Research on the Spatiotemporal Characteristics and Influencing Mechanisms of Sustainable Plateau Urban Building Carbon Emissions: A Case Study of Qinghai Province DOI Creative Commons

Haifa Jia,

Bo Su, Jianxun Zhang

et al.

Buildings, Journal Year: 2025, Volume and Issue: 15(8), P. 1307 - 1307

Published: April 16, 2025

Buildings account for 39% of global carbon emissions, making the construction sector a pivotal contributor to climate change. In ecologically fragile plateau regions, tension between urban development and environmental sustainability poses significant challenge. This study examines spatiotemporal characteristics influencing mechanisms building emissions (BCEs) in cities using an empirical analysis 13-year panel data (2010–2022) from two municipalities six prefectures Qinghai Province, China. By employing eXtreme Gradient Boosting (XGBoost) model, we comprehensively assess drivers across four dimensions: socioeconomic structure, demographic factors, expansion patterns, climatic topographic attributes. Key findings include: (1) The XGBoost model exhibits robust predictive performance (R2 > 0.9, MSE < 0.1, RMSE 0.3), validating its effectiveness systems. (2) Socioeconomic structure significantly positively influence with GDP, per capita built-up areas being particularly influential. (3) interaction terrain increases buildings. (4) While is common factor affecting BCEs different types buildings, other such as population density, housing area, shape index, exhibit variability. These insights inform policy recommendations cross-regional flow balancing adaptive low-carbon planning strategies tailored ecosystems.

Language: Английский

Life Cycle Carbon Emissions Analysis of a Detached House in Thailand DOI

Nattaya Sangngamratsakul,

Kuskana Kubaha,

Siriluk Chiarakorn

et al.

Springer proceedings in energy, Journal Year: 2025, Volume and Issue: unknown, P. 159 - 165

Published: Jan. 1, 2025

Language: Английский

Citations

0

Evaluating the carbon footprint of a hospital from the dynamic life cycle perspective:A case study in Shanghai DOI
Yongkui Li, Yong Zha,

M. J. Li

et al.

Building and Environment, Journal Year: 2025, Volume and Issue: unknown, P. 112950 - 112950

Published: March 1, 2025

Language: Английский

Citations

0

Carbon-friendly design method of tunnel lining segments based on Pareto optimal analysis DOI
Tao Liu,

Hehua Zhu,

Yi Shen

et al.

Tunnelling and Underground Space Technology, Journal Year: 2025, Volume and Issue: 161, P. 106602 - 106602

Published: April 4, 2025

Language: Английский

Citations

0

Multi-objective Optimization of Embodied Carbon Emission, Energy Consumption, and Daylighting Performance of Educational Building in the Schematic Design Stage DOI

Yongpeng Shi,

Zhen Yang,

Shu Zheng

et al.

Journal of Building Engineering, Journal Year: 2025, Volume and Issue: unknown, P. 112594 - 112594

Published: April 1, 2025

Language: Английский

Citations

0

Research on the Spatiotemporal Characteristics and Influencing Mechanisms of Sustainable Plateau Urban Building Carbon Emissions: A Case Study of Qinghai Province DOI Creative Commons

Haifa Jia,

Bo Su, Jianxun Zhang

et al.

Buildings, Journal Year: 2025, Volume and Issue: 15(8), P. 1307 - 1307

Published: April 16, 2025

Buildings account for 39% of global carbon emissions, making the construction sector a pivotal contributor to climate change. In ecologically fragile plateau regions, tension between urban development and environmental sustainability poses significant challenge. This study examines spatiotemporal characteristics influencing mechanisms building emissions (BCEs) in cities using an empirical analysis 13-year panel data (2010–2022) from two municipalities six prefectures Qinghai Province, China. By employing eXtreme Gradient Boosting (XGBoost) model, we comprehensively assess drivers across four dimensions: socioeconomic structure, demographic factors, expansion patterns, climatic topographic attributes. Key findings include: (1) The XGBoost model exhibits robust predictive performance (R2 > 0.9, MSE < 0.1, RMSE 0.3), validating its effectiveness systems. (2) Socioeconomic structure significantly positively influence with GDP, per capita built-up areas being particularly influential. (3) interaction terrain increases buildings. (4) While is common factor affecting BCEs different types buildings, other such as population density, housing area, shape index, exhibit variability. These insights inform policy recommendations cross-regional flow balancing adaptive low-carbon planning strategies tailored ecosystems.

Language: Английский

Citations

0