sustenability aquaculture development

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Review

Sustainability assessment tools to support aquaculture development

Biniam Samuel-Fitwi a , b , * , Sven Wuertz a , b, Jan P. Schroeder b, Carsten Schulz a , ba Institute of Animal Breeding and Animal Husbandry, Christian-Albrechts-Universitt zu Kiel, Olsenhausenstrasse 40, 24098 Kiel, Germanyb Gesellschaft fr Marine Aquakultur (GMA) mbH, Hafentrn 3, D-25761 Besum, Germany

a r t i c l e i n f o

Article history:Received 28 June 2011Received in revised form21 March 2012Accepted 31 March 2012Available online 13 April 2012

Keywords:SustainabilityAquacultureAssessmentEnvironmentLife cycle assessmentEcological footprint

a b s t r a c t

Aquaculture production has doubled every decade for the past fty years, representing the fastest

growing food sector. This increase re

ects the expansion of production areas, increased know-how inhusbandry and advances in production technologies, but most importantly it entails increased use of production-inputs that lead to exploitation of natural resources and hence raising concern on environ-mental distress. In addition, it suggests a similar range of production-outputs apart from the actual targetproducts that are hardly quanti ed but often are recognized for causing impacts on the environment aswell as potential risks for human health. Although several quantitative multi-impact assessment toolshave been explored to evaluate environmental impacts of industrial activities, applications in aquacul-ture have only recently been carried out. However, impact assessment tools applied so far do not re ectthe full range of aquaculture activities, and hence incorporate limitations that impair their use inaquaculture environmental assessment. Therefore, the development of tailored environmental assess-ment tool incorporating impacts distinctive to aquaculture is necessary. By reviewing recent method-ologies used in aquaculture, their limitations are identi ed and future research needs are highlighted.Although large strides have been made in reaching standardized methods for environmental assessmenttools such as life cycle assessment (LCA), their use in policy formulation and decision making requiresrelentless effort to develop the tools using fundamental problems known to aquaculture. As a prereq-uisite, the most signi cant impacts of aquaculture are identi ed but need to be characterized andintegrated in aquacultural assessment tool. Furthermore, social aspects of sustainability should beconsidered; and linkage of operational ef ciency with environmental performance can support inoptimizing the allocation of resources while minimizing impacts.

2012 Elsevier Ltd. All rights reserved.

1. Introduction

World aquaculture production has increased from 1.7 million tin 1957, to 68 million t in 2008 ( FAO, 2009, 2010 ). Consequently,doubling every decade in the past ve decades, aquacultureproduction has seen a 39 fold increment, and contributes largely toglobal sh production for human consumption ( Tacon and Metian,2009 ), surpassing for the rst time the supply from capture

sheries ( FAO, 2010 ). This increase re ects the expansion of cultureareas, increased know-how in husbandry and advances inproduction technologies. Most importantly it entails increased useof production-inputs such as land, water, feeds, energy, ther-apeutants and chemicals that lead to exploitation of naturalresources and hence raising concern on environmental distress.Furthermore, the increased production-inputs suggest a similarrange of production-outputs, potentially coupled with environ-mental impacts, comprising mainly airborne and waterborneemissions from the farms. These emissions may result in localecosystem imbalances, particularly when carrying capacity isexceeded in the recipient water body. Recently, however, importantglobal scale impacts that may arise during aquaculture production,such as global warming, acidi cation, ozone layer depletion, havegained popularity in environmental studies ( Pelletier et al., 2007 ).

Several recent studies focused on the outputs from aquacultureand quanti ed their release ( Wu et al.,1994 ; Wu,1995 ; Enell,1995 ;Muir, 2005 ; Colt et al., 2008 ; Roque d Orbcastel et al., 2009b ).However, quanti cation of some of the releases is dif cult due to

Abbreviations: BOD, Biological Oxygen Demand; DEA, Data Enveloping Analysis;EF, Ecological Footprint; EU, European Union; FAO, Food and Agriculture Organi-zation; LCA, Life Cycle Assessment; IFOAM, International Federation of OrganicAgriculture; OECD, Organization for Economic Co-operation and Development;SLCA, Social Life Cycle Assessment; UNEP, United Nation EnvironmentalProgramme.

* Corresponding author. Gesellschaft fr Marine Aquakultur (GMA) mbH,Hafentrn 3, D-25761 Besum, Germany. Tel.: 49 (0) 4834 96539914; fax: 49 (0)4834 96539999.

E-mail address: [email protected] (B. Samuel-Fitwi).

Contents lists available at SciVerse ScienceDirect

Journal of Cleaner Production

j ou rna l homepage : www.e l sev i e r. com/ loca t e / j c l ep ro

0959-6526/$ e see front matter 2012 Elsevier Ltd. All rights reserved.

doi: 10.1016/j.jclepro.2012.03.037

Journal of Cleaner Production 32 (2012) 183 e 192
mailto:[email protected]://www.sciencedirect.com/science/journal/09596526http://www.elsevier.com/locate/jcleprohttp://dx.doi.org/10.1016/j.jclepro.2012.03.037http://dx.doi.org/10.1016/j.jclepro.2012.03.037http://dx.doi.org/10.1016/j.jclepro.2012.03.037http://dx.doi.org/10.1016/j.jclepro.2012.03.037http://dx.doi.org/10.1016/j.jclepro.2012.03.037http://dx.doi.org/10.1016/j.jclepro.2012.03.037http://www.elsevier.com/locate/jcleprohttp://www.sciencedirect.com/science/journal/09596526mailto:[email protected]


