10.9.2.              Criteria For Assessment of Effects

  1. The process for determining the significance of effects is a two-stage process that involves defining the magnitude of the potential impacts and the sensitivity of the receptors. This section describes the criteria applied in this chapter to assign values to the magnitude of potential impacts and the sensitivity of the receptors. The terms used to define magnitude and sensitivity are based on those which are described in further detail in volume 1, chapter 6 of the Offshore EIA Report.
  2. The criteria for defining magnitude in this chapter are outlined in Table 10.18   Open ▸ . In determining magnitude within this chapter, each assessment considered the spatial extent, duration, frequency and reversibility of impact and these are outlined within the magnitude section of each impact assessment (e.g. a duration of hours or days would be considered for most receptors to be of short term duration, which is likely to result in a low magnitude of impact).

 

Table 10.18:
Definition of Terms Relating to the Magnitude of an Impact

Table 10.18: Definition of Terms Relating to the Magnitude of an Impact

 

  1. The sensitivity of marine mammal IEFs has been defined by an assessment of the ability of a receptor to adapt to a given impact, its tolerance to that impact and its ability to recover back to pre-impact conditions. Tolerance is defined as the susceptibility of a species to disturbance, damage or death, from a specific external factor. Recoverability is the ability of the same species to return to a state close to that which existed before the activity or event which caused change. It is dependent on the ability of the individuals to recover subject to the extent of disturbance/damage incurred. Information on these aspects of sensitivity of the marine mammal IEFs to given impacts has been informed by the best available evidence from scientific research on marine mammals (studies on captive animals as well as observations from field studies). In particular, evidence from field studies of marine mammals during the construction and operation of offshore wind farms (and analogous activities such oil and gas surveys) has been used to inform this assessment of effects. The review of vulnerability and recoverability of marine mammal IEFs has been combined to provide an overall evaluation of the sensitivity of a receptor to an impact as outlined in Table 10.19   Open ▸ .

 

Table 10.19:
Definition of Terms Relating to the Sensitivity of the Receptor

Table 10.19: Definition of Terms Relating to the Sensitivity of the Receptor

 

  1. The significance of the effect upon marine mammals is determined by correlating the magnitude of the impact and the sensitivity of the receptor. The particular method employed for this assessment is presented in Table 10.20   Open ▸ . As per Guidelines for Ecological Impact Assessment in the UK and Ireland (CIEEM, 2018), the significance of effect is considered with regard to impacts on the structure and function of defined sites, habitats or ecosystems and the conservation status of habitats and species (including extent, abundance and distribution). Assessment of significant effects provided in section 10.11 is quantified with reference to appropriate geographic scales (e.g. species-specific MUs and SCANS III Block R).
  2. In cases where a range is suggested for the significance of effect, there remains the possibility that this may span the significance threshold (i.e. the range is given as minor to moderate). In such cases, the final significance conclusion is based upon the author's professional judgement as to which outcome delineates the most likely effect. Where professional judgement is applied to quantify final significance from a range, the assessment will set out the factors that result in the final assessment of significance. These factors may include the likelihood that an effect will occur, data certainty and relevant information about the wider environmental context.  
  3. For the purposes of this assessment:
  • A level of residual effect of moderate or more will be considered a ‘significant’ effect in terms of the EIA Regulations; and
  • a level of residual effect of minor or less will be considered ‘not significant’ in terms of the EIA Regulations.
    1. Effects of moderate significance or above are therefore considered important in the decision-making process, whilst effects of minor significance or less warrant little, if any, weight in the decision-making process.

 

Table 10.20:
Matrix Used for the Assessment of the Significance of the Effect

Table 10.20: Matrix Used for the Assessment of the Significance of the Effect

 

10.9.3.              Designated Sites

  1. Where Natura 2000 sites (i.e. nature conservation sites in Europe designated under the Habitats or Birds Directives[5]) or sites in the UK that comprise the National Site Network (collectively termed ‘European sites’) are considered, this chapter makes an assessment of the likely significant effects in EIA terms on the qualifying interest feature(s) of these sites as described within section 10.10 of this chapter. The assessment of the potential impacts on the site itself are deferred to the RIAA for the Proposed Development; SSER, 2022d). A summary of the outcomes reported in the RIAA is provided in section 10.15 of this chapter.
  2. With respect to locally designated sites and national designations (other than European sites), where these sites fall within the boundaries of a European site and where qualifying interest features are the same, only the features of the European site have been taken forward for assessment. This is because potential impacts on the integrity and conservation status of the locally or nationally designated site are assumed to be inherent within the assessment of the features of the European site (i.e. a separate assessment for the local or national site features is not undertaken). However, where a local or nationally designated site falls outside the boundaries of a European site, but within the regional marine mammals study area, an assessment of the likely significant effects on the overall site is made in this chapter using the EIA methodology.

10.10. Measures Adopted as part of the Proposed Development

  1. As part of the Project design process, a number of measures have been proposed to reduce the potential for impacts on marine mammals (see Table 10.21   Open ▸ ). As there is a commitment to implementing these measures, they are considered inherently part of the design of the Proposed Development and have therefore been considered in the assessment presented in section 10.11 (i.e. the determination of magnitude and therefore significance assumes implementation of these measures). These measures are considered standard industry practice for this type of development.

