McManus, Marcelle and Taylor, Caroline and Mohr, Alison and Whittaker, Carly and Scown ...

19 Pages·2017·2 MB·English

by  Christine Middleton

Challenge clusters facing LCA in
environmental decision-making—what we
can learn from biofuels
Marcelle C. McManus, Caroline
M. Taylor, Alison Mohr, Carly
Whittaker, Corinne D. Scown, Aiduan Li
Borrion, Neryssa J. Glithero, et al.
The International Journal of Life
Cycle Assessment

ISSN 0948-3349

Int J Life Cycle Assess
DOI 10.1007/s11367-015-0930-7
1 23
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1 23
IntJLifeCycleAssess
DOI10.1007/s11367-015-0930-7
LCAFORENERGYSYSTEMSANDFOODPRODUCTS
Challenge clusters facing LCA in environmental
—
decision-making what we can learn from biofuels
MarcelleC.McManus1&CarolineM.Taylor2&AlisonMohr3&CarlyWhittaker1,4&
CorinneD.Scown5&AiduanLiBorrion1,6&NeryssaJ.Glithero7&YaoYin8,9
Received:19December2014/Accepted:30June2015
#TheAuthor(s)2015.ThisarticleispublishedwithopenaccessatSpringerlink.com
Abstract development, so that its use can more effectively inform
Purpose Bioenergy is increasingly used to help meet green- policymakers.
house gas (GHG) and renewable energy targets. However, Methods Thereview isbased on the results froma seriesof
bioenergy’s sustainability has been questioned, resulting in workshopsfocusedonbioenergylifecycleassessment.Expert
increasinguseoflifecycleassessment(LCA).Bioenergysys- submissions were compiled and categorized within the first
temsareglobalandcomplex,andmarketforcescanresultin two workshops. Over 100 issues emerged. Accounting for
significantchanges,relevanttoLCAandpolicy.Thegoalof redundanciesandclosesimilaritiesinthelist,thisreducedto
this paper is to illustrate the complexities associated with around60challenges,manyofwhicharedeeplyinterrelated.
LCA,withparticularfocusonbioenergyandassociatedpolicy Some ofthese issueswerethenexploredfurther ata policy-
facingworkshopinLondon,UK.Theauthorsappliedarigor-
ous approach to categorize the challenges identified to be at
theintersectionofbiofuels/bioenergyLCAandpolicy.
Results and discussion The credibility of LCA is core to its
useinpolicy.EvenLCAsthatcomplywithISOstandardsand
Responsibleeditor:RolfFrischknecht policyandregulatoryinstrumentsleaveagreatdealofscope
forinterpretationandflexibility.Withinthebioenergysector,
MarcelleC.McManusandCarolineM.Taylorarethejointfirstauthors.
thishasledtofrustrationandattimesalackofobviousdirec-
* MarcelleC.McManus tion. This paper identifies the main challenge clusters: over-
[email protected] archingissues,applicationandpracticeandvalueandethical
judgments.Manyofthesearereflectiveofthetransitionfrom
applicationofLCAtoassessindividualproductsorsystemsto
1 DepartmentofMechanicalEngineering,UniversityofBath,
the wider approach that is becoming more common. Uncer-
BathBA27AY,UK
taintyinimpactassessmentstronglyinfluencesplanningand
2 EnergyBiosciencesInstitute,UniversityofCalifornia,
complianceduetochallengesinassigningaccountability,and
Berkeley,CA94704,USA
communicatingtheinherentcomplexityanduncertaintywith-
3 InstituteforScienceandSociety,SchoolofSociologyandSocial
inbioenergyisbecomingofgreaterimportance.