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unavailable data and insuf cient ndings of their impacts on theenvironment ( Wu, 1995 ). Classical environmental studies targetedlocal emissions categorized into few classes of pollutants, namelynutrients and organic matter, pathogens, introduction of geneti-cally modi ed organisms and escapees. Recently, global emissions,predominantly comprising greenhouse gases (carbon dioxide,methane, nitrous oxides, and uorocarbon) originating fromenergy consumption and their contribution to global warming andocean acidi cation have been addressed. Energy use in aquacultureis linked to intensi cation of culture and involves an increasedenergy use due to a large-scale automation and complexity of work ows as well as indirect energy utilization for manufacturingof feed, chemicals or material inputs as well as transportation, andis highly variable between culture systems ( Colt et al., 2008 ; Roqued Orbcastel et al., 2009a ) and management practices. Therefore,assessing aquaculture environmental impact and examining thearray of multi-impact assessment tools already used in publishedcase studies will highlight the limitations and suggest needs/options for improvement.

The objective of this work is to evaluate a set of analytical multi-impact environmental assessment tools with regard to an appli-cation for aquaculture-related studies including the identi cationof potentials and limitations of these tools. This study focuses onanalytical assessment tools including ecological footprint (EF) andlife cycle assessment (LCA) in the aquaculture context.

2. Environmental impact assessment tools

Several tools have been presented in the past to facilitate theinclusion of various environmental aspects in decision making.However, the diverse and multidisciplinary nature of the environ-mental aspects and highly variable production processes involved

in aquaculture as well as their interlinkages ( Fig. 1) impede thedevelopment of quanti cation tools in evaluating the complexinteractions.

Often, aquaculture systems reveal complex process linkagesinvolving multiple variables that are mostly not parameterized.High input of nutrients and organic material from arti cial feedingresults in nutrient loaded ef uents leading to a substantial increasein primary production, subsequent decomposition and biochemicaloxygen demand (BOD), limiting the carrying capacity of therecipient aquatic system, although this is highly dependent on thereceiving ecosystem. Furthermore, the amount of nutrients andorganic load from aquaculture ef uents largely depend on thequantity of feed used and utilized by the target organism.

The release of escaped sh or other aquatic organisms from farmsites e in addition to the risk of disease transmission e lead to theintroduction of non-endemic or even invasive species, potentiallyoutcompeting native ora and fauna ( Casal, 2006 ; Stepien andTumeo, 2006 ). Such effects are barely quanti able but may highlymodify the complex ecologic interplay. Furthermore, escapees mayinterbreed with native stocks, entailing hybridization and intro-gression of native genomes, thereby in uencing the reproductiveperformance of individuals as well as populations in terms of allelicfrequency. These dependencies are rarely understood in unaffectedsituations, and case-speci c impact of highly variable aquacultureactivities will require the incorporation of speci c measuringmechanism, which is not yet available.

2.1. Impact assessment tools

Recently, environmental case studies of aquaculture activitiesfocused on quanti able emissions, making modeling of respectiveimpacts easier. The most widely-used impact assessment methods

Fig. 1. Major environmental interactions supporting increased aquaculture production.

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cover climate change arising from greenhouse gas emissions,acidi cation from acid gas emissions, eutrophication as a result of nutrifying emissions (such as nitrate, ammoniacal nitrogen andphosphates), the release of ozone-depleting substances, and abioticand biotic resource depletion ( Pelletier et al., 2007 ). These multi-impact categories encompass global impacts departing from thetraditional single impact assessment tools.

However, it is alarming to observe that the most popularassessment focused mainly on climate change especially carbonfootprint. Carbon footprint has its bene t in in uencing consumerchoices and decision making, as it is easy to communicate andcompare between products using a single carbon dioxide emissionvalue. However, carbon footprint is one of several impact categoriesand do not re ect overall impact of the production for severalreasons; for example, carbon dioxide emissions are mainly relatedto fuel-based energy use and aquaculture production systems withno energy use are selected as environmentally preferred produc-tion systems; and non-energy emissions potentially impacting theenvironment are completely ignored. Therefore, to meet objectiveevaluation in aquaculture, overall analysis is utmost essential dueto the variety of alternative production systems shifting the impactfrom one eld to another if undetectable in the analysis (problemshifting). As a consequence, multi-impact assessment tools used inaquaculture are focused on here.

Among the multi-impact tools used, EF and LCA representmethodologically the most advanced tools and are increasinglyused in aquaculture studies. Both aim at providing a completepicture of a product s environmental impacts and attempt to avoidproblem shifting. Problem shifting involves a shift in production inorder to reduce identi ed environmental impacts by shifting theirform or location of release. For example, by taking a holistic multi-impact approach these tools consider all emission forms globally,hence avoid geographic problem shifting. Analyzing severalpotential impacts such as energy expenditure and emissions,impact-speci c problem shifting is avoided.

