Опубликована: Янв. 1, 2024
Язык: Английский
Journal of Environmental Management, Год журнала: 2025, Номер 376, С. 124517 - 124517
Опубликована: Фев. 18, 2025
Язык: Английский
Процитировано
4
Environmental Impact Assessment Review, Год журнала: 2024, Номер 105, С. 107422 - 107422
Опубликована: Янв. 20, 2024
Язык: Английский
Процитировано
14
The Science of The Total Environment, Год журнала: 2024, Номер 934, С. 173199 - 173199
Опубликована: Май 14, 2024
Язык: Английский
Процитировано
4
Maritime Policy & Management, Год журнала: 2025, Номер unknown, С. 1 - 24
Опубликована: Янв. 19, 2025
Ports play a crucial role in facilitating global trade and logistics, serving as vital hubs that connect countries continents. However, they are susceptible to disruptions disasters due their natural characteristics, while resilience is essential for maintaining regular operations, especially the face of disruptions. From perspective inputs outputs, this study evaluates nine major Chinese ports from 2011 2021, using super-efficiency slacks-based measure network data envelopment analysis (SBM-NDEA). This approach extends beyond evaluating port's internal capacities, incorporating urban economic factors critical ensuring long-term resilience. The novel method assessing port its positive ramifications offers clearer understanding specific stages requiring improvement, thereby enhancing overall ports. Specifically, three considered: absorptive, adaptive, restorative. results reveal different exhibits distinct trends above stages. Shenzhen Port demonstrates superior performance both absorptive adaptive stages, Rizhao excels restorative stage. research contributes advancing academic knowledge industry practices by offering new insights, methodologies, practical implications
Язык: Английский
Процитировано
0
International Journal of Disaster Risk Reduction, Год журнала: 2025, Номер unknown, С. 105257 - 105257
Опубликована: Янв. 1, 2025
Язык: Английский
Процитировано
0
Sustainable Development, Год журнала: 2025, Номер unknown
Опубликована: Фев. 27, 2025
ABSTRACT Greenhouse gas (GHG) emissions continue to affect the climate; extreme weather events frequently exacerbate global climate risks, leading significant reflections on change and sustainable development due immense losses from natural disasters. This paper develops a dynamic three‐stage network directional distance function (DDF) data envelopment analysis (DEA) model. The model is used evaluate efficiency of China's Sustainable Development Goal 13 (SDG13) assess across three stages: greenhouse emissions, change, disaster management. innovation this that, compared previous studies, selected variables align more closely with targets SDG13, systematic. Additionally, based performance, provinces are categorized into four warning levels, comparative conducted by grouping 30 seven geographic regions. approach offers robust foundation for policymaker decision‐making. Results indicate that SDG13 concerning; GHG perform best, followed management being weakest. Regionally, North East China excel in green low‐carbon management, while Northwest demonstrates poorest performance. evaluation Total‐Factor Efficiency key indicators revealed CO 2 PM 2.5 emission efficiencies relatively acceptable. However, reflecting capacity respond disasters, such as population affected economic loss, demonstrate vulnerabilities.
Язык: Английский
Процитировано
0
Energy, Год журнала: 2025, Номер unknown, С. 136098 - 136098
Опубликована: Апрель 1, 2025
Язык: Английский
Процитировано
0
Forests, Год журнала: 2025, Номер 16(5), С. 843 - 843
Опубликована: Май 19, 2025
Under accelerated global warming, frequent droughts pose mounting threats to vegetation productivity, yet the spatiotemporal patterns and primary controls of drought resilience (DR) in China remain insufficiently quantified. This study aimed characterize DR trends across Köppen–Geiger climate zones from 2001 2020 identify dominant drivers their interactions. We constructed a hazard–exposure–adaptability framework, combining multi-source satellite observations station data. A Bayesian-optimized Light Gradient Boosting Machine (LightGBM, version 4.3.0) model was trained under five-fold cross-validation. Shapley Additive exPlanations (SHAP) analysis decomposed each driver’s main interaction effects on DR. The results indicated that better tropical regions, whereas arid polar regions require more attention. From 2020, 45.3% China’s land area saw increases, while 36.4% declined. key influencing were temperature, sunlight hours, potential evapotranspiration, precipitation. Notably, an increase hours often accompanied by decrease precipitation, resulting suboptimal China. When normalized precipitation fell within range 0.12 0.65, elevated temperature exhibited inhibitory effect Overall, this established assessment elucidated its dynamics, revealed driver interactions, offering timely insights for ecosystem research management face change.
Язык: Английский
Процитировано
0
Natural Hazards, Год журнала: 2024, Номер 120(7), С. 5987 - 6009
Опубликована: Фев. 22, 2024
Язык: Английский
Процитировано
2
Heliyon, Год журнала: 2024, Номер 10(19), С. e38533 - e38533
Опубликована: Сен. 26, 2024
Язык: Английский
Процитировано
2