scholarly journals Monitoring of Caged Bluefin Tuna Reactions to Ship and Offshore Wind Farm Operational Noises

Sensors ◽  
2021 ◽  
Vol 21 (21) ◽  
pp. 6998
Author(s):  
Vicente Puig-Pons ◽  
Ester Soliveres ◽  
Isabel Pérez-Arjona ◽  
Victor Espinosa ◽  
Pedro Poveda-Martínez ◽  
...  

Underwater noise has been identified as a relevant pollution affecting marine ecosystems in different ways. Despite the numerous studies performed over the last few decades regarding the adverse effect of underwater noise on marine life, a lack of knowledge and methodological procedures still exists, and results are often tentative or qualitative. A monitoring methodology for the behavioral response of bluefin tuna (Thunnus thynnus) when exposed to ship and wind turbine operational noises was implemented and tested in a fixed commercial tuna feeding cage in the Mediterranean sea. Fish behavior was continuously monitored, combining synchronized echosounder and video recording systems. Automatic information extracted from acoustical echograms was used to describe tuna reaction to noise in terms of average depth and vertical dimensions of the school and the indicators of swimming speed and tilt direction. Video recordings allowed us to detect changes in swimming patterns. Different kinds of stimuli were considered during bluefin tuna cage monitoring, such as noise generated by feeding boats, wind farm operational noise, and other synthetic signals projected in the medium using a broadband underwater projector. The monitoring system design was revealed as a successful methodological approach to record and quantify reactions to noise. The obtained results suggested that the observed reactions presented a strong relationship with insonification pressure level and time. Behavioral changes associated with noise are difficult to observe, especially in semi-free conditions; thus, the presented approach offered the opportunity to link anthropogenic activity with possible effects on a given marine species, suggesting the possibility of achieving a more realistic framework to assess the impacts of underwater noise on marine animals.

Author(s):  
Chih-Hao Wu ◽  
Wei-Chieh Wang ◽  
Yao-Sung Hsu ◽  
Dai-Hua Liu ◽  
Chi-Fang Chen ◽  
...  

2010 ◽  
Vol 127 (3) ◽  
pp. 1755-1755
Author(s):  
James H. Miller ◽  
Gopu R. Potty ◽  
Kathleen Vigness Raposa ◽  
David Casagrande ◽  
Lisa A. Miller ◽  
...  

Author(s):  
Daniel Buhagiar ◽  
Tonio Sant

Offshore wind farms are presently facing numerous technical challenges that are affecting their viability. High failure rates of expensive nacelle-based electronics and gearboxes are particularly problematic. On-going research is investigating the possibility of shifting to a seawater-based hydraulic power transmission, whereby wind turbines pressurise seawater that is transmitted across a high-pressure pipeline network. A 9-turbine hydraulic wind farm with three different configurations is simulated in the present work and a previously developed method for open-loop pressure control of a single turbine has been adapted for this multiple-turbine scenario. A conceptual quasi-constant-pressure accumulator is also included in the model. This system is directly integrated within each hydraulic wind turbine and it allows the output power from the wind farm to be scheduled on an hourly basis. The shift in control methodology when integrating storage is illustrated in the present work. Simulation results indicate a strong relationship between hydraulic performance attributes and the specific wind turbine array layout. The beneficial effects of storage can also be observed, particularly in smoothing the output power and rendering it more useable. Finally, the energy yields from 24-hour simulations of the 9-turbine wind farms are calculated. Integrated storage leads to a slight increase in yield since it eliminates bursts of high flow, which induce higher frictional losses in the pipeline network.


2020 ◽  
Vol 12 (22) ◽  
pp. 9352
Author(s):  
Andrea E. Copping ◽  
Alicia M. Gorton ◽  
Roel May ◽  
Finlay Bennet ◽  
Elise DeGeorge ◽  
...  

Acceptance of wind energy development is challenged by stakeholders’ concerns about potential effects on the environment, specifically on wildlife, such as birds, bats, and (for offshore wind) marine animals, and the habitats that support them. Communities near wind energy developments are also concerned with social and economic impacts, as well as impacts on aesthetics, historical sites, and recreation and tourism. Lack of a systematic, widely accepted, and balanced approach for measuring the potential damage to wildlife, habitats, and communities continues to leave wind developers, regulators, and other stakeholders in an uncertain position. This paper explores ecological risk-based management (RBM) in wind energy development for land-based and offshore wind installations. This paper provides a framework for the adaptation of ecosystem-based management to wind energy development and examines that framework through a series of case studies and best management practices for applying risk-based principles to wind energy. Ten case studies indicate that wind farm monitoring is often driven by regulatory requirements that may not be underpinned by scientific questions. While each case applies principles of adaptive management, there is room for improvement in applying scientific principles to the data collection and analysis. Challenges and constraints for wind farm development to meet RBM framework criteria include collecting sufficient baseline and monitoring data year-round, engaging stakeholder facilitators, and bringing together large and diverse scientific teams. The RBM framework approach may provide insights for improved siting and consenting/permitting processes for regulators and their advisors, particularly in those nations where wind energy is still in the early development stages on land or at sea.


Energies ◽  
2020 ◽  
Vol 13 (12) ◽  
pp. 3037 ◽  
Author(s):  
Apostolos Tsouvalas

The growing demand for renewable energy supply stimulates a drastic increase in the deployment rate of offshore wind energy. Offshore wind power generators are usually supported by large foundation piles that are driven into the seabed with hydraulic impact hammers or vibratory devices. The pile installation process, which is key to the construction of every new wind farm, is hindered by a serious by-product: the underwater noise pollution. This paper presents a comprehensive review of the state-of-the-art computational methods to predict the underwater noise emission by the installation of foundation piles offshore including the available noise mitigation strategies. Future challenges in the field are identified under the prism of the ever-increasing size of wind turbines and the emerging pile driving technologies.


2021 ◽  
Author(s):  
Yi Liang ◽  
Zhenyi Ou ◽  
Weiqi Zhong ◽  
Ke Qu ◽  
Mingxia Hu ◽  
...  

2022 ◽  
Vol 8 ◽  
Author(s):  
Dong-Gyun Han ◽  
Jee Woong Choi

Offshore wind power plants are under construction worldwide, and concerns about the adverse effects of underwater noise generated during their construction on the marine environment are increasing. As part of an environmental impact assessment, underwater noise generated by impact pile driving was measured during the construction of an offshore wind farm off the southwest coast of Korea. The sound exposure levels of impact pile driving noise were estimated as a function of distance and compared with those predicted by a damped cylindrical spreading model and broadband parabolic equation simulation. Source level at 1 m was estimated to be in a range of 183–184 dB re 1μPa2s in the sound exposure level based on the model predictions and it tended to decrease by 21log⁡r as the distance increased. Finally, the spatial distribution of impact pile driving noise was predicted. This result, if combined with noise-induced damage thresholds for marine life, may be used to assess the effects of wind farm construction on marine ecosystems.


2019 ◽  
Vol 139 (4) ◽  
pp. 259-268
Author(s):  
Effat Jahan ◽  
Md. Rifat Hazari ◽  
Mohammad Abdul Mannan ◽  
Atsushi Umemura ◽  
Rion Takahashi ◽  
...  

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