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Offshore wind farms are projected to impact primary production and bottom water deoxygenation in the North Sea

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The wind wake effect of offshore wind farms affects the hydrodynamical conditions in the ocean, which has been hypothesized to impact marine primary production. So far only little is known about the ecosystem response to wind wakes under the premisses of large offshore wind farm clusters. Here we show, via numerical modeling, that the associated wind wakes in the North Sea provoke large-scale changes in annual primary production with local changes of up to ±10% not only at the offshore wind farm clusters, but also distributed over a wider region. The model also projects an increase in sediment carbon in deeper areas of the southern North Sea due to reduced current velocities, and decreased dissolved oxygen inside an area with already low oxygen concentration. Our results provide evidence that the ongoing offshore wind farm developments can have a substantial impact on the structuring of coastal marine ecosystems on basin scales.
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ARTICLE
Offshore wind farms are projected to impact
primary production and bottom water
deoxygenation in the North Sea
Ute Daewel 1, Naveed Akhtar 1, Nils Christiansen1& Corinna Schrum1,2
The wind wake effect of offshore wind farms affects the hydrodynamical conditions in the
ocean, which has been hypothesized to impact marine primary production. So far only little is
known about the ecosystem response to wind wakes under the premisses of large offshore
wind farm clusters. Here we show, via numerical modeling, that the associated wind wakes in
the North Sea provoke large-scale changes in annual primary production with local changes
of up to ±10% not only at the offshore wind farm clusters, but also distributed over a wider
region. The model also projects an increase in sediment carbon in deeper areas of the
southern North Sea due to reduced current velocities, and decreased dissolved oxygen inside
an area with already low oxygen concentration. Our results provide evidence that the ongoing
offshore wind farm developments can have a substantial impact on the structuring of coastal
marine ecosystems on basin scales.
https://doi.org/10.1038/s43247-022-00625-0 OPEN
1Institute for Coastal Systems - Analysis and Modelling, Helmholtz-Zentrum Hereon, Max-Planck-Str. 1, D-21502 Geesthacht, Germany. 2Institute of
Oceanography, CEN, Universität Hamburg, Hamburg, Germany. email: ute.daewel@hereon.de
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The North Sea is a shallow shelf sea system in which the
interactions between bathymetry, tides and a strong
freshwater supply at the continental coast foster a complex
frontal system, which separates well-mixed coastal waters from
seasonally stratied deeper areas. The shallow coastal areas and
sandbanks combined with stable wind resources make the North
Sea an ideal area for renewable energy production and have made
the North Sea a global hotspot for offshore wind energy
production1. The recently negotiated European Green Deal to
support the European target to phase out dependence on fossil
fuels will further accelerate the development of offshore renew-
able energy2and a substantial increase of installed capacity
(212 GW by 20503) is planned in the North Sea as a consequence
to Europe´s strategy to be carbon neutral by 2050. The size and
magnitude of the already installed (28 GW European offshore
wind farm capacity by 20214) and the planned offshore wind
farm (OWF) installation5has raised concerns about their impact
on the marine environment6and scientic efforts have increased
to understand and assess the implications of these large structures
for the marine system. In addition to impacts on the regional
atmosphere7, multiple physical8,9, biological6,10 and chemical11
impacts on the marine system have been identied. The under-
water structures, such as foundations and piles may cause tur-
bulent current wakes, which impact circulation, stratication,
mixing, and sediment resuspension1214. Most studies conclude
that the direct hydrodynamic consequences of the windfarm
structures are mainly restricted to the area within the wind
farms15,16. However, some speculate also, that the cumulative
impacts of an increasing number of offshore installations might
result in substantial impacts on the larger scale stratication13,17.
Larger scale effects of offshore wind energy production, well
beyond the wind farm areas, are introduced to the atmosphere by
infrastructures above the sea level and the energy extraction
itself18. Atmospheric wakes appearing in the lee of wind farms
extend on scales up to 65 km and beyond, depending on atmo-
spheric stability, with a wind speed reduction of up to 43% inside
the wakes18 leading to upwelling and downwelling dipoles in the
ocean beneath19. Previous modeling studies9,19 showed that these
dipoles are associated with vertical velocities in the order of
meters per day and consequent changes in mixing, stratication,
temperature, and salinity. Recently, Floeter et al.20 provided
empirical evidence for the existence of these upwelling/down-
welling dipoles showing distinct structural changes in mixed layer
depth and potential energy anomaly inside the wind wake area of
OWFs in the summer stratied area of the southern North Sea. A
rst assessment of the large-scale integrated impact of atmo-
spheric wakes from already existing OWFs on the hydrography of
the southern North Sea revealed the emergence of large-scale
oceanic structures with respect to currents, sea surface elevation,
and stratication8.
For the marine ecosystem the effects of OWFs might or might
not be severe, positive or negative. As van Berkel et al.16 explain,
the evaluation of ecosystem effects through BACI (before-after-
control-impact) surveys are challenging due to the spatio-
temporal variability of the natural system, regional and global
trends, as well as other anthropogenic impacts, such as changes
in shing effort, eutrophication, and noise levels, while the focus
of investigations is on selected sh and seabird species. In the
literature we nd, so far, a number of studies related to immediate
impacts of OWFs on marine fauna6, such as the articial reefs
effect21,22 or the impacts of acoustic disturbances on sh and
marine mammals23,24. Indirect impacts are, however, likely even
more important, more complex, and more difcult to investigate.
This includes consequences of restricted sheries inside the
OWFs25 as well as the impacts of the above-described modulation
of the physical environment on the structuring of the pelagic10
and benthic22 ecosystem. It is well known that modications in
mixing and stratication also impacts nutrient availability in the
euphotic zone26,27, however, the picture of the ecosystem impacts
is less clear for some obvious reasons: (i) The changes in nutrient
concentration would start a cause-effect chain that translates into
changes in primary production and effectively alters the food
chain; (ii) In a dynamic system like the southern North Sea,
which is characterized by strong tidal and residual currents,
changes in the biotic and abiotic environment are exposed to
advective processes; (iii) The expected changes depend strongly
on the prevailing hydrodynamic conditions, which makes it dif-
cult to disentangle natural from inicted changes. Other than a
high-density suite of physical and biological observations,
numerical modeling studies are the only means to build BACI
studies as scenarios with and without the disturbance can be
simulated28. In a previous modeling study, van der Molen et al.28
proposed such an approach for an OWF at Dogger Bank, a
relatively shallow, well-mixed area of the North Sea using a
relatively coarse hydrodynamics-ecosystem model in combina-
tion with a wave model. Their study, however, was restricted to a
single OWF, which was parameterized simply as a reduction in
wind speed above the OWF.
Future OWF installations are planned to be far more
extensive29 and the consequences of accelerated deployment for
atmospheric dynamics and thermodynamics were shown to be
substantial and large scale in the area of the North Sea7. The
implications of these atmospheric changes for the future ocean
dynamics are still unclear. The question on how and to what
degree the emergent large-scale structural changes in atmosphere
and ocean7,8, under the premisses of large OWF clusters, might
affect marine ecosystem productivity remains yet unanswered.