2.2. Expressing assessment results

Obviously, the presentation of data needs to summarize thecomplexity of the analysis to allow for a comparative assessmentbetween impacts and systems and provide an overall evaluation.Ideally, this summarized presentation needs to provide an easy-to-understand message, used to compare and further balanceproduction parameters, environmental impacts in order toharmonize consumer s as well as producer s interests. Currently,comprehensive single-score units such as the footprint of a stan-dardized unit s impact on a given area provide consumersa consistent measurement, and allow for integration in thepurchase decision that appeals to consumer s responsibility but caneasily be implemented in taxation policy or the legislative frame-

work of production and sales. However, limitations exist inapplying these tools, hindering their extensive purpose as a reliablecommunication tool for ecological labeling. For example, organiclabeling can be misleading, as available standards for organicaquaculture fail to reduce the majority of environmental impacts(Pelletier and Tyedmers, 2007 ). What organic labeling has achievedin the last few years is environmental awareness amongconsumers. The sector has grown signi cantly in the last decade asa result of consumer and market reaction to concerns about poortaste and texture, contamination, animal welfare, etc. ( Mente et al.,2011 ). However, the major organic labels (such as Naturland, EUlabel, KRAV) offer comparison across the various mixes of impactassessment tools which is not consistent across the various labelscurrently available. The disadvantage of this approach is that the

information obtained from the various tools can be confusing to

consumers and data requirements may be extensive and costly.However, particular claims of bio-integrated systems such asaquaponics or polyculture systems need to be analyzed carefullyand holistically to improve the techniques currently developed.Recent advances by researchers and growers have turned thesesystems into a working model of sustainable aquaculture produc-tion. However, comprehensive evaluation on the sustainability hashardly been carried out and emerging technology is mainly focusedon production parameters rather than impact data. De ning stan-dards for organic labeling is particularly important as a 240-foldincrease is predicted by 2030 ( El-Hage Scialabba and Hattam,2002 ). The International Federation of Organic Agriculture(IFOAM) has established standards for organic agriculture produc-tion and the need for coherent EU framework and standards foraquaculture products led to the inclusion of these products withinthe EU regulation for organic production, although more efforts arerequired in terms of legislative and institutional framework ( Menteet al., 2011 ). Moreover, inclusion of multi-impact assessment toolsfor evaluation of environmental impact is necessary to have accu-rate environmental evaluation.

3. Ecological footprint (EF) analysis

In the 1990s, the concept of the EF was introduced as a measureof human demand on Earth s ecosystem by comparing the amountof human appropriation with the amount of global bio-capacity toregenerate each year ( Monfreda et al., 2004 ; Wackernagel et al.,2004 ). In other words, EF analyses quantify human demand onnature by assessing the biologically productive land and water arearequired to produce the resources consumed and to absorb corre-sponding waste. The human consumption of natural resources isconverted into a normalized measure of land area known as globalhectares (gha). The EF is adopted in aquaculture revealing enor-mous differences in the impacts assessed in different productionsystems ( Larsson et al., 1994 ; Berg et al., 1996 ; Kautsky et al.,1997 ;Folke et al., 1998 ; Roth et al., 2000 ; Bunting, 2001 ). It appears that

increasing intensi cation demands larger amount of global hect-ares for bio-capacity to regenerate each year, making productionscale one of the most important factors affecting the environment.

3.1. EF in aquaculture production

Berg et al. (1996) estimate that 1 m 2 of semi-intensivelymanaged tilapia pond requires a pond area of 0.9 m 2 for phos-phorus assimilation and 0.5 m 2 for oxygen production. Whenconsidering tilapia production in 1 m 2 intensively managed cages itis estimated that an ecosystem area of up to 115 m 2 and 160 m 2 isrequired for phosphorus assimilation and oxygen production,respectively. Moreover, the ecosystem area required for feedproduction was estimated to be 21,000 m 2 m 2. The authors

concluded that from the ecological point of view, the semi-intensive tilapia pond production is more sustainable ascompared to the intensive cage production of tilapia. Comprehen-sively, sustainability needs to consider actual productive output tobe able to compare in a broader economic point of view. In otherwords, semi-intensive farming needs to take into consideration theproduced amount of sh to assure comparability with the intensivesystem. From an ecological perspective, each ecosystem hasa carrying capacity, which is constrained by maximum impact stillleading to regeneration from the impacts, independent of produc-tion units. In this context, it needs to be emphasized that the EF isnot constant for a given impact, but needs to re ect also thecapacity of an ecosystem to regenerate. Folke et al. (1998)concluded that larger ecosystem areas are required to sustain

more intensive and concentrated activities such as intensive

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monocultures of salmon and shrimp farming than less intensivesystems. Thus, carrying capacity (EF) is highly dependent onecosystem characteristics and represents a rather dynamic prop-erty, which indicates shortcomings for the EF assessment.

Bunting (2001) recalculated the EF of tilapia production in semi-intensive and intensive farming systems normalizing ecosystemarea to the appropriated annual sh production (m 2 kg 1) - incontrast to the original approach referringto ecosystemarea to areaaquaculture facility (m 2 m 2), using the information from Berget al.(1996) . Consequently, the area required for excess phosphorusassimilation of intensive farming systems was lower (0.78 m 2)when compared with semi-intensive tilapia farms (1.78 m 2) on thebasis of 1 kg of tilapia produced. Furthermore, the land required toproduce the same quantities of tilapia in intensive farming is 210times lower than the semi-intensive farm, re ecting the economicconstrains of semi-intensive farming of tilapia in acquiring land. Onthe other hand, the supply of oxygen in intensive farms is found tobe higher than that of semi-intensive farms, involving additionalcosts (shifting the 1:210 ratio) and resources (shifting the 0.78:1.78ratio) slightly.

