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  <front>
    <journal-meta>
<journal-id journal-id-type="publisher">WE</journal-id>
<journal-title-group>
<journal-title>Web Ecology</journal-title>
<abbrev-journal-title abbrev-type="publisher">WE</abbrev-journal-title>
<abbrev-journal-title abbrev-type="nlm-ta">Web Ecol.</abbrev-journal-title>
</journal-title-group>
<issn pub-type="epub">1399-1183</issn>
<publisher><publisher-name>Copernicus Publications</publisher-name>
<publisher-loc>Göttingen, Germany</publisher-loc>
</publisher>
</journal-meta>

    <article-meta>
      <article-id pub-id-type="doi">10.5194/we-16-73-2016</article-id><title-group><article-title>Greening offshore wind with the Smart Wind Chart evaluation tool</article-title>
      </title-group><?xmltex \runningtitle{Greening offshore wind with the Smart Wind Chart evaluation tool}?><?xmltex \runningauthor{T.~Soukissian et al.}?>
      <contrib-group>
        <contrib contrib-type="author" corresp="yes" rid="aff1">
          <name><surname>Soukissian</surname><given-names>Takvor</given-names></name>
          <email>tsouki@hcmr.gr</email>
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff1">
          <name><surname>Reizopoulou</surname><given-names>Sofia</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff1">
          <name><surname>Drakopoulou</surname><given-names>Paraskevi</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff1">
          <name><surname>Axaopoulos</surname><given-names>Panagiotis</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff1 aff2">
          <name><surname>Karathanasi</surname><given-names>Flora</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff3">
          <name><surname>Fraschetti</surname><given-names>Simona</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff1">
          <name><surname>Bray</surname><given-names>Laura</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff4">
          <name><surname>Foglini</surname><given-names>Federica</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff1">
          <name><surname>Papadopoulos</surname><given-names>Anastasios</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff3">
          <name><surname>De Leo</surname><given-names>Francesco</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff1">
          <name><surname>Kyriakidou</surname><given-names>Chara</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff5">
          <name><surname>Voukouvalas</surname><given-names>Evangelos</given-names></name>
          
        <ext-link>https://orcid.org/0000-0002-8812-2613</ext-link></contrib>
        <contrib contrib-type="author" corresp="no" rid="aff1">
          <name><surname>Papathanassiou</surname><given-names>Evangelos</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff3 aff6">
          <name><surname>Boero</surname><given-names>Ferdinando</given-names></name>
          
        </contrib>
        <aff id="aff1"><label>1</label><institution>Hellenic Centre for Marine Research, P.O. Box 712, 190 13 Anavyssos, Greece</institution>
        </aff>
        <aff id="aff2"><label>2</label><institution>School of Naval Archit. &amp; Marine Eng., National Technical Univ. of Athens, Heroon Polytechneiou 15573, Zografos, Athens, Greece</institution>
        </aff>
        <aff id="aff3"><label>3</label><institution>Dipartimento di Scienze e Tecnologie Biologiche ed Ambientali, Università del Salento, CoNISMa, <?xmltex \hack{\break}?> Via Prov.le Lecce Monteroni, 73100 Lecce, Italy</institution>
        </aff>
        <aff id="aff4"><label>4</label><institution>CNR-National Research Council of Italy, ISMAR-Marine Sciences Institute, via Gobetti 101, <?xmltex \hack{\break}?> 40129, Bologna, Italy</institution>
        </aff>
        <aff id="aff5"><label>5</label><institution>European Commission, Joint Research Centre (JRC), Institute for Environment and Sustainability,
<?xmltex \hack{\break}?> Climate Risk Management Unit, Via Enrico Fermi 2749, 21027 Ispra (VA), Italy</institution>
        </aff>
        <aff id="aff6"><label>6</label><institution>Istituto di Scienze Marine del CNR, 16149, Genoa, Italy</institution>
        </aff>
      </contrib-group>
      <author-notes><corresp id="corr1">Takvor Soukissian (tsouki@hcmr.gr)</corresp></author-notes><pub-date><day>9</day><month>March</month><year>2016</year></pub-date>
      
      <volume>16</volume>
      <issue>1</issue>
      <fpage>73</fpage><lpage>80</lpage>
      <history>
        <date date-type="received"><day>1</day><month>November</month><year>2015</year></date>
           <date date-type="rev-recd"><day>18</day><month>February</month><year>2016</year></date>
           <date date-type="accepted"><day>25</day><month>February</month><year>2016</year></date>
      </history>
      <permissions>
<license license-type="open-access">
<license-p>This work is licensed under a Creative Commons Attribution 3.0 Unported License. To view a copy of this license, visit <ext-link ext-link-type="uri" xlink:href="http://creativecommons.org/licenses/by/3.0/">http://creativecommons.org/licenses/by/3.0/</ext-link></license-p>
</license>
</permissions><self-uri xlink:href="https://we.copernicus.org/articles/16/73/2016/we-16-73-2016.html">This article is available from https://we.copernicus.org/articles/16/73/2016/we-16-73-2016.html</self-uri>
<self-uri xlink:href="https://we.copernicus.org/articles/16/73/2016/we-16-73-2016.pdf">The full text article is available as a PDF file from https://we.copernicus.org/articles/16/73/2016/we-16-73-2016.pdf</self-uri>