 

Table 10.21:
Designed in Measures Adopted as Part of the Proposed Development

Table 10.21: Designed in Measures Adopted as Part of the Proposed Development

 

  1. In some cases, particularly where potentially significant effects are identified, there may be additional mitigation measures required that are not "built in" to the Project design ahead of the assessment (secondary mitigation). These are discussed in “Further mitigation and residual effect” and “Future monitoring” paragraphs in section 10.11.

10.11. Assessment of Significance

  1. The potential effects arising from the construction, operation and maintenance and decommissioning phases of the Proposed Development are listed in Table 10.16   Open ▸ along with the maximum design scenario against which each impact has been assessed.
  2. An assessment of the likely significance of the effects of the Proposed Development on marine mammal receptors caused by each identified impact is given below. As many of the impacts identified for marine mammals relate to underwater noise, the assessment has been informed by subsea noise modelling, the scope of which was agreed through the pre-application consultation ( Table 10.9   Open ▸ ). An overview of the potential effects of underwater noise on marine mammals as well as the sensitivity of marine mammal groups is provided in paragraph 69 et seq. with the approach to the noise modelling assessment given in each impact section. Further detail about noise modelling is provided in volume 3, appendix 10.1.

10.11.1.         Marine Mammals and Underwater noise

  1. Marine mammals, particularly cetaceans, are capable of generating and detecting sound (Au et al., 1974; Bailey et al., 2010) and are dependent on sound for many aspects of their lives (i.e. prey identification; predator avoidance; communication and navigation). Increases in anthropogenic noise may consequently lead to a potential effect within the marine environment (Parsons et al., 2008; Bailey et al., 2010). Richardson et al. (1995) described four zones of noise influence which vary with the distance from the source, including: audibility (sound is detected); masking (interfere with detection of sounds and communication); responsiveness (behavioural or physiological response) and injury/hearing loss (tissue damage in the ear).
  2. For this study, it is the zones of injury (auditory) and disturbance (i.e. responsiveness) that are considered in the assessment (there is insufficient scientific evidence to properly evaluate masking). The following sections summarise the relevant thresholds for onset of effects and describe the evidence base used to derive them.

Injury

  1. Auditory injury in marine mammals can occur as either a Permanent Threshold Shift (PTS), where there is no hearing recovery in the animal, or as a Temporal Threshold Shift (TTS), where an animal can recover from the tissue damage. The ‘onset’ of TTS is deemed to be where there is a temporary elevation in the hearing threshold by 6 dB and is “the minimum threshold shift clearly larger than any day to day or session to session variation in a subject’s normal hearing ability”, and which “is typically the minimum amount of threshold shift that can be differentiated in most experimental conditions” (Southall et al., 2007). Since it is considered unethical to conduct experiments measuring PTS in animals the onset of PTS was extrapolated from early experiments on TTS growth rates in chinchillas (Henderson and Hamernick, 1986) and is conservatively considered to occur where there is 40 dB of TTS (Southall et al., 2007). Whether such these shifts in hearing would lead to loss of fitness will depend on several factors including the frequency range of the shift and the duty cycle of impulsive sounds. For example, if a shift occurs within a frequency band that lays outside of the main hearing sensitivity of the receiving animal there may be a ‘notch’ in this band but potentially no effect on the animal’s ability to survive. Further discussion on the sensitivity of marine mammals to hearing shifts is provided later in this assessment.
  2. For the purposes of the assessment of injury the emphasis is on PTS as the appropriate threshold due to the irreversible nature of the effect whereas TTS is temporary and reversible. A likely response of an animal exposed to noise levels that could induce TTS is to flee the ensonified area. It is therefore considered that there is also a behavioural response (disturbance) that overlaps with potential TTS ranges, and animals exposed to noise levels that have the potential to induce TTS are likely to actively avoid hearing damage by moving away from the area. Since derived thresholds for the onset of TTS are based on the smallest measurable shift in hearing (paragraph 71), TTS thresholds are likely to be very precautionary and could result in overestimates of effect ranges. In addition, the assumptions and limitations of subsea noise modelling (e.g. equal energy rule, reduced sound levels near the surface, conservative swim speeds, and use of impulsive sound thresholds at large ranges; see paragraph 95) also lead to an overestimation of effect ranges. Notably, Hastie et al. (2019) found that during pile driving there were range dependant changes in signal characteristics with received sound losing its impulsive characteristics at ranges of several kilometres, especially beyond 10 km. For these reasons TTS is not considered a useful predictor of the impacts of underwater noise on marine mammals where ranges exceed more than c. 10 km and therefore, where this is the case (i.e. piling and UXO clearance) TTS is not included in the assessment of significance. To support this reasoning a synthesis of the use of impulsive sound thresholds at large ranges is presented volume 3, appendix 10.1. Ranges for TTS were, however, modelled for completeness for all noise-related impacts and are presented in volume 3, appendix 10.1.
  3. For marine mammals, injury thresholds are based on both linear (i.e. un-weighted) peak sound pressure levels (SPLpk) and marine mammal hearing-weighted cumulative sound exposure level (SELcum). The SELcum takes account of the cumulative sound received by an animal within the ensonified area over the entire piling sequence and is weighted by marine mammal hearing groups based on similarities in known or expected hearing capabilities (Southall et al., 2007). Marine mammal hearing groups are described in the latest guidance (Southall et al., 2019) as follows:
  • Low frequency (LF) cetaceans (i.e. marine mammal species such as baleen whales with an estimated functional hearing range between 7 Hz and 35 kHz); minke whale is the marine mammal IEF in the LF cetacean group.
  • High frequency (HF) cetaceans (i.e. marine mammal species such as dolphins, toothed whales, beaked whales and bottlenose whales with an estimated functional hearing range between 150 Hz and 160 kHz); bottlenose dolphin and white-beaked dolphin are the marine mammal IEFs in the HF cetacean group.
  • Very High frequency (VHF) cetaceans (i.e. marine mammal species such as true porpoises, Kogia, river dolphins and cephalorhynchid with an estimated functional hearing range between 275 Hz and 160 kHz); harbour porpoise is the marine mammal IEF in the HF cetacean group.
  • Pinnipeds in water (PW) (i.e. true seals with an estimated functional hearing range between 50 Hz and 86 kHz); grey seal and harbour seal are the marine mammal IEFs in the PW group.
    1. Injury criteria are proposed in Southall et al. (2019) for both impulsive and non-impulsive (continuous) sound and are summarised in Table 10.22   Open ▸ and Table 10.23   Open ▸ .