3.2. Limitations of EF in aquatic environments

Most importantly, EF methodology refers to a product-speci cland required to regenerate impacts from a speci c activity.Hereby, ecosystem properties are generalized assuming a stan-dardized global ecosystem in terms of averaged bioproductivity.Thereby, EF is expressed as hypothetical number of global hectares,required to sustain a designated human activity. Interactionsspeci c for a distinct ecosystem are neglected so far. This isparticularly critical in isolated, vulnerable ecosystems such as coralreefs. In particular, aquatic ecosystems are characterized bya multitude of opposing biotic and abiotic factors which subse-quently determine the impact of a given anthropogenic stressor. Forexample, the spread of emissions is highly dependent on themovement of the water and the accumulation or metabolisation is

highly variable for different ecosystems based on local bioticdistribution and abundance. Applying a generalized procedure forenvironmental assessment dangerously simpli es ecologicalinteractions, leading to a product having an identical footprintregardless of its origin ( Monfreda et al., 2004 ; Wackernagel et al.,2004 ). As such, values of EF do not depict the varied quality of the physical ecosystem in use, such as a desert or forest ecosystem.In order to address this limitation, Limnios et al. (2009) used directland area usage rather than land area derived from the volumes of outputs. However, application of direct land use measurement inseafood production is not straightforward, as the features of landand water used in seafood production are dynamic and relativelyunpredictable. Furthermore, in marine ecology, assimilativecapacity can also be de ned in relation to speci c environmental

target criteria re ecting dynamic ecological pathways rather thanarea-related measures ( Roth et al., 2000 ). Therefore, EF needs to beadapted to speci c ecosystems in the future and appropriatedcarrying capacity of speci c ecosystems have to be de ned withregard to distinctive types of impact.

Intensive production systems imply the use of resources forhigher short-term production-outputs with consequently envi-ronmentally damaging productivity in long-term. For example,increases in shrimp production demanded the expansion of hatcheries in many parts of the world leading to local depletion of wild broodstocks, thereby reducing long-term productivity of local sheries and biotic depletion of stocks. The short-term increase inproductivity of hatcheries indicating deceptive lower values of EF,due to avoided post larval collection from the wild. However, this

illusion of lower values of EF causes depletion of broodstocks in

a long-term due to the exploited wild stocks. Limnios et al. (2009)recently have addressed the problem by accounting for bothcurrent and potential land disturbances. Categorizing currentimpacts is relatively well established, however assigning potentialfuture ecological impact on biodiversity and area degradation isdif cult and highly speculative. Minor deviations and inaccuracieson prediction intensely diverge from accurate results mainlybecause of the network of ecological relationships to be considered.Furthermore, beyond all doubt, aquatic ecosystems are by far lessunderstood than terrestrial ones, turning ecosystem-speci capproaches a major problem for EF assessments.

4. Life cycle assessment (LCA)

In the past two decades, LCA has seen a tremendous amount of applications as an assessment tool in different elds for evaluatingresource utilization and environmental impact assessment, therebyidentifying hot spots in the production process. Therefore, based onthe goal of the synopsis, extraction and processing of raw materialsare carried out throughout the life cycle of the product, typicallyintegrating manufacturing; transportation and distribution; use,reuse, and maintenance; and recycling and waste ( Curran, 1993;Guine, 2002; ISO, 1997, 2006 ). As such, LCA in aquaculture isa departure from evaluating waste release management alterna-tives of environmental assessments of the 1980s that looked mainlyat a single issue such as local emission from sh farms. Instead, itdescribes the incoming (food production, including the energyused, broodstock, water etc.) and out-coming ow (emissions,product) in order to give an overall statement based on the inclu-sion of all relevant activities along a life cycle.

There are few published articles on LCA research in aquacultureproduction systems, including different salmonid feeds(Papatryphon et al., 2004 ), Thai shrimp products ( Mungkung et al.,2006 ), French land based turbot production ( Aubin et al., 2006 ),Norwegian net-cage farmed salmon ( Ellingsen and Aanondsen,2006 ), Finnish trout production ( Grnroos et al., 2006 ), conven-

tional and organic salmon feed production ( Pelletier and Tyedmers,2007, 2008 ), alternative salmon production technology ( Ayer andTyedmers, 2009 ), global salmon production impacts involvingNorway, the UK, Canada and Chile ( Pelletieret al., 2009 ) and musselculture, consumption and reuse in Spain ( Iribarren et al., 2010a ).Very recently, several studies (e.g. Aubin et al., 2009 ; Roqued Orbcastel et al., 2009a ; Pelletier et al., 2009 ; Pelletier andTyedmers, 2010 ; Phong et al., 2011 ; Jerbi et al., 2012 ) havecompared production systems, including a comparison betweenspecies, different geographical positions of production sites as wellas polyculture vs. mono-species systems. Still, the majority of thestudies are focused on salmonids, assessing a variety of impactcategories, e.g. global warming, acidi cation and eutrophicationpotentials. Some of methodological issues related to aquacultural

LCA is reviewed elsewhere ( Henriksson et al., 2012 ) and are notdetailed in this review.