      <abstract>
    <p>The development of offshore wind farms (OWFs) and the
establishment of marine protected areas (MPAs) comprise two main elements
for the production of clean energy, and the simultaneous maintenance and
protection of biodiversity in the Mediterranean and Black seas. Successful,
efficient, and sustainable coupling of these two aspects presumes that the
criteria for selecting suitable locations for the deployment of OWFs should
not only include technical-engineering terms (e.g. high wind energy
efficiency, bottom suitability, inland infrastructures) but also
ecological–environmental considerations (e.g. the least possible impact on
biodiversity, ecosystem functioning) and socio-economic aspects (e.g.
effects on coastal and marine activities, development of marine spatial
planning). In the context of the FP7 CoCoNet project, the integration
between OWFs and MPAs is based on four main steps: (i) the identification of
existing (networks of) MPAs focusing on the biodiversity distribution
patterns and current legislation, (ii) the coupling of offshore wind
potential within networks of MPAs, (iii) the evaluation of the knowledge
gained up to date and the theoretical approaches at the two pilot sites of
the Mediterranean and Black sea basins, and (iv) the development of the
“Smart Wind Chart”, a convenient and rational tool addressed to scientists
and policy makers for the evaluation of maritime policy management schemes.
The latter step comprises the core of this work.</p>
  </abstract>
    </article-meta>
  </front>
<body>
      

<sec id="Ch1.S1" sec-type="intro">
  <title>Introduction</title>
      <p>The exploitation of wind energy has long been recognized as a key element in
the common EU energy policy in order to reduce the dependence on fossil fuel
and emissions from carbon sources, to decouple energy costs from oil prices,
and to ensure a secure energy supply. Although onshore wind energy generation
is currently cheaper than offshore, finding new suitable onshore sites is
becoming increasingly difficult in Europe. Offshore wind energy (OWE) is an
attractive alternative solution to take advantage of marine winds, which
tend to be higher, more frequent, and less variable than inland winds.
Despite the tremendous development of offshore wind farms (OWFs) in the
northern European countries, with more than half of the installed offshore
capacity belonging to the UK, no full-scale OWFs have been developed yet in
the Mediterranean and Black seas.</p>
      <p>The development of OWFs in these two basins seems to be an appealing and
environmentally friendly pathway. According to Gaudiosi and Bori (2010), the
total wind energy production (offshore and onshore) could cover 10 % of
electricity demand of the Mediterranean countries by 2030. On the other
hand, the development of OWFs alongside other offshore (and coastal) human
activities and the imperative need for the conservation of marine habitats
seem to be, at first sight, heterogeneous (and often conflicting) aspects.
In this regard, it is not straightforward or evident how to harmonize these
aspects into a single holistic framework. The relevant arguments that have
been raised concerning the impacts of OWFs on the local biotic and abiotic
elements (EEA, 2009) necessitate the synthesis of
these seemingly opposing aspects into a single holistic framework, where
networks of marine protected areas (MPAs) will form the most important
marine environmental conservation and protection units.</p>
      <p>The EU-funded coordinated project “Towards COast to COast NETworks of
Marine Protected Areas (from the shore to the high and deep sea), coupled
with sea-based wind energy potential” (CoCoNet) is focused inter alia on the
fulfilment of the synthesis of a holistic framework related to the
protection and connection of the ecologically important areas in the
Mediterranean and Black seas along with the exploitation of the
climate-friendly offshore wind power (see also <uri>http://www.coconet-fp7.eu/</uri>). The CoCoNet project aims firstly to identify
interconnected MPA networks within the Mediterranean and Black seas at the
local, regional, and basin scale. According to Article 13 of the Marine Strategy
Framework Directive, coherent, representative, and interconnected networks of
MPAs should represent an integrated system of multiple protected areas
designed to conserve regional biodiversity and ecosystem function. In this
respect, the approaches considered for the evaluation of the degree of
connectivity at the spatial scale are currents, propagules, beta diversity
analysis on communities, and genetic diversity. The second main aim of the
CoCoNet project is linked to the exploitation of OWE and deals with the
integration of geotechnical, socioeconomic, and environmental aspects into a
geospatial tool in order to evaluate the feasibility of the installation of
OWFs in the examined basins. The identification of the “overall”
favourable OWF locations is important in order to secure the financial
viability and sustainability of the offshore project, as well as to minimize
the negative impacts and maximize the positive effects of OWF installations
in the marine environment as a whole. The major outputs from the CoCoNet
project are (i) a set of guidelines for the design, management, and
monitoring of networks of MPAs and the sustainable development of OWE along
with marine conservation goals, and (ii) the Smart Wind Chart (SWC).</p>