 

Table 10.22:
Summary of PTS Criteria for Impulsive and Non-Impulsive Noise

Table 10.22: Summary of PTS Criteria for Impulsive and Non-Impulsive Noise

 

Table 10.23:
Summary of TTS Criteria for Impulsive and Non-impulsive Noise

Table 10.23: Summary of TTS Criteria for Impulsive and Non-impulsive Noise

 

  1. To carry out exposure calculations (SELcum metric) the noise modelling assessment made a simplistic assumption that an animal would be exposed over a 24-hour period and that there would be no breaks in activity during this time. It was assumed that an animal would swim away from the noise source at the onset of activity at a constant rate and subsequently, conservative species specific swim speeds were incorporated into the model following agreement with statutory nature conservation bodies (swim speeds presented during Road Map Meeting 2 with no queries raised - see volume 3, appendix 10.2; Table 10.24   Open ▸ ).

 

Table 10.24:
Swim Speeds Assumed for Exposure Modelling (SELcum) for Marine Mammal IEFs

Table 10.24: Swim Speeds Assumed for Exposure Modelling (SELcum) for Marine Mammal IEFs

 

Disturbance

  1. Beyond the zone of injury, noise levels are such that they no longer result in physical injury but can result in disturbance to marine mammal behaviour. A marine mammal’s response to disturbance will depend on the individual and the context; previous experience and acclimatisation will affect whether an individual exhibits an aversive response to noise, particularly in a historically noisy area. Typically, a threshold approach has been adopted in offshore wind farm assessments in the UK to quantify the scale of the effects. For example, the United States (US) National Marine Fisheries Service (NMFS) (NMFS, 2005) define strong disturbance in all marine mammals as Level B harassment and for impulsive noise suggests a threshold of 160 dB re 1 μPa (root mean square (rms)). This threshold meets the criteria defined by JNCC (2010a) as a ‘non-trivial’ (i.e. significant) disturbance and is equivalent to the Southall et al., (2007) severity score of five or more on the behavioural response scale. Beyond this threshold the behavioural responses are likely to become less severe (e.g. minor changes in speed, direction and/or dive profile, modification of vocal behaviour and minor changes in respiratory rate (Southall et al., 2007)). The NMFS guidelines suggest a precautionary level of 140 dB re 1 μPa (rms) to indicate the onset of low-level marine mammal disturbance effects for all mammal groups for impulsive sound (NMFS, 2005), although this is not considered likely to lead to a ‘significant’ disturbance response.
  2. More recently, to illustrate the variation in behavioural responses of marine mammals, Graham et al. (2017) used empirical evidence collected during piling at the Beatrice Offshore Wind Farm (Moray Firth, Scotland) to demonstrate that the probability of occurrence of harbour porpoise (measured as porpoise positive minutes) increased exponentially moving further away from the source. The study showed a 100% probability of disturbance at an (un-weighted) SEL of 180 dB re 1 μPa2s, 50% at 155 dB re 1 μPa2s and dropping to approximately 0% at an SEL of 120 dB re 1 μPa2s. The dose response thresholds tie in with the NMFS (2005) criteria since a mild behavioural response is suggested to occur at a threshold of 140 dB re 1 μPa (rms) which is equivalent of 130 dB 1 μPa2s where a small response (c. 10% of animals) would occur according to the dose response. Dose response is an accepted approach to understanding the behavioural effects from piling and has been applied at other UK offshore wind farms (for example Seagreen (Seagreen Wind Energy Ltd, 2012) and Hornsea Project Three (GoBe, 2018a).
  3. For the assessment of piling noise, subsea noise modelling was undertaken using the dose-response approach with SELsingle-strike (SELss) contours modelled in 5 dB increments. For all other noise impacts the simple threshold approach using the NMFS criteria (NMFS, 2005) was adopted. Disturbance criteria are presented in the following table ( Table 10.31   Open ▸ ).