Policy,UniversityofNottingham,NottinghamNG72RD,UK
Conclusions The emergence of LCA in bioenergy gover-
4 Presentaddress:RothamstedResearch,HarpendenAL52JQ,UK
nanceisparticularlysignificantbecauseothersectorsarelike-
5 LawrenceBerkeleyNationalLaboratory,Berkeley,CA94720,USA ly to transition to similar governance models. LCA is being
6 Presentaddress:DepartmentofCivil,EnvironmentalandGeomatic stretchedtoaccommodatecomplexandbroadpolicy-relevant
Engineering,UniversityCollegeLondon,London,UK questions,seekingtoincorporateexternalitiesthathavemajor
7 SchoolofBiosciences,UniversityofNottingham,NottinghamLE12 implications for long-term sustainability. As policy increas-
5RD,UK ingly relies on LCA, the strains placed on the methodology
8 EBI,Berkeley,CA,USA are becoming both clearer and impedimentary. The implica-
9 Presentaddress:IdahoPublicUtilitiesCommission,Boise,ID,USA tionsforenergypolicy,andinparticularbioenergy,arelarge.
IntJLifeCycleAssess
Keywords Biofuels .Bioenergy.LCA .Policy. crops will lead to competition between the use of crops for
Sustainability.Uncertainty food/feed or for fuel or that using land for bioenergy could
potentiallycontributetoothereffectsthroughglobalmarkets.
There have also been concerns that the production of
1Introduction bioenergy crops being carried out on environmentally sensi-
tivelands,orthatlandwhichhasbeenacquiredintheGlobal
Climatechangemitigation,energysecurityandsustainability South, leads to the loss of livelihoods and local food and
have become increasingly important in global policy. These energy production (van Eijck and Romijn 2008). Further,
havebeenmajordriversbehindtheincreaseduseofbiofuels many of the potential sustainability impact categories for
and biopower in renewable energy portfolios. As climate biofuels occur at the systems level and so cannot be easily
change and greenhouse gas (GHG) reduction has played a separatedintodistinctcategoriesamongenvironmental,eco-
more central role in international policy agendas, nomicorsocialimpacts(MohrandRaman2013),thusmak-
policymakers and regulators have looked to existing tools, ingLCA’staskofanticipatingtheunanticipatedallthemore
suchaslifecycleassessment(LCA)toaddressnewormore challenging.
complexquestions. Because heavy use of LCA in bioenergy policy entered
LCAhasemergedasanapproachtoquantifyandaccount from the climate discourse, most of the emphasis thus far
for environmental impacts in a product life cycle and has has been on GHG balances (McManus and Taylor 2015).
served regulatory and permitting needs for decades (Taylor However, as engagement with broader sustainability stan-
andMcManus2013).Whenatoolwasneeded,itwasalogical dards has grown, the metrics space has begun to broaden to
choice,anditnowformsacorecomponentofseveralbiofuels include social and ecosystem impacts among others. While
policyinstruments(i.e.EURenewableEnergyDirective(EU theemergenceofsuchmetricsdirectlyservesthepolicypro-
2009), UK DfT Renewable Transport Fuel Obligation (UK cess,theparticularchallengehereisthatapproachestodoso
DTI 2012), US EPA Renewable Fuel Standard (RFS2, US are still in early stages and have correspondingly higher un-
EPA2010)andCaliforniaAirResourcesBoard’sLowCarbon certainty. LCA is balanced between its past and continuing
FuelStandard(CARB2014)).Originallyfocusedonaccount- futureasadata-based,rigorousretrospectivetoolforproduct
ing for current or past impacts in existing projects, LCA is andprocessoptimizationanditsparallelfutureasapolicyor
becomingforwardlookingtoassessfutureimpactsofamore strategicplanningtool.
