Cited by Urban low-carbon governance zoning coupled with urban attributes and spatial networks: Theoretical framework and practical path

Scenario simulation of carbon balance in carbon peak pilot cities under the background of the "dual carbon" goals DOI

Jinting Zhang, Kui Yang,

Jingdong Wu

et al.

Sustainable Cities and Society, Journal Year: 2024, Volume and Issue: unknown, P. 105910 - 105910

Published: Oct. 1, 2024

Language: Английский

Citations

Carbon peak evaluation and causal drivers of net carbon emission time-series dynamics in typical Chinese cities DOI

Bingbing Zhao, Min Deng, Siuming Lo

et al.

Cities, Journal Year: 2025, Volume and Issue: 160, P. 105856 - 105856

Published: Feb. 27, 2025

Language: Английский

Citations

AI Analytics for Carbon-Neutral City Planning: A Systematic Review of Applications DOI

Cong Cong, Jessica Page, Yoonshin Kwak

et al.

Urban Science, Journal Year: 2024, Volume and Issue: 8(3), P. 104 - 104

Published: Aug. 1, 2024

Artificial intelligence (AI) has become a transformative force across various disciplines, including urban planning. It unprecedented potential to address complex challenges. An essential task is facilitate informed decision making regarding the integration of constantly evolving AI analytics into planning research and practice. This paper presents review how methods are applied in studies, focusing particularly on carbon neutrality We highlight already being used generate new scientific knowledge interactions between human activities nature. consider conditions which advantages AI-enabled studies can positively influence decision-making outcomes. also importance interdisciplinary collaboration, responsible governance, community engagement guiding data-driven suggest contribute supporting carbon-neutrality goals.

Language: Английский

Citations

Causal discovery and analysis of global city carbon emissions based on data-driven and hybrid intelligence DOI

Xiaoyan Li, Wenting Zhan,

Fumin Deng

et al.

Computers Environment and Urban Systems, Journal Year: 2024, Volume and Issue: 115, P. 102206 - 102206

Published: Nov. 9, 2024

Language: Английский

Citations

Spatial association network structure of agricultural carbon emission efficiency in Chinese cities and its driving factors DOI

Wei Xu,

Bohong Chen

Scientific Reports, Journal Year: 2024, Volume and Issue: 14(1)

Published: Dec. 30, 2024

In light of the Chinese government's dual carbon goals, achieving cleaner production activities has become a central focus, with regional environmental collaborative governance, including management agricultural reduction, emerging as mainstream approach. This study examines 268 prefecture-level cities in China, measuring emission efficiency city agriculture from 2001 to 2022. By integrating social network analysis and modified gravity model, reveals characteristics spatial association China. Additionally, quadratic assignment procedure is employed investigate driving factors. The findings indicate that: (1) China displays substantial spatiotemporal heterogeneity, characterized by marked clustering. Central generally exhibit higher levels, while surrounding tend have lower efficiency. (2) multidimensional, complex, organic characteristics, potential for enhanced stability. (3) Agricultural regions southeastern dominate network, weaker sectors, like Beijing, Shanghai, Ningxia, occupy peripheral positions. (4) Within Intra block correlations are low, interblock strong, exhibiting significant spillover effects. (5)Variations development levels mechanization significantly enhance formation networks related Conversely, differences industrial structure fertilizer application exert negative influence on these networks.

Language: Английский

Citations

Scenario Simulation of Carbon Balance in Carbon Peak Pilot Cities Under the Background of the "Dual Carbon" Goals DOI

Jinting Zhang, Kui Yang,

Jingdong Wu

et al.

Published: Jan. 1, 2024

Language: Английский

Citations

Spatial Association Network Structure of Agricultural Carbon Emission Efficiency in Chinese Cities and Its Driving Factors DOI

Wei Xu,

Bohong Chen

Research Square (Research Square), Journal Year: 2024, Volume and Issue: unknown

Published: Sept. 13, 2024

Abstract In light of the Chinese government's dual carbon goals, achieving cleaner production activities has become a central focus, with regional environmental collaborative governance, including management agricultural reduction, emerging as mainstream approach. This study examines 268 prefecture-level cities in China, measuring emission efficiency city agriculture from 2000 to 2021. By integrating social network analysis and modified gravity model, reveals characteristics spatial association China. Additionally, quadratic assignment procedure is employed investigate driving factors. The findings indicate that: (1) China displays substantial spatiotemporal heterogeneity, characterized by marked clustering. Central generally exhibit higher levels, while surrounding tend have lower efficiency. (2) multidimensional, complex, organic characteristics, potential for enhanced stability. (3) Agricultural regions southeastern dominate network, weaker sectors, like Beijing, Shanghai, Ningxia, occupy peripheral positions. (4) Within Intra block correlations are low, interblock strong, exhibiting significant spillover effects. (5)Variations development levels mechanization significantly enhance formation networks related Conversely, differences industrial structure fertilizer application exert negative influence on these networks.

Language: Английский

Citations

Urban low-carbon governance zoning coupled with urban attributes and spatial networks: Theoretical framework and practical path DOI

Xinhui Feng,

Sensen Wang,

Nengjun Wu

et al.

Journal of Environmental Management, Journal Year: 2024, Volume and Issue: 373, P. 123865 - 123865

Published: Dec. 29, 2024

Language: Английский

Citations