# Land and sea transport options for the installation of green artificial reefs (GARs) in shallow waters: a Galician case study

**Authors:** Juan José Cartelle Barros, Alicia Munín-Doce, Laura Castro-Santos, Javier Lamas, Luis Carral

PMC · DOI: 10.1038/s41598-024-53183-0 · Scientific Reports · 2024-02-01

## TL;DR

This paper introduces a new method for installing green artificial reefs in shallow waters, focusing on transport options and using a simulation tool to compare costs, emissions, and time.

## Contribution

The novel contribution is the development of AGARDO, a simulation tool for optimizing the transport and deployment of green artificial reefs.

## Key findings

- AGARDO can evaluate different transport scenarios for green artificial reefs in terms of cost, emissions, and time.
- Three sea transport options were compared, including a liquefied natural gas-powered workboat and an electric barge.
- The methodology is adaptable to other case studies with different onshore and offshore conditions.

## Abstract

The aim of the present paper is to propose a new methodology for the production and installation of green artificial reefs (GARs) in shallow waters, with special attention to the transport stages. The process includes both onshore (manufacturing, road transport and unload at port) and offshore (load at port, sea transport, positioning, and deployment tasks) stages. Two different types of truck were analysed for the road transport. Furthermore, three different options were considered for sea transport: a workboat powered by liquefied natural gas, a barge using diesel (0.1% sulphur) as fuel, and an electric specific design barge. A simulation tool called AGARDO (Automatic Green Artificial Reef Deploy Optimisation) was developed for such a purpose. An estuary located in Galicia (North-West of Spain), where 180 GAR units must be installed, has been considered as case study. AGARDO was used to obtain results concerning process total time, equivalent CO2 emissions and costs for different scenarios. Consequently, the use of the proposed methodology allows the decision-maker to select the best option in terms of costs, emissions and time. AGARDO can be easily adapted to other case studies, with different onshore and offshore options.

## Full-text entities

- **Diseases:** NM (MESH:D007674), AR (MESH:D013734)
- **Chemicals:** ozone (MESH:D010126), sulphur (MESH:D013455), CH4 (MESH:D008697), Lithium (MESH:D008094), carbon (MESH:D002244), LNG (MESH:D016912), N2O (MESH:D009609), ion (MESH:D007477), AGARDO (-), oil (MESH:D009821), Si (MESH:D012825), CO2 (MESH:D002245), CS (MESH:D002586)
- **Species:** Octopus (genus) [taxon 6643], Eucalyptus (genus) [taxon 3932]

## Full text

_Full body text omitted from this summary view._ Fetch the complete paper as Markdown: https://tomesphere.com/paper/PMC10834440/full.md

## Figures

7 figures with captions in the complete paper: https://tomesphere.com/paper/PMC10834440/full.md

## References

48 references — full list in the complete paper: https://tomesphere.com/paper/PMC10834440/full.md

---
Source: https://tomesphere.com/paper/PMC10834440