Here we address this question while concentrating on the effects
of atmospheric wakes to the ocean. Mixing induced by the turbine
foundations in the ocean was neglected. For a future offshore
wind farm installation scenario, we consider the atmospheric
impact as simulated by a high-resolution (~2 km) atmospheric
model7to force a fully coupled physical-biogeochemical model
for the North Sea and Baltic Sea30. Different to earlier studies8we
employ an atmospheric model including a dynamical para-
meterization of OWFs, which takes into account the size of the
windfarm and the number of turbines7, and estimates impacts not
only on the wind eld but on the entire atmospheric physics. The
experiment including OWFs (Exp. 1: OWF) follows the design
given in Akhtar et al.7that includes all existing and planned
OWFs in the North Sea area based on information available in
2015 (see Supplementary Fig. 1) and is compared to a reference
simulation (Exp. 2: REF) without OWFs. For our idealized sce-
nario simulation, wind farm parameterization for 5 MW turbines
and hub heights of 90 m are used, the rotor diameter was con-
sidered as 126 m. The density of installed turbines was chosen to
be comparable to currently used densities for similar turbine
types. For the spatial distribution of installed capacity all planned
wind farm areas (planning status 2015) were used to distribute
the turbines for the wind farm parameterization. The installed
capacity for this scenario amounts to 120 GW, which is between
the 2030 high scenario of 65 GW for the North Sea and the
recently agreed commitment of the four countries Denmark,
Netherlands, Germany and Belgium (Esbjerg declaration) to
install a capacity of at 150 GW by 205031 in the North Sea. The
EUs overall plan for the installed capacity in 2050 in the North
Sea amounts to 212 GW. Hence, our simplied scenario corre-
sponds approximately to the installed capacity reached in about
15 yrs, by 2037.
The scenario simulations provide evidence that the increasing
amount of future OWF installations will substantially impact and
restructure the marine ecosystem of the southern and central
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North Sea. Changing atmospheric conditions will propagate
through ocean hydrodynamics and change stratication intensity
and pattern, slow down circulation and systematically decrease
bottom shear stress. The model projects that wind wakes of large
OWF clusters in the North Sea provoke large scale changes in
annual primary production with local changes (increase/decrease)
of up to 10%, while region-wide averages in estimated annual
primary production remain almost unchanged. In addition, the
results show an increase in sediment carbon in deeper areas of the
southern North Sea with local increases of up to 10%, and
reduced dissolved oxygen at the Oyster Grounds, which is an area
where oxygen levels can occasionally fall below 3 mg l132.
Results and discussion
Average system response to OWFs. Our results conrm the
direct ocean response identied by earlier studies8,9to the
alterations in the wind eld (Supplementary Fig. 2) with clearly
dened upwelling and downwelling dipoles in the vicinity of the
OWF clusters. However, none of the earlier studies could show
the systematic, large-scale, time-integrated response of the ocean
to large OWF clusters as they are planned to be implemented in
the southern North Sea. As a consequence of the substantial
amount of energy that is extracted from the lower atmosphere7,
the ocean responds with a clear and systematic change in strati-
cation, both in strength of stratication (Supplementary Fig. 3)
and depths of the seasonal mixed layer. The latter was estimated
to be, on average, 12 m shallower in and around the OWF
clusters (Fig. 1a). This effect occurred most clearly in the deeper
stratied German Bight area and around the Dogger Bank region.
For OWFs in mixed areas this effect is per denition not relevant
and in frontal, less stratied areas the effect is less clear as the
stratication becomes naturally interrupted by changes in the
frontal position. Changes in mixed layer depth have been
reported earlier as a consequence of offshore wind farm wakes
due to the reduced wind induced mixing8, but also due to the
upwelling and downwelling dipoles20. Since the dipole structure is
associated with both an uplift and a depression in mixed layer
depth20 and is variable in dependence of the wind direction
(Supplementary Fig. 2), we hypothesize that the annual average
response is mainly a consequence of the reduced wind mixing.
Apart from the effect on the stratication, our simulations show
that the ocean responds with a substantial decrease in the annual
mean of the vertically-averaged horizontal current velocities in the
range of 0.003 m s1in large parts of the southern North Sea, but
which can locally reach up to 0.0087 m s1at the OWFs at Dogger
Bank and 0.0091 m s1in the seasonally stratied reach of the
German Bight (Fig. 1b). In both of these areas this means a
reduction of 15% of the prevailing residual current. At the same
time there are also local increases in mean current velocities in the
German Bight area and, specically between the OWF clusters in
that area. These result locally in changes in current velocities of
about ±10% of the prevailing residual currents, which corroborates
the ndings by Christiansen et al.8, who studied the impacts of
existing OWFs in the German Bight area by using an unstructured
grid model and a very simple satellite-derived wind wake
parameterization. This also shows that the large-scale circulation
of the area will be strongly altered with potential consequences for
sediment transport as shown below.
Ecosystem impacts. In the southern North Sea, areas with par-
ticularly high primary production are co-located with the frontal
belt off the coast and around Dogger Bank (Fig. 2a, insert). The
majority of future OWF installations are planned in exactly those
highly productive areas, which are known to be ecologically
highly important33. Our model results show that the systematic
modications of stratication and currents alter the spatial pat-
tern of ecosystem productivity (Fig. 2a). Annual net primary
production (netPP) changes in response to OWF wind wake
effects in the southern North Sea show both areas with a decrease
and areas with an increase in netPP of up to 10%. Most obvious is
the decrease in the center of the large OWF clusters in the inner
German Bight and at Dogger Bank, which are both clearly situ-
ated in highly productive frontal areas, and an increase in areas
around these clusters in the shallow, near-coastal areas of the
German Bight and at Dogger Bank. The latter might be fueled by
nutrient supply from subsurface waters as a consequence of the
upwelling and downwelling dipole as suggested in earlier
studies20. Additionally, we also nd changes in netPP in areas
further away from the OWF clusters, such as a decrease along the
fresh water front of the German and Danish coasts and an
increase south-east of Dogger Bank at Oyster Grounds, which is
typically seasonally stratied and shows lower productivity.
Identifying the robustness of these patterns with respect to dif-
ferent weather conditions and interannual variations requires
additional analysis and simulations. When integrated over a lar-
ger area, the estimated positive and negative changes tend to even
Fig. 1 Annual mean ocean response to atmospheric changes due to offshore windfarms. a Estimated change (OWF-REF) in mixed layer depth (MLD);
bvertically averaged current velocity for REF (arrows) and changes (OWF-REF) (color). Gray polygons indicate location of offshore wind farms. (OWF:
simulation experiment considering offshore wind farms; REF: reference simulation).
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out. Regional averages for the whole North Sea (model area with
longitude <9°E) as well as for the southern North Sea area (as in
Fig. 2a) and the German Bight (latitude: 53.555.5°N; longitude:
49°E) only show reductions down to 0.5%, while the average
reductions in netPP directly at the OWF locations adds up to
1.2 %. The direct response of the ecosystem at the OWF sites
can be assigned to the changed hydrodynamic conditions. This
includes, on the one hand, the clearly dened upwelling and
downwelling patterns (Supplementary Fig. 2), which have been
hypothesized to play a major role in the changes OWFs provoke
in marine ecosystems10,20. Those patterns depend on the wind
direction and can be expected to modify the nutrient exchange at
the thermocline, as has been shown for temperature and salinity9,
at and around the OWF clusters. On the other hand, the pro-
duction changes are directly related to the changes in stratica-
tion. A closer look at the vertical distribution of netPP change
(Fig. 2b) averaged over the areas with OWF installations (parti-
tioned spatially into OWFs at strongly stratied and less stratied
regions and temporally into spring and summer periods) shows
that OWFs in clearly seasonally stratied waters experience an
upward shift of the vertical production maximum, which occurs
typically at the mixed layer depth in summer. This is a con-
sequence of the shallower mixed layer depth, due to reduced wind
mixing. This signal is more prominent in summer than in spring.
In contrast, OWFs in less stratied and frequently mixed waters
show a decrease in production in the upper 20 m of the water
column in spring and at the depth of the thermocline in summer.
Additionally, changes in netPP might translate into changes in
trophic interactions. The changes in netPP are clearly converted
into changes in phytoplankton biomass (Supplementary Fig. 4).