consequential nature. The methods are slowly evolving as Thegoalofthispaperisthereforetoillustratethecomplex-
LCAisaskedtoanswerfundamentallydifferentquestions. itiesassociatedwithusingLCAandthewayitisdeveloping,
Traditionally, LCAwas used toanswer specific questions with particular focus on bioenergy, so that its use can effec-
(SandénandKarlström2007)thataredirectlyattributableto tivelyinformpolicy.Theanalysisdrawsonexpertinputfrom
the life cycle of a product in the existing technological and a series of workshops in the UK and USA. It identifies and
economicclimate(Sanchezetal.2012).Thisisnowknownas discussesthespecificissuesassociatedwiththeapplicationof
attributionalLCA(aLCA).LCA’snewer,undisputedlyimpor- bioenergy/biofuelsLCAinapolicycontext,basedoncatego-
tanttaskistohelptoanticipatefutureimpacts,soastoinflu- rizingexpertinputofchallengesarisingintheapplicationof
ence and evaluate policy options as part of governance for LCA.Itreflectsthethreeprimarystakeholdercommunitiesin
sustainabilityinenergy, emerging technology and resources. biofuels/bioenergy LCA: policymakers and other decision-
ThisisconsequentialLCA(cLCA)andallowsimpactstobe makerswhorelyupontheresults;practitionersandreporters
consideredinawider,evenglobal,contextofproducersand who use the methods for compliance and study; and re-
consumers (Nuffield 2011). This more consequential ap- searchers focused on expansion, development and improve-
proach is considered to be the appropriate method for mentofthemethods.TheseissuesseeninbioenergyLCAare
policymakers(Branderetal.2009).However,thisexpansion not restricted to bioenergy, but they are being experienced
has been proven challenging and, in some cases, here first due to the global nature of bioenergy production
controversial. anduseandthesystemiclinksbetweenagricultureandener-
LCAisnowbecomingmoreheavilyreliedupontoreveal gy.Therefore,lessonslearnedfromthisareawillhaveimpli-
potential unintended consequences of bioenergy. This use is cations across both LCA methodology and (energy) policy
almost unique to the (bio)energy field and, in some cases, development.
masks a high degree of uncertainty. Since biofuel policies
wereestablishedintheUSAandEuropeanUnion(EU),there
has been concern that unintended consequences could arise 2Methods
and threaten climate and other sustainability goals (e.g. Mol
2007; Jaeger and Egelkraut 2011). Among these have been Issues associated with the use of LCA for bioenergy and
concernsthatamajorswitchtobiofuelsproducedfromfood biofuels were compiled from open expert submissions in
IntJLifeCycleAssess
associationwithtwoworkshopsrunasaresultofapartnership significantlytomajordrawbacksexperiencedinthebioenergy
betweentwooftheinstitutions(BathandBerkeley)intheUK sectoroverthelastdecade(Adamsetal.2013).
andUSAonbioenergylifecycleassessment.Thecontributors Transparencyacrossstudiesisvitalforanyharmonization
werenotrestrictedinanywayintermsofwhattheysubmitted, of similar analyses; otherwise, large differences can occur,
andthegroupdiscussedallindepthduringthefirstworkshop. leading to uncertainty (Hennecke et al. 2013). Even small
Some of the issues raised within these workshops were ex- inconsistenciesinemissionfactorsusedbetweenGHGcalcu-
plored further at a policy-facing workshop in London, UK. lationtoolscangenerateverydifferentresultsusingthesame
Thecallforissueswasdeliberatelybroadtoencourageawide inputdata.Forexample,betweenthe‘BioGracetool’andthe
range of contributions but framed as ‘challenges’ associated ‘Roundtable on Sustainable Biofuels (RSB) GHG tool’ for
with LCA in bioenergy. Over 100 issues were contributed. assessing the GHG balance of biofuels, economic operators
Accountingforredundanciesandclosesimilaritiesinthelist, couldenhancethecalculatedGHGperformanceoftheirbio-
thisreducedtoaround60challenges,manyofwhicharedeep- fuel by 20–35 % without changing the production process,
ly interrelated. These were sorted into three supergroups taking advantage ofdifferencesintheir emissionsfactors by
(Fig. 1): overarching issues, application/practice and uptake, selectingthemorefavourabletool(Henneckeetal.2013).
eachofwhichisdiscussedbelow,illustratingthecomplexities A numberofregulatoryagencieshaveattempted toover-
associatedwithusingLCAandthewayitisdevelopingwith comethisbyreleasingdetailedguidelinesforproductsunder
particularfocusonbioenergypolicy.Detailandexamplesas- theirpurview(DECC:approvalunderRTFO;EPA:pathway
sociated with the issues identified were provided by the au- for RINs under RFS2; CARB: pathway under LCFS). This
thorsthroughtheirexpertknowledgeandliteraturereview. has resultedina proliferation ofnon-transferableguidelines,
aseachwasoriginallydesignedforaspecificproductorpur-
pose.Forexample,theEuropeanRenewableEnergyDirective
3Results:issues/challenges calculation methodology was designed to account for the
GHGemissions frombiofuels.Theallocationmethodspeci-
3.1Overarchingissues fiedintheRED(energycontent)cannoteasilybeemployed
by those performing similar GHG assessments in other
Thereisageneralizedsetofoverarchingissuesunderpinning bioenergy systems, for example anaerobic digestion, as the
thepolicyuseofLCAwhichemergedintheissuessubmitted: technology generates large quantities of a valuable co-prod-
credibility,transparency,complexityandcommunication.The uct, digestate, but has negligible energy content (Manninen
credibility of LCA is core to its use in policy. Transparency etal.2013).Asaresult,themethodsofassessmentbetween
andeffectivemanagementofcomplexityandcommunication each set of guidelines differ considerably in their system
are key to this; without them, perception and support falter boundaries,co-productandwastedefinitionsandmethodsof
(DragojlovicandEinsiedel2015).Uncertaintiesandcomplex, allocationofenvironmentalimpacts(Whitakeretal.2010).