4.1. LCA and its limitations

Frequently, standardization is an issue since studied sites rarelyvary in a single parameter. For example, there are no standardizedproduction systems, thus evaluation at different geographicallocations is consequently also a comparison of production tech-nology in uenced by changes in regional husbandry conditions.Furthermore, such a comparison may involve backgroundprocesses of economic nature on a broader scale that accordinglybias overall assessment results, if not evaluated carefully. Forexample, careful observation in many aquaculture LCAs indicate

that cumulative emissions of energy utilization largely contribute



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to potential impacts within several impact categories. The cumu-lative emissions from energy dependent production are quite oftendominated by direct emissions from the combustion process(Dones et al., 2007 ). Therefore, the delivery of the primary energyinputs causes important elementary ows to production as well asresource utilization, for example land occupation or fossil energyresources and cannot be disregarded. This implies that differentenergy sources (wind in one region vs. fuel in another) subse-quently may result in drastically large differences in emissionvalues even at comparable energy consumption of the selectedfarming sites. Environmental burdens related to natural gasproduction, for example, are highly dependent on the importstructure, ultimately in uencing the gas transport distances(Heijungs et al., 2006 ). For example, Pelletier et al. (2009) analyzedthe LCA of different salmonic production using regional energysupply for the different regions including Norway, UK, Canada, andChile that the result of the assessment indicate bias. For example,Chile s main energy source is based on fuel, while in Norwaynatural gas is common. The impact from these different sources isdrastically varying that the LCIA result, and thus LCA quanti cationof the aquaculture production, is mainly swayed by the differentsources of energy and not on sh production itself. On a regionalscale involving several countries, normalization of certain ow (e.g.input) should be considered in order to provide a comprehensiveanalysis.

Hence, comparisons are limited by the diversity of culturespecies, the use of varied functional units, diverse farming systemsand the in uence of farm- level management practices andconsequent results of impact on environment. Despite these limi-tations, the LCA tool shows a potential for systemic assessment,integrating this variability. However, interpretations are usually notconclusive due to the diversity of aquaculture activities and speciesof culture.

A main general limitation of LCA is the quantity of ows to bede ned during LCI. Thus, data quality and collection, de nition of the system, time boundaries, and process modeling need to be

carried out carefully ( de Benedettoand Klemes, 2009 ). Collection of data can be problematic due to the fact that quality data needed forLCA frequently involves several processes (e.g. farming, sheries,agriculture, feed manufacturing, etc) and that transparency of business data is delicate and analysis is complicated by the numberof parties involved. When conducting LCA, it is important to weighthe availability of data, the time necessary to conduct the study, andthe nancial resources required against the projected bene ts of the assessment. Ellingsen et al. (2009) described the current statusof seafood environmental analyses and concluded that comparativeanalysis for only one or a few of the environmental impacts such asCO2 or energy consumption reduces costs but still may provideadequate environmental analysis. Consequently, the study assessedCO2 emission of farmed salmon in Norway from production to

consumption and identi ed the farming phase as the maincontributor to CO 2 emission, mainly due to fuel consumptionduring feed production. However, limiting the choice of the impactcategories to only few can underestimate the potentially severeenvironmental problems resulting in inaccurate assessment, ulti-mately diminishing the con dence of using LCA as reliableassessment tool in comparing products.

4.1.1. Handling co-productsMany aquaculture production systems produce more than one

economic output, or co-products. Integrated farming systems or sh cultured under a polyculture system or horizontal culturesystem ( Bunting and Shpigel, 2009 ) can be a good example, wherethe resources of the farm are used by other products produced

alongside the main produce resulting in more than one products.

The environmental impact during the production process of suchsystems can generally be allocated between its co-products and isoften based on mass or economic values of the co-products ( Ayeret al., 2007 ) and may be highly in uenced by the temporal uc-tuation common to the food market. However, co-product alloca-tion in inputs of raw materials, such as in feed input production,demands allocation in co-product outputs that are not representedwith economic or mass values. For example, Pelletier et al. (2009)used the gross chemical energy content of co-products to allocatethe resource use and emission of each co-product, consequentlyre ecting the ow of material, energy utilization and associatedemission, attributable to the functioning of the product system andis consistent with the ISO recommendation that the allocationcriterion be based on the function of the co-products. However,according to ISO standard ( ISO, 2006 ) the rst option with regardsto dealing with co-products is system expansion to avoid co-product allocation ( ISO, 2006). The main concern is that co-product allocation determines system boundaries normatively,instead of system boundary delimitation based on causality orconsequences which is re ective of the real-world behavior basedon market signals. For example, Schmidt (2007, 2010) hassuccessfully implemented the system expansion on all stages of agricultural production for studying LCA of vegetable oil. Detailedexplanation of system expansion delimitation is given by Weidema(2003) . System expansion, however, has rarely been applied in LCAsof aquaculture until recently ( Iribarren et al., 2010a ).

However, Pelletier and Tyedmers (2011) argue that the currentmarket signals are largely devoid of environmentally relevantcontents for managing the environmental dimensions of ouractivities that LCA results utilizing the current economic system areinadequate. Consequently, the authors suggested basing allocationcriteria on causality (e.g. physical) relational properties that linksystem inputs and co-product outputs in a logical manner. Thus,allocation procedures should approximate as much as possible thefundamental input e output relationships and characteristics ( ISO,2006 ) de ned in biophysical terms rather than economic terms.

