Sustainable use of marine resources through offshore wind and mussel farm co-location

Giacomo R. Di Tullio, Patrizio Mariani, Guido Benassai*, Diana Di Luccio, Luisa Grieco

*Corresponding author for this work

Research output: Contribution to journalJournal articleResearchpeer-review

Abstract

Marine Spatial Planning (MSP) can offer significant benefits in terms of economic conservation strategies, optimizing spatial planning and minimizing the impact on the environment. In this paper, we focused on the application of multi-criteria evaluation (MCE) technique for co-locating offshore wind farms and open-water mussel cultivation. An index of co-location sustainability (SI) was developed based on the application of MCE technique constructed with physical and biological parameters on the basis of remote-sensing data. The relevant physical factors considered were wind velocity, depth range, concerning the site location for energy production, and sea surface temperature anomaly. The biological variables used were Chlorofill-a (as a measurement of the productivity) and Particle Organic Carbon(POC) concentration, in order to assess their influence on the probable benefits and complete the requirements of this management framework. This SI can be easily implemented to do a first order selection of the most promising areas to be more specifically studied in a second order approach based on local field data.
Original languageEnglish
JournalEcological Modelling
Volume367
Pages (from-to)34-41
ISSN0304-3800
DOIs
Publication statusPublished - 2018

Cite this

Di Tullio, Giacomo R. ; Mariani, Patrizio ; Benassai, Guido ; Di Luccio, Diana ; Grieco, Luisa. / Sustainable use of marine resources through offshore wind and mussel farm co-location. In: Ecological Modelling. 2018 ; Vol. 367. pp. 34-41.
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title = "Sustainable use of marine resources through offshore wind and mussel farm co-location",
abstract = "Marine Spatial Planning (MSP) can offer significant benefits in terms of economic conservation strategies, optimizing spatial planning and minimizing the impact on the environment. In this paper, we focused on the application of multi-criteria evaluation (MCE) technique for co-locating offshore wind farms and open-water mussel cultivation. An index of co-location sustainability (SI) was developed based on the application of MCE technique constructed with physical and biological parameters on the basis of remote-sensing data. The relevant physical factors considered were wind velocity, depth range, concerning the site location for energy production, and sea surface temperature anomaly. The biological variables used were Chlorofill-a (as a measurement of the productivity) and Particle Organic Carbon(POC) concentration, in order to assess their influence on the probable benefits and complete the requirements of this management framework. This SI can be easily implemented to do a first order selection of the most promising areas to be more specifically studied in a second order approach based on local field data.",
author = "{Di Tullio}, {Giacomo R.} and Patrizio Mariani and Guido Benassai and {Di Luccio}, Diana and Luisa Grieco",
year = "2018",
doi = "10.1016/j.ecolmodel.2017.10.012",
language = "English",
volume = "367",
pages = "34--41",
journal = "Ecological Modelling",
issn = "0304-3800",
publisher = "Elsevier",

}

Sustainable use of marine resources through offshore wind and mussel farm co-location. / Di Tullio, Giacomo R.; Mariani, Patrizio; Benassai, Guido; Di Luccio, Diana; Grieco, Luisa.

In: Ecological Modelling, Vol. 367, 2018, p. 34-41.

Research output: Contribution to journalJournal articleResearchpeer-review

TY - JOUR

T1 - Sustainable use of marine resources through offshore wind and mussel farm co-location

AU - Di Tullio, Giacomo R.

AU - Mariani, Patrizio

AU - Benassai, Guido

AU - Di Luccio, Diana

AU - Grieco, Luisa

PY - 2018

Y1 - 2018

N2 - Marine Spatial Planning (MSP) can offer significant benefits in terms of economic conservation strategies, optimizing spatial planning and minimizing the impact on the environment. In this paper, we focused on the application of multi-criteria evaluation (MCE) technique for co-locating offshore wind farms and open-water mussel cultivation. An index of co-location sustainability (SI) was developed based on the application of MCE technique constructed with physical and biological parameters on the basis of remote-sensing data. The relevant physical factors considered were wind velocity, depth range, concerning the site location for energy production, and sea surface temperature anomaly. The biological variables used were Chlorofill-a (as a measurement of the productivity) and Particle Organic Carbon(POC) concentration, in order to assess their influence on the probable benefits and complete the requirements of this management framework. This SI can be easily implemented to do a first order selection of the most promising areas to be more specifically studied in a second order approach based on local field data.

AB - Marine Spatial Planning (MSP) can offer significant benefits in terms of economic conservation strategies, optimizing spatial planning and minimizing the impact on the environment. In this paper, we focused on the application of multi-criteria evaluation (MCE) technique for co-locating offshore wind farms and open-water mussel cultivation. An index of co-location sustainability (SI) was developed based on the application of MCE technique constructed with physical and biological parameters on the basis of remote-sensing data. The relevant physical factors considered were wind velocity, depth range, concerning the site location for energy production, and sea surface temperature anomaly. The biological variables used were Chlorofill-a (as a measurement of the productivity) and Particle Organic Carbon(POC) concentration, in order to assess their influence on the probable benefits and complete the requirements of this management framework. This SI can be easily implemented to do a first order selection of the most promising areas to be more specifically studied in a second order approach based on local field data.

U2 - 10.1016/j.ecolmodel.2017.10.012

DO - 10.1016/j.ecolmodel.2017.10.012

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VL - 367

SP - 34

EP - 41

JO - Ecological Modelling

JF - Ecological Modelling

SN - 0304-3800

ER -