 

Table 10.25:
Disturbance Criteria for Marine Mammals Used in this Study

Table 10.25: Disturbance Criteria for Marine Mammals Used in this Study

 

  1. In applying these criteria it is possible to provide quantification of the magnitude of effects with respect to the spatial extent of disturbance and subsequently the number of animals potentially disturbed. There is, however, a note of caution associated with this approach. Southall et al. (2021) highlights that the challenges for developing a comprehensive set of empirically derived criteria for such a diverse group of animals are significant. Extensive data gaps have been identified (e.g. measurements of the effects of elevated noise on baleen whales) which mean that extrapolation from other species has been necessary. Sounds that disturb one species may, however, be irrelevant or inaudible to other species since there are broad differences in hearing across the frequency spectrum for different marine mammal hearing groups. Variance in responses even within a species are well documented to be context and sound-type specific (Ellison et al., 2012; ). In addition, the potential interacting and additive effects of multiple stressors (e.g. reduction in prey, noise and disturbance, contamination, etc.) is likely to influence the severity of responses (Lacy et al., 2017).
  2. For these reasons, neither a threshold approach nor a dose-response function was provided in the original guidance (Southall et al., 2007) and subsequently the recent recommendations by Southall et al. (2021) also steer away from a single overarching approach. Instead, Southall et al. (2021) proposes a framework for developing probabilistic response functions for future studies. The paper suggests different contexts for characterising marine mammal responses for both free ranging and captive animals with distinctions made by sound sources (i.e. active sonar, seismic surveys, continuous/industrial noise and pile driving). Three parallel categories have been proposed within which a severity score from an acute (discrete) exposure can be allocated:
  • survival – defence, resting, social interactions and navigation;
  • reproduction – mating and parenting behaviours; and
  • foraging – search, pursuit, capture and consumption.
    1. Even where studies have been able to assign responses to these categories based on acute exposure there is still limited understanding of how longer term (chronic) exposure could translate into population-level effects. To explore this, Southall et al. (2021) reported observations from long term whale watching studies and suggested that there were differences in the ability of marine mammals to compensate for long term disturbance which related to their breeding strategy. Mysticetes are capital breeders - accumulating energy in their feeding grounds and transferring this to calves in their breeding ground – and their ability to compensate for chronic exposure to noise will depend on a range of ecological factors. Such factors include the relative importance of the disturbed area and prey availability within their wider home range, individual exposure history, and the presence of concurrent disturbances in other areas of their range. Animals may be able to compensate for short term disturbances by feeding in other areas, for example, which would reduce the risk of longer-term population consequences. Christiansen and Lusseau (2015) studied the effect of whale watching on minke whales in Faxafoi Bay, Iceland and found no significant long-term effects on vital rates although years with low sandeel density led to increased exposure to whale watching as whales were forced to move into disturbed areas to forage. Odontocetes, however, may be more vulnerable to whale watching compared to mysticetes due to their more localised, and often, coastal home ranges. Bejder et al. (2006) documented a decrease in local abundance of bottlenose dolphin which was associated with an increase in whale watching in a tourist area compared to a control area.
    2. The marine mammals considered in this assessment vary biologically and therefore have different ecological requirements that may affect their sensitivity to disturbance. This point is illustrated by the differences between the two seal species identified as key biological receptors in the baseline. Grey seals are capital breeders (foraging to build up stored fat reserves for lactation) and often make long foraging trips from haul-outs. In contrast, harbour seals are income breeders (feeding throughout the pupping season) and make shorter foraging trips from haul-outs.
    3. In summary, Southall et al (2021) clearly highlights the caveats associated with simple, one-size-fits-all, threshold approaches that could lead to errors in disturbance assessments. Recognising this inherent uncertainty in the quantification of effects the assessment has adopted a precautionary approach at all stages of assessment including:
  • Conservative assumptions in the marine mammal baseline (e.g. use of seasonal density peaks) ( Table 10.13   Open ▸ );
  • Conservative assumptions in the maximum design scenario for the project parameters ( Table 10.16   Open ▸ ), and;
  • Conservative assumptions in the subsea noise modelling (paragraph 95).
    1. Relevant assumptions have been described throughout this chapter and demonstrate that such layering of conservatism is likely to lead to a very precautionary assessment.

10.11.2.         Assessment of Impacts and Mitigation

Injury and Disturbance from Elevated Underwater Noise During Piling

  1. Pile driving during the construction phase of the Proposed Development has the potential to result in elevated levels of underwater noise that are detectable by marine mammals above background levels, and could result in injury or behavioural effects on marine mammal IEFs. A detailed underwater noise modelling assessment has been carried out to investigate the potential for injury and behavioural effects on marine mammal IEFs as a result of piling (impulsive sounds), using the latest assessment criteria (volume 3, appendix 10.1).

