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

Environmental Impact Assessment Review, Journal Year: 2025, Volume and Issue: 114, P. 107895 - 107895

Published: March 5, 2025

Language: Английский

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

Energy, Journal Year: 2025, Volume and Issue: unknown, P. 134597 - 134597

Published: Jan. 1, 2025

Language: Английский

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

Heliyon, Journal Year: 2024, Volume and Issue: 10(17), P. e37001 - e37001

Published: Aug. 27, 2024

Language: Английский

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

Environmental Impact Assessment Review, Journal Year: 2024, Volume and Issue: 108, P. 107607 - 107607

Published: July 22, 2024

Language: 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, Journal Year: 2025, Volume and Issue: 329, P. 115289 - 115289

Published: Jan. 11, 2025

Language: Английский

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

Environmental Impact Assessment Review, Journal Year: 2025, Volume and Issue: 112, P. 107856 - 107856

Published: Feb. 11, 2025

Language: Английский

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

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

Published: Feb. 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.

Language: 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, Journal Year: 2025, Volume and Issue: unknown

Published: March 22, 2025

Language: Английский

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

Forests, Journal Year: 2025, Volume and Issue: 16(4), P. 656 - 656

Published: April 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.

Language: Английский

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Unveiling the Coupling Coordination and Interaction Mechanism between the Local Heat Island Effect and Urban Resilience in China

Sustainability, Journal Year: 2024, Volume and Issue: 16(6), P. 2306 - 2306

Published: March 11, 2024

Climate change and urbanization have led to the increasing prominence of urban heat islands (UHIs) today, posing a huge challenge cities. Urban resilience (UR) refers ability city or region adapt changes risks. However, influence between island effect regional is not well understood. In this study, we proposed methodological framework for unveiling coupling coordination interaction mechanism UHIs UR. This study first explored in Guangdong-Hong Kong-Macao Greater Bay Area (GBA) described creation multidimensional index system that evaluates across social, economic, ecological, engineering dimensions. Furthermore, unveiled UR through degree model, drivers was detected using geographic probe. The results showed UHI forms ring-shaped belt around entrance Pearl River Delta. GBA show significant trend expansion escalation over time. shows spatial distribution pattern high among central cities low peripheral cities, with significantly uneven development sub-resilience certain effect, improving from barely synergistic primary state. Among UHIs, population density, precipitation, average nighttime light brightness, ground-average CO2 emissions strong explanatory power variation two factors has stronger on than individual factors. purpose paper initially reveal provide theoretical basis further exploring path sustainable development.

Language: Английский

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