conflicting results reported in studies of the greenhouse gas These methods all comply with the ISO standards
(GHG) savings from utilizing biomass contributed (14040:2006 (CEN 2006a) and ISO 14044:2006 (CEN
Fig.1 ChallengeclustersinLCAforbioenergy
IntJLifeCycleAssess
2006b))thatgoverntheLCApractice,buttheISOstandards misinterpretationthattransportemissionswereamajorcause
leaveagreatdealofscopeforinterpretationandflexibilityto forconcerninnetGHGemissionsofbioenergysupplychains.
the LCA practitioner (Aylott et al. 2011). As a result, it is Media reports and local anti-biomass websites then
virtuallyimpossibletomakeconfidentcomparisonsbetween reproduced this, emphasizing the less significant transporta-
studiesastheycandiffernotonlyduetoinherentvariability tionimpactsratherthannitrogenfertilizeruse.
betweensystemsbutalsoduetothemethodsinwhichtheyare Transparency, relying on detailed communications and
examined(MenichettiandOtto2008).Thislackofconsisten- chainsof evidence,can increasethe value of LCA compari-
cy,andhencecredibilityinplaces,makesitdifficultforgov- sons.However,therearetrade-offsfortransparency.Thelevel
ernment departments and policymakers to use LCA studies ofdetailoftendesiredbyscientistsandpractitionerscompared
(UKWorkshop2012). withthetimeavailabletothepolicymakerisoftenconflicting;
Thereisagreatdealofvariabilityandcomplexityinvolved therefore,inordertosupportcredibility,somemechanismto
in bioenergy system GHG analysis, some of it tied to meth- communicatecomplexityisrequired.
odological decisions consistent with standards for LCA and
some of it particular to biomass systems. Direct GHG emis- 3.2Methodology:applicationandpractice
sion means ranged from −56 to 163 g CO eq/MJ of fuel in
2
studies oflignocellulosicethanol ina recentstatistical meta- Issues associated with LCA methodology fell into two
analysis(Mentenetal.2013),respondingtocultivation,yield categories. The first centers around the formulation of
and soil carbon factors, among others, beyond the obvious questions for analysis and boundary issues, including
differences in feedstock. For GHG emissions from indirect models to address these issues. The second set focuses
(market mediated) land use change, a summary of midpoint on technologies assessed, mechanisms of impact and
values for corn ethanol (US) from high resolution models data representation.