<?xmltex \floatpos{t}?><table-wrap id="Ch1.T1" specific-use="star"><caption><p>Ranking score and corresponding weightings of potential “go” areas.</p></caption><oasis:table frame="topbot"><oasis:tgroup cols="7">
     <oasis:colspec colnum="1" colname="col1" align="left"/>
     <oasis:colspec colnum="2" colname="col2" align="left"/>
     <oasis:colspec colnum="3" colname="col3" align="left"/>
     <oasis:colspec colnum="4" colname="col4" align="left"/>
     <oasis:colspec colnum="5" colname="col5" align="left"/>
     <oasis:colspec colnum="6" colname="col6" align="left"/>
     <oasis:colspec colnum="7" colname="col7" align="left"/>
     <oasis:thead>
       <oasis:row>  
         <oasis:entry colname="col1"/>  
         <oasis:entry colname="col2">Offshore wind</oasis:entry>  
         <oasis:entry colname="col3">Water</oasis:entry>  
         <oasis:entry colname="col4">Distance</oasis:entry>  
         <oasis:entry colname="col5">Proximity to very</oasis:entry>  
         <oasis:entry colname="col6">Electrical grid</oasis:entry>  
         <oasis:entry colname="col7">Bottom</oasis:entry>
       </oasis:row>
       <oasis:row rowsep="1">  
         <oasis:entry colname="col1"/>  
         <oasis:entry colname="col2">speed (10 m a.s.l.)</oasis:entry>  
         <oasis:entry colname="col3">depth</oasis:entry>  
         <oasis:entry colname="col4">from shore</oasis:entry>  
         <oasis:entry colname="col5">large or large ports</oasis:entry>  
         <oasis:entry colname="col6">infrastructure</oasis:entry>  
         <oasis:entry colname="col7">sediments</oasis:entry>
       </oasis:row>
     </oasis:thead>
     <oasis:tbody>
       <oasis:row>  
         <oasis:entry colname="col1">Categorization</oasis:entry>  
         <oasis:entry colname="col2">&gt; 6.9 m s<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> (5)</oasis:entry>  
         <oasis:entry colname="col3">10–40 m (5)</oasis:entry>  
         <oasis:entry colname="col4">10–20 km (5)</oasis:entry>  
         <oasis:entry colname="col5">0–100 km (5)</oasis:entry>  
         <oasis:entry colname="col6">&gt; 400 kV (5)</oasis:entry>  
         <oasis:entry colname="col7">Sand (5)</oasis:entry>
       </oasis:row>
       <oasis:row>  
         <oasis:entry colname="col1">(rank)</oasis:entry>  
         <oasis:entry colname="col2">6.3–6.9 m s<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> (4)</oasis:entry>  
         <oasis:entry colname="col3">–</oasis:entry>  
         <oasis:entry colname="col4">5–10 km (4)</oasis:entry>  
         <oasis:entry colname="col5">100–200 km (4)</oasis:entry>  
         <oasis:entry colname="col6">225–400 kV (4)</oasis:entry>  
         <oasis:entry colname="col7">–</oasis:entry>
       </oasis:row>
       <oasis:row>  
         <oasis:entry colname="col1"/>  
         <oasis:entry colname="col2">5.7–6.3 m s<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> (3)</oasis:entry>  
         <oasis:entry colname="col3">70–200 m (3)</oasis:entry>  
         <oasis:entry colname="col4">20–100 km (3)</oasis:entry>  
         <oasis:entry colname="col5">200–300 km (3)</oasis:entry>  
         <oasis:entry colname="col6">36–225 kV (3)</oasis:entry>  
         <oasis:entry colname="col7">Mud (3)</oasis:entry>
       </oasis:row>
       <oasis:row>  
         <oasis:entry colname="col1"/>  
         <oasis:entry colname="col2">4.9–5.7 m s<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> (2)</oasis:entry>  
         <oasis:entry colname="col3">–</oasis:entry>  
         <oasis:entry colname="col4">0–5 km (2)</oasis:entry>  
         <oasis:entry colname="col5">300–500 km (2)</oasis:entry>  
         <oasis:entry colname="col6">&lt; 36 kV (2)</oasis:entry>  
         <oasis:entry colname="col7">–</oasis:entry>
       </oasis:row>
       <oasis:row rowsep="1">  
         <oasis:entry colname="col1"/>  
         <oasis:entry colname="col2">4.1–4.9 m s<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> (1)</oasis:entry>  
         <oasis:entry colname="col3">40–70 m (1)</oasis:entry>  
         <oasis:entry colname="col4">&gt; 100 km (1)</oasis:entry>  
         <oasis:entry colname="col5">&gt; 500 km (1)</oasis:entry>  
         <oasis:entry colname="col6">Distribution grid (1)</oasis:entry>  
         <oasis:entry colname="col7">Rock (1)</oasis:entry>
       </oasis:row>
       <oasis:row>  
         <oasis:entry colname="col1">Weighting (%)</oasis:entry>  
         <oasis:entry colname="col2">35</oasis:entry>  
         <oasis:entry colname="col3">25</oasis:entry>  
         <oasis:entry colname="col4">15</oasis:entry>  
         <oasis:entry colname="col5">5</oasis:entry>  
         <oasis:entry colname="col6">15</oasis:entry>  
         <oasis:entry colname="col7">5</oasis:entry>
       </oasis:row>
     </oasis:tbody>
   </oasis:tgroup></oasis:table></table-wrap>