4.1.2. Functional unit One of the important characteristics of agricultural LCA is the

use of multiple functional units ( de Boer, 2003 ). Such multiplefunctional units help in the interpretation and better under-standing of the environmental burden, productivity and farmincome, as different impact categories represent different effects onthe environment. However, several case studies in aquaculturerelate environmental impact to the mass of the product (e.g. per kg sh produced) and other representation of the function of theproducts such as economic value (per US$), area of production (perha), etc. are hardly studied and therefore cannot be used inter-changeably. This is mainly due to the fact that mass representationof the functional unit considers both production ef ciency and

environmental impact. Nevertheless, we support the simultaneoususe of an economic-based (US$), product related (kg) as well asprotein- or energy-based (kJ) unit, to allow for fast conversion of gures and assure fast comparison between studies. Furthermore,comparison of different species of sh and livestock productswithout considering the qualitative dimension of the functionalunit is misleading, as there is a danger that reality is not re ectedwell ( Reap et al., 2008 ). For example, the study by Aubin et al.(2009) assessed impacts of aquaculture involving differentspecies and production systems in different countries using thefunctional unit of sh weight. However, it failed to consider thequalitative differences of the different sh species with differentvalue functions, such as the function of providing protein andenergy ( Haard, 1992 ). Similarly, the study by Papatryphon et al.

(2004) , comparing environmental impact of feed based on



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different animals (pigs, poultry and sh) produced at differentculture environments, cannot re ect the accurate impact tosupport decision in selecting feed.

4.1.3. Choice of impact categoriesAppropriate impact categories are essential to arrive at

comprehensive evaluations of the environmental impacts fromaquaculture. Global warming, acidi cation, eutrophication, photo-chemical oxidant formation, aquatic/terrestrial ecotoxicity, humantoxicity, energy use, abiotic resource use, biotic resource use andozone depletion are impact categories that have frequently beenused in studies on seafood production ( Ellingsen et al., 2009 ;Pelletier et al., 2007 ). Still, clear prioritizations can be identi edsuch as impacts are chosen as appropriate to the practitioner, forexample, water use and land use can be excluded, and someimpacts may be restricted to speci c production systems. On theother hand, impact categories speci c to aquaculture such asspread of disease, overexploitation of wild sh, escape, by-catch,use of antibiotics and aquatic medicines, etc. are currently notconsidered in LCA ( Table 1 ), but have been major issues in thedebate on sustainability and environmental risks of aquaculture(Arthur, 2008 ). This indicates that the scope and scale of aquacul-ture impact needs to be de ned speci cally. At the same time,former categories allow for a broader comparison, i.e. between foodsectors. Clearly parallel analysis of speci c and generalized criteriashould preferentially be carried out.

Most of the aquaculture-related environmental impacts are notincorporated in appropriate impact categories in LCA. Severalreasons have to be mentioned here. First, it is not easy to distin-guish between the impacts and their impact categories, it is dif cultto assign impact categories to an impact, or dif cult to attributeimpacts to the functioning of the products. Selecting impact cate-gories in aquaculture requires careful de nition of the environ-mental impacts, and description of the link between the impactsand the appropriate impact categories, either quantitatively orqualitatively. This is crucial in making comprehensive assessment,

especially for decision making process, and needs to be addressedin the future.

5. Broadening sustainability assessment in aquaculture

It is important to broaden the inclusion of the different facets of sustainability to include economic, social, and environmentalaspects, as well as increasing the scope for inclusion of impactcategories crucial for accuratedecisionmaking, for example, impactcategories related to aquaculture. Diana (2009) made similarobservation in identifying the critical environmental impacts of aquaculture on biodiversity conservation indicating that anexpanded LCA methodology holds much promise in providingquantitative sustainability comparisons among aquaculture,

capture sheries, and agriculture systems. Moreover, other aspectsof sustainability, such as social aspects, incorporated in theassessment could improve the suitability of the tool for decisionmaking. Furthermore, resource use ef ciency through an optimizeduse of inputs at maximized outputs obtained re ects operationalef ciency stipulating a link between operational ef ciency analysismethod and LCA. Similar research efforts may lead to a new level of re ning the technique for direct use in managerial decision makingprocess.

5.1. Social life cycle assessment (SLCA)

In the context of aquaculture production, the environmental,social and economic facets are often listed as the main pillars of

sustainability. Up to now, aquaculture supports rather local

economy. For example, about 70% of global aquaculture is assignedto China and Chinese aquaculture mainly comprises smallproduction units ( FAO, 2009 ), which support local economies andmarkets. Thus, one could argue that aquaculture needs to be eval-uated with regard to social impact, particularly for local commu-nities. Although environmental aspects of sustainability havegained increasing importance, the social aspects are mainly ignoredin the discussion of sustainability. Recent publications( Dreyer et al.,2006 ; Hauschild et al., 2008 ; Kruse et al., 2009 ; UNEP, 2009 ) in theLCA tool development have consequently focused on the develop-ment of the economic and social counterparts of LCA, namely, lifecycle costing (LCC) and social life cycle assessment (SLCA),respectively. The economic LCA is well established, but beyond thescope of this review.

Here, use of SLCA in aquaculture will focus on the identi cationsocial impact categories and use of qualitative data. Still, SLCAneeds to be explored further as it is undoubtedly important insustainable aquaculture development. Kruse et al. (2009) haveattempted to apply SLCA in salmon production to compare therelative socio-economic impacts of comparable products comingfrom different production systems. The authors described thesocio-economic impact with two impact indicators selected, anadditive indicator and a descriptive (general and speci c) indicator.At present the methods used in SLCA are largely inconsistent withone another and efforts in developing a standard SLCA is underway.For example, in an effort to complement environmental LCA, UNEP(2009) developed a guideline for social LCA of products byfollowing the general guideline established in environmental LCA.Such efforts are fundamental for further development and re ne-ment of methods to assessthe results of social indicators using a lifecycle perspective in the future.