ranged from 14 to 82 g CO eq/MJ, reflecting prior land use
2
and management assumptions, as well as global market 3.2.1MethodologyI:methods:scope,systemboundaries
models(Chumetal.2011),introducingadditionalcomplexity andmodelintegration
andvariability.Evenwithinacoordinatedanalysisvaluescan
differ widely; GHG emissions including indirect land use Goaland scopesettingisthe firststepinperformingaLCA
changecomparinguncertaintypropagationanddifferentallo- andthusinfluencesthesubsequentphases(Tillman2000).It
cation types ranged from about 35 to 85 g CO eq/MJ fallstothetrainedpractitionertoenforcethevalidityofgoal
2
(midpoints) for wheat bioethanol in the UK (Yan and Boies andscopesettingfortherequiredanalyses.Forexample,the
2013). In some cases, poor documentation prevents readers levelandqualityofdatacollectedmustbesufficientinorder
fromreproducingtheresultsorevaluatingthequalityofinput tofulfilltheoriginalaimofthestudy(Singhetal.2010).The
data;lackofdetailandinformationalsoresultsinirreconcil- systemboundariesaresetduringthisstage,andthesearekey
able discrepancies (e.g. Yates and Barlow 2013). In a sam- toanyanalysis(Birdetal.2011).Thechoiceofsystembound-
plingofmorethan40studiesforcomparativeassessmentof ary incomparative studies may leadtodifferentconclusions
rapeseedbiodieselthatmetabaselinelevelofdetailonmeth- and decisions about which products to promote, as in the
od,dataandassumptions,only28hadsufficienttransparency classicdebatesurroundingnappies/diapers(Bond2005),and
forcomparison(MalçaandFreire2011). have an influence on rankings through variation in scope or
Failuretotransparentlyreportormanagethecomplexities the impact that is assessed (Suh et al. 2004). Bio-based
in bioenergy GHG assessments can lead to confusion and (poly)lactic acid, for example, out-performed conventional
misleadingresults(Adams etal.2013)and facilitatemisrep- polymersonenergyconsumptionandGHGs;however,clear
resentation that has the potential to focus policies on the ranking was lost when ecosystem quality metrics were
wrong areas. The ‘carbon sink or sinner’ report (AEA assessed(YatesandBarlow2013).
Technology/Ricardo-AEA 2009) reviewed the sensitivity of Allocationmethods(thewayinwhichimpactsareassigned
the results in the Biomass Environmental Assessment Tool toco-products)givequantitativelydifferentresults,whichcan
(BEATv2 (AEATechnology and Associates 2010)) to bio- also lead to incomparability (Wang et al. 2011). An assess-
mass supply chain parameter assumptions, concluding, mentofUKwheatethanolwithregionalN Oparametersre-
2
among other things, that the lifecycle GHG emissions were ported GHG emissions (midpoint values) of 51, 64 and
stronglyinfluencedbyhowthefuelwasproduced,transported 68 g CO eg/MJ for energy allocation based on energy, eco-
2
and processed. They stated that ‘bad practices’ involving nomics and substitution, respectively (Yan and Boies 2013).
transportingfuelsatverylongdistancesandexcessiveuseof This affects both comparison and compliance, as policies
nitrogenfertilizerscouldreducetheemissionssavingsforthe mandate different allocation types: by substitution on the
same fuel by 15 to 50 % (Bates et al. 2009). Collectively RTFO, RFS2, LCFS and RED for electricity co-production,
assessing these two stages of the supply chain created a byenergycontentinREDandasfallbackforRFS2andLCFS
IntJLifeCycleAssess
andbyeconomicvalueasafallbackfortheRTFO.Thus,the productallocationandhighuncertaintyassociatedwithsome
same pathway ranks differently across policies. Direct GHG emissionsparameters.
emissions for bioelectricity from rapeseed using allocation Currently,GHGassessmentsdominatethebiofuelssustain-
choices from primary renewable policies improved on the ability debate; for example, more than half of 53 sampled
reference case by 60 % (sub peas) or 21 % (sub soy) with LCA studies of lignocellulosic biofuels published between
substitution,33%forenergyallocationand16%foreconom- 2005and2011wereGHGfocused(Borrionetal.2012).Al-
icallocation(Wardenaaretal.2012).Suchincompatibilitycan though bioenergy is a global commodity, local values and
occur even with methodologies compliant with industry or drivers may differ, and effects like GHG emissions are not
regulatory standards for biofuels GHG reporting (Whittaker always observed near their cause. Location-specific metrics
etal.2011). are expanding, though, particularly as water captures more
System boundaries can become inconsistent because of attention and the relevance of other resource competition
allocationdecisionsorbecausethescopeorthegoalsofanal- emerges in the discourse. However, issues other than GHG
ysischanges.Forexample,methodsforreducingtheoverall tendtobespecifictothelocationofproductionorprocesses.