      <p>Aiming our attention at the second major output, SWC represents a robust and
unbiased favourable site identification approach that should be implemented
for the integration of all the available information in order to illustrate
potential sites for deploying offshore wind installations and to join the
networks of MPAs. The visualizing aiding tool for this approach is based on
Geographic Information System (GIS) environment. During recent years, due to
its flexibility and available features, this spatial analysis tool has been
extensively used by renewable energy developers in the context of
multi-criteria decision analysis for OWF site selection procedure (see, for
example, Atici et al., 2015). Moreover, there are recent studies evaluating
OWE development through GIS tools, but only at a national level; for
instance, there are assessment studies for Denmark (Möller et al.,
2012), Greece (Vagiona and Karanikolas, 2012), Portugal (Costa et al.,
2006), and the UK (Cavazzi and Dutton, 2016). Although there are numerous
studies proposing multi-criteria approaches for wind farm siting (mainly
onshore), an integrated approach combining the aforementioned viewpoints
with evaluation procedures is still missing for offshore wind applications
with reference to an extended spatial scale, such as a large basin.</p>
      <p>In this work, the procedure for the implementation of the SWC is presented
and applied in the Mediterranean Sea (MS), focused on the corresponding
pilot area located in the northern Ionian Sea, in order to formalize the
route leading to the identification of favourable zones for OWF development.
The comparability of potential locations for developing offshore wind
projects is based on quantifiable multi-parameter technical criteria, which
are considered of most importance in the OWE industry, combined with
environmental restrictions.</p>
      <p>The structure of this work is the following: in Sect. 2, the methodology
developed in the context of the SWC analysis is presented in more detail. In
Sect. 3, the input data, including technical and environmental factors,
and the pilot study area in the MS are described at length, and the results
obtained after the implementation of the SWC are presented in the subsequent
section. In Sect. 5, there is a discussion with reference to some important aspects
related to potential misinterpretations of the SWC results and some
generic knowledge/information gaps that were encountered at the basin scale. In the last section, some concluding remarks and suggestions are
provided for further research.</p>
</sec>
<sec id="Ch1.S2">
  <title>Methodology for the development of the Smart Wind Chart</title>
      <p>A first step towards the development of a structured methodology, from which
optimal OWF sites are determined, is the identification of the main key
actors that are involved in the development of OWE projects and are
characterized by different, and often contradictory, priorities and
requirements. Some of the included key actors include government bodies,
policy makers, financing mechanisms, scientists, local communities, NGOs,
and wind industry. Seen in this context, a holistic approach for OWF
development requires the rational interweaving of geotechnical/engineering,
socioeconomic, and environmental aspects. The development of the SWC moves
towards this direction.</p>
      <p>SWC is a flexible tool for the comparison and evaluation of the potential
OWF locations according to some quantifiable multi-parameter eligibility
criteria. However, the locations evaluated through this tool should not be
considered as direct suggestions for future OWF development, but merely as
favourable candidate areas that deserve further in-depth assessment in the
context of detailed feasibility studies. Consequently, the SWC should be
regarded as a marine planning tool rather than a decision-making platform.</p>
      <p>There are two major steps for the implementation of the SWC: (i) preparatory
actions and (ii) processing phase (see also Fig. 1).
Preparatory actions include the assessment of the most important
quantifiable factors (technical criteria), the factor rating table, and the
identification of “no-go/restricted” areas, i.e. areas that are either
excluded from further consideration or restricted under specific conditions,
mainly due to environmental considerations. The primary technical factors
consist of mean annual wind speed and bottom depth whilst the additional
factors that were considered include distance to shore, proximity to ports,
electrical grid infrastructure, and type of bottom sediments. These factors
are categorized in rating tables, and rankings from 1 (least feasible) to 5
(most feasible) are provided for each category. Then, each factor is
assigned a weight corresponding to its relative importance on the
feasibility of an OWF development. Thus, the overall score for each location
is a combination between the factor rating table and the relative weights
assigned to each factor (see Table 1). A simple
linearly weighted methodology was adopted in order to keep the methodology
as straightforward as possible and be easily adoptable and flexible
according to the different demands and requirements of the involved key
actors. Moreover, future alteration of costs, diversity of local conditions,
and any progress in offshore wind technology can be easily integrated in the
developed methodology.</p>
      <p>In this approach, the exclusion/restriction of an area is primarily based on
environmental restrictions, namely national protected sites/MPAs and Natura
2000 sites, areas characterized by meadows of the seagrass <italic>Posidonia oceanica</italic>, fields of the
algae <italic>Phyllophora crispa</italic>, biogenic habitats such as coralligenous, marl, and deep sea
coral formations. Let us note that national protected areas/MPAs and Natura
2000 sites may belong to either restricted or no-go areas; they can be
definitively characterized as no-go areas after detailed  in situ assessment. On the
other hand, areas where the rest of the environmental features are met are
characterized as no-go areas; the sensitivity and the vital role (at
biological/ecological level) of such features in maintaining the marine
coastal equilibrium and preserving marine biodiversity over the long term
impose the need to prohibit any (harmful) human marine activity in the
corresponding areas. For example, the Mediterranean endemic seagrass species
<italic>Posidonia oceanica</italic> is considered among the natural habitats requiring conservation under the
EU's Habitats and Water Framework Directive, since it is among the few
representatives of biological quality elements in the MS waters due to its
recognized ecological indicator possibilities (Lopez y Royo et al., 2011),
while <italic>Phyllophora</italic> beds supply benthic primary production and water oxygenation in the
circalittoral zone, and provide breeding and feeding grounds, and nursery
for diverse invertebrate and fish species (Salomidi et al., 2012). Other
restrictions may be attributed to marine and maritime uses (e.g.
military exercise areas, areas of fisheries and aquaculture, shipping lanes,
oil and gas extraction areas). However, such considerations are the main
object of marine spatial planning and refer to site-specific studies
concerning OWF development (see Sect. 5 for more details).</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F1" specific-use="star"><caption><p>Flow chart for the development of the SWC.</p></caption>
        <?xmltex \igopts{width=455.244094pt}?><graphic xlink:href="https://we.copernicus.org/articles/16/73/2016/we-16-73-2016-f01.png"/>

