Relational Global Value Chain Carbon Emissions and Their Network Structure Patterns: Evidence from China DOI Open Access
Youfu Yue,

Junjun Hou,

Nuoya Yue

et al.

Sustainability, Journal Year: 2024, Volume and Issue: 16(16), P. 6940 - 6940

Published: Aug. 13, 2024

The structure of the network among firms participating in global value chains is an important factor understanding changes China’s carbon emissions. This paper focuses on interdependence between and interconnected networks to which they belong, utilizing inter-country input–output model that distinguishes domestic-owned enterprises foreign-invested for measurement purposes. By distinguishing domestic cross-border chains, we illustrate emission effects relational their structures, thereby contributing a Chinese perspective reduction. study reveals (1) chain activities have emerged as significant contributor emissions, constituting approximately 26.8%, with its growth mainly stemming from expansion At sectoral level, lead higher emissions service sector than manufacturing sector. (2) Domestic relationship are more likely favorable economic environmental trade-offs, evidenced by lower intensity chain. circle-structured associated sustainable greater potential reduction structure. (3) Structural decomposition analysis indicates impact has been decreasing since 2012, while influence rise surpasses end period.

Language: Английский

Spatial and temporal evolution patterns and spatial spillover effects of carbon emissions in China in the context of digital economy DOI
Congqi Wang, Haslindar Ibrahim,

Fanghua Wu

et al.

Journal of Environmental Management, Journal Year: 2024, Volume and Issue: 373, P. 123811 - 123811

Published: Dec. 24, 2024

Language: Английский

Citations

4
Regional carbon emission efficiency evaluation combining gray forecasting and game cross-efficiency analysis: The case of Yangtze River Delta DOI
Youyang Ren, Yuhong Wang, Dongdong Wu

et al.

Energy & Environment, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 15, 2025

Carbon emission efficiency (CEE) reflects the interplay between carbon emissions and economy, which refers to achieving more economic benefits lower while considering energy, labor, capital inputs. Assessing regional CEE is crucial for evaluating level of China's low-carbon development. Thus, this paper proposes a scenario-based hybrid model with foresight perspective game cross-efficiency (GCE) analysis. It measures future 41 Yangtze River Delta (YRD) cities from 2023 2030. The improved gray forecasting models generate input output datasets GCE analysis, assurance region constraint simulates energy consumption dual-control policy. results show that: (1) CEEs are generally low, an average 0.2142. Shanghai has highest CEE, 0.8089, Tongling lowest, 0.0307, under current policy constraint. (2) Under four control scenarios, YRD urban agglomeration follows U-shaped trend. indicates that may lead short-term decline in YRD, but long term, it gradually increase 2025 or 2026. (3) Spatial–temporal analysis reveals government should flexibly optimize update intensity value based on development differences focus consumption. These provide forward-looking guidance high-quality

Language: Английский

Citations

0
The spatiotemporal evolution and influencing factors of carbon emissions in the Yellow River Basin based on nighttime light data DOI Creative Commons
Congqi Wang,

Fanghua Wu,

Haslindar Ibrahim

et al.

Humanities and Social Sciences Communications, Journal Year: 2025, Volume and Issue: 12(1)

Published: March 18, 2025

Language: Английский

Citations

0
Relational Global Value Chain Carbon Emissions and Their Network Structure Patterns: Evidence from China DOI Open Access
Youfu Yue,

Junjun Hou,

Nuoya Yue

et al.

Sustainability, Journal Year: 2024, Volume and Issue: 16(16), P. 6940 - 6940

Published: Aug. 13, 2024

The structure of the network among firms participating in global value chains is an important factor understanding changes China’s carbon emissions. This paper focuses on interdependence between and interconnected networks to which they belong, utilizing inter-country input–output model that distinguishes domestic-owned enterprises foreign-invested for measurement purposes. By distinguishing domestic cross-border chains, we illustrate emission effects relational their structures, thereby contributing a Chinese perspective reduction. study reveals (1) chain activities have emerged as significant contributor emissions, constituting approximately 26.8%, with its growth mainly stemming from expansion At sectoral level, lead higher emissions service sector than manufacturing sector. (2) Domestic relationship are more likely favorable economic environmental trade-offs, evidenced by lower intensity chain. circle-structured associated sustainable greater potential reduction structure. (3) Structural decomposition analysis indicates impact has been decreasing since 2012, while influence rise surpasses end period.

Language: Английский

Citations

0