The Influencing Effects of Industrial Eco-Efficiency on Carbon Emissions in 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, a...

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Main Authors: Zaijun Li, Xiang Zheng, Dongqi Sun
Format: Article
Language:English
Published: MDPI AG 2021-12-01
Series:Energies
Subjects:
Online Access:https://www.mdpi.com/1996-1073/14/23/8169
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author Zaijun Li
Xiang Zheng
Dongqi Sun
author_facet Zaijun Li
Xiang Zheng
Dongqi Sun
author_sort Zaijun Li
collection DOAJ
description 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.
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spelling doaj.art-4184f8ddda3c440fbb00c74a721b0c182023-11-23T02:23:43ZengMDPI AGEnergies1996-10732021-12-011423816910.3390/en14238169The Influencing Effects of Industrial Eco-Efficiency on Carbon Emissions in the Yangtze River DeltaZaijun Li0Xiang Zheng1Dongqi Sun2Research Institute of Central Jiangsu Development, Yangzhou University, Yangzhou 225009, ChinaResearch Institute of Central Jiangsu Development, Yangzhou University, Yangzhou 225009, ChinaKey Laboratory of Regional Sustainable Development Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, ChinaA 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.https://www.mdpi.com/1996-1073/14/23/8169industrial eco-efficiencycarbon emissionsspatio-temporal correlationspatial econometric modelYangtze River Delta
spellingShingle Zaijun Li
Xiang Zheng
Dongqi Sun
The Influencing Effects of Industrial Eco-Efficiency on Carbon Emissions in the Yangtze River Delta
Energies
industrial eco-efficiency
carbon emissions
spatio-temporal correlation
spatial econometric model
Yangtze River Delta
title The Influencing Effects of Industrial Eco-Efficiency on Carbon Emissions in the Yangtze River Delta
title_full The Influencing Effects of Industrial Eco-Efficiency on Carbon Emissions in the Yangtze River Delta
title_fullStr The Influencing Effects of Industrial Eco-Efficiency on Carbon Emissions in the Yangtze River Delta
title_full_unstemmed The Influencing Effects of Industrial Eco-Efficiency on Carbon Emissions in the Yangtze River Delta
title_short The Influencing Effects of Industrial Eco-Efficiency on Carbon Emissions in the Yangtze River Delta
title_sort influencing effects of industrial eco efficiency on carbon emissions in the yangtze river delta
topic industrial eco-efficiency
carbon emissions
spatio-temporal correlation
spatial econometric model
Yangtze River Delta
url https://www.mdpi.com/1996-1073/14/23/8169
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