Decoding spatial patterns of urban thermal comfort: Explainable machine learning reveals drivers of thermal perception

Environmental Impact Assessment Review, Год журнала: 2025, Номер 114, С. 107895 - 107895

Опубликована: Март 5, 2025

Язык: Английский

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Combating urban heat: Systematic review of urban resilience and adaptation strategies

Heliyon, Год журнала: 2024, Номер 10(17), С. e37001 - e37001

Опубликована: Авг. 27, 2024

Язык: Английский

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Study on the Measurement of Interprovincial Carbon Emission Reduction Performance, Regional Gaps, and Spatial Convergence in China

Energy, Год журнала: 2025, Номер unknown, С. 134597 - 134597

Опубликована: Янв. 1, 2025

Язык: Английский

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Exploring the low-carbon development path of resource-based cities based on scenario simulation

Scientific Reports, Год журнала: 2025, Номер 15(1)

Опубликована: Фев. 18, 2025

Abstract Resource-based cities (RBCs) have historically been constrained by their inherent characteristics, impeding rapid shifts in energy consumption patterns and exerting substantial pressure on regional decarbonization efforts. Herein, 18 RBCs southwestern China were taken as the research object. Firstly, a resilience index system was constructed for resource ecosystem socio-economic of RBCs, optimization mutation level algorithm used to measure each city. Secondly, an interval prediction model established carbon emissions based GA-DBN-KDE algorithm. Finally, setting 16 scenarios, emission range “carbon peak” time Southwest from 2023 2040 predicted, scientific path low-carbon development explored under differentiated scenarios. The results indicated that: (1) urban levels both rise; (2) demonstrated excellent performance; (3) simulation scenarios revealed varying specific paths achieve peak, underscoring necessity city-specific policy formulation. Overall, this paper provides new analytical method transformation further forging basis decision-makers formulate reduction measures.

Язык: Английский

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Unveiling environmental resilience: A data-driven multi-criteria decision-making approach

Environmental Impact Assessment Review, Год журнала: 2024, Номер 108, С. 107607 - 107607

Опубликована: Июль 22, 2024

Язык: Английский

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Urban resilience assessment and multi-scenario simulation: A case study of three major urban agglomerations in China

Environmental Impact Assessment Review, Год журнала: 2024, Номер 111, С. 107734 - 107734

Опубликована: Ноя. 23, 2024

Язык: Английский

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Exploring the spatial association characteristics of carbon emission efficiency in China’s construction industry: A network perspective

Energy and Buildings, Год журнала: 2025, Номер 329, С. 115289 - 115289

Опубликована: Янв. 11, 2025

Язык: Английский

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Toward a low-carbon economy: Insights from low- carbon complexity index

Environmental Impact Assessment Review, Год журнала: 2025, Номер 112, С. 107856 - 107856

Опубликована: Фев. 11, 2025

Язык: Английский

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Spatial heterogeneity in the impact of urban spatial structure on carbon emissions and storage in coastal region: a case study of Samarinda Metropolitan Area, Indonesia

Environment Development and Sustainability, Год журнала: 2025, Номер unknown

Опубликована: Март 22, 2025

Язык: Английский

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Intelligence Approach-Driven Bidirectional Analysis Framework for Efficiency Measurement and Resource Optimization of Forest Carbon Sink in China

Forests, Год журнала: 2025, Номер 16(4), С. 656 - 656

Опубликована: Апрель 9, 2025

A critical natural solution to combat global warming and reduce carbon emission is the forest sink (FCS). Owing variations in geographic location, policy formulation, economic development, Chinese provinces exhibit significant disparities efficiency (FCSE). Therefore, evaluating enhancing FCSE optimizing resource allocation have emerged as pressing issues. This study develops a pioneering analytical framework for systematic estimation optimization of FCS resources. It measures FCSE, considering both dynamic static aspects adopting spatial–temporal perspective, utilizing Malmquist Index Super Efficiency Slacks-Based Measure analyze primary factors influencing FCSE. The Autoregressive Integrated Moving Average method forecasts goals typical regions years 2030, 2045, 2060. To effectively enhance rationally optimize allocation, this constructs Inverse Data Envelopment Analysis. study’s findings indicate extremes average across regions, with mean value difference 2.2188. Technological change driver advancements achieve 2060 goal, each input indicator requires substantial increase. Drawing on insights into landscape, delineates regional offers scientific foundation policymakers devise strategies address sustainability concerns regarding FCS.

Язык: Английский

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