farm environmental footprint will not necessarily result in a For example, Scown et al. (2011) demonstrated the location
lowcarboncrop(bothofwhichareassessedwithvalidLCAs) specificityofwaterconsumption/withdrawalandpollutionin
and vice versa, and the differing purposes lead to different biofuelproductionsystems.Integratingsuchimpactsisham-
boundaries, which are often conflated (Whittaker et al. pered since LCA is, traditionally, not a tool that examines
2013). The farm-based approach considers the overall envi- local impacts and thushas crucial gaps. Forexample,water,
ronmentalfootprintofafarmsite,whereasacrop-basedanal- particulate emissions and wider impacts on ecosystem ser-
ysis focuses on crop- and product-specific aspects that go vices are often not well modelled and may lack spatial or
beyondthefarmgate.Agriculturalassessmentsareparticular- biophysical data. Gaps in data availability and data quality,
lysensitivetoscopechangesinresponsetopurpose(Royetal. as addressed elsewhere, are generally not highlighted in the
2009),whichhasmajorimplicationsforbioenergypolicyde- finalresult,whichareoftendistilleddowntoasinglenumber
cisions.Forexample,theREDwas designedtopromote the (e.g.N OemissionsfromsoilundertheIPCCguidelines(De
2
production of biofuels from ‘non-food’ biomass feedstocks Kleinetal.2006)).
anddoesthisbyspecifyingintheGHGaccountingmethod- Analyses with complex boundaries often result in mul-
ology that cereal residues are not allocated upstream emis- tiple models in the final analysis. Ecosystem, market and
sions from cultivation. This immediately places these feed- social dynamics contribute to impact processes. Structural
stocksatanadvantagebutisanexamplewheretheintention changes, such as infrastructure and technology changes
andapproachofthe analysishasbeenheavilyinfluencedby and other progress along the innovation trajectory and
policy(Whittaker2014).Perhapsmoresignificantly,thedetail adoption rates and patterns, contribute to scenarios for
of goal and scope is seldom conserved when analyses are impact and are also beyond LCA’s scope. All of these
merged into the policy process, because data, for example introduce the need to rely on and integrate increasingly
GHG values, are taken from a range of studies to inform complex and speculative modelling and shape the devel-
policyorregulationortobethebasisoffinancialincentives, opment of assessment tools (Wicke et al. 2015) and lead
suchasfeed-intariffs.Often,severalstudies,whichmayhave to efforts to develop general quality criteria for modelling
beenoriginallyproducedforadifferentpurpose,aretakento and recommend best-practice LCIA models for particular
informpolicy(McManusandTaylor2015). impacts from the plethora available (Hauschild et al.
ThistendencytoaggregatetheGHGestimatesforcompar- 2013). Because advances in elucidating or representing
ative decisions is logical but overlooks the complexity and the mechanisms that underpin models occur in many dif-
detail specificity associated with GHG analyses for ferent academic disciplines (see, e.g. Arbault et al. 2014),
bioenergysystems.Forexample,Farrelletal.(2006)conduct- integrating the sets of data or models to give a picture of
edameta-analysisofearlycornethanolLCAsandfoundthat, the life cycle impacts is challenging, though essential for
even for direct effects (attributional analysis), the GHG and LCA to contribute policy setting or analysis (Wicke et al.
net energy results varied substantially. Studies with the least 2015). In connecting models to describe various portions
favourableresultsforcornethanolyieldedacarbon-intensity of the overall value chain and potential consequences, the
of nearly 120 g CO eq/MJ, which is approximately 30 % overall complexity and level of detail in the analysis can
2
higherthangasoline.However,thosestudiesfailedtoallocate mask areas where boundaries conflict, even for relatively
anybiorefineryimpactstoco-productsandusedoutdateddata narrow studies. Ensuring that the full set of models inte-
forkeyindustrialprocesses.ForrapeseedbiodieselinEurope, grate harmoniously and preserve reasonable levels of
acarefulanalysisfoundcalculatedemissionsrangingfrom5 transparency, rigour and robustness is an ongoing chal-
to170gCO eq/MJ(MalçaandFreire2011),arisingprimarily lenge that worsens as use of custom-built tools proliferate
2
fromdifferencesinmodellingsoilemissionsandlanduse,co- (see, for example, CA-GREET 2014).
