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Cross-vessel eco-efficiency analysis. A case study for purse seining fishing from North Portugal targeting European pilchard

  • OCEAN RESOURCES & MARINE CONSERVATION
  • Published:
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Abstract

Purpose

European pilchard captures constitute an important source of income for the Portuguese fishing sector. This raw material is used for a varied range of final seafood products, such as canning, fresh seafood consumption or bait for other fisheries. The Portuguese purse seining fleet, which concentrates most of the pilchard landings, has recently obtained the Marine Stewardship Council certification scheme, demonstrating the effort of the fleet to comply with sustainable fishing practices. However, this scheme does not consider the human inputs to the fishery, such as fuel consumption or the use of other materials and resources. Consequently, life-cycle methods, such as Life Cycle Assessment (LCA), have arisen to provide a thorough assessment of the environmental profile of fishing fleets. In the current study, LCA is combined with Data Envelopment Analysis (DEA), a management tool, in order to understand the eco-efficiency of the individual vessels that compose this fleet.

Methods

A 5-step LCA + DEA method, previously used to assess resembling vessel samples, was used to examine the efficiency of 20 purse seiners in the northern Portugal for years 2011 and 2012. Individual Life Cycle Inventories (LCIs) were gathered for each vessel to perform, thereafter, the Life Cycle Impact Assessment (LCIA). DEA matrices were generated based on the LCI in order to obtain the efficiency values for each unit. Finally, based on the efficiency projections provided by the DEA model, a new LCIA was performed for inefficient vessels in order to calculate the potential environmental benefits of operating at higher levels of efficiency.

Results and discussion

The average efficiency of the fleet in the two different years of assessment was slightly above 60 %. Moreover, individual vessels showed a fairly low standard deviation across the 2 years of assessment, demonstrating that units with higher levels of efficiency tend to maintain these values through the analysed window. In fact, this result, given its strong correlation with fuel use, appears to have relation with the existence of a certain level of “skipper effect”. Important environmental benefits, mainly linked to the optimisation of fuel resources, could be attained if inefficient vessels were to operate efficiently, especially in terms of two main impact categories: climate change and fossil depletion.

Conclusions

The results in this study confirm that fishing small-pelagic fish shows low energy intensity as compared to other fisheries. However, despite this worldwide tendency, the use of LCA + DEA confirms that substantial improvements in terms of optimising energy and material inputs, as well as in reducing environmental impacts, can be attained in these fishing fleets.

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Notes

  1. One of the main features of DEA matrices is the metrics that are assumed. These can either be radial, in which collective improvement calculations among inputs and outputs are considered, or non-radial, when individual improvement calculations within each input and output dimension are taken into consideration (Cooper et al. 2007).

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Acknowledgments

The authors belong to the Galician Competitive Research Group GRC 2013–032. Dr. Ian Vázquez-Rowe wishes to thank the Galician Government for the financial support (I2C postdoctoral student grants programme). Dr. Sara González-García would like to express her gratitude to the Galician Government (DOG number 62, pages 9405–9410, 1 April 2013) for a Postdoctoral Research Fellowship at the University of Aveiro (Portugal), and to the Spanish Ministry of Economy and Competitivity (Grant reference JCI-2012-11898) for the financial support.

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Correspondence to Ian Vázquez-Rowe.

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González-García, S., Villanueva-Rey, P., Belo, S. et al. Cross-vessel eco-efficiency analysis. A case study for purse seining fishing from North Portugal targeting European pilchard. Int J Life Cycle Assess 20, 1019–1032 (2015). https://doi.org/10.1007/s11367-015-0887-6

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