Wind turbine fires pose a significant global problem, leading to substantial financial losses. However, due to limited open discussions and lax regulations in the wind power industry, progress in addressing this issue has been hindered. This study aims to shed light on the fire risks associated with wind turbine nacelles and blades, while also exploring preventive measures and the latest fire detection and extinguishing technologies. The research conducted in this study involves a comprehensive investigation of various case studies, utilizing causal examination to identify common failure forms and their roles in fire incidents. Additionally, typical hazards, with a focus on fire incidents, in wind turbines are diagnosed. The primary causes of these fires were determined to be lightning strikes and hydraulic faults, often exacerbated by the presence of combustible materials. To conclude, the study includes a survey that encompasses education, knowledge analysis, and real-life accident experiences to assess fire risks and prevention measures in wind turbines. The participation of experts from wind farms, including those from the People's Republic of Bangladesh and other countries, adds valuable insights. The findings from this study serve as a crucial resource for enhancing safety standards and mitigating fire incidents within the wind power industry.
Plastic waste and its environmental hazards have been attracting public attention as a global sustainability issue. This study builds a neural network model to forecast plastic waste generation of the EU-27 in 2030 and evaluates how the interventions could mitigate the adverse impact of plastic waste on the environment. The black-box model is interpreted using SHapley Additive exPlanations (SHAP) for managerial insights. The dependence on predictors (i.e., energy consumption, circular material use rate, economic complexity index, population, and real gross domestic product) and their interactions are discussed. The projected plastic waste generation of the EU-27 is estimated to reach 17 Mt/y in 2030. With an EU targeted recycling rate (55%) in 2030, the environmental impacts would still be higher than in 2018, especially global warming potential and plastic marine pollution. This result highlights the importance of plastic waste reduction, especially for the clustering algorithm-based grouped countries with a high amount of untreated plastic waste per capita. Compared to the other assessed scenarios, Scenario 4 with waste reduction (50% recycling, 47.6% energy recovery, 2.4% landfill) shows the lowest impact in acidification, eutrophication, marine aquatic toxicity, plastic marine pollution, and abiotic depletion. However, the global warming potential (8.78 Gt CO2eq) is higher than that in 2018, while Scenario 3 (55% recycling, 42.6% energy recovery, 2.4% landfill) is better in this aspect than Scenario 4. This comprehensive analysis provides pertinent insights into policy interventions towards environmental hazard mitigation.