Areas of future development efforts should focus on the devel-opment of impact indicators and on the methodological develop-ments particularly de ning system boundaries, on populatingdatabases and identifying trade-offs between stakeholders andpillars of sustainability ( Kruse et al., 2009 ). LCAs applied in aqua-

culture have not yet integrated SLCA in the assessment and futureresearch needs to develop and integrate SLCA based on socialindicators speci c to the sector.

5.2. Towards environmental ef ciency

The linkage between operational ef ciency and environmentalperformance shows that the way the operational ef ciencies arecarried out greatly in uences the environmental impact of theprocesses ( Zhou et al., 2007 ), reducing impact with increasingef ciency. Furthermore, benchmarking of operations is possiblewith the aim of identifying operational inef ciencies that allowreduction of input consumption and increase of production.

Some studies ( Bunting, 2001 ; Bunting and Shpigel, 2009 ) sug-

gested an integration of seaweeds and lter feeders as lter units inaquaculture systems. Other studies have demonstrated how effec-tively commercial scale intensive ow-through trout cultureef uents are treated with constructed wetlands ( Schulz et al., 2003,2004; Sindilariu et al., 2009 ). In such an integrated horizontalsystem, LCA represents a tool to describe environmental quality, incontrast to intensive mono-species aquaculture. Consequently,culture systems combining species from different trophic levels,apply horizontal integration and generate multiple services andoutputs, which is bene cial from an environmental as well aseconomic (e.g. co-product diversi cation) point of view.

5.2.1. LCA for environmental ef ciencyCurrent LCA research can be used to indicate biophysical

sustainability ( Pelletier et al., 2007 ) and can be used to identify



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critical processes in production (hot spots) that contribute largelyto speci c kinds of environmental impacts (e.g. Ayer and Tyedmers,2009 ; Roque d Orbcastel et al., 2009a ; Pelletier et al., 2009 ;Mungkung et al., 2006 ). This can be incorporated for formulatingeco-labeling and certi cation criteria in aquaculture that mayimprove production ef ciency as well as identifying potentialenvironmental trade-offs. Still, LCA reports are extremely technical,characterized by long list of environmental pollutants ( Nissinenet al., 2007 ) that hinder consumers from making informedchoices about sh products. Therefore, for the purchase decision,sustainability needs to be expressed in a simpli ed form with easyaccess to information by consumers, in a way which is comparableto the illustrative presentation of the EF with ease for visualizingthe impacts. Standardization such as the development of a singleindex would enable furthermore the direct comparison of differentcase studies and broaden their practical relevance ( Roy et al., 2009 ).Still converting the impact in a single score requires the use of validated criteria, which is seen with skepticism with respect to itsscienti c rigor.

5.2.2. Joint data enveloping analysis (DEA) - LCA method for environmental ef ciency

Data enveloping analysis (DEA) is a well established method-ology used to evaluate the relative ef ciency of a set of comparableentities called decision making units with multiple inputs andoutputs by some speci c mathematical programming models(Lozano et al., 2009 ). DEA has been recently applied to measureecological ef ciency ( Dyckhoff and Allen, 2001 ; Zhou et al., 2007 ;Lozano et al., 2009 ). However, in the context of environmentalperformance measurement, the assumption of radial ef ciencymeasures used by the traditional DEA models that all the outputsshould be maximized is not appropriate when undesirable outputsare also generated as a by-product of the desirable outputs in theproduction process. Thus, using radial ef ciency measures oftenleads to the case where a lot of decision-making units have thesame ef ciency score and hence dif culty in ranking the environ-

mental performance of these decision making units only based ontheir ef ciency scores. Since non-radial ef ciency measures havea higher discriminating power in evaluating the ef ciencies of decision making units, non-radial DEA-based models seem to bemore effective in measuring environmental performance ( Dyckhoff and Allen, 2001 ; Zhou et al., 2007 ).

Zhou et al. (2007) have developed a non-radial DEA approach tomeasuring environmental performance using the case study onOrganization for economic co-operation and development (OECD)countries. Although a series of non-radial DEA models have beendeveloped in the traditional DEA framework, the development of such non-radial DEA model applicable to environmental perfor-mance is the rst.

Recently, a joint application of DEA and LCA, linking both

operational ef ciency and environmental impact has been appliedin aquaculture ( Lozano et al., 2009 ). Assuming that life cycleinventory data are available on multiple decision making units, DEAcan be used to gauge their ef ciency and establish ef ciencytargets. In this sense, the study compared the results of the originallife cycle impact assessment (LCIA) and the computed targets lifecycle impact assessment (LCIA). This results in reduced environ-mental impacts for the computed targets because for the sameamount of output, a lower amount of inputs will be used. Lozanoet al. (2009) used a case study of 62 mussel cultivation sites(rafts) in Galicia, Spain. They performed LCA for each raft andcomputed non-radial DEA with the aim of reducing inputs andincreasing outputs in mussel cultivation ( Fig. 2). The result showedthat the target total environmental impact is lower than the current

one for all the impact categories considered. This indicates that

reduction in environmental impact is possible provided that theestimated operational inef ciencies are removed. Similarly,Iribarren et al. (2010a) suggested the use of joint application of DEAand LCA to remove operational inef ciencies in dispatch centers of Spanish mussel sector. The proposed approach has the advantage of detecting and removing the technical inef ciencies that are thesource of unnecessary environmental impact by using LCI data thatare directly related to the operation of the facilities ( Iribarren et al.,2010b ; Vazquez-Rowe et al., 2010 ).