However, the response in phytoplankton biomass is relatively
small; on average below 1% both inside and outside the OWF
clusters (Fig. 3), but can reach up to 10% locally (Supplementary
Fig. 4). An exception is the biomass change inside OWF clusters
positioned in stratied areas, where the average response is about
2.4% but with large variations. Interestingly these locations also
show a relatively strong increase in zooplankton biomass (12%),
which indicates that the local ecosystem is additionally structured
by top-down control through increased grazing pressure34.In
reality the increased zooplankton production at these locations
might be mitigated by additional higher trophic levels feeding on
zooplankton, which is not represented in the model used here. In
contrast, outside OWF clusters and OWF clusters in less stratied
and mixed areas the model estimates a slight average reduction in
zooplankton biomass (<0.5%). In these regions it is difcult to
conclude on the overall trophic response, since the average
fractional change in biomass is very small and shows a large
regional variation (Fig. 3).
Besides the changes in the pelagic ecosystem our model results
highlight a substantial impact on sedimentation and seabed
processes. The overall, large-scale reduction in average current
velocities (Fig. 1b) results in reduced bottom-shear stress to up to
10% locally (Fig. 4a). The reduced resuspension of organic carbon
from the sediments results in an increased amount of organic
carbon in the sediments in large parts of the southern North Sea
(Fig. 4b). This becomes specically evident at and close to the
OWF locations in deeper areas and at the Dogger Bank. The
average increase in sediment organic carbon amounts to almost
Fig. 2 Annual mean response of net primary productions (netPP) to atmospheric changes due to offshore wind farms. a Relative change in annual
averaged net primary production for 2010 (OWF-REF). Black contour line indicates potential energy anomaly (PEA) of 85 J m3roughly separating seasonally
stratied from mixed areas; gray polygons indicate location of considered offshore wind farms (insert: annual average of netPP simulated for 2010). bVertical
proles of change (mean and standard deviation) in netPP inside the offshore wind farm areas; blue: less stratied and mixed areas (PEA < 85 J m3); green:
stratied areas (PEA 85 J m3) (solid lines: spring; dashed lines: summer). (OWF: simulation experiment considering offshore wind farms; REF: reference
simulation).
Fig. 3 Fractional change ((OWF-REF)/REF) in annually and vertically
averaged phytoplankton and zooplankton biomass. Mean and standard
deviation for areas inside and outside the OWF clusters separated based on
the potential energy anomaly (PEA) into stratied (PEA 85 J m3) and
less stratied and mixed areas (PEA < 85 J m3). Note, for the analysis
areas deeper than 60 m were excluded. (OWF: simulation experiment
considering offshore wind farms; REF: reference simulation).
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10% directly at the OWF locations and 6% in the German Bight
area. However, averaged over larger areas the effect is less
pronounced with only a 0.2% increase North Sea wide. Our
ndings on reduced resuspension are consistent with ndings
from van der Molen et al.28 for his case study of an OWF located
on Dogger Bank. Their model indicated an associated reduction
in light attenuation in the water column leading to a slight
increase in primary production. In large parts of the southern
North Sea light can be considered the major limiting factor for
primary production in summer26. Our results conrm changes in
light availability (Supplementary Fig. 4c) in the subsurface,
however, the pattern is strongly related to the pattern of change in
primary production, which indicates a dominant effect of
phytoplankton self-shading. In addition, our results do not show
that the reduction in resuspension is necessarily related to an
overall reduction of particulate organic matter concentration in
the water column. Considering the cause-effect chain that leads to
higher-primary production under improved light conditions, but
would in turn increase phytoplankton self-shading, the quanti-
cation of this effect on longer time scales remains to be studied
in the future.
In addition to changes in sediment-carbon distribution the
model indicates an impact of OWF on bottom water oxygen in
the southern North Sea (Fig. 4c). Oxygen is a key biogeochemical
component in marine ecosystems, and often considered as an
indicator for ecosystem health35. Even though the highly dynamic
North Sea is not known for extensive low oxygen areas, earlier
studies reported the potential for low oxygen events in the central
North Sea, more specically at the Oyster Grounds32,36. The
Oyster Grounds denotes a bathymetric depression, which partly
limits the exchange with the surrounding water and supports the
development of summer stratication. As a consequence, organic
material tends to accumulate in bottom waters at the Oyster
Grounds, which is associated with enhanced oxygen consump-
tion. Observations in this area show that dissolved oxygen
concentrations in bottom waters can occasionally fall below
3mgl
132, and also in our reference simulation dissolved oxygen
in bottom water was below 4 mg l1in late summer and autumn.
According to our simulation the Oyster Grounds is an area,
which would be especially impacted by large-scale OWF
installations. Due to increased primary production on the one
hand, but also by the reduced advective currents and bottom
shear stress the dissolved oxygen concentrations in late summer
and autumn were further reduced by about 0.3 mg l1on average
and up to 0.68 mg l1locally in our simulations. In other areas of
the southern North Sea, the effect was estimated to be less severe,
or even showing an increase in dissolved oxygen concentration,
like e.g., along the edges of Dogger Bank.
Consequences for higher tropic levels and management.Within
this study, we estimated the so far underrated effects of the changed
atmospheric conditions by OWFs on the large-scale features of the
lower trophic levels of the marine ecosystem in the southern North
Sea. The results highlight that, considering the extensive OWF
installation plans for the area, the marine ecosystem responds very
clearly to the changes in the atmosphere leading to changes in
ocean stratication, advective processes and a systematic decrease
in bottom shear stress. These changes can be expected to progress
into higher trophic levels of the marine ecosystem. The southern
North Sea is well-known for supporting a diversity of marine
fauna37,38 and especially the near-coastal areas are nursery grounds
for many economically relevant sh stocks. The estimated changes
in the spatial distribution of primary production might impact the
survival of sh early life stages in specic areas due to e.g., varia-
tions in the match-mismatch dynamics39 with their prey or as a
consequence of low oxygen conditions. Understanding these
changes is pivotal for successful future sheries management in the
North Sea and could inuence the identication and imple-
mentation of marine protected areas. Additionally, the estimated
changes in organic sediment distribution and quantity could have
an effect on the habitat quality for benthic species such as lesser
sandeel (Ammodytes marinus) and other benthic species that live in
the sediments in the deeper areas of the southern North Sea40.
Their spatial distributions might change as it has been shown to
depend on the available food quantity and quality41 as well as the
prevailing bottom shear stress42.
The quantication of the effects on species distribution and
diversity remains a topic for future studies as the model used here
is truncated at the secondary production level and does not allow
for species-specic estimates. In addition, the high computational
demand for running both models (atmosphere and ocean) on a
high resolution currently limits our simulation to one year only,
without an additional spinup period to allow for the system to
adjust to the OWF-induced changes. The average physical
response can be, at least partly (e.g., with respect to mixed layer
depth and reduced residual currents), considered immediate and
is mainly related to the reduced energy in the wind eld.
The ecosystem components, in contrast, might need a transition
phase to establish a new ecosystem state under OWF inuence.
Still, the changes we see are a systematic response to the energy
Fig. 4 Annual mean response of benthic processes to atmospheric changes due to offshore wind farms. a Relative change in annually averaged bottom
shear stress; brelative change in annually averaged sediment organic carbon; cabsolute change in dissolved bottom water oxygen (average July-
September). Black contour line indicates potential energy anomaly of 85 J m3; gray polygons indicate location of considered OWFs. (OWF: simulation
experiment considering offshore wind farms; REF: reference simulation).
