Spatial-Temporal Analysis and Driving Factors Decomposition of (De)Coupling Condition of SO2 Emissions in China

Wang, Yue; Shi, Lei; Chen, Di; Tan, Xue

doi:10.3390/ijerph17186725

Cited by 4 publications

(2 citation statements)

References 35 publications

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“…Therefore, these provinces can achieve SO 2 emission reduction goals by optimizing industrial structures. Specifically, the government can encourage non-industrial enterprises to drive economic development, reduce the proportion of secondary industry, and increase the proportion of primary and tertiary industry enterprises in the industrial structure [ 57 ].…”

Section: Discussionmentioning

confidence: 99%

Quantitative Analysis of Sulfur Dioxide Emissions in the Yangtze River Economic Belt from 1997 to 2017, China

Guo

Zhou

Zhang

et al. 2022

IJERPH

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Economic development is responsible for excessive sulfur dioxide (SO2) emissions, environmental pressure increases, and human and environmental risks. This study used spatial autocorrelation, the Environmental Kuznets Curve (EKC), and the Logarithmic Mean Divisia Index model to study the spatiotemporal variation characteristics and influencing factors of SO2 emissions in the Yangtze River Economic Belt (YREB) from 1997 to 2017. Our results show that the total SO2 emissions in the YREB rose from 513.14 × 104 t to 974.00 × 104 t before dropping to 321.97 × 104 t. The SO2 emissions from 11 provinces first increased and then decreased, each with different turning points. For example, the emission trends changed in Yunnan in 2011 and in Anhui in 2015, while the other nine provinces saw their emission trends change during 2005–2006. Furthermore, the SO2 emissions in the YREB showed a significant agglomeration phenomenon, with a Moran index of approximately 0.233–0.987. Moreover, the EKC of SO2 emissions and per capita GDP in the YREB was N-shaped. The EKCs of eight of the 11 provinces were N-shaped (Shanghai, Zhejiang, Anhui, Jiangxi, Sichuan, Guizhou, Hunan, and Chongqing) and those of the other three were inverted U-shaped (Jiangsu, Yunnan, and Hubei). Thus, economic development can both promote and inhibit the emission of SO2. Finally, during the study period, the technical effect (approximately −1387.97 × 104–130.24 × 104 t) contributed the most, followed by the economic (approximately 27.81 × 104–1255.59 × 104 t), structural (approximately −56.45 × 104–343.90 × 104 t), and population effects (approximately 4.25 × 104–39.70 × 104 t). Technology was the dominant factor in SO2 emissions reduction, while economic growth played a major role in promoting SO2 emissions. Therefore, to promote SO2 emission reduction, technological innovations and advances should be the primary point of focus.

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Section: Discussionmentioning

confidence: 99%

Quantitative Analysis of Sulfur Dioxide Emissions in the Yangtze River Economic Belt from 1997 to 2017, China

Guo

Zhou

Zhang

et al. 2022

IJERPH

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“…Wu and Shan et al presented a study on the decoupling of GDP and CO 2 at the regional level in China [ 19 , 62 ]. Wang focuses on the evolutionary trends of GDP growth and SO 2 decoupling at the provincial level in China [ 63 ]. Other single variables are similarly used as indicators of environmental impact, including threatened species, water pollution, forest destruction, conversion of agricultural land, and industrial waste.…”

Section: Literature Reviewmentioning

confidence: 99%

Can Economic Growth and Environmental Protection Achieve a “Win–Win” Situation? Empirical Evidence from China

Yang

Gao

2022

IJERPH

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Achieving a “win–win” situation regarding economic growth and environmental protection has become a common goal for sustainable development in all countries around the world. As the world’s largest developing country and the second largest economy, China has been striving to maintain economic growth while improving environmental quality to achieve its sustainable development goals. Applying the decoupling approach, a model widely used to quantify the relationship between the environment and the economy, this study analyzed the relationship between the economy and the environment, examining the decoupling performance of economic growth and environmental impacts in 30 Chinese provinces, autonomous regions, and municipalities to investigate whether economic growth and environmental protection have achieved a “win–win” situation. Nighttime light (NTL) data were used to measure the performance of economic growth. In addition, an environmental pressure index (EPI) assessment framework covering 6 primary and 11 secondary indicators was constructed to measure the environmental quality of China over time. First, NTL data proved to be a valid data source for assessing decoupling performance; second, environmental pressure at both the national and provincial levels significantly decreased during the study period; third, the relationship between the economy and the environment has been further improved, and economic growth and environmental protection have achieved a “win–win” situation. These findings offer an in-depth analysis of the decoupling of the economy and the environment in China and serve as a guide for future implementation strategies for sustainable development in various regions.

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Energy efficiency’s key role in explaining the performance of energy consumption in Andalusia (Spain)

Collado

Carmona

2021

Environ Sci Pollut Res

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The EU commitment to improve energy efficiency will help the EU economies to reduce energy consumption and achieve the desired decoupling between economic and energy consumption growth. For that aim, not only are the member states' commitments important, the role that the European regions adopt when they develop their own energy policies is also paramount. Among them, the Andalusia region (south of Spain) has been chosen as a case study due to its economic and energy characteristics. This paper aims to inform about the role played by energy efficiency, explaining the energy consumption behaviour in Andalusia and in comparison with the Spanish average for the period 2000-2015, through the Logarithmic Mean Divisia Index (LMDI) decomposition method.

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Spatial-Temporal Analysis and Driving Factors Decomposition of (De)Coupling Condition of SO2 Emissions in China

Cited by 4 publications

References 35 publications

Quantitative Analysis of Sulfur Dioxide Emissions in the Yangtze River Economic Belt from 1997 to 2017, China

Quantitative Analysis of Sulfur Dioxide Emissions in the Yangtze River Economic Belt from 1997 to 2017, China

Can Economic Growth and Environmental Protection Achieve a “Win–Win” Situation? Empirical Evidence from China

Energy efficiency’s key role in explaining the performance of energy consumption in Andalusia (Spain)

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