Summary of Noise Modelling (Piling)

  1. With respect to the SPLpk metric, the soft start initiation is the most relevant noise source and period, as this is the range at which animals may potentially experience injury from the initial strike of the hammer, after which point it is assumed that they will move away from the noise source. Secondly, injury ranges were predicted for marine mammals exposed to impulsive noise from multiple hammer strikes over a prolonged period (i.e. using the SELcum metric); the assumption being that a marine mammal exposed to lower noise levels over a prolonged period (as it moves away from the source) could experience auditory injury. The maximum injury ranges for each species have been provided with reference to the largest impact range from the dual criteria approach as outlined in paragraph 73 et seq., and a proposed marine mammal mitigation zone has been determined on the basis of the largest range across all species (see paragraph 244 et seq.).
  2. Taking a precautionary approach, in line with SNCBs advice as discussed during Road Map Meetings (volume 3, appendix 10.3) and via the Scoping Opinion (Marine Scotland, 2022), the Subsea Noise assessment considered a range of different conversion factors (the amount of hammer energy converted into received sound by marine mammal receptors): 1% constant, 4% reducing to 0.5% and 10% reducing to 1%.
  3. A detailed study was undertaken reviewing noise modelling methodologies across different UK offshore wind farms and investigating energy conversion factors for determining sound source levels during piling. Published literature on energy conversion factors were explored together with available noise measurements taken during offshore wind farm construction and the results presented as an evidence-based, peer-reviewed report (volume 3, appendix 10.1, annex A). The study recommended that the most representative and precautionary conversion factor was 4% reducing to 0.5% as piling progresses. However, a sensitivity assessment was also undertaken to compare the results of noise modelling for different conversion factors requested by consultees (volume 3, appendix 10.1, annex B). Subsequently, considering the evidence-base and the results of the sensitivity assessment, a precautionary approach was adopted for the marine mammal assessment of effects whereby both a conversion factor of 4% reducing to 0.5% and the 1% constant throughout the piling period has been taken forward to the quantitative assessment for marine mammals. As requested by consultees, a third conversion factor of 10% reducing to 1% was also quantified with respect to effects on marine mammal receptors, although not taken forward to the assessment of effects as it was determined to be overly conservative and therefore not realistic. Volume 3, appendix 10.5 to this chapter presents a comparison of the numbers of animals affected for all three conversion factors scenarios. Additionally, as requested by consultees during Road Map Meeting 4 (volume 3, appendix 10.3), supplementary information with results for 4% constant and 10% constant conversion factor was added to the sensitivity analysis (volume 3, appendix 10.1, annex B) and conversion factor appendix (volume 3, appendix 10.5). A more detailed overview of conversion factors is provided in paragraph 103 et seq.
  4. The scenarios modelled were based on the absolute maximum hammer energy (4,000 kJ) and a realistic maximum hammer energy (3,000 kJ). The assessment has been carried out at two locations on opposite sides of the Proposed Development array area, chosen to represent extremes of location (points closest and furthest away from the shoreline; see volume 3, appendix 10.1 for more details). These are represented by the indicative wind turbine foundation locations wind turbine 40 and wind turbine 135 (used in the assessment of underwater noise impacts for all species, except bottlenose dolphin, as these represent the largest area of impact, Figure 10.10   Open ▸ ) or wind turbine 1 and wind turbine 179 (used in the assessment of underwater noise impacts for bottlenose dolphin due to proximity to the areas of high coastal density, Figure 10.13   Open ▸ ).
  5. For piling at wind turbines it is assumed that two vessels would pile concurrently, and two scenarios were modelled in this respect:
  • separation distance of 1.78 km (minimum distance between foundations) would result in the greatest potential for injury since animals could be exposed to sound from both rigs at relatively high levels; and
  • separation distance of c. 50 km (maximum separation distance between vessels) would result in the maximum area of disturbance since the overlap between disturbed areas would be smaller compared to vessels piling close together.
    1. Using the equation below (see volume 3, appendix 10.1), a broadband source level value was evaluated for the noise emitted during impact pile driving operation in each operation window.

SEL = .

