1. Sustainability of the Peruvian anchoveta-based supply chains from sea to plate ANCHOVETA-SC PROJECT status report Angel Avadi, IRD, Université Montpellier II
Main project collaborators:
Marilú Bouchon, IMARPE
Camilo Cuba, UNFV
Dr. Pierre Fréon, IRD
Federico Iriarte, UNFV
Ana Medina, IMARPE
Jesus Nuñez, IRD
Jorge Tam, IMARPE
Rosa Vinatea, UNFV
Otros colaboradores en IMARPE, e.g. Rocío Joo
DISCOH Scientific Workshop
29-31 March 2012

2. Outline The ANCHOVETA-SC project Supply chain modelling and evaluation
Sustainability indicators
Initial LCA results

3. ANCHOVETA-SC Project financed by IRD and project partners
Coordinator: Pierre Fréon, IRD
Location: Peru
Duration: 4 years ( )
Theme: Environmental and socio-economic assessment of major international supply chains consuming Peruvian anchoveta (aligned to WP5 DISCOH)
Outputs:
Sustainability assessment
Policy and sustainability suggestions
PhD thesis (plus other theses)

4. Focus
Characterisation of biophisical flows along the supply chains (SC)
Featuring ecosystem-SC interactions
Comparison of scenarios based on different fishing intensities and “fate” of landings (DHC vs IHC)
Sustainability comparison of chains/scenarios based upon:
Energy performance
Environmental impacts (LCA)
Seafood-specific impact categories
Nutritional value
Selected socio-economic indicators
LCA o ACV: estudio de los impactos ambientales, expresados en una serie de categorías de impacto (e.g. GWP, eutrophication), asociados a la provisión de un bien o servicio a lo largo de todo su ciclo de vida, desde la extracción de materias primas pasando por la transformación y uso hasta la disposición final. La idea principal es permitir la comparación de productos y procesos productivos desde el punto de vista de su impacto ambiental.

5. 1) Simplified SC diagram
Inputs
Anchoveta,
predators
Canned, cured,
frozen
Ecosystem dynamics
DHC processing
Inputs
Emissions
Fisheries
Con-sumption
Inputs
(including crops)
Emissions
Inputs
Inputs
Chinese finfish?
European salmon?
Shrimp?
Reduction
Aquafeed
Aquaculture
Anchoveta
Emissions
Emissions
Emissions

6. Modelling ecosystem-SC interactions
Ecopath with Ecosym
Trophic model
Lindeman spine: gráfico de cadenas tróficas lineales
Umberto
Material and energy flow model

7. 2) Scenarios and 3) Indicators
Status quo
(maximum anchoveta stock exploitation)
(1-2% DHC)
Increase in DHC
(10-15% DHC)
Diversification
(reduction of anchoveta catches + increase of predator catches)
Mixed model with anchoveta DHC/IHC and anchoveta predators DHC
Harvest
Fate
Indicators rationale
To compare feed ingredients, feed formulations and seafood products:
Gross energy content (MJ/kg)
Edible protein Energy Return On Investment (%)
Biotic Resource Use (g C/kg)
Ecological Footprint (ha/t)
To compare intermediate and final seafood products, and competing supply chains:
LCA impact categories
Socio-economic indicators (to be defined)

8. LCAs carried out Two fishmeal plants:
a conventional one producing only Fair Average Quality (FAQ) fishmeal and using mainly heavy fuel as energy source
a more modern steam plant producing both FAQ and prime quality fishmeal and using both heavy fuel and natural gas
Detailed inventories of industrial anchoveta fleet under processing
preliminary LCA of representative “average“ 395 m3 vessel category
Two aquafeed plants (Iquitos)
A pilot facility and a working commercial facility
One aquaculture farm (Iquitos)
Peruvian Amazonian species

9. Iquitos Colossoma farm
Colossoma macropomum (Gamitana), a large Amazonian fish
Farm: 30 ha, converted from rain forest, 11.2 ha of ponds (no wastewater treatment), production: 100 t/a, feed: 150 t/a

10. Network: Colossoma farm

11. Characterisation: Colossoma farm
Main impact contributors: feed and rain forest transformation
FRY
Marine ecotoxicity
Freshwater ecotoxicity
Freshwater eutrophication
Terrestrial acidification
Photochemical oxidant formation
Ozone depletion
Urban land occupation
Terrestrial ecotoxicity
Ionising radiation
Agricultural land occupation
Climate change Ecosystems
Natural land transformation
Particulate matter formation
Human toxicity
Climate change Human Health
Metal depletion
Fossil depletion

12. Iquitos Aquafeed plants
2 plants visited:
30 t/a IIAP plant
8 t/m commercial plant (competing with Purina, etc.)
< 6% Peruvian fishmeal content in feeds
> 33% Bolivian soymeal content
> 45% local cornmeal content

13. Network: Aquafeed plant (8 t/m)

14. Characterisation: Aquafeed plant
Main impact contributor: use phase
LCA FISHMEAL PLANT
Marine ecotoxicity
Freshwater ecotoxicity
Freshwater eutrophication
Terrestrial acidification
Photochemical oxidant formation
Ozone depletion
Urban land occupation
Terrestrial ecotoxicity
Ionising radiation
Agricultural land occupation
Climate change Ecosystems
Natural land transformation
Particulate matter formation
Human toxicity
Climate change Human Health
Metal depletion
Fossil depletion

15. Aquafeed plant use phase
Impact contributors in use phase:
oil-powered electricity
feed ingredients, mainly Bolivian soymeal (due to clearcutting in Bolivia)
Marine ecotoxicity
Freshwater ecotoxicity
Freshwater eutrophication
Terrestrial acidification
Photochemical oxidant formation
Ozone depletion
Urban land occupation
Terrestrial ecotoxicity
Ionising radiation
Agricultural land occupation
Climate change Ecosystems
Natural land transformation
Particulate matter formation
Human toxicity
Climate change Human Health
Metal depletion
Fossil depletion

16. Network: Hypothetical trout feed plant
(43% fishmeal)

17. Comparison of feed plants

18. Network: Fishing vessel 395 m3

19. Design remarks
Key aquaculture products haven’t been characterised for Peruvian conditions
E.g. Peruvian rice and corn.
Proxies were used and adaptations introduced when possible (e.g. Bolivian soymeal adapted from Brazilian)
Key industrial products haven’t been characterised, yet it’s composition is known/estimated
E.g. electric and combustion engines

20. LCA results
Construction and maintenance of (reduction, feed) plants contributes negligibly
Fuel use is the main contributor to impacts in all activities (fishing, reduction, feed processing)
Feed provision is the main contributor to impacts in extensive Peruvian aquaculture
The sourcing of feed ingredients is a critical factor for associated environmental impacts of feeds
E.g. Brazilian soymeal performing much worst than Bolivian one, due to clear cutting of rain forest vs. of shrublands.

21. Further (ongoing) work
EwE scenarios definition and integration with Umberto
Selection of and data gathering for socio-economic indicators
Statistical processing of fleet inventories and comprehensive LCA of fleet categories
Further LCAs:
Canning, curing and freezing plants
Carnivore fish and shrimp aquaculture farms
Gathering supply chains operative data and LCIs
Background processes for provision of feed ingredients
Published LCI/LCA data must be recalculated to ensure consistency

22. Gracias por su atención… Preguntas, comentarios?
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