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extraction from the atmosphere and will likely consolidate after a
few years of simulation, but with interannual variations related to
changes in the environmental conditions. A repetition of the
simulation experiments with an end-to-endmodel approach43
and multi-annual simulations are required to shed further light
on the robustness of the estimated pattern, the transfer of the
changes into the food web and its implications for ecosystem
services and management. Additionally, further research on the
combined effects of atmospheric wakes and anthropogenic
mixing induced by the pile structures17 in the ocean is necessary,
as this might counteract the stabilizing effect of the wind wakes.
Under the ambitious plans for OWF constructions in the North
Sea17 space becomes one of the major limiting resources for a
large number of partly conicting usage interests44. Our results
can serve to support the inevitable development of co-use
management strategies under the given conditions.
Methods
ECOSMO model description and setup. ECOSMO is a well-established, fully
coupled marine ecosystem model for the North Sea and Baltic Sea area. The version
of ECOSMO II used here has been presented in detail before45 and contains a total
of 16 state variables that describes the lower trophic components (phytoplankton
and zooplankton) of the marine ecosystem as well as the major macro-nutrient
cycles (nitrogen, phosphorus, silicon) relevant for the North Sea and Baltic Sea
system. The sediment compartment is included through a simple bottom layer
which accumulates organic material. Benthic uxes of the different nutrients are
estimated separately in a non-Redeld manner to account for oxygen-dependent
chemical processes in the sediment. On the basis of the free-surface 3D baroclinic
coupled sea-ice model HAM(burg)S(chelf)O(cean) M(odel)46, the non-linear pri-
mitive equations are solved on a staggered Arakawa-C grid with a horizontal
resolution of ~2 km and a time step of 90 s. The impacts of the OWF wind wakes
were earlier found to be related to the internal radius of deformation19, which is
about 10 km in the North Sea area47. The smallest scales resolved by the model are
twice the grid size (approx. 4 km). Hence, the internal radius of deformation is well
resolved by the model. The vertical dimension is simulated with z-level coordinates
with a maximum of 30 layers, with a higher resolution in the upper layers the
surface to represent ocean stratication, and increasing level thickness in deeper
layers (5 m for the rst two layers; 4 m up to depths of 50 m; 6 m for depths
between 50 and 92 m; 100 m; 120 m; 140 m; 160 m; 180m; 200 m; 250 m; 300 m;
400 m; 500 m; 630 m). In total, this adds up to 2516251 wet grid cells. The model
uses a second-order LaxWendroff advection scheme that was made TVD (total
variation diminishing) by a superbee-limiter48 that has been described in detail in
an earlier study49, and which has been shown to adequately represent the frontal
structures in the southern North Sea.
The overall model setup including forcing data is comparable to the setup used
in Zhao et al.26 but with a different set of open boundary conditions for
temperature and salinity. The latter were provided by a global simulation using the
Max Planck Institute Ocean Model (MPI-OM)50 in a higher resolution setup51
forced with the NCEP/NCAR reanalysis52.
Atmospheric forcing and Windfarm scenarios. A non-hydrostatic model
COSMO-CLM with atmospheric grid resolution of ~ 2 km (1100 × 980 grid cells)
has been used to simulate the regional climate with and without OWFs in the North
Sea. It uses 62 vertical levels with 5 levels within the rotor area. To include the
impact of OWFs in COSMO-CLM a wind farm parameterization7,53 has been
implemented that represents wind-turbine effects as momentum sink and source of
turbulent kinetic energy. In this experiment, a theoretical OWF model was used
based on the theoretical National Renewable Energy Laboratory (NREL) 5 MW
reference wind turbine. It uses a wind turbine with a hub height of 90 m and rotor
diameter of 126 m54. These turbines have a cut-in wind speed of 3 ms1, rated wind
speed of 11.4 ms1, and a cut-out wind speed of 25 ms1. The atmospheric model
used a wind turbine density of about 1.8 × 106m2. Due to coarse atmospheric
grid resolution (~2 km), the average effect of the wind turbines within the gridbox is
estimated using the average grid box velocity. For both the experiments, with and
without wind farms, initial and boundary conditions from coastDat3 simulations55
were used. The latter were forced by the European Center for Medium-Range
Weather Forecast (ECMWF) ERA-Interim reanalysis56. A more detailed description
of the experimental conguration, wind farm parameterization and a validation of
the parameterization can be found in a previous study7.
Strategy for using the models and data analysis. ECOSMO was forced by the
COSMO-CLM simulations with and without OWF parameterization for the year
2010. The change in forcing is thereby not constrained to the change in the wind
eld but comprises changes in all required forcing parameters including pressure,
short wave radiation, 2 m air temperature, humidity, and precipitation. The
simulations in 2010 were initialized using a 2-year long (20082009) spinup
simulation also forced by COSMO-CLM (without OWF parameterization). Con-
sidering that the characteristic time scale of the North Sea is in the order of 13
years a two-year spinup is sufcient for initializing the simulation, especially since
the initial elds for physical state variables were retrieved from a previously con-
ducted simulation with a similar model setup but a different atmospheric and river
forcing. The latter simulation started in 1995 with the same setup but atmospheric
forcing from the COSMO REA6 reanalysis57 and freshwater discharges provided
by the mesoscale hydrological model (mHM)58, which is a calibrated, grid-based
hydrological model for Europe59. Ecosystem state variables were initialized from
climatological values based on the World Ocean Atlas60. Since the atmospheric
simulation is computationally very demanding, only one year of the simulation is
currently available covering the full ocean model domain.
Model data output has been postprocessed based on daily mean values available
for all state variables as well as for biogeochemical uxes and bottom-shear stress.
Potential energy anomaly61, the energy required to homogenize the water column,
provides a measure for the strength of stratication. For the denition of the mixed
layer depth we used a temperature criterion suggested by de Boyer Montégut
et al.62 where the mixed layer depth is dened as the depths at which ΔT0.2 °C
with respect to the surface layer temperature. Figures were compiled with matlab
using the cmocean colormap63.
Reporting summary. Further information on research design is available in the Nature
Portfolio Reporting Summary linked to this article.
Data availability
The datasets generated and/or analyzed during the current study are publicly available at
the world data center for climate (www.wdc-climate.de) under http://hdl.handle.net/21.
14106/d116dd4f38f47f150e655ab9441601b34b312583.
Code availability
Model code access for the marine ecosystem model ECOSMO can be obtained upon
request.
Received: 13 June 2022; Accepted: 11 November 2022;
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Acknowledgements
The study is a contribution to the BMBF funded project CoastalFutures (03F0911E), the
Helmholtz Research Program Changing Earth- Sustaining our Futureand the EXC
2037 Climate, Climatic Change, and Society(Project Number: 390683824 funded by the
German Research Foundation (DFG)). The authors would like to acknowledge the
German Climate Computing Center (DKRZ) for providing computational resources.
Author contributions
C.S. and U.D. conceived the study and designed the study setup. U.D. performed the
model simulation with ECOSMO, data analysis, and prepared the manuscript with
contributions from all co-authors. N.A. performed the atmospheric model simulation
COMMUNICATIONS EARTH & ENVIRONMENT | https://doi.org/10.1038/s43247-022-00625-0 ARTICLE
COMMUNICATIONS EARTH & ENVIRONMENT | (2022) 3:292 | https://doi.org/10.1038/s43247-022-00625-0 |www.nature.c om/commsenv 7
Content courtesy of Springer Nature, terms of use apply. Rights reserved
and prepared the atmospheric forcing data for the ecosystem model. U.D., C.S., N.A., and
N.C. contributed to data analysis and manuscript writing.
Funding
Open Access funding enabled and organized by Projekt DEAL.
Competing interests
The authors declare no competing interests.