      </fig>

      <p>In the processing phase, the two most important (technical) parameters have
been firstly taken into consideration for the primary identification of the
site suitability: mean annual wind speed and bottom depth. The former is
evaluated for the grid points that are not under any environmental
restriction, and then the corresponding value for the latter one is
extracted. Regarding mean annual wind speed, the lowest threshold was set to
4.1 m s<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> at 10 m a.s.l.  (meters above sea level). This rather low limit is
justifiable since Eta-SKIRON underestimates (sometimes significantly) wind
speed with respect to satellite data and buoy measurements (see Soukissian
and Papadopoulos, 2015). Regarding bottom depth, three different water depth
ranges were considered: (i) 0–40 m (“shallow waters”), (ii) 40–70 m
(“intermediate” or “transitional waters”), and (iii) 70–200 m (“deep
waters”). Shallow and intermediate water depths refer to monopile,
gravity-based, tripod, jacket, and tripile supporting structure, while deep
waters refer to floating wind turbines technologies. Although fixed
foundations are to date dominant in the offshore wind market, floating
structures seem to be a viable alternative solution, especially for the
Mediterranean waters, provided that the relevant floating technology
reach the desired maturity level in the coming years.</p>
      <p>If the combination of wind speed and bottom depth satisfies the adopted
thresholds (i.e. mean annual wind speeds greater than 4.1 m s<inline-formula><mml:math display="inline"><mml:msup><mml:mi/><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:math></inline-formula> at 10 m
a.s.l. height and water depths smaller than 200 m), then the point (area) is
characterized as “potentially go” area and is graded according to the
examined factors and the relative weights, so that the final rankings of the
locations are derived. At the end of the analysis, the potentially suitable
sites worth being further assessed for OWF development are identified with
the highest overall scores characterizing the most favourable sites. Let us
note that any preliminary national spatial planning for OWFs is also
included in the analysis. Such plans exist for France, Greece, Italy, and
Spain; however, some of these plans are currently under revision.</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F2" specific-use="star"><caption><p>Results from the SWC as regards technical
criteria in the Mediterranean pilot area: score for wind resource <bold>(a)</bold>, score for bottom depth <bold>(b)</bold>,
score for distance from the shore <bold>(c)</bold>, score for proximity to ports <bold>(d)</bold>, score for bottom sediment
type <bold>(e)</bold>, and score for electrical grid infrastructure <bold>(f)</bold>.</p></caption>
        <?xmltex \igopts{width=369.885827pt}?><graphic xlink:href="https://we.copernicus.org/articles/16/73/2016/we-16-73-2016-f02.jpg"/>

      </fig>

</sec>
<sec id="Ch1.S3">
  <title>Data and study area</title>
<sec id="Ch1.S3.SS1">
  <title>Data sources</title>
      <p>Wind data can be obtained from various sources that may use different
measuring principles, devices, and configurations; these variations
contribute to uncertainties in the long-term wind speed (and resource)
assessment and should be properly considered (Soukissian and Papadopoulos,
2015). In this work, the results obtained from the Eta-SKIRON model
(Papadopoulos et al., 2011) were used since they have the finest available
spatial (<inline-formula><mml:math display="inline"><mml:mrow><mml:mn mathvariant="normal">1</mml:mn><mml:mo>/</mml:mo><mml:msup><mml:mn>10</mml:mn><mml:mo>∘</mml:mo></mml:msup><mml:mo>×</mml:mo><mml:mn mathvariant="normal">1</mml:mn><mml:mo>/</mml:mo><mml:msup><mml:mn>10</mml:mn><mml:mo>∘</mml:mo></mml:msup></mml:mrow></mml:math></inline-formula>) and temporal (3 h) resolution.
The simulation period is 15 years (1995–2009) with reference height at 10 m a.s.l., and the initial conditions were provided by the ERA-40 reanalysis data
and the operational analyses of the European Centre for Medium-Range Weather
Forecasts (ECMWF), through the Hellenic National Meteorological Service. The
Eta-SKIRON model is based on the Eta-NCEP (National Centre for Environmental
Prediction) model and was developed for operational purposes. Its unique
capabilities make it appropriate for mesoscale simulations in regions with
varying geographic characteristics.</p>
      <p>The bathymetric information was obtained by the EMODnet Bathymetry portal
(generated in February 2015) with grid size resolution <inline-formula><mml:math display="inline"><mml:mrow><mml:mn mathvariant="normal">1</mml:mn><mml:mo>/</mml:mo><mml:mn mathvariant="normal">8</mml:mn><mml:mo>×</mml:mo><mml:mn mathvariant="normal">1</mml:mn><mml:mo>/</mml:mo><mml:mn mathvariant="normal">8</mml:mn></mml:mrow></mml:math></inline-formula> arcmin
(see also <uri>http://www.emodnet-hydrography.eu/</uri>). This bathymetry
has been produced from bathymetric survey data and aggregated bathymetry
data sets collated from public and private organizations.</p>
      <p>Distance from the shore is highly connected with socio-economic aspects; a short
distance from the shore minimizes all the costs related to the technical
infrastructure, installation and maintenance activities (i.e. capital and
operating expenditures), but on the other hand it maximizes visual
disturbance. The coastline from EEA was used for delimiting the specified
distances from the shore (Table 1).</p>
      <p>Similarly, regarding proximity to ports, as distances from ports shorten,
the accessibility to the offshore wind project area is faster and more
economical. These distances were derived from the World Port Index Database
of the National Geospatial Intelligence Agency (WPI 2015 pub. 150,
<uri>http://msi.nga.mil/NGAPortal/MSI.portal</uri>). The ports included in the analysis
are those whose controlling depth of the principal or deepest channel or the
greatest depth alongside the wharf/pier is over 10 m.</p>
      <p>Regarding bottom sediments, the existence of cobbles, boulders, dense or
soft sand, etc., affects the foundation design and cable laying. The type of
bottom sediments was derived via digitization of the Unconsolidated Bottom
Surface Sediments of the International Bathymetric Chart of the
Mediterranean (IBCM) of the Intergovernmental Oceanographic Commission, and
the scale of the corresponding map is <inline-formula><mml:math display="inline"><mml:mrow><mml:mn mathvariant="normal">1</mml:mn><mml:mo>:</mml:mo><mml:mn>1 000 000</mml:mn></mml:mrow></mml:math></inline-formula>.</p>
      <p>The assessment of the existing electrical grid infrastructure was based on
the 2014 ENTSO-E Interconnected Network Grid Maps (see <uri>www.entsoe.eu</uri>). ENTSO-E's Interconnected Grid Map is one of the
publications of this association. It displays the electricity transmission
grid as of 31 December 2014, and the scale of the map is <inline-formula><mml:math display="inline"><mml:mrow><mml:mn mathvariant="normal">1</mml:mn><mml:mo>:</mml:mo><mml:mn>4 000 000</mml:mn></mml:mrow></mml:math></inline-formula>.</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F3" specific-use="star"><caption><p>Overall score for candidate locations for OWF
development in the Mediterranean pilot area <bold>(a)</bold>. Overall score combined with
habitats (coralligenous formations, marls, <italic>Posidonia oceanica</italic>
meadows) with high suitability in the Mediterranean pilot area <bold>(b)</bold>.</p></caption>
          <?xmltex \igopts{width=341.433071pt}?><graphic xlink:href="https://we.copernicus.org/articles/16/73/2016/we-16-73-2016-f03.jpg"/>

