Research on the Nonlinear Relationship Between Carbon Emissions from Residential Land and the Built Environment: A Case Study of Susong County, Anhui Province Using the XGBoost-SHAP Model

Land, Год журнала: 2025, Номер 14(3), С. 440 - 440

Опубликована: Фев. 20, 2025

Residential land is the basic unit of urban-scale carbon emissions (CEs). Quantifying and predicting CEs from residential are conducive to achieving urban neutrality. This study took 84 communities in Susong County, Anhui Province as its research object, exploring nonlinear relationship between built environment land. By identifying through building electricity consumption, 14 indicators, including area (LA), floor ratio (FAR), greening (GA), density (BD), gross (GFA), use mix rate (Phh), permanent population (PPD), were selected establish an interpretable machine learning (ML) model based on XGBoost-SHAP attribution analysis framework. The results show that, first, goodness fit XGBoost reached 91.9%, prediction accuracy was better than that gradient boosting decision tree (GBDT), random forest (RF), Adaboost model, traditional logistic model. Second, compared with other ML models, explained influencing factors more clearly. SHAP indicate BD, FAR, Phh most important affecting CEs. Third, there a significant threshold effect characteristic variables Fourth, interaction different dimensions environmental factors, played dominant role interaction. Reducing FAR considered be effective CE reduction strategy. provides practical suggestions for planners reducing land, which has policy implications significance.

Язык: Английский

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A breakthrough land-use-based carbon accounting framework for multi-scale evaluation: Coupling optimization algorithm and LCA

Sustainable Cities and Society, Год журнала: 2025, Номер unknown, С. 106132 - 106132

Опубликована: Янв. 1, 2025

Язык: 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, Год журнала: 2025, Номер 15(1)

Опубликована: Март 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.

Язык: Английский

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Data-driven neighborhood-level carbon emission accounting models and decarbonization strategies: Empirical study on Central Shenyang City

Sustainable Cities and Society, Год журнала: 2025, Номер 125, С. 106346 - 106346

Опубликована: Апрель 4, 2025

Язык: Английский

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