Additional information
Supplementary information The online version contains supplementary material
available at https://doi.org/10.1038/s43247-022-00625-0.
Correspondence and requests for materials should be addressed to Ute Daewel.
Peer review information Communications Earth & Environment thanks Rodney Forster,
Göran Broström and the other, anonymous, reviewer(s) for their contribution to the peer
review of this work. Primary Handling Editors: Olivier Sulpis, Clare Davis, Heike
Langenberg. Peer reviewer reports are available.
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... Strong local effects do occur in the model, and the wind wakes and pile turbulence production cause the impacts to extend to considerable distances from the OWFs themselves. A holistic assessment of OWF impacts on sediment OC should consider the OC loss due to seafloor disturbance during construction and decommissioning, as well as secondary effects, such as the colonization of organisms at the foundations of wind turbines and wind wake impacts on the ecosystem structure (de Borger et al., 2021a;Daewel et al., 2022;Heinatz and Scheffold, 2023). Using an ecosystem model that considers wind wake effects, Daewel et al. (2022) simulated local increases in sedimentary carbon of up to 10 % after 1 year but only a slight net increase of 0.2 % for the entire North Sea. ...
... Strong local effects do occur in the model, and the wind wakes and pile turbulence production cause the impacts to extend to considerable distances from the OWFs themselves. A holistic assessment of OWF impacts on sediment OC should consider the OC loss due to seafloor disturbance during construction and decommissioning, as well as secondary effects, such as the colonization of organisms at the foundations of wind turbines and wind wake impacts on the ecosystem structure (de Borger et al., 2021a;Daewel et al., 2022;Heinatz and Scheffold, 2023). Using an ecosystem model that considers wind wake effects, Daewel et al. (2022) simulated local increases in sedimentary carbon of up to 10 % after 1 year but only a slight net increase of 0.2 % for the entire North Sea. ...
... A holistic assessment of OWF impacts on sediment OC should consider the OC loss due to seafloor disturbance during construction and decommissioning, as well as secondary effects, such as the colonization of organisms at the foundations of wind turbines and wind wake impacts on the ecosystem structure (de Borger et al., 2021a;Daewel et al., 2022;Heinatz and Scheffold, 2023). Using an ecosystem model that considers wind wake effects, Daewel et al. (2022) simulated local increases in sedimentary carbon of up to 10 % after 1 year but only a slight net increase of 0.2 % for the entire North Sea. Though our OWF scenario shows a slight decrease in OC, this is primarily due to the trawling effort redistribution, whereas the wind wake effect shows a similar sign and magnitude to Daewel et al. (2022). ...
Article
Full-text available
The depletion of sedimentary organic carbon stocks by the use of bottom-contacting fishing gear and the potential climate impacts resulting from remineralization of the organic carbon to CO2 have recently been heavily debated. An issue that has remained unaddressed thus far regards the fate of organic carbon resuspended into the water column following disturbance by fishing gear. To resolve this, a 3D-coupled numerical ocean sediment macrobenthos model is used in this study to quantify the impacts of bottom trawling on organic carbon and macrobenthos stocks in North Sea sediments. Using available information on vessel activity, gear components, and sediment type, we generate daily time series of trawling impacts and simulate 6 years of trawling activity in the model, as well as four management scenarios in which trawling effort is redistributed from areas inside to areas outside of trawling closure zones. North Sea sediments contained 552.2±192.4 kt less organic carbon and 13.6 ± 2.6 % less macrobenthos biomass in the trawled simulations than in the untrawled simulations by the end of each year. The organic carbon loss is equivalent to aqueous emissions of 2.0 ± 0.7 Mt CO 2 each year, roughly half of which is likely to accumulate in the atmosphere on multi-decadal timescales. The impacts were elevated in years with higher levels of trawling pressure and vice versa. Results showed high spatial variability, with a high loss of organic carbon due to trawling in some areas, while organic carbon content increased in nearby untrawled areas following transport and re-deposition. The area most strongly impacted was the heavily trawled and carbon-rich Skagerrak. Simulated trawling closures in planned offshore wind farms (OWFs) and outside of core fishing grounds (CFGs) had negligible effects on net sedimentary organic carbon, while closures in marine protected areas (MPAs) had a moderately positive impact. The largest positive impact arose for trawling closures in carbon protection zones (CPZs), which were defined as areas where organic carbon is both plentiful and labile and thereby most vulnerable to disturbance. In that scenario, the net impacts of trawling on organic carbon and macrobenthos biomass were reduced by 29 % and 54 %, respectively. These results demonstrate that carbon protection and habitat protection can be combined without requiring a reduction in net fishing effort .
... FOWFs generally have the hub at ca 170 m above sea level and the height at the tip of the blades can be higher than 250 m at a 50-km distance from the shore they would be invisible to the human eye. Atmospheric wakes appearing in the lee of wind farms extend on scales up to 65 km, with a wind speed reduction of up to 43% inside the wakes leading to turbulence effects [90][91][92] altering the meteorology at the micro-scale [93,94] and an increase or decrease of temperature [93]. They can locally alter the precipitation regimen [95,96], and potentially alter the spread of air pollutants through an edge effect [97,98]. ...
... Since FOWFs do not have a fixed foundation, these effects might be strongly reduced. Larger scale effects of OWFs can alter the stratification, which is on average 1-2 m shallower in and around the OWF clusters and alter the current speed (±10% [91]). The influence of FOWFs on natural upwellings [126] is less plausible, nonetheless, large FOWFs can increase or decrease the net primary production with consequences on the survival of fish larvae [91]. ...
... Larger scale effects of OWFs can alter the stratification, which is on average 1-2 m shallower in and around the OWF clusters and alter the current speed (±10% [91]). The influence of FOWFs on natural upwellings [126] is less plausible, nonetheless, large FOWFs can increase or decrease the net primary production with consequences on the survival of fish larvae [91]. Field investigations confirmed the increased vertical mixing leading to a doming of the thermocline and subsequent transport of nutrients into the surface mixed layer (SML). ...
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Floating Offshore Wind Farms (FOWFs) are the most promising renewable energy resource. Floating turbines are installed at progressively increasing water depths, interacting with offshore and deep-sea ecosystems. Thus, specific criteria to enable a sound and accurate Environmental Impact Assessment (EIA) are required. The still limited understanding of the impacts of FOWFs, and the concerns for the conflicts in the use of maritime space (e. g., fisheries), might lead to a more precautionary approach and constrain their development. Here we describe the characteristics of the deep habitats potentially impacted and identify a set of comprehensive and standardized criteria, response variables and approaches for a reliable EIA based on an Ecosystem-based approach. These analyses will support an appropriate design and site prioritization to respect the "Do No Significant Harm" principle. Considering the wide heterogeneity among habitats and geographic regions, we examined the potential interactions of FOWFs with i) Vulnerable Marine Ecosystems; ii) critical habitats; iii) migratory routes of large marine vertebrates; iv) habitat-forming species, benthic/pelagic organisms, v) migratory routes of birds/ chiropters; vi) other human uses leading to cumulative/synergistic effects and any other potential interference. We identified mitigation and compensation measures and explored the potential of wind-farm areas as "Other Effective Conservation Measures" to support sustainable fisheries and passive restoration. Adequate siting, EIA and systematic monitoring can minimize FOWFs' environmental interactions, with final negligible, or even positive effects on marine ecosystems. Standardized criteria could significantly reduce the bottlenecks in permitting while offering a strategic vision for the sustainable use of the maritime space.
... Expansive clusters of OW turbines modify the physical and chemical habitat of an area and, therefore, will also change the sensory world that marine animals experience on vast expanses of the continental shelf, both at the sea bottom and in the water column . Turbines reduce wind forcing and modify water circulation, changing the primary productivity, oxygenation, and sedimentation rate at the sea bottom (Daewel et al. 2022 ). These habitat modifications, in combination with the newly introduced hard substrates from turbines, substations, cables, and moorings will affect many species of macro and mega-zooplankton, birds, marine mammals, benthic animals, and fishes . ...
... characterize the disturbances introduced by OW farms (Lindeboom et al. 2011 ). Large datasets are collected at existing OW facilities to characterize changes in noise conditions during the installation and operational phases (Matuschek and Betke 2009, Tougaard et al. 2020, Wang et al. 2022, electromagnetic fields (EMFs) in proximity of the subsea cables connecting the turbines , Imperadore et al. 2023, water stratification, oxygenation and productivity (Daewel et al. 2022), hydrodynamics (van Berkel et al. 2020, and sedimentation rates (Harris et al. 2011 ). These data are related to specific facilities and locations and, therefore, cannot be used to assess, a priori , the impacts that OW farms would have at different locations. ...
Article
Stakeholders need scientific advice on the environmental impacts of offshore wind (OW) before the facilities are installed. The utility of conventional environmental monitoring methods as a basis for forecasting OW impacts is limited because they do not explain the causes of the observed effects. We propose a multistep approach, based on process-oriented hypothesis testing, targeted monitoring and numerical modeling, to answer key stakeholder questions about planning an OW facility: Q1—Where do we place future OW farms so that impacts on the ecosystem are minimized? Q2—Which species and ecosystem processes will be impacted and to what degree? Q3—Can we mitigate impacts and, if so, how? and Q4—What are the risks of placing an OW facility in one location vs. another? Hypothesis testing can be used to assess impacts of OW facilities on target species-ecological process. This knowledge is transferable and is broadly applicable, a priori, to assess suitable locations for OW (Q1). Hypothesis testing can be combined with monitoring methods to guide targeted monitoring. The knowledge generated can identify the species/habitats at risk (Q2), help selecting/developing mitigation measures (Q3), and be used as input parameters for models to forecast OW impacts at a large spatial scale (Q1; Q4).
... In the BML, net O 2 removal can occur as a result of restricted ventilation due to seasonal thermal stratification, oxygen consumption via pelagic and benthic respiration of organic matter, and nitrification. An important mechanism in sustaining high productivity in shelf seas is the diapycnal upward mixing of nutrients across the base of the thermocline barrier (Sharples et al., 2007;Rippeth, 2005;Rippeth et al., 2014;Williams et al., 2013a;Davis et al., 2014;Brandt et al., 2015). There is also potential for diapycnal mixing to help alleviate O 2 deficiency in the BML by providing a downward turbulent flux of O 2 across the thermocline (Queste et al., 2016;Rovelli et al., 2016;Williams et al., 2022). ...
... Coastal and shelf seas are increasingly being looked to as an energy source with the development of wind and tidal renewable energy, with the aim for 40 GW of energy being harnessed from the wind by 2030. Research on the impact of these floating and static wind farms on stratification, mixing, and deoxygenation is premature, but a recent study has indicated that deoxygenation will increase in areas of the North Sea already at risk of low oxygen levels as a result of the presence of static wind farms increasing primary production but also reducing advective currents and bottom shear stress (Daewel et al., 2022). It is therefore imperative that we continue to monitor dissolved oxygen concentrations alongside measurements of hydrography and mixing in coastal and shelf sea waters, especially as offshore installations expand, with unknown consequences on ecosystem health. ...
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There is an immediate need to better understand and monitor shelf sea dissolved oxygen (O2) concentrations. Here we use high-resolution glider observations of turbulence and O2 concentrations to directly estimate the vertical O2 flux into the bottom mixed layer (BML) immediately before the autumn breakdown of stratification in a seasonally stratified shelf sea. We present a novel method to resolve the oxycline across sharp gradients due to slow optode response time and optode positioning in a flow “shadow zone” on Slocum gliders. The vertical O2 flux to the low-O2 BML was found to be between 2.5 to 6.4 mmol m−2 d−1. Episodic intense mixing events were responsible for the majority (up to 90 %) of this oxygen supply despite making up 40 % of the observations. Without these intense mixing events, BML O2 concentrations would approach ecologically concerning levels by the end of the stratified period. Understanding the driving forces behind episodic mixing and how these may change under future climate scenarios and renewable energy infrastructure is key for monitoring shelf sea health.
... This decrease in the annual mean wind speed results in a reduction in the annual mean values of net heat flux, indicating a 2% less heating of the atmosphere from the sea surface 14 . Further investigation revealed that the wakes generated by wind farms induce significant alterations in annual biomass primary production, causing local changes of up to ± 10%, not only within the wind farm clusters but also distributed across a broader region in the North Sea 31 . ...
... This could mean that larger wind turbines have less impact on the ocean dynamics and ecosystem, as sea surface winds and heat fluxes are important drivers of these systems. A recent study 31 , employing consistent atmospheric forcing and wind farm scenarios, along with the identical 5 MW turbines used in this experiment, emphasizes the substantial impact of wind wakes on the ecosystem of the North Sea. Ocean and ecosystem modeling studies, employing the strategy of incorporating atmospheric forcing to account for wake effects, aim to enhance our understanding of the potential impacts of various types of wind farms on ocean dynamics and ecosystems. ...
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The EU aims for carbon neutrality by 2050, focusing on offshore wind energy. Investments in North Sea wind farms, with optimal wind resources, play a crucial role. We employed a high-resolution regional climate model, which incorporates a wind farm parametrization, to investigate and address potential mitigating impacts of large wind farms on power generation and air-sea fluxes. Specifically, we examined the effects of replacing 5 MW turbines with larger 15 MW turbines while maintaining total capacity. Our study found that substituting 15 MW turbines increases the capacity factor by 2–3%, enhancing efficiency. However, these turbines exhibit a slightly smaller impact on 10 m wind speed (1.2–1.5%) and near-surface kinetic energy (0.1–0.2%), leading to reduced effects on sea surface heat fluxes compared to 5 MW turbines. This was confirmed by a stronger reduction in net heat flux of about 0.6–1.3% in simulations with 5 MW compared to 15 MW wind turbines. Air-sea fluxes influence ocean dynamics and marine ecosystems; therefore, minimizing these impacts is crucial. Overall, deploying 15 MW turbines in offshore wind farms may offer advantages for ocean dynamics and marine ecosystems, supporting the EU's carbon–neutral objectives.
... However, the majority of research centers on the wind wake and its consequential induction of turbulence within the stratified water column. The impact of offshore foundations on sediment transport has been evaluated in a number of research, both during the construction phase involving activities such as pile driving and cable laying [13] and in the postconstruction period [3,14,15]. ...
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This work aims to investigate how the presence of Offshore Wind Farms (OWFs) could have local and potentially regional environmental impacts, as the turbine foundations serve as artificial habitats for various benthopelagic species, creating reef ecosystems. This study investigates how under met-oceanic forcings these farms could control the larval dispersion in the extended Bay of Seine. The dispersion of both natural species (mussel and European green crab) and introduced species (e.g. Japanese oyster and Asian shore crab) is simulated with coupled physical-biological numerical model combining MARS3D and ICHTHYOP. After a successful qualitative validation step using DILEMES data, it is observed that wind farms serve as relay points for species, facilitating connectivity between the farms and the shores of the extended Bay of Seine. Larval dispersal from the wind farms shows connectivity not only between the farms themselves but also between the farms and the shores of the extended Seine Bay, with approximately 7.44$\%$ of initially emitted larvae settling inside the Courseulles-sur-Mer OWF. As expected, the spatial resolution of the hydrodynamic model impacts the results, influencing larval retention particularly at the intersection of different nested grids. Our results indicate that it would be preferable to include effects of OWFs in future coastal management scenarios and underline the need to study cumulative impacts.
... Therefore, coupling with wave and ocean models could provide insight into potential wake impacts on the ocean. Daewel et al. (2022) considers the impact of offshore wakes on primary production, but additional analysis on surface currents would provide a more 415 complete picture of wake impacts. ...
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Offshore wind energy projects are currently in development off the east coast of the United States and will likely influence the local meteorology of the region. Wind power production and other commercial uses in this area are related to atmospheric conditions, and so it is important to understand how future wind plants will change the local meteorology. We compared one year of simulations from the Weather Research and Forecasting model with and without wind farms incorporated, focusing on the lease area south of Massachusetts and Rhode Island. We assessed changes in wind speeds, 2 m temperature, surface heat flux, turbulent kinetic energy, and boundary layer height during different stability classifications and ambient wind speeds over the entire year. Because the wake behavior may be a function of boundary-layer stability, in this paper, we also present a machine learning algorithm to quantify the area and distance of the wake generated by the wind plant. This analysis enables us to identify the relationship between wake extent and boundary-layer height. Hub-height wind speed is reduced within and downwind of the wind plant, with the strongest impacts occurring during stable conditions and faster wind speeds. Wind speeds at 10 m increase within the wind plant area during stable conditions. Differences in 2 m temperatures and surface heat fluxes are small, but are largest during stable conditions and strong wind speeds. Turbulence kinetic energy (TKE) increases within the lease area with increasing wind speeds at both the surface and at hub height. At hub height, TKE increases do not depend on stability, but at the surface, TKE increases most during unstable conditions as the turbulence injected at hub height is mixed down to the surface. Boundary-layer heights increase within the wind plant, and decrease slightly downwind during stable conditions. Deeper boundary-layer heights, exceeding 100 m, tend to correlate with smaller wake areas and distances, though other factors likely also play a role in determining the extent of the wind farm wake.
... Wind power generation reduces the wind speed in the vicinity which translates to possible changes in turbulence, mixing, stratification and hydrodynamics in general [19]. Effects may be highly variable, but these changes could also lead to changes in primary production and onwards to the rest of the food chain [20]. ...
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This paper introduces the MARCO (MARine CO-existence scenario building) concept for using scenario exploration in stakeholder engagement processes in offshore wind. MARCO builds on spatial analyses using geographic information systems (GIS), and projections over time using system dynamics simulation models. We position the concept within the existing literature on tools for decision support and stakeholder participation, and provide a preliminary status on the spatial baselines, as well as example scenarios for area usage in offshore wind and implications, including risks and co-existence opportunities, on other sectors and nature.
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The urgency to mitigate the effects of climate change necessitates an unprecedented global deployment of offshore renewable-energy technologies mainly including offshore wind, tidal stream, wave energy, and floating solar photovoltaic. To achieve the global energy demand for terawatt-hours, the infrastructure for such technologies will require a large spatial footprint. Accommodating this footprint will require rapid landscape evolution, ideally within two decades. For instance, the United Kingdom has committed to deploying 50 GW of offshore wind by 2030 with 90–110 GW by 2050, which is equivalent to four times and ten times more than the 2022 capacity, respectively. If all were 15 MW turbines spaced 1.5 km apart, 50 GW would require 7500 km² and 110 GW would require 16 500 km². This review paper aims to anticipate environmental impacts stemming from the large-scale deployment of offshore renewable energy. These impacts have been categorised into three broad types based on the region (i.e. atmospheric, hydrodynamic, ecological). We synthesise our results into a table classifying whether the impacts are positive, negative, negligible, or unknown; whether the impact is instantaneous or lagged over time; and whether the impacts occur when the offshore infrastructure is being constructed, operating or during decommissioning. Our table benefits those studying the marine ecosystem before any project is installed to help assess the baseline characteristics to be considered in order to identify and then quantify possible future impacts.
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The offshore wind energy sector has rapidly expanded over the past two decades, providing a renewable energy solution for coastal nations. Sector development has been led in Europe, but is growing globally. Most developments to date have been in well-mixed, i.e., unstratified, shallow-waters near to shore. Sector growth is, for the first time, pushing developments to deep water, into a brand new environment: seasonally stratified shelf seas. Seasonally stratified shelf seas, where water density varies with depth, have a disproportionately key role in primary production, marine ecosystem and biogeochemical cycling. Infrastructure will directly mix stratified shelf seas. The magnitude of this mixing, additional to natural background processes, has yet to be fully quantified. If large enough it may erode shelf sea stratification. Therefore, offshore wind growth may destabilize and fundamentally change shelf sea systems. However, enhanced mixing may also positively impact some marine ecosystems. This paper sets the scene for sector development into this new environment, reviews the potential physical and environmental benefits and impacts of large scale industrialization of seasonally stratified shelf seas and identifies areas where research is required to best utilize, manage, and mitigate environmental change.
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The potential impact of offshore wind farms through decreasing sea surface wind speed on the shear forcing and its consequences for the ocean dynamics are investigated. Based on the unstructured-grid model SCHISM, we present a new cross-scale hydrodynamic model setup for the southern North Sea, which enables high-resolution analysis of offshore wind farms in the marine environment. We introduce an observational-based empirical approach to parameterize the atmospheric wakes in a hydrodynamic model and simulate the seasonal cycle of the summer stratification in consideration of the recent state of wind farm development in the southern North Sea. The simulations show the emergence of large-scale attenuation in the wind forcing and associated alterations in the local hydro- and thermodynamics. The wake effects lead to unanticipated spatial variability in the mean horizontal currents and to the formation of large-scale dipoles in the sea surface elevation. Induced changes in the vertical and lateral flow are sufficiently strong to influence the residual currents and entail alterations of the temperature and salinity distribution in areas of wind farm operation. Ultimately, the dipole-related processes affect the stratification development in the southern North Sea and indicate potential impact on marine ecosystem processes. In the German Bight, in particular, we observe large-scale structural change in stratification strength, which eventually enhances the stratification during the decline of the summer stratification toward autumn.
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The European Union has set ambitious CO 2 reduction targets, stimulating renewable energy production and accelerating deployment of offshore wind energy in northern European waters, mainly the North Sea. With increasing size and clustering, offshore wind farms (OWFs) wake effects, which alter wind conditions and decrease the power generation efficiency of wind farms downwind become more important. We use a high-resolution regional climate model with implemented wind farm parameterizations to explore offshore wind energy production limits in the North Sea. We simulate near future wind farm scenarios considering existing and planned OWFs in the North Sea and assess power generation losses and wind variations due to wind farm wake. The annual mean wind speed deficit within a wind farm can reach 2–2.5 ms ⁻¹ depending on the wind farm geometry. The mean deficit, which decreases with distance, can extend 35–40 km downwind during prevailing southwesterly winds. Wind speed deficits are highest during spring (mainly March–April) and lowest during November–December. The large-size of wind farms and their proximity affect not only the performance of its downwind turbines but also that of neighboring downwind farms, reducing the capacity factor by 20% or more, which increases energy production costs and economic losses. We conclude that wind energy can be a limited resource in the North Sea. The limits and potentials for optimization need to be considered in climate mitigation strategies and cross-national optimization of offshore energy production plans are inevitable.
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We review the state of knowledge about offshore wind farm (OWF) development-related effects on hydrodynamics and their possible secondary effects on fishes derived from European studies. Theoretical, modeling, and observational studies of OWF developments are relatively advanced and identify potential impacts resulting from OWF changes to local or regional hydrodynamics through modification of (1) the wind fields, and (2) oceanographic parameters including turbulence, mixing, and vertical stratification. While limited, studies discuss local OWF (i.e., within the OWF footprint) impacts on fishes due to sediment resuspension or sedimentation, temperature change, nutrient transport, and substrate availability. These studies largely neglect possible effects further afield and generally conclude that any hydrodynamic impact of OWFs on fishes cannot be distinguished when compared to natural variability. To further understanding of the cumulative risk from extensive OWF developments requires additional research on OWF-related spillover effects on surrounding ecosystems and on natural oceanographic connectivity. The use of dynamic habitat or agentbased models coupled with refined hydrodynamic models can help quantify the scale of spatial and temporal effects of hydrodynamic cues on the movement of fishes and their habitats, which is not currently possible via conventional modeling, quantitative analysis approaches, or field-based observational studies and surveys.
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Offshore wind farms (OWFs) are proliferating globally. The submerged parts of their structures act as artificial reefs, providing new habitats and likely affecting fisheries resources. While acknowledging that the footprints of these structures may result in loss of habitat, usually soft sediment, we focus on how the artificial reefs established by OWFs affect ecosystem structure and functioning. Structurally, the ecological response begins with high diversity and biomass in the flora and fauna that gradually colonize the complex hard substrate habitat. The species may include nonindigenous ones that are extending their spatial distributions and/or strengthening populations, locally rare species (e.g., hard substrate-associated fish), and habitat-forming species that further increase habitat complexity. Functionally, the response begins with dominant suspension feeders that filter organic matter from the water column. Their fecal deposits alter the surrounding seafloor communities by locally increasing food availability, and higher trophic levels (fish, birds, marine mammals) also profit from locally increased food availability and/or shelter. The structural and functional effects extend in space and time, impacting species differently throughout their life cycles. Effects must be assessed at those larger spatiotemporal scales.
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The Block Island Wind Farm (BIWF), situated offshore of Block Island, Rhode Island, is the first commercial offshore wind farm (OWF) in the United States. We briefly review pre-siting studies, which provide contextual information about the benthic habitats and fish in the Block Island Sound area before the BIWF jacket foundations were installed in 2015. We focus on benthic monitoring that took place within the BIWF. This monitoring allowed for assessments of spatiotemporal changes in sediment grain size, organic enrichment, and macrofauna, as well as the colonization of the jacket structures, up to four years post-installation. The greatest benthic modifications occurred within the footprint of the foundation structures through the development of mussel aggregations. Within four years, changes in benthic habitats (defined as biotopes) were observed within the 90 m range of the study, clearly linked to the musseldominated colonization of the structures, which also hosted numerous indigenous fish species. We discuss the evident structural and functional effects and their ecological importance at the BIWF and for future US OWFs, drawing on similarities with European studies. While reviewing lessons learned from the BIWF, we highlight the need to implement coordinated monitoring for future developments and recommend a strategy to better understand environmental implications.
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ARTICLE INFO Keywords Offshore wind farms Offshore wind support structures Offshore wind turbines Renewable energy Wind farm layout Worldwide coastline offshore projects ABSTRACT The present paper provides an overview of the current state and future trends of the offshore wind farms worldwide along with the technological challenges, especially the wind farm layout and the main components. First, this paper provides a review of the operative wind farms, main components characteristics and the wind farms dimensions. This is followed by a correlation analysis between offshore wind farm layout parameters such as the number of turbines, the installed capacity, the distance from shore and the water depth. Moreover, the present paper reviews the available data regarding the future projects' portfolio. The evolution of offshore wind technology related to the pre-and under-construction projects is discussed. The data showed an increase in the wind farm dimensions and the capacity of the turbines for wind power generation more in line with that from other energy resources, which is, thereby, enhancing the potential and attractiveness of offshore wind industry for future investors. Finally, a discussion of future previsions related to offshore wind farm layout and capacity concludes the paper.
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The impact of offshore constructions on the marine environment is unknown in many aspects. The application of Al- and Zn-based galvanic anodes as corrosion protection results in the continuous emission of inorganic matter (e.g. >80 kg Al-anode material per monopile foundation and year) into the marine environment. To identify tracers for emissions from offshore wind structures, anode materials (Al-based and Zn-based) were characterized for their elemental and isotopic composition. An acid digestion and analysis method for Al and Zn alloys was adapted and validated using the alloy CRMs ERM®-EB317 (AlZn6CuMgZr) and ERM®-EB602 (ZnAl4Cu1). Digests were measured for their elemental composition by ICP-MS/MS and for their Pb isotope ratios by MC ICP-MS. Ga and In were identified as potential tracers. Moreover, a combined tracer approach of the elements Al, Zn, Ga, Cd, In and Pb together with Pb isotope ratios is suggested for a reliable identification of offshore-wind-farm-induced emissions. In the Al anodes, the mass fractions were found to be >94.4% of Al, >2620 mg kg⁻¹ of Zn, >78.5 mg kg⁻¹ of Ga, >0.255 mg kg⁻¹ of Cd, >143 mg kg⁻¹ of In and >6.7 mg kg⁻¹ of Pb. The Zn anodes showed mass fractions of >2160 mg kg⁻¹ of Al, >94.5% of Zn, >1.31 mg kg⁻¹ of Ga, >254 mg kg⁻¹ of Cd, >0.019 mg kg⁻¹ of In and >14.1 mg kg⁻¹ of Pb. The n(²⁰⁸Pb)/n(²⁰⁶Pb) isotope ratios in Al anodes range from 2.0619 to 2.0723, whereas Zn anodes feature n(²⁰⁸Pb)/n(²⁰⁶Pb) isotope ratios ranging from 2.0927 to 2.1263.
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This publication synthesizes the results of the WIPAFF (WInd PArk Far Fields) project. WIPAFF focused on the far field of large offshore wind park wakes (more than 5 km downstream of the wind parks) located in the German North Sea. The research project combined in situ aircraft and remote sensing measurements, satellite SAR data analysis and model simulations to enable a holistic coverage of the downstream wakes. The in situ measurements recorded on-board the research aircraft DO‑128 and remote sensing by laser scanner and SAR prove that wakes of more than 50 kilometers exist under certain atmospheric conditions. Turbulence occurs at the lateral boundaries of the wakes, due to shear between the reduced wind speed inside the wake and the undisturbed flow. The results also reveal that the atmospheric stability plays a major role in the evolution of wakes and can increase the wake length significantly by a factor of three or more. On the basis of the observations existing mesoscale and industrial models were validated and updated. The airborne measurement data is available at PANGAEA/ESSD.
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Understanding the influence of man-made infrastructures on fish population dynamics is an important issue for fisheries management. This is particularly the case because of the steady proliferation of offshore wind farms (OWFs). Several flatfish species are likely to be affected because areas with OWFs in place or planned for show a spatial overlap with their spawning grounds. This study focuses on six commercially important flatfish species in the North Sea: common sole (Solea solea), European plaice (Pleuronectes platessa), turbot (Scophthalmus maximus), brill (Scophtalmus rhombus), European flounder (Platichthys flesus), and common dab (Limanda limanda). We used a particle-tracking model (Larvae&Co) coupled to a 3D hydrodynamic model to assess the effects of spatial overlap of OWFs with the species’ spawning grounds on the larval fluxes to known nursery grounds. An important overlap between planned areas of OWFs and flatfish spawning grounds was detected, with a resulting proportion of settlers originating from those areas varying from 2% to 16%. Our study suggests that European plaice, common dab, and brill could be the most affected flatfish species, yet with some important local disparities across the North Sea. Consequently, the study represents a first step to quantify the potential impact of OWFs on flatfish settlement, and hence on their population dynamics.