In conclusion, the linkage between operational ef ciency andenvironmental performance shows that the way the operationalef ciencies are carried out greatly in uences the environmentalimpact of the processes, reducing impact with increasing ef ciency.

Furthermore, benchmarking of operations is possible with the aimof identifying operational inef ciencies that allow reduction of input consumption and increase of production.

5.3. EF and LCA as communication tool

Although EF has the advantage in illustrating the environmentalimpacts in a visual, simple way, expressing impacts as globalhectares, its application in a dynamic interacting aquatic environ-ment is often restricted. Therefore, it can be misleading inmeasuring aquaculture sustainability. Roth et al. (2000) concludedthat the static measurement of a footprint-based approach will notin itself explain the reason for a non-sustainable development of aquaculture. Consequently, the use of EF as a reliable tool for the

support of a comprehensive decision making process in aquacul-ture is limited compared to other sectors ( Roth et al., 2000 ).

Consequently, Mungkung et al. (2006) advocated the use of LCA inseafood eco-labeling, certi cation and consumer education practices.However, Pelletier and Tyedmers (2008) identi ed that current LCApractices consider a range of environmental impacts that differ fromthe most eco-labeling, certi cation and consumer awareness pro-grammes currently practiced. Similarly, Ellingsen et al. (2009) pointedoutthe limiteduse fordeterminingtheessenceof an environmentally-friendly sheries and aquaculture industry in the public environ-mental debate and stressed the need of scienti cally sound, e.g.environmental analyses to communicate the basis of eco-labeling.

The growing interest on certi cation of aquaculture productsindicates a potential in reducing production externalities and

increasing ef ciency. However, most certi cation practices mainlyfocus on high-value species intended for export and are based onthe willingness of the farmer to get such certi cation. Hence,a coherent regulation and framework for aquaculture products isrequired. European Union regulation EC No. 710/2009 addressingthe issue of organic aquaculture production came into force in 2009(EU, 2009 ) setting a number of guidelines and principles related tothe origin of animals, husbandry practices, breeding, feeds andfeeding, disease prevention and veterinary treatment. This regu-lation will result in major changes to sh production throughcerti cation, while at the same time in uencing the role of government regulations and institutions, in the near future.However, the regulation is not comprehensive and the progress onthe development of legislative and institutional framework is slow

(Mente et al., 2011 ). Therefore, LCA-based certi

cation scheme

Fig. 2. Simpli cation of data enveloping analysis (DEA) of mussel production.



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needs to be implemented in the legislative framework to enforcesustainable aquaculture development.

Undoubtedly, the growing importance of global aquaculturedemandsfor theevaluation andadaptation of quantitative tools for theidenti cation of hot spots for potential technical improvements withregard to economic ef ciency, environmental and social concerns.Thus, in addition to supporting policy making processes, futuredevelopmentof the aquaculture industryrelies on assessment tools toevaluate prospected expansion under the dominion of sustainability.

6. Conclusions

For sustainable aquaculture development, a broader range of science based decision making tools is the key to enhance aware-ness and policy formulation. Key global problems generated fromaquaculture are water use, nutrient and organic matter releases,impacts associated with provision of feed, introduction of diseases,introduction of exotic species, escapes, changed usage of coastalareas, and climate change. Thus, application of assessment toolsneeds to be speci cally adapted. Several tools have been presentedin the past, but adaptation to aquaculture is insuf cient. The failureto include impacts distinctive to aquaculture is accompanied withlarge discrepancies in methods employed. To summarize, limita-tions stem out the fact that no single tool alone is capable orsuf cient in itself for generating a comprehensive assessmentappropriately encompassing the different aspects of sustainability.Although large strides have been made in reaching standardizedmethods for environmental assessment tools such as LCA, their usein policy formulation and decision making requires relentless effortto develop the tools using fundamental problems known to aqua-culture. This underscores the use of these tools as only one of several tools that should be integrated to assure comparability.Furthermore, comparability is only achieved if inter-conversion of data can easily be conducted, demanding for guidelines on thefunctional units used and normalizations carried out in parallel.Development of a comprehensive tool integrating the various

aspects of sustainability in aquaculture could potentially easedecision making. However, the development of such universalassessment tool requires more contextual understanding andbroader participation that will expand the realm of choice availableto decision makers.

Decision making should incorporate feedback and sociallearning processes and re ect what is continually being learnedfrom the mutual evolution of tools andtechniques, its social setting,and consequent outcomes. Efforts to improve the sustainability of aquaculture production will require efforts that must include anoptimization on how to ef ciently allocate resources betweencompeting users, maximizing returns (outputs) and minimizingimpacts (from inputs). The new approach of linking DEA and LCAstimulates new methodological developments and presents

a driving force to environmental sustainability through economicbene ts envisaged by increased operational ef ciency. Finally,sustainability includes many economic and social aspects, apartfrom the environmental ones. LCA or other assessment tools needto combine economic, environmental and social aspects tocomprehensively support sustainable aquaculture development.New approaches in aquaculture LCA parting from the traditionalLCA methodology is thus needed, including the development of appropriate impact categories, distinctive to the aquaculturesystem, providing the basis for coherent regulatory framework.

Acknowledgment

The authors would like to thank Karsten Tusche, Saskia Kroekel,

and Chris van Bussel for their contribution in proof reading the

article and support during the review process and writing of themanuscript. Financial assistance is provided by Deutscher Akade-mischer Austauschdienst (DAAD) and Gesellschaft fr MarineAquakultur (GMA) mbH, which the authors are grateful.

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