IntJLifeCycleAssess
3.2.2Methodology2:technicaluse:mechanisms, primary product. For example, Scown et al. (2014) showed
technologiesandrepresentationsofdata thatthenetGHGandwaterimpactsofutilizingligninforheat
and power at cellulosic biorefineries or exporting lignin for
Systemsustainabilityisoftenestimatedbysummingtheim- co-firing with coal varied greatly depending on long-term
pactsofvaluechaincomponentsandattributionalLCAs(see, trendsinpowerplantretirementandnewconstruction.Ifthe
e.g.BentoandKlotz2014).Inordertoassessthesustainabil- export of additional biopower to the grid encourages early
ityofbiofuelproduction,itisnecessarytoconsidereachbio- retirementofagingcoal-firedpowerplants,theGHGfootprint
fuel from each feedstock, according to its own merits, and ofethanolintheirscenariowaspredictedtobeapproximately
alongside specified sustainability criteria (Royal Society 50%lowerthanifbiopowerexportsencouragedeferredcon-
2008). There is, however, a lack of the necessary codified structionofnewnaturalgascombinedcycle(NGCC)power
sustainabilitycriteriaandarecognitionofdataneedstosup- plants.
portthem(Hechtetal.2008),andmostprogressioninLCA- Interactionmechanismscanalsobethroughmarketmedi-
based reportingmethodshas focused ondevelopingasingle ation that emerges within or across borders and/or sectors,
method (predominantly based around GHG measurement which may rely on speculative global market dynamics.
(McManusandTaylor2015))toassessallbiofuelsinasimilar Though such consequential approaches started with general
manner.Thesuccessofthisismixed,especiallywiththein- product life cycles (Weidema 1993; Zamagni et al. 2012),
creasingimportanceofsocialandeconomicsustainabilitypa- attempts to assess the impact of global commodity market-
rameters, and with mismatches between regulatory mecha- driven land use dynamics in relation to biofuels have made
nisms in methodological approaches such as allocation and it a common concept to guide policy in attempting to avoid
defaultvaluesforfuelsandsystems. unintended consequences in the form of indirect land use
Tobeincludedinanassessment,mechanismsforinterac- change(McManusandTaylor).Thedrawbackisthatconsen-
tionsamongportionsofthephysicalsystemorvaluechainare susaroundtheapproachhasnotyetemerged(Marvugliaetal.
also needed. The fundamental interactions are bio/geophysi- 2013;RosegrantandMsangi2014;Schmidtetal.2015);thus
cal, such as in soil carbon accumulation and mobility, or in incorporating such market-mediated impacts for consequen-
nutrientandwatercycles,andgiverisetofeedbacksatava- tialanalysisincreasesthevariabilitydramatically(Vázquez-
riety of spatial and time scales (Bagley et al. 2014). These Rowe et al. 2013). For example, estimates of ILUC GHG
mechanismsdrawonscientificallyactiveareaswhereknowl- impactsrangedfromabout3toabove220gCO eq/MJrape-
2
edgeisevolvingrapidlywithbothhighandlowuncertainties seed biodiesel and ~5 to ~100 g CO eq/MJ for bioethanol
2
(see,e.g.Balvaneraetal.2014;Greeneetal.2015)andpro- from maize over the last 5 years, even in current analyses
vide an idea of the necessary scale of the system boundary whenrangesforsuchvalueshavetightenednoraretheauthors
neededtocapturerelevantimpacts.Sustainabilityassessments of thatanalysis optimistic about such uncertainty decreasing
ofbiofuelsystems showverystrongsensitivity tosoilemis- soon (Ahlgren and Di Lucia 2014). Thus far, ILUC has re-
sions, particularly nitrogen. Using different N O emission ceived the bulk of attention among consequential LCA of
2
methodsgaveGHGvalues(midpoint)differingby25%when biofuels.Butmarket-mediatedmechanismsarealsobeingex-
usingIPCCTier1methodsoraUK-specificmodelwithinthe plored for other properties, such as indirect fuel use
sameassessmentofUKwheatethanol(YanandBoies2013). (Rajagopal et al. 2011) and rebound effects (Vivanco and
A meta-analysis of LCA studies on European rapeseed bio- vanderVoet2014;Smeetsetal.2014).Likewise,socialim-
