Environmental Issues for Offshore Renewable Energy

Wolf, Judith; Dominicis, Michela De; Lewis, Matt; Neill, Simon P.; Murray, Rory O’Hara; Scott, Beth E.; Zampollo, Arianna; Chapman, J. D.; Declerck, Morgane

doi:10.1016/b978-0-12-819727-1.00036-4

Cited by 5 publications

(3 citation statements)

References 172 publications

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“…A step-change is occurring in the use of coastal seas globally, specifically by the addition of large-scale ORE developments, to combat climate change and achieve sustainable affordable green energy. Considering the relationship between species distribution, population dynamics and physical habitats, and to ensure the compatibility of ORE developments with other marine management sectors, it is evident that a holistic approach, to account for cumulative impacts of ORE at an ecosystem scale, is an essential goal to address baselines for consenting and decision processes (Wolf et al 2021). Using ecosystem models at ecologically meaningful scales to understand how ecosystems respond to multiple stressors will support the cumulative assessment process and the inherent multi-objective decision process of integrating ORE into the marine environment (Piroddi et al 2015).…”

Section: Discussionmentioning

confidence: 99%

An ecosystem-based natural capital evaluation framework that combines environmental and socio-economic implications of offshore renewable energy developments

et al. 2022

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There is about to be an abrupt step-change in the use of coastal seas around the globe, specifically by the addition of large-scale offshore renewable energy developments to combat climate change. Developing this sustainable energy supply will require trade-offs between both direct and indirect environmental effects, as well as spatial conflicts with marine uses like shipping, fishing, and recreation. However, the nexus between drivers, such as changes in the bio-physical environment from the introduction of structures and extraction of energy, and the consequent impacts on ecosystem services delivery and natural capital assets is poorly understood and rarely considered through a whole ecosystem perspective. Future marine planning needs to assess these changes as part of national policy level assessments but also to inform practitioners about the benefits and trade-offs between different uses of natural resources when making decisions to balance environmental and energy sustainability and socio-economic impacts. To address this shortfall, we propose an ecosystem-based natural capital evaluation framework that builds on a dynamic Bayesian modelling approach which accounts for the multiplicity of interactions between physical (e.g., bottom temperature), biological (e.g., net primary production) indicators and anthropogenic marine use (i.e., fishing) and their changes across space and over time. The proposed assessment framework measures ecosystem change, changes in ecosystem goods and services and changes in socio-economic value in response to offshore renewable energy deployment scenarios as well as climate change, to provide objective information for decision processes seeking to integrate new uses into our marine ecosystems. Such a framework has the potential of exploring the likely outcomes in the same metrics (both ecological and socio-economic) from alternative management and climate scenarios, such that objective judgements and decisions can be made, as to how to balance the benefits and trade-offs between a range of marine uses to deliver long-term environmental sustainability, economic benefits, and social welfare.

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Section: Discussionmentioning

confidence: 99%

An ecosystem-based natural capital evaluation framework that combines environmental and socio-economic implications of offshore renewable energy developments

et al. 2022

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“…The UK created MEDIN, an open-access metadata portal, gathering marine datasets on geophysics, primary producers, fish and fisheries activities, top predators from the MSFD, industrial actors, decisionmaking bodies, stakeholders and academics. Although MARLIN and MEDIN share similar objectives, some sectors remain unwilling to upload their data on MEDIN due to commercial data sensitivity concerns, but none yet contain outputs from ecosystem models (Wolf et al, 2022).…”

Section: Tool 3: a Holistic Databasementioning

confidence: 99%

Cumulative Effects of Offshore Renewables: From Pragmatic Policies to Holistic Marine Spatial Planning Tools

Declerck¹,

Trifonova²,

Hartley³

et al. 2022

SSRN Journal

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“…In regions where fish stocks are managed or listed for special protections, regulators require monitoring for potential effects for fish as a condition for licensing tidal and other marine renewable energy (MRE) projects. Depending on local flow and bathymetric characteristics in the nearshore environments, the current flows suitable for tidal energy development can be turbulent (Cornett et al, 2015;Melvin and Cochrane, 2015;Williamson et al, 2017;Perez et al, 2021;Wolf et al, 2022), entraining persistent and deeply penetrating air into the water column. An efficient backscatterer of sound, the presence of air in the water column complicates the post-processing activities for data collected with acoustic instruments.…”

Section: Introductionmentioning

confidence: 99%

Echofilter: A Deep Learning Segmention Model Improves the Automation, Standardization, and Timeliness for Post-Processing Echosounder Data in Tidal Energy Streams

Lowe

McGarry²,

Douglas³

et al. 2022

Front. Mar. Sci.

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Understanding the abundance and distribution of fish in tidal energy streams is important for assessing the risks presented by the introduction of tidal energy devices into the habitat. However, tidal current flows suitable for tidal energy development are often highly turbulent and entrain air into the water, complicating the interpretation of echosounder data. The portion of the water column contaminated by returns from entrained air must be excluded from data used for biological analyses. Application of a single algorithm to identify the depth-of-penetration of entrained air is insufficient for a boundary that is discontinuous, depth-dynamic, porous, and varies with tidal flow speed.Using a case study at a tidal energy demonstration site in the Bay of Fundy, we describe the development and application of deep machine learning models with a U-Net based architecture that produce a pronounced and substantial improvement in the automated detection of the extent to which entrained air has penetrated the water column.Our model, Echofilter, was found to be highly responsive to the dynamic range of turbulence conditions and sensitive to the fine-scale nuances in the boundary position, producing an entrained-air boundary line with an average error of 0.33 m on mobile downfacing and 0.5–1.0 m on stationary upfacing data, less than half that of existing algorithmic solutions. The model’s overall annotations had a high level of agreement with the human segmentation, with an intersection-over-union score of 99% for mobile downfacing recordings and 92–95% for stationary upfacing recordings. This resulted in a 50% reduction in the time required for manual edits when compared to the time required to manually edit the line placement produced by the currently available algorithms. Because of the improved initial automated placement, the implementation of the models permits an increase in the standardization and repeatability of line placement.

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Environmental Issues for Offshore Renewable Energy

Cited by 5 publications

References 172 publications

An ecosystem-based natural capital evaluation framework that combines environmental and socio-economic implications of offshore renewable energy developments

An ecosystem-based natural capital evaluation framework that combines environmental and socio-economic implications of offshore renewable energy developments

Cumulative Effects of Offshore Renewables: From Pragmatic Policies to Holistic Marine Spatial Planning Tools

Echofilter: A Deep Learning Segmention Model Improves the Automation, Standardization, and Timeliness for Post-Processing Echosounder Data in Tidal Energy Streams

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