  1. In this equation, β is the energy transmitted from the pile into the water column, E is the hammer energy employed in joules, C0 is the speed of sound in the water column, and ρ is the density of the water. From the SEL result calculated using the equation above, source-level spectra can also be calculated for different third octave frequency bands.
  2. Following a noise modelling workshop to test sensitivities of different scenarios, the piling campaign was developed with a low hammer energy and slow initiation phase in order to provide designed in measures to reduce the potential risk of injury. Four scenarios were investigated in the subsea noise modelling assessment and are summarised as follows:
  • wind turbine foundations (piled jacket) maximum design scenario - 24 MW wind turbines using an absolute maximum hammer energy of 4,000 kJ for the longest possible duration (up to ten hours);
  • wind turbine foundations (piled jacket) realistic design scenario - 24 MW wind turbine using a realistic average maximum hammer energy of 3,000 kJ for a realistic maximum duration (up to nine hours);
  • OSPs/Offshore convertor station platform foundations (jacket) maximum design scenario – using a maximum hammer energy of 4,000 kJ for a duration of up to eight hours; and
  • OSPs/Offshore convertor station platform foundations (jacket) realistic design scenario – using a maximum hammer energy of 3,000 kJ for a duration of up to seven hours.
    1. The marine mammal assessment was based on the maximum design scenario with piling at a maximum energy of 4,000 kJ for both wind turbine foundations and OSPs/Offshore convertor station platform foundations. However, since piling is unlikely to reach and maintain the absolute maximum hammer energy of 4,000 kJ at all locations, results for a realistic design scenario were also provided for context using an average maximum hammer energy of 3,000 kJ for both foundations. Results for all scenarios presented in paragraph 93 including details of the hammer energies, strike rate and duration, are presented in Tables 5.7 to 5.8 in volume 3, appendix 10.1. There will be a maximum of two piling events at any one time and subsea noise modelling assumed concurrent piling at two wind turbine foundations as a maximum design scenario. This was due to the distances between wind turbines (i.e. maximum spatial separation) as well as the longer duration of piling at wind turbine foundations compared to OSPs/Offshore convertor station platform foundations ( Table 10.16   Open ▸ ). Installation does not, however, preclude a concurrent piling at a wind turbine foundation and OSPs/Offshore convertor station platform foundation but this scenario is captured in the maximum design scenario for concurrent piling at two wind turbine foundations. Results presented in the chapter are therefore for concurrent piling at two wind turbine foundations and single piling at wind turbine or OSPs/Offshore convertor station platform foundations.
    2. A number of conservative assumptions were adopted in the subsea noise model that resulted in a precautionary assessment (volume 3, appendix 10.1). These are summarised here:
  • The modelling assumed that the maximum hammer energy would be reached and maintained for 195 minutes at all locations, whereas this is unlikely to be the case based on examples from other offshore wind farms (e.g. Beatrice Offshore Wind Farm where the mean actual hammer energy averages were considerably lower than the maximum design scenario assessed in the ES and only six out of 86 asset locations reached maximum hammer energy (Beatrice, 2018)).
  • The soft start procedure simulated does not allow for short pauses in piling (e.g. for realignment) and therefore the modelled SELcum is likely to be an overestimate since, in reality, these pauses will reduce the noise exposure that animals experience whilst fleeing.
  • The modelling assessment assumed that animals swim directly away from the noise source at constant and conservative average speeds based on published values ( Table 10.30   Open ▸ ). This is likely to lead to overestimates of the potential range of effect where animals exceed these speeds. For example, Otani et al. (2000) note that horizontal speed for harbour porpoise can be significantly faster than vertical speed and cite a maximum speed of 4.3 m/s. Similarly, Leatherwood et al. (1988) reported harbour porpoise swim speeds of approximately 6.2 m/s. For minke whale speeds of up to 4.2 m/s have been reported during acoustic deterrent exposure experiments on free ranging animals (McGarry et al., 2017).
  • The use of the SELcum metric is described as an equal energy rule where exposures of equal energy are assumed to produce the same noise-induced threshold shift regardless of how the energy is distributed over time. This means that for intermittent noise, such as piling, the equal-energy rule overestimates the effects since the quiet periods between noise exposures will allow some recovery of hearing compared to continuous noise.
