mechanism of the spatial correlation network of carbon emission, scholars conducted correlation or regression analyses by using the Quadratic Assignment Procedure (QAP) on the basis of SNA [12][13][14]. In addition to the geographical spatial proximity [15], the factors considered in these analyses also include the differences in the economic development level [16], energy consumption [17], industrial structure [18], environmental policy [19], urbanization rate [20], and foreign direct investment [21].…”

Section: Introductionmentioning

confidence: 99%

Analysis of the Driving Mechanism of Urban Carbon Emission Correlation Network in Shandong Province Based on TERGM

Song,

Xiao,

Liu

2024

Sustainability

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Analyzing the driving factors and mechanisms of urban carbon emission correlation networks can provide effective carbon reduction decision-making support for Shandong Province and other regions with similar industrial characteristics. Based on industrial carbon emission data from various cities in Shandong Province from 2013 to 2021, the spatial correlation network of carbon emission was established by using a modified gravity model. The characteristics of the network were explored by using the Social Network Analysis (SNA) method, and significant factors affecting the network were identified through Quadratic Assignment Procedure (QAP) correlation analysis and motif analysis. The driving mechanism of the carbon emission correlation network was analyzed by using Temporal Exponential Random Graph Models (TERGMs). The results show that: (1) The spatial correlation network of urban carbon emission in Shandong Province exhibits multi-threaded complex network correlations with a relatively stable structure, overcoming geographical distance limitations. (2) Qingdao, Jinan, and Rizhao have high degree centrality, betweenness centrality, and closeness centrality in the network, with Qingdao and Jinan being relatively central. (3) Shandong Province can be spatially clustered into four regions, each with distinct roles, displaying a certain “neighboring clustering” phenomenon. (4) Endogenous network structures such as Mutual, Ctriple, and Gwesp significantly impact the formation and evolution of the network, while Twopath does not show the expected impact; FDI can promote the generation of carbon emission reception relationships in the spatial correlation network; IR can promote the generation of carbon emission spillover relationships in the spatial correlation network; GS, differences in GDP, differences in EI, and similarities of IR can promote the generation of organic correlations within the network; on the temporal level, the spatial correlation network of urban carbon emission in Shandong Province has shown significant stability during the study period.

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RETRACTED ARTICLE: Spatial effects of green finance development in Chinese provinces under the context of high-quality energy development

Lian,

Shang,

Qian

2024

Econ Change Restruct

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Analysis of spatial correlation networks of carbon emissions in emerging economies

Cited by 10 publications

References 48 publications

Unpacking the Sub-Regional Spatial Network of Land-Use Carbon Emissions: The Case of Sichuan Province in China

Unpacking the Sub-Regional Spatial Network of Land-Use Carbon Emissions: The Case of Sichuan Province in China

Analysis of the Driving Mechanism of Urban Carbon Emission Correlation Network in Shandong Province Based on TERGM

RETRACTED ARTICLE: Spatial effects of green finance development in Chinese provinces under the context of high-quality energy development

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