dieselfoundthatGHGintensitiescorrelateddirectlywithhow pacts, crucial for sustainability assessments, arise through
soilemissionsweremodelled(MalçaandFreire2011).Some cross-cuttingmechanisms(see,e.g.Benoîtetal.2010).About
ofthesemechanismsdiffersubstantiallybetweenfirstgener- 20%ofannualLCApublicationstouchonoraddresssocial
ationandadvancedbioenergysystems.Forexample,perenni- factors(McManusandTaylor2015)andguidelinesandmeth-
alcropscanhavebelowgroundcarbonallocationsmorethan odologiesaredevelopingbroadlybecauseofthelabyrinthine
fourtimeshigherthanatraditionalcorn-soyrotation,andbe- relationshipsamonggroupsandtherangeofpotentialimpacts
lowground biomass increased by 400–750 %, measured for (Wuetal.2014).Manyofthesearereflectedqualitativelyin
miscanthus, switchgrass and native prairie during establish- internationalsustainabilitystandards(see,forexample,FAO’s
ment ( Anderson-Teixeira et al. 2013). The potential for pe- CompilationofBioenergySustainabilityInitiatives2011).In
rennial bioenergy crops to increase soil carbon under some nearlyallthesemechanisms,thescienceorstateofknowledge
conditions has contributed directly totheir preferentialrank- is changing rapidly. As new insights emerge, accounting for
inginoverfirstgenerationpathwaysinpolicyinstruments. impactsintheLCAthatdependonthemislagging.
Multi-sectoranalysesorso-calledconsequentialfactorsin- Theabsenceofspatiotemporalcomponents,whichunder-
troduce additional complex mechanisms for interactions lie most mechanisms in LCA, is of particular concern for
among the value chain and potential consequences. One bioenergy. Time is most commonly incorporated with set-
routeisthrough mechanismsthatdonotdirectlyinclude the year analyses (e.g. N years in the future) and linear
IntJLifeCycleAssess
annualization. While the former is a viable, if limited, ap- practices (Glendiningetal. 2009;NaturalEngland2013),as
proach,thelatterisproblematicforagriculture.Simpleannual doestheglobalcommoditiesfeed/foodmarket.Theeffective-
croprotationsthatmakeupthebulkofagriculture(corn,soy, nessofsuchincentivestoserveclimatepolicygoalsdepends
wheat, etc.) are well represented this way, but, for perennial on the accuracy of calculated avoided life cycle GHG emis-
crops,whereyieldsdevelopovertimeandmanagementprac- sionsandthesystemboundariesconsidered.Farmersarekey
ticesmayvaryfromyeartoyear,simpleannualizationisnot totheprovisionofempiricaldata;increasingthecertaintyof
alwaysreflectiveofreality.Thedifferencebetweenestablish- the assessments for that portion of the life cycle. However,
mentandproductionperiodsforsuchcropsarekeytoemis- becauseagriculturalpracticesdifferbyregion,evenoverrel-
sionsestimates;simulationsofnitrogenlossfrom2-year-old ativelysmalldistances,andmanagementdecisionshavelarge
switchgrasswere360–410%higherthanformaturestandsat impactsinbioenergy(Davisetal.2013),transferabilityofdata
the same fertilization levels, depending on harvest number, orexistinganalysisfromaregionwheremuchisknowntoone
resultingina15-yearaverageof20–30%thatofcottonunder wherelittleisknown(acommontechniqueinothersectors)is
thesameconditions(Sarkaretal.2011).Likewise,thetempo- questionable.
ral mismatch between conversion or harvest and carbon up- LCA for agricultural production is well-established (Roy
take in forest-based resources introduces decadal and longer etal.2009),butLCAforpolicyplanninginbioenergyincor-
time frames, and concerns over the potential carbon debt porates the potential implementation of large-scale biomass
caused between harvesting and re-establishing timber stands production, which lacks certainty. Improvements in agricul-
have become an important issue for climate and bioenergy turalyieldshavebeensubstantialoverthepastdecades(e.g.
policy(LamersandJunginger2013). UScornyieldshaveroughlydoubledsince1976,USDAda-
Location-dependentissuesforLCAarenotlimitedtositing ta).Projections ofproductivity changes overtimeare specu-
informationandlandusechanges;theyaredominatedbythe lativebutimportantforlong-termplanning.Forexample,car-
limitations