Regional Differences and Convergence of Carbon Emissions Intensity in Cities along the Yellow River Basin in China

Chen, Xiaolan; Meng, Qinggang; Shi, Jianing; Liu, Yuanyuan; Sun, Jun; Shen, Wanfang

doi:10.3390/land11071042

Cited by 22 publications

(13 citation statements)

References 36 publications

(37 reference statements)

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“…In 2019, China's president Xi Jinping proposed a primary national strategy for ecological protection and high-quality development of the YRB at the Symposium on Ecological Protection and High-Quality Development of the YRB [21]. Indeed, the YRB consists of many resourcebased cities with developed secondary industries and heavy energy consumption, which constitutes an essential source of carbon emissions and industrial pollution [22]. The scientific identification of the development pattern of cities in the YRB is significant for implementing national policies and promoting regional development.…”

Section: Introductionmentioning

confidence: 99%

Spatio-Temporal Urban Land Green Use Efficiency under Carbon Emission Constraints in the Yellow River Basin, China

Yang

2022

IJERPH

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In the context of rapid urbanization and limited land amount, it is essential to scientifically evaluate the urban land green use efficiency (ULGUE) to promote regional sustainable development. Current studies are of great value for enriching the theoretical system and application research of ULGUE. Still, most of them only consider industrial pollution but ignore carbon emission as an essential environmental influencing indicator. This paper introduced carbon emissions into the input-output indicator system, measured ULGUE of 57 cities in the Yellow River Basin (YRB) over the 2004–2017 periods using the super-efficiency slacked-based measure (Super-SBM) model, analyzed its spatio-temporal patterns with the kernel density estimation (KDE) model and spatial autocorrelation model, and then identified the influencing factors with the Spatial Durbin model (SDM). As shown by the results, firstly, the ULGUE in the YRB over the 2004–2017 periods showed a trend of first decreasing and then increasing. Secondly, the ULGUE exhibited spatio-temporal imbalance characteristics across the YRB. Thirdly, ULGUE was the interaction of multiple indicators, and its influencing factors had spatial spillover effects. All in all, this paper is fundamental to the high-quality development of cities in the background of the Chinese policy of “carbon peak, carbon neutralization”.

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Section: Introductionmentioning

confidence: 99%

Spatio-Temporal Urban Land Green Use Efficiency under Carbon Emission Constraints in the Yellow River Basin, China

Yang

2022

IJERPH

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“…The Dagum Gini coefficient decomposition method was first proposed by Dagum, C. [47]. Applying the Dagum Gini coefficient to the measurement of the digital economy can not only measure the total regional differences but also decompose the sources of differences according to regional division [48]. The specific equation is shown in (8):…”

Section: Dagum Gini Coefficientmentioning

confidence: 99%

Spatial Imbalance, Dynamic Evolution and Convergence of the Digital Economy: Analysis Based on Panel Data of 278 Cities in China

et al. 2023

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Accelerating the development of the digital economy is the way to build a modern industrial system and promote sustainable development. In order to accurately analyze the development status of China’s digital economy, this study introduced a text analysis method to construct an index of the digital economy and surveyed the digital economy based on the panel data of 278 Chinese cities from 2011 to 2019. Moran’s I index, the Dagum Gini coefficient, the kernel density and a Markov chain were used to reveal the space-time difference and dynamic change characteristics. Considering the impact of the spatial correlation and regional division on convergence, we compared the σ values and spatial σ values to study the convergence characteristics after grouping with the decision tree method. The research showed that the digital economy had greatly improved, but it showed a significant imbalance. The research on the regional division of cities according to their geographical distribution and grade showed that the development status of the digital economy was increasingly different, and there was no convergence feature. We chose continuous classification variables and used the decision tree method to divide cities into 10 groups to investigate the convergence. The results showed that the σ values and spatial σ values decreased significantly and showed convergence characteristics. The development of the digital economy showed convergence, indicating that the convergence was greatly affected by the geographical location and grouping basis. Overall, this study contributes to our understanding of the development status of the digital economy, and targeted policy recommendations were proposed to improve the level of digital economy development.

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“…Given the data availability with carbon source and its corresponding emission coefficient of agricultural productionas well as the increasing consumption of agricultural diesel CO 2 emissions requiring be further considered [30], then, agricultural carbon emissions are adopted to measure the undesired output variable of agricultural green total factor productivity in this paper. In addition, referring to the research [31,32], this paper calculates CO 2 emissions by using the emission coefficients of four inputs: chemical fertilizer, pesticide, agricultural film and diesel oil. The total agricultural CO 2 emissions could be obtained by adding the product of agricultural pollution input (P), related net calorific value (NCV), carbon emission factor (CEF), carbon oxidation factor (COF) and carbon quantity factor (12/44), which is setas follows:…”

Section: Variable Measurements 231 Measurement Of the Explained Varia...mentioning

confidence: 99%

The Dual Effects of Environmental Regulation and Financial Support for Agriculture on Agricultural Green Development: Spatial Spillover Effects and Spatio-Temporal Heterogeneity

Jiang

2022

Applied Sciences

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Environmental regulation and financial support for agriculture are regarded as important means to promote agricultural green development. Based on provincial panel data of 31 provinces in China between the years 2000 and 2020, this paper explores the interactive effect, spatial spillover effect and spatio-temporal heterogeneity of environmental regulation and financial support for agriculture on agricultural green development. The empirical conclusions are as follows: (1) The level of agricultural green development increases year by year with a spatial characteristic of high in the east and low in the west. Moreover, there is a spatial spillover effect of agricultural green development with spatiotemporal heterogeneity. (2) Environmental regulation would not only reduce the level of local agricultural green development but also inhibit the adjacent regions, which is contrary to the impact of financial support for agriculture. (3) The interactive relationship of environmental regulation and financial support for agriculture has a spatial spillover effect on agricultural green development, which is more significant in the systematization stage of agricultural green development and most significant in the east-middle region.

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Regional Differences and Convergence of Carbon Emissions Intensity in Cities along the Yellow River Basin in China

Cited by 22 publications

References 36 publications

Spatio-Temporal Urban Land Green Use Efficiency under Carbon Emission Constraints in the Yellow River Basin, China

Spatio-Temporal Urban Land Green Use Efficiency under Carbon Emission Constraints in the Yellow River Basin, China

Spatial Imbalance, Dynamic Evolution and Convergence of the Digital Economy: Analysis Based on Panel Data of 278 Cities in China

The Dual Effects of Environmental Regulation and Financial Support for Agriculture on Agricultural Green Development: Spatial Spillover Effects and Spatio-Temporal Heterogeneity

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