The Influencing Factors and Emission Reduction Pathways for Carbon Emissions from Private Cars: A Scenario Simulation Based on Fuzzy Cognitive Maps

Sustainability, Journal Year: 2025, Volume and Issue: 17(5), P. 2268 - 2268

Published: March 5, 2025

The promotion of carbon reduction in the private car sector is crucial for advancing sustainable transportation development and addressing global climate change. This study utilizes vehicle trajectory big data from Guangdong Province, China, employs machine learning, an LDA topic model, a gradient descent-based fuzzy cognitive map grey correlation analysis to investigate influencing factors emission pathways emissions cars. findings indicate that (1) population density exhibits strongest with emissions, coefficient 0.85, rendering it key factor (2) public emerges as primary pathway under single-factor scenario, (3) coordinating transport road network fuel prices traffic congestion are both viable well reducing sector. attempts integrate multiple within unified research framework, exploring elucidating cars objective providing valuable insights into green low-carbon transition

Language: Английский

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Carbon neutral spatial zoning and optimization based on land use carbon emission in the qinba mountain region, China

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: March 25, 2025

Amid global climate change, the pursuit of low-carbon development has become a unified international goal. The Qinba Mountain region plays an important role in maintaining China's ecological security, making spatial zoning tailored for carbon neutrality vital local sustainable development. Using land use and socioeconomic data from 2000 to 2020 81 county-level units, neutral framework was developed, considering natural, economic, resource factors. This study further integrated spatiotemporal dynamics index multi-scenario predictions future emission (CE) zoning. results revealed that had overall positive net-carbon trend without significant deficits, central faced increased CE northern weak carrying capacity. predicted continued decrease under scenario reached 30.55 million t by 2060, with only nine units failing reach their peaking 2030. Five different zones were identified: sink functional zone, stabilization high-carbon control zone source optimization zone. Tailored strategies each proposed enhance regional environment contribute green These findings offer insights into achieving regions or cities.

Language: Английский

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The Spatiotemporal Evolution of Buildings’ Carbon Emissions in Siping, a Chinese Industrial City

Buildings, Journal Year: 2025, Volume and Issue: 15(7), P. 1101 - 1101

Published: March 28, 2025

Industrial cities in transition face multiple pressures of socio-economic development and carbon emission reduction. Studying the spatiotemporal evolution urban emissions helps us understand spatial adaptability low-carbon cities. In this study, we took Siping, an industrial city China, as example; spatially mapped buildings’ by combining statistical data points interest; used exploratory analysis to dynamically evolve distribution spatiotemporal-dependent paths over years. The results presented aggregation heterogeneity four types Siping. contrast, block-scale related residential buildings commercial was stronger, standard deviation ellipses showed a trend expanding outward. However, with large total volume ellipse distribution, targeting remains priority for With expansion land use, population density intensity central area decreased. Therefore, Siping should slow down its rate expansion, improve use efficiency, achieve new balance complex relationship between society, economy, environment.

Language: Английский

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Multi-Scale Spatial Structure Impacts on Carbon Emission in Cold Region: Case Study in Changchun, China

Sustainability, Journal Year: 2024, Volume and Issue: 17(1), P. 228 - 228

Published: Dec. 31, 2024

Cities in cold regions face significant challenges, including high carbon emissions, intense energy use, and outdated structures, making them critical areas for achieving neutrality sustainable development. While studies have explored the impact of spatial structures on urban effects multi-scale remain insufficiently understood, limiting effective planning strategies. This research examines Changchun, a city severe region, using data from 2012 to 2021, road networks, land nighttime light, statistics. Employing syntax, landscape pattern indices, random forests, segmented linear regression, this establishes emission translation pathway analyze nonlinear structures. Findings reveal 26.70% annual decrease with winter emissions 1.84 times higher than summer ones. High-emission zones shifted industrial transportation, commercial, residential zones, reflecting growing seasonal variability structural changes. Spatial complexity increased while connectivity declined. Multi-scale analysis identified “decrease–increase–decrease” pattern, macro-scale centrality declining micro-scale hierarchy rising. These results provide both theoretical practical guidance regions, supporting early long-term development goals.

Language: Английский

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