        </fig>

      <p>The data of all the environmental variables were derived from the
“Mediterranean Sensitive Habitat” (MEDISEH) project (see <uri>http://mareaproject.net/</uri>). These data were partially based on (i) revision of
historical and current data from the compilation of published and
unpublished information, and (ii) habitat suitability modelling that was
applied to fill spatial information gaps on the distribution of such species
by predicting the locations that habitats are likely to be suitable for
species to live (Giannoulaki et al., 2013). For the pilot site, the model
results were based on a large number of personal observations that were
collected related to the occurrence of <italic>Posidonia oceanica</italic>, and some point data sources for
coralligenous and marl beds.</p>
</sec>
<sec id="Ch1.S3.SS2">
  <title>Description of study area</title>
      <p>The Diapontia Islands, an island complex opposite to the north-western
coasts of Corfu, Greece, were selected as a pilot area for OWF
development in the context of the CoCoNet project and were used to develop
the rationale of SWC. The main reason for this selection is that the Greek
government (by the Ministry of Environment, Energy and Climate Change in
2011) has already preselected the area for potential OWF development; from
this point of view, it comprises a realistic case to be studied in depth.
The relevant activities are scheduled to take place in various phases. In
the first phase (which is at the concept/early planning status), the
foreseen capacity is 15 MW (three turbines each of 5 MW nominal power) (see
<uri>www.4coffshore.com</uri>).</p>
      <p>On the other hand, the selected area encompasses features that are very
representative of the coastal areas of the MS. Specifically, Diapontia
Islands do not belong to the few top-ranked areas according to the wind
resource availability while the wind and wave climate is rather mild.
Moreover, a Natura 2000 site is designated in the proximity of the examined
area and, in the meantime, the wider area is well developed as regards
tourism and fisheries, which comprise two of the most characteristic marine
uses in the MS.</p>
</sec>
</sec>
<sec id="Ch1.S4">
  <title>Results</title>
      <p>Based on the methodology discussed in Sect. 2, the results for each
examined parameter are firstly presented and described separately
(Fig. 2a–f) for the pilot site in order to
identify step by step favourable candidate locations for offshore wind
exploitation, and then the final output is depicted
(Fig. 3a) after combining the data sets via raster
calculation method.</p>
      <p>Specifically, the score as regards wind resource
(Fig. 2a) is marginally appropriate (rank 1) for
potential OWF development in the pilot site, while bottom depth
(Fig. 2b) is ideal and characterized by the best
score (rank 5). The score for distance from the shore
(Fig. 2c) ranges between 2 and 4 in the wider
examined pilot area while the corresponding score for distance from ports
(Fig. 2d) is right before the top (rank 4).
Finally, from Fig. 2e and f, it is evident that the bottom sediment
type and the existing electrical grid infrastructure, respectively, are
optimum for potential OWF development in this site (rank 5), since the
existent electrical grid infrastructure seems to be adequate and the sea bed
composition is sandy. The final scores as regards the examined technical
parameters are depicted in Fig. 3a. The total
technical suitability rating for the Othonoi site (one of the main islands of Diapontia Islands), shown with an arrow in the
same figure, is between 3.0 and 3.5. Let us reiterate that the overall score of
the candidate areas for OWF development are obtained by applying a linear
weighting scheme. Comparing this rank to the other locations and according
to the overall score scale, this area is considered “fair” as regards its
favourability for OWF development.</p>
      <p><?xmltex \hack{\newpage}?>Finally, superimposing the technical criteria with available data based on
environmentally sensitive areas, we obtain the synthetic
Fig. 3b. According to the obtained results, the
likelihood for formation of <italic>Posidonia oceanica</italic> meadows, coralligenous formations, and
marls is not very high in the study area based on the simulation
models. However, in-depth assessment of these environmental aspects along
with submarine archaeological findings and migratory bird routes are some of
the main objectives of environmental impact assessment studies and require a
systematic survey of any candidate area for OWF development. In conclusion,
with a total relative score 3.0–3.5, it seems that Othonoi is a good
choice in the northern part of the Ionian Sea. In this respect, the site has
been rightly pre-selected from the Greek government as a site for potential OWF
development.</p>
</sec>
<sec id="Ch1.S5">
  <title>Discussion</title>
      <p>For the sake of completeness of this work, in this section some problems
encountered during the development and implementation of the SWC are
presented, along with some relevant remarks as regards the interpretation of
the SWC results. The majority of the problems are related to the main
knowledge/information gaps that were identified during the background data
collection and assessment.</p>
      <p>The first issue refers to data availability and quality. Specifically,
regarding wind data the following (interconnected) issues are of most
importance:
<list list-type="custom"><list-item><label>i.</label><p>There is lack of high-resolution data at the basin scale. High-resolution
wind data (usually obtained from numerical models or gridded satellite
products) are necessary for the accurate estimation of the wind energy
characteristics in nearshore/coastal areas (where the coastal morphology
plays an important role in wind patterns) and the more detailed estimation
of the relevant uncertainties.</p></list-item><list-item><label>ii.</label><p>There is lack of offshore measurements at the usual operational turbine hub
heights (i.e. within the range of 70–110 m a.s.l.). Measured wind data of the
wind profile are necessary in order to estimate reliably the actual wind
energy characteristics at hub heights. The wind profile can be accurately
deduced only by utilizing measured wind data at various heights a.s.l., which,
currently, may be obtained either by meteorological masts or lidar (light
detection and ranging) measurements. Furthermore, such measurements are also
necessary in order to evaluate less reliable data sources such as numerical
models or satellite products. However, there is lack of lidar measurements
in the Mediterranean and Black seas, and the installation, operation and maintenance of