  • The model overestimates the noise exposure an animal receives since it does not account for any time that marine mammals spend at the surface and the reduced sound levels near the surface.
  • Due to a combination of factors (e.g. dispersion of the waveform, multiple reflections from sea surface and seafloor, and molecular absorption of high frequency energy), impulsive sounds are likely to transition into non-impulsive sounds at distance from the sound source with empirical evidence suggesting such shifts in impulsivity could occur markedly within 10 km from the sound source (Hastie et al., 2019) (see volume 3, appendix 10.1). Since the precise range at which this transition occurs is unknown, noise models still adopt the impulsive thresholds at all ranges which is likely to lead to an overestimate of effect ranges at larger distances (tens of kilometres) from the sound source.
    1. A final scenario was modelled to include the use of an ADD activated for a period of 30 minutes prior to initiation of piling to illustrate the potential efficacy of using this as a secondary mitigation measure (see paragraph 244 et seq. in section 10.11). The injury scenarios with and without use of ADDs were suggested by NatureScot in representations for the 2020 Berwick Bank Scoping Opinion (MS-LOT, 2021).on 07 October 2020. Therefore, additional noise modelling was undertaken to determine whether the potential for injury to marine mammals would be reduced through the application of ADDs.
Dose response
  1. Empirical evidence from monitoring at offshore wind farms during construction suggests that pile driving is unlikely to lead to 100% avoidance of all individuals exposed, and that there will be a proportional decrease in avoidance at greater distances from the pile driving source (Brandt et al., 2011). This was demonstrated at Horns Rev Offshore Wind Farm, where 100% avoidance occurred in harbour porpoises at up to 4.8 km from the piles, whilst at greater distances (10 km plus) the proportion of animals displaced reduced to < 50% (Brandt et al., 2011). Similarly, Graham et al. (2019) used empirical evidence collected during piling at the Beatrice Offshore Wind Farm (Moray Firth, Scotland) to demonstrate that the probability of occurrence of harbour porpoise (measured as porpoise positive minutes) increased exponentially moving further away from the noise source (Figure 10.6). Importantly, Graham et al. (2019) demonstrated that the response of harbour porpoise to piling diminished over the piling phase such that, for a given received noise level or at a given distance from the source, there were more detections of animals at the last piling location compared to the first piling location (Figure 10.6).
  2. Similarly, a telemetry study undertaken by Russell et al. (2016) investigating the behaviour of tagged harbour seals during pile driving at the Lincs Offshore Wind Farm in the Wash found that there was a proportional response at different received noise levels. Dividing the study area into a 5 km x 5 km grid, the authors modelled SELss levels and matched these to corresponding densities of harbour seals in the same grids during non-piling versus piling periods to show change in usage. The study found that there was a significant decrease in usage (abundance) during piling at predicted received SEL levels of between 142 dB and 151 dB re 1 µPa2s.
  3. A dose response curve was applied to this assessment to determine the number of animals that may potentially respond behaviourally to received noise levels during piling. Unweighted SELss contours were plotted in 5 dB isopleths in decreasing increments from 180 dB to 120 dB re.1 µPa2s using the highest modelled received noise level for 4% reducing to 0.5% conversion factor and 1% constant conversion factor.
  4. To adopt the most precautionary approach, the dose response contours were plotted in Geographical Information System (GIS) for all modelled locations and the location selected for assessment was the one whereby the contours covered the greatest spatial area, thereby representing the maximum adverse scenario. The areas within each 5 dB isopleth were calculated from the spatial GIS map and a proportional expected response, derived from the dose response curve for each isopleth area, was used to calculate the number of animals potentially disturbed. These numbers were subsequently summed across all isopleths to estimate the total number of animals disturbed during piling. The number of animals predicted to respond was based on species specific densities as agreed with statutory consultees ( Table 10.13   Open ▸ ).
  5. For harbour porpoise the dose-response curve was applied from the first location modelled as shown by Graham et al. (2017) where the probability of response approaches zero at c. 120 dB SELss. In the absence of species-specific data for other cetacean species the same dose response curve was assumed to apply to all cetacean IEFs in this assessment (Figure 10.6).

