Carbon Emission Reduction Potential Dataset Balancing per Capita and Benefit in Each of Province of China

Zhou, Dadi; R, Hua S

doi:10.3974/geodp.2019.04.07

Cited by 1 publication

(13 citation statements)

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“…where represents the sum of all the cities that belong to i type in t year and transfer to j type in t+d years during the whole study period, and n represents the total number of cities whose carbon emission efficiency (industrial structure) belongs to i type in t year. Different types of transition probabilities are estimated respectively, and then d year long Markov transition probability matrix is obtained 53 : where the scale of class i horizontal region is nid, is ∑t=t0T−dnit; Piid represents the transfer probability of i type regions remaining i type after d year, and the larger the value, the higher the degree of regional differences in carbon emission efficiency (industrial structure) is solidified, which also indicates the existence of club convergence.…”

Section: Research Methods and Data Sourcesmentioning

confidence: 99%

Section: Markov Chain Modelmentioning

confidence: 99%

“…The index takes into account both the size of different types of regions (clubs) and the degree of convergence within each club. Specifically, the formula for calculating the club convergence index of the year is as follows 53 :…”

Section: Markov Chain Modelmentioning

confidence: 99%

“…In order to compare the curing degree of different indexes, the transfer probability matrix needs to be tested statistically. In this paper, likelihood ratio statistics are constructed in the following way 53 :…”

Section: Markov Chain Modelmentioning

confidence: 99%

“…According to the research of relevant scholars 53 and discussion in this paper, the coupling and coordination characteristics of "carbon emission efficiency and industrial structure" system can be divided into the following four types:…”

Section: Coupling Coordination Type Classification Of Carbon Emission...mentioning

confidence: 99%

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Spatial characteristics and coupling coordination between carbon emission efficiency and industrial structure in three metropolitan areas of Jiangsu Province, China

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It is of great practical significance to study the spatial characteristics of carbon emission efficiency, industrial structure, their coupling and coordination relationship for China's green development and industrial structure transformation in the new era. From the perspective of coupling, coordination and space, this paper analyzes and summarizes the spatial characteristics of carbon emission efficiency and industrial structure of 19 cities in three metropolitan areas of Jiangsu Province during 2009–2019 and their coupling and coordination relationship. The carbon emission efficiency in this study is represented by the carbon emission economic efficiency index and carbon emission social efficiency index. The results show that (a) the high-emission centers in the three metropolitan areas developed from “three centers” in 2009 to “five centers” in 2019. The continuous high-energy consumption of the secondary industry and the growth of the economic aggregate of the third industry kept the regional high carbon dioxide emissions. (b) The average value of carbon emission economic efficiency in 19 cities continued to increase, indicating that the contribution rate of the same amount of carbon emissions to economic income gradually increased; the growth range of carbon emission economic efficiency index is greater than that of carbon emission social efficiency index, indicating that carbon emission has a more significant effect on the improvement of regional economic development than on the improvement of public service level and residents’ living quality. (d) The solidification degree of carbon emission efficiency is greater than that of the industrial structure (solidification degree carbon emission social efficiency > carbon emission economic efficiency > industrial structure). The high-grade industrial structure in Xuzhou metropolitan area is closely related to the improvement of carbon emission economic efficiency and carbon emission social efficiency, and both are in moderate antagonism. The rationalizing industrial structure in Nanjing metropolitan area is closely related to the improvement of carbon emission economic efficiency, which is in high coordination run-in. The concentration degree of industrial structure in Suzhou-Wuxi-Changzhou metropolitan area is closely related to the improvement of carbon emission economic efficiency and carbon emission social efficiency, which are in polar coordination coupling and high coordination run-in, respectively. The proposed coupling path of carbon emission efficiency-industrial structure can not only alleviate the dynamic disharmony in different cities but also effectively improve the coupling degree in cities.

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