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Sustainability of the Peruvian anchoveta-based supply chains from sea to plate

ANCHOVETA-SC PROJECT status report

Angel Avadi, IRD, Université Montpellier II

DISCOH Scientific Workshop29-31 March 2012

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

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Outline1. The ANCHOVETA-SC project2. Supply chain modelling and evaluation

– Modelling– Sustainability indicators

3. Initial LCA results

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ANCHOVETA-SC• Project financed by IRD and project partners• Coordinator: Pierre Fréon, IRD• Location: Peru• Duration: 4 years (01.2010 - 12-2013)• 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)

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Focus1. Characterisation of biophisical flows along

the supply chains (SC)– Featuring ecosystem-SC interactions

2. Comparison of scenarios based on different fishing intensities and “fate” of landings (DHC vs IHC)

3. Sustainability comparison of chains/scenarios based upon:– Energy performance– Environmental impacts (LCA)– Seafood-specific impact categories– Nutritional value– Selected socio-economic indicators

Marine Ecosystem Extraction Trans-

formationAqua-culture

DHC

IHC

Harvest

• Anchoveta catches• Predatorscatches• Catches for DHC or IHC

• Final product

Fate

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1) Simplified SC diagramEc

osys

tem

dyn

amic

s

Fisheries

Emissions

Inputs

DHC processing

Emissions

Inputs

Reduction

Emissions

Inputs

Anchoveta,predators

Anchoveta Aquafeed

Emissions

Inputs(including

crops)

Aquaculture

Emissions

Inputs

Con-sumption

Canned, cured, frozen

Chinese finfish?European salmon?Shrimp?

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Modelling ecosystem-SC interactionsEcopath with Ecosym

Trophic model

UmbertoMaterial and energy

flow model

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2) Scenarios and 3) Indicators

• 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)

Status quo(maximum anchoveta

stock exploitation)

Status quo(1-2% DHC)

Status quo(maximum anchoveta

stock exploitation)

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

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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

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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

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Network: Colossoma farm

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Characterisation: Colossoma farm• Main impact contributors: feed and rain forest

transformationFRY

Marine ecotox

icity

Freshwater

ecotoxicity

Freshwater eutrophicatio

n

Terrestrial

acidification

Photochemical oxidant formatio

n

Ozone depleti

on

Urban land

occupation

Terrestrial

ecotoxicity

Ionising

radiation

Agricultural land

occupation

Climate

change

Ecosystems

Natural land

transformation

Particulate

matter formatio

n

Human

toxicity

Climate change Human Health

Metal deplet

ion

Fossil depleti

on

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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

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Network: Aquafeed plant (8 t/m)

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Characterisation: Aquafeed plant• Main impact contributor: use phase

Marine ecotox

icity

Freshwater

ecotoxicity

Freshwater eutrophicatio

n

Terrestrial

acidification

Photochemical oxidant formatio

n

Ozone depleti

on

Urban land

occupation

Terrestrial

ecotoxicity

Ionising

radiation

Agricultural land

occupation

Climate

change

Ecosystems

Natural land

transformation

Particulate

matter formatio

n

Human

toxicity

Climate change Human Health

Metal deplet

ion

Fossil depleti

on

LCA FISHMEAL PLANT

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Aquafeed plant use phase• Impact contributors in use phase:

– oil-powered electricity – feed ingredients, mainly Bolivian soymeal (due to clearcutting in Bolivia)

Marine ecotox

icity

Freshwater

ecotoxicity

Freshwater

eutrophication

Terrestrial

acidification

Photochemical oxidant

formation

Ozone

depletion

Urban land

occupation

Terrestrial

ecotoxicity

Ionising

radiation

Agricultural land

occupation

Climate change Ecosyst

ems

Natural land

transformation

Particulate

matter formatio

n

Human

toxicity

Climate change Human Health

Metal depletio

n

Fossil depletion

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Network: Hypothetical trout feed plant

(43% fishmeal)

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Comparison of feed plants

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Network: Fishing vessel 395 m3

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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

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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.

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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

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Gracias por su atención… Preguntas, comentarios?

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