 

Figure 10.6: The Probability of a Harbour Porpoise Response (24 h) in Relation to the Partial Contribution of Unweighted Received Single-Pulse SEL for the First Location Piled (Purple Line), the Middle Location (Teal Line) and the Final Location Piled (Grey Line). Reproduced with Permission from Graham et al. (2019)

 

  1. For harbour seal and grey seal the most appropriate dose response curve was derived from the Russell et al. (2017) study which has been previously applied to other Offshore Wind Farm assessments in the UK (e.g. Hornsea Project Three (GoBe, 2018a) and Seagreen optimised design (Seagreen Wind Energy, 2018)). In the Russell et al. (2017) study the highest received level at which a response was detected was at 135 dB SELss with a zero probability of response measured at 130 dB SELss ( Figure 10.7   Open ▸ ).

Figure 10.7:
The Predicted Percentage Change in Seal Usage During Piling (Compared to Non-piling Periods) in Relation to Unweighted SEL at 5 dB Increments. Source: Russell et al. (2017)

Figure 10.7: The Predicted Percentage Change in Seal Usage During Piling (Compared to Non-piling Periods) in Relation to Unweighted SEL at 5 dB Increments. Source: Russell et al. (2017)

Conversion Factors
  1. At the request of MS-LOT, a range of conversion factors – 1% constant, 4% reducing to 0.5% and 10% reducing to 1% - have been modelled with respect to how much of the hammer energy is converted into received sound. Based on a comprehensive, peer-reviewed study, it was recommended that 4% reducing to 0.5% is most representative of a precautionary estimate of the conversion factor for the type of hammer to be used at the Proposed Development. A summary of the reasoning behind this conclusion is provided in paragraph 104 et seq. with full detail given in the Subsea Noise Technical Report (volume 3, appendix 10.1, annex A).
  2. The study on conversion factors (volume 3, appendix 10.1, annex A) found that theoretical values for representative conversion factors were likely to reach an upper limit of 1.5% for an above water hammer throughout a piling sequence with a conversion factor of 1% being typical throughout the majority of the piling (as estimated from in field measurements e.g. Dahl and Reinhall, 2013). Several of the offshore wind farms in Scotland assessed impacts on marine mammals based on subsea noise modelling using 0.5% constant conversion factor (Inch Cape Offshore Ltd, 2018; Moray West, 2018). However, the 1% constant conversion factor is deemed representative of the theoretical average based on field measurements and was also included more recently alongside a 0.5% conversion factor for the Seagreen Offshore Wind Farm (revised design) in the outer Firth of Forth (although noting it was presented for context only with 0.5% conversion factor adopted in the main assessment) (Seagreen, 2018).
  3. There is, however, likely to be differences in conversion factors depending on the type of hammer used. The use of a submersible hammer, as opposed to an above water hammer, can result in a conversion factor that varies with pile penetration depth. Since the piling at the Proposed Development is likely to involve a partially submersible hammer, the literature review explored the conversion factors that may be applicable in this situation. A key study cited in the review was by Lippert et al., (2017) where both modelled and measured data were used to estimate a conversion factor of between 2% and 0.5% for a partially submersible hammer. In this study the modelled and measured data were strongly correlated suggesting that the estimated conversion factors were very representative. Nevertheless, it was recognised that for the Lippert et al. (2017) study a significant proportion of the pile was above water at the start of the piling sequence which could have reduced the apparent conversion factor compared to a situation where the pile starts just above the water line. Assuming that the energy radiated into the water is approximately proportional to the length of pile which is exposed to the water then the conversion factor at the start of piling from the Lippert study can be estimated to be approximately 3.5% (see volume 3, appendix 10.1, annex A). Thus, the 4% conversion factor requested by SNCBs is considered to be close to, but more precautionary, than the empirically derived value based on the Lippert et al., (2017) study.
  4. The study on conversion factors (volume 3, appendix 10.1, annex A) found that a conversion factor of 10% was likely to be over precautionary and therefore more likely to lead to an overestimate of effect ranges, particularly considering the transition from impulsive to continuous noise over distance from the source. The 10% reducing conversion factor was based upon a study conducted at the Beatrice Offshore Wind Farm for a fully submersible hammer which suggested that higher conversion factors were found for longer exposed lengths of pile towards the start of the piling and reduced to 1% as the pile penetrated further into the seabed (Thompson et al., 2020). However, there were large discrepancies between the noise modelling and real-world propagation particularly at further distances from the pile. By reanalysing the data from the Beatrice Offshore Wind Farm, it was determined that, at closer distances the modelled and measured levels were closer in value and suggested a conversion factor closer to 5% rather than the 10% cited in the study (see section 3.3.2 of volume 3, appendix 10.1, annex A for more details)
  5. Acknowledging that the conversion factor of 10% reducing to 1% as unrealistic and likely to be over precautionary, the sensitivity assessment found that for the peak pressure metric (SPLpk) the maximum injury ranges for all species were derived using the 1% conversion factor as opposed to the 4% reducing to 0.5% conversion factor. This is because the higher conversion rate for the 4% reducing to 0.5% conversion factor occurs when the hammer is at its lowest energy at the start of the piling sequence, so the highest estimated SPLpk levels are later in the piling sequence once the conversion factor has reduced. In contrast, with a constant 1% conversion factor throughout the piling sequence, the SPLpk ranges increase throughout the piling sequence with increasing hammer energy.
  6. As previously, discounting the conversion factor of 10% reducing to 1% as over-precautionary for the cumulative exposure metric (SELcum), the maximum injury ranges for all species were derived using both the 4% reducing to 0.5% conversion factor and 1% constant conversion factor. Since the noise modelling for injury adopts a dual metric approach using both SPLpk and SELcum the most precautionary approach was to assess the greatest injury range using either metric and considering both conversion factors. With the exception of minke whale, the maximum injury ranges for all species were predicted using the 1% constant conversion factor throughout the piling period and were based on the SPLpk metric. For minke whale (a low frequency cetacean) the maximum injury range was predicted using the SELcum metric on the basis of the 4% reducing to 0.5% conversion factor. The number of animals affected were subsequently estimated on this basis and differs by species hearing group. This was to ensure that for mitigation purposes the most precautionary approach was adopted. The topic of different hearing frequencies is covered in volume 3, appendix 10.2.
  7. In terms of behavioural effects, the 1% constant conversion factor was found to result in the highest SELss at any point over the piling sequence compared to the 4% reducing to 0.5% conversion factor and therefore resulted in the largest potential effect area ( Figure 10.8   Open ▸ ). The reason for this is that the maximum SEL for the 1% constant scenario is at the end of the piling sequence, which is when the hammer energy is maximum (i.e. up to 4,000 kJ) because for a constant conversion factor of 1% the SEL will increase with increasing hammer energy ( Figure 10.9   Open ▸ ). This is not the case for the 4% reducing to 0.5% scenario as in this instance, the highest SEL occurs during initiation as the 4% conversion factor at this point leads to a higher SELss than at any other point during the piling sequence ( Figure 10.9   Open ▸ ). The SELss is an unweighted metric and therefore there is no difference in modelled contours by marine mammal hearing group.

Figure 10.8:
An Example of Unweighted SELss Contours due to Single Piling with 4,000 kJ Hammer Energy at 1% Constant Conversion Factor and 4% Reducing to 0.5% Conversion Factor

Figure 10.8: An Example of Unweighted SELss Contours due to Single Piling with 4,000 kJ Hammer Energy at 1% Constant Conversion Factor and 4% Reducing to 0.5% Conversion Factor

Figure 10.9:
SELss Throughout the Piling for 1% Constant Conversion Factor, 4% Reducing to 0.5% Conversion Factor and 10% Reducing to 1% Conversion Factor

Figure 10.9: SELss Throughout the Piling for 1% Constant Conversion Factor, 4% Reducing to 0.5% Conversion Factor and 10% Reducing to 1% Conversion Factor

 

  1. Although not considered as part of the assessment of effects for the reasons described above (paragraph 106), for completeness the dose-response contours were also plotted for the 10% reducing to 1% conversion factor to allow estimates of the numbers of animals potentially disturbed by this scenario. The results are presented in volume 3, appendix 10.5.