meteorological masts are expensive procedures, especially for offshore
locations.</p></list-item></list>
The data quality issue is also associated with the inherent uncertainties of
wind speed data and, consequently, wind power density estimates, i.e. the
most determinative parameter for SWC analysis. Before the implementation of
the SWC, four different wind data sources (measurements from two buoy
networks, satellite products, and results from two numerical weather
prediction models) were assessed for the MS in order to be statistically
analysed and evaluated. The analysis revealed that there were statistically
significant deviations between the examined data sources. However, as it was
recommended by Soukissian and Papadopoulos (2015), calibration schemes can
be efficient in local spatial scales while it is very risky to apply them in
large spatial scales, such as the examined basins. Eventually, the most
representative data source with the highest spatiotemporal resolution was
adopted. On the other hand, such uncertainties necessarily should be taken
into consideration when site-specific studies are made for potential OWF
development.</p>
      <p>More detailed spatial information is vital regarding also marine
environmental data. The more accurate mapping of important habitats at the
critical bottom depths for OWF development, such as meadows of <italic>Posidonia oceanica</italic>, fields of
<italic>Phyllophora crispa</italic>, coralligenous, and deep-water white coral formations, provide necessary
background information for efficient OWF planning in wide areas. Moreover,
bird migration routes over the same areas should be defined as accurately as
possible and relevant quantitative information should be available.</p>
      <p>However, the most important information gap seems to be the lack of a
basin-wide marine spatial planning. Some European Mediterranean countries
have coarse preliminary spatial plans and very few detailed plans at
regional level tailor-made for OWE projects (e.g. at the Gulf of Lions in
France). In addition, since OWF installations are expected to affect coastal
zone activities, integrated coastal zone management (combined with relevant
information on the socio-economic status of the area) is also required as a
necessary complementary tool for marine spatial planning. In this regard,
socio-economic aspects could be included in future SWC applications, even in
extended sea areas.</p>
      <p>Another aspect to call attention to, especially when interpreting the SWC
results, is related to the appropriate consideration of the involved spatial
scales. The spatial extent of the examined basin, the heterogeneity of the
considered data sets, and the data spatial scales do not allow a detailed (in
the spatial domain) and in-depth (as regards the involved parameters)
analysis, let alone the lack of data, especially with respect to
socio-economic aspects. Specifically, the geographical extent of the MS is
of the order of several hundreds of kilometres, which assigns the magnitude
of the spatial scale, and, in turn, the data involved. The next most
important spatial scale is connected to the spatial resolution of wind data.
The resolution of the numerical model we have used is roughly of the order
of 10 km <inline-formula><mml:math display="inline"><mml:mo>×</mml:mo></mml:math></inline-formula> 10 km (see also Sect. 3.1). Here, the underlying assumption is
that the wind information contained in the area corresponding to the model
grid point (i.e. 100 km<inline-formula><mml:math display="inline"><mml:mrow><mml:msup><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msup><mml:mo>)</mml:mo></mml:mrow></mml:math></inline-formula> is homogeneous and representative of the
entire “pixel”. Although this assumption can be valid for morphologically
homogeneous sea areas (e.g. offshore areas), there are cases in which it may be
incorrect (e.g. for coastal areas). Moreover, the spatial resolution of
bathymetric data is, in principle, not compatible with the wind data
resolution, since it is roughly of the order of 200 m. Let us also mention
that a large part of bathymetric data have been produced by interpolation
methods and thus cannot be considered as fully accurate. In this respect,
outputs of the SWC can only provide some preliminary suggestions for
potential OWF development, mainly through indicative zones, in the examined
basin. Since this spatial scale may lead to misjudgements as regards the
development of offshore wind projects, a detailed local assessment of
technical, socio-economic, and environmental features at the finest possible
spatial scale is required for localized cases in order to reach final
decisions and form strategies.</p>
</sec>
<sec id="Ch1.S6" sec-type="conclusions">
  <title>Conclusions</title>
      <p>The identification of potential zones for offshore wind farm development is
a very delicate procedure and should be based on sufficient and high-quality
data regarding both biotic and abiotic elements of the marine environment.
An integrated and interdisciplinary approach has been adopted integrating
technical, and environmental criteria and data related to the offshore wind
energy exploitation. The integration is implemented through a robust
tool – the so-called Smart Wind Chart, aiming to maintain and secure the
sustainable blue growth in the Mediterranean and Black seas through the
support of offshore wind energy projects and marine habitat conservation.
The application of the Smart Wind Chart in the northern Ionian Sea provided one of the
most favourable candidate areas for offshore wind farm development in this
part of the Hellenic seas, which, in this case, coincides with the
suggestion of the Greek government. On the other hand, some knowledge and
information gaps were evident during the implementation of the Smart Wind
Chart while some additional aspects, related to the uncertainties of the
wind data involved and the involved spatial scale of the data, were
explicated in order to prevent misinterpretations of the outputs.</p>
      <p>It is, however, important to note that the results obtained from the Smart
Wind Chart cannot replace an in-depth environmental and socio-economic
impact assessment study, which includes the corresponding mapping and
monitoring of any candidate area and, in general, more detailed analysis
with high-resolution data. Considering the future introduction of offshore
wind farm installations in the Mediterranean Sea, the potential impacts
should be closely linked to the environmental and ecological processes.
Standardized monitoring protocols and a clear guidance on the assumptions
and requirements of monitoring programmes are necessary, in agreement with
the scientific community and regulatory bodies (Franco et al., 2015).</p>
</sec>

