scholarly journals Multi-Perspective Influence Mechanism Analysis and Multi-Scenario Prediction of Carbon Emissions——A Case of the Yangtze River Delta, China

2019 ◽  
Vol 118 ◽  
pp. 04014
Author(s):  
Tao Yi ◽  
Mohan Qiu ◽  
Zhengang Zhang ◽  
Song Mu ◽  
Yu Tian
Keyword(s):  
Carbon Emissions ◽  
Emission Reduction ◽  
Yangtze River ◽  
Carbon Emission ◽  
Yangtze River Delta ◽  
Mechanism Analysis ◽  
The Yangtze River ◽  
Carbon Emission Reduction ◽  
Influence Mechanism ◽  
The Yangtze River Delta

Under the mandatory push of meeting carbon emission reduction commitments proposed in the Paris Agreement, the analysis on the peaking time of China’s carbon emissions deserves enough attention. This paper focuses on the peaking times of total carbon emissions (TCE) and carbon emission intensity (CEI) in the Yangtze River Delta (YRD). According to the development of carbon emissions in YRD and related targets in the 13th Five-Year Plan, the peaking times of TCE and CEI in different scenarios are predicted based on the influence mechanism analysis of carbon emissions in YRD from the perspective of energy, economy and society. Considering the development characteristics of China at this stage, this paper introduces several new indicators such as full-time equivalent of research and development (R&D) personnel and investment in environmental pollution control. Based on the study results, several policy recommendations are put forward to fulfil China’s carbon emission reduction commitments.

scholarly journals A Comprehensive Evaluation of Carbon Emission Reduction Capability in the Yangtze River Economic Belt

2020 ◽  
Vol 17 (2) ◽  
pp. 545 ◽  
Author(s):  
Decai Tang ◽  
Yan Zhang ◽  
Brandon J Bethel
Keyword(s):  
Energy Consumption ◽  
Carbon Emissions ◽  
Emission Reduction ◽  
Yangtze River ◽  
Carbon Emission ◽  
The Yangtze River ◽  
Low Carbon ◽  
Carbon Sinks ◽  
Carbon Emission Reduction ◽  
Low Carbon Economy

The Yangtze River Economic Belt (YREB) is an essential part of China’s goal of reducing its national carbon emissions. Focusing on economic and social development, the development of science and technology, carbon sinks, energy consumption, and carbon emissions, this paper uses “the Technique for Order of Preference by Similarity to Ideal Solution mode” (TOPSIS) and “an obstacle factor diagnosis method” to measure the reduction capacity of each province and municipality of the YREB. Key obstacles to achieving the goal of carbon emission reduction are also identified. The main finding is that the emission reduction capacities of Shanghai, Jiangsu and Zhejiang in China’s east is far greater than that of all other provinces and municipalities, the main obstacle of Shanghai, Jiangsu, and Zhejiang are carbon sinks, energy consumption and carbon emission, and other provinces and municipalities are social and economic development. Taking into consideration those evaluation results and obstacles, paths for carbon emission reduction are delineated through a four-quadrant matrix method with intent to provide suitable references for the development of a low-carbon economy in the YREB.

scholarly journals Land-Use Carbon Emissions Estimation for the Yangtze River Delta Urban Agglomeration Using 1994–2016 Landsat Image Data

2018 ◽  
Vol 10 (9) ◽  
pp. 1334 ◽  
Author(s):  
Yifan Cui ◽  
Long Li ◽  
Longqian Chen ◽  
Yu Zhang ◽  
Liang Cheng ◽  
...  
Keyword(s):  
Land Use ◽  
Spatial Autocorrelation ◽  
Carbon Emissions ◽  
Yangtze River ◽  
Carbon Emission ◽  
Image Data ◽  
Yangtze River Delta ◽  
Carbon Intensity ◽  
The Yangtze River ◽  
The Yangtze River Delta

The amount and growth rate of carbon emissions have been accelerated on a global scale since the industrial revolution (1800), especially in recent decades. This has resulted in a significant influence on the natural environment and human societies. Therefore, carbon emission reduction receives continuously increasing public attention and has long been under debate. In this study, we made use of the land-use specific carbon emission coefficients from previous studies and estimated the land-use carbon emissions and carbon intensities of the Yangtze River Delta Urban Agglomeration (YRDUA)—which consists of 26 eastern Chinese cities—from Landsat image data and socio-economic statistics in 1995, 2005, and 2015. In addition, spatial autocorrelation models including both global and local Moran’s I were used to analyze the spatial autocorrelation of carbon emissions and carbon intensities. It was found that (1) the YRDUA witnessed a rapidly increasing trend for net carbon emissions and a decreasing trend for carbon intensity over the two decades; (2) the spatial differences in carbon intensity had gradually narrowed, but were large in carbon emissions and had gradually increased; and (3) the carbon emissions in 2005 and 2015 had significant spatial autocorrelations. We concluded that (1) from 1995 to 2015 in the YRDUA, carbon emissions were large for the cities along the Yangtze River and carbon intensities were high for Anhui province’s resource-based cities, while both carbon emissions and carbon intensities were small for Zhejiang province’s cities; (2) over two decades, the increase in carbon emissions from urban land was approximately twice the increase in urban land area. Our study can provide useful insights into the assignment of carbon reduction tasks within the YRDUA.

scholarly journals The Influencing Effects of Industrial Eco-Efficiency on Carbon Emissions in the Yangtze River Delta

Energies ◽  
2021 ◽  
Vol 14 (23) ◽  
pp. 8169
Author(s):  
Zaijun Li ◽  
Xiang Zheng ◽  
Dongqi Sun
Keyword(s):  
Spatial Correlation ◽  
Carbon Emissions ◽  
Yangtze River ◽  
Temporal Correlation ◽  
Yangtze River Delta ◽  
River Delta ◽  
Direct And Indirect Effects ◽  
The Yangtze River ◽  
Spatio Temporal ◽  
The Yangtze River Delta

A low-carbon economy is the most important requirement to realize high-quality integrated development of the Yangtze River Delta. Utilizing the following models: a super-efficiency slacks-based measure model, a spatio-temporal correlation model, a bivariate LISA model, a spatial econometric model, and a geographically weighted random forest model, this study measured urban industrial eco-efficiency (IEE) and then analyzed its influencing effects on carbon emission in the Yangtze River Delta from 2000 to 2017. The influencing factors included spatio-temporal correlation intensity, spatio-temporal association type, direct and indirect impacts, and local importance impacts. Findings showed that: (1) The temporal correlation intensity between IEE and scale efficiency (SE) and carbon emissions exhibited an inverted V-shaped variation trend, while the temporal correlation intensity between pure technical efficiency (PTE) and carbon emissions exhibited a W-shaped fluctuation trend. The negative spatial correlation between IEE and carbon emissions was mainly distributed in the developed cities of the delta, while the positive correlation was mainly distributed in central Anhui Province and Yancheng and Taizhou cities. The spatial correlation between PTE and carbon emissions exhibited a spatial pattern of being higher in the central part of the delta and lower in the northern and southern parts. The negative spatial correlation between SE and carbon emissions was mainly clustered in Zhejiang Province and scattered in Jiangsu and Anhui provinces, with the cities with positive correlations being concentrated around two locations: the junction of Anhui and Jiangsu provinces, and within central Jiangsu Province. (2) The direct and indirect effects of IEE on carbon emissions were significantly negative, indicating that IEE contributed to reducing carbon emissions. The direct impact of PTE on carbon emissions was also significantly negative, while its indirect effect was insignificant. Both the direct and indirect effects of SE on carbon emissions were significantly negative. (3) It was found that the positive effect of IEE was more likely to alleviate the increase in carbon emissions in northern Anhui City. Further, PTE was more conducive to reducing the increase in carbon emissions in northwestern Anhui City, southern Zhejiang City, and in other cities including Changzhou and Wuxi. Finally, it was found that SE played a relatively important role in reducing the increase in carbon emissions only in four cities: Changzhou, Suqian, Lu’an, and Wenzhou.

scholarly journals An Empirical Study on the Impact Path of Urbanization to Carbon Emissions in the China Yangtze River Delta Urban Agglomeration

2019 ◽  
Vol 9 (6) ◽  
pp. 1116 ◽  
Author(s):  
Feng Wang ◽  
Mengnan Gao ◽  
Juan Liu ◽  
Yuhui Qin ◽  
Ge Wang ◽  
...  
Keyword(s):  
Economic Development ◽  
Carbon Emissions ◽  
Yangtze River ◽  
Industrial Structure ◽  
Yangtze River Delta ◽  
River Delta ◽  
Test Method ◽  
The Yangtze River ◽  
Development Level ◽  
The Yangtze River Delta

Urbanization is an important factor in the growth of carbon emissions, as the city is a dense area of carbon emissions. This paper estimates the carbon emissions at the provincial, municipal, and county spatial scales in the Yangtze River Delta region during 2008–2015. On this basis, this paper makes a comprehensive analysis of the pathway and difference of the urbanization to the carbon emission by using the scale variance decomposition method, the space correlation analysis method, the mediation effect test method, and the space panel data model. The results show that the urbanization of the Yangtze River Delta has a significant positive impact on carbon emissions; The pathway from urbanization to industrial structure has a significant impact on carbon emissions. Although the pathway from industrial structure to urbanization to carbon emissions is insignificant, the industrial structure directly affects carbon emissions. There is a significant path from urbanization to the level of economic development to carbon emissions, but there is no mechanism for the economic development level to adversely affect the level of urbanization and thus affect carbon emissions; the chain action pathway from the urbanization level to the employment level to the economic development level to carbon emissions is not significant. Finally, based on the research conclusions, the corresponding policy recommendations are submitted.

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