      
      </body>
    <back><ack><title>Acknowledgements</title><p>The research leading to these results has received funding from the European
Community's Seventh Framework Programme (FP7/2007-2013) under grant
agreement no. 287844 for the project “Towards COast to Coast NETworks of
marine protected areas (from the shore to the high and deep sea), coupled
with sea-based wind energy potential”.<?xmltex \hack{\newline}?><?xmltex \hack{\newline}?>
Edited by:  D. Montesinos<?xmltex \hack{\newline}?>
Reviewed by: two anonymous referees</p></ack><ref-list>
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    <!--<article-title-html>Greening offshore wind with the Smart Wind Chart evaluation tool</article-title-html>
<abstract-html><p class="p">The development of offshore wind farms (OWFs) and the
establishment of marine protected areas (MPAs) comprise two main elements
for the production of clean energy, and the simultaneous maintenance and
protection of biodiversity in the Mediterranean and Black seas. Successful,
efficient, and sustainable coupling of these two aspects presumes that the
criteria for selecting suitable locations for the deployment of OWFs should
not only include technical-engineering terms (e.g. high wind energy
efficiency, bottom suitability, inland infrastructures) but also
ecological–environmental considerations (e.g. the least possible impact on
biodiversity, ecosystem functioning) and socio-economic aspects (e.g.
effects on coastal and marine activities, development of marine spatial
planning). In the context of the FP7 CoCoNet project, the integration
between OWFs and MPAs is based on four main steps: (i) the identification of
existing (networks of) MPAs focusing on the biodiversity distribution
patterns and current legislation, (ii) the coupling of offshore wind
potential within networks of MPAs, (iii) the evaluation of the knowledge
gained up to date and the theoretical approaches at the two pilot sites of
the Mediterranean and Black sea basins, and (iv) the development of the
“Smart Wind Chart”, a convenient and rational tool addressed to scientists
and policy makers for the evaluation of maritime policy management schemes.
The latter step comprises the core of this work.</p></abstract-html>
<ref-html id="bib1.bib1"><label>1</label><mixed-citation>
Atici, K. B., Simsek, A. B., Ulucan, A., and Tosun, M. U.: A GIS-based Multiple
Criteria Decision Analysis approach for wind power plant site selection,
Utilities Policy, 37, 86–96, <a href="http://dx.doi.org/10.1016/j.jup.2015.06.001" target="_blank">doi:10.1016/j.jup.2015.06.001</a>,
2015.
</mixed-citation></ref-html>
<ref-html id="bib1.bib2"><label>2</label><mixed-citation>
Cavazzi, S.  and Dutton, A. G.: An Offshore Wind Energy Geographic
Information System (OWE-GIS) for assessment of the UK's offshore wind energy
potential, Part 1, Renew. Energ., 87, 212–228,
<a href="http://dx.doi.org/10.1016/j.renene.2015.09.021" target="_blank">doi:10.1016/j.renene.2015.09.021</a>, 2016.
</mixed-citation></ref-html>
<ref-html id="bib1.bib3"><label>3</label><mixed-citation>
Costa, P., Simoes, T., and Estanquero, A.: Assessment of Sustainable Offshore Wind
Potential in Portugal, in: Proceedings of European Wind Energy Conference and
Exhibition (EWEC), Athens, Greece, 27 February–2 March 2006, 3, 2006.

</mixed-citation></ref-html>
<ref-html id="bib1.bib4"><label>4</label><mixed-citation>
European Environmental Agency: Europe's onshore and offshore wind energy
potential. An assessment of environmental and economic constraints,
Technical report No 6, 90 pp., 2009.
</mixed-citation></ref-html>
<ref-html id="bib1.bib5"><label>5</label><mixed-citation>
Franco, A., Quintino, V., and Elliott M.: Benthic monitoring and sampling
design and effort to detect spatial changes: A case study using data from
offshore wind farm sites, Ecol. Indicators, 57, 298–304, <a href="http://dx.doi.org/10.1016/j.ecolind.2015.04.040" target="_blank">doi:10.1016/j.ecolind.2015.04.040</a>, 2015.
</mixed-citation></ref-html>
<ref-html id="bib1.bib6"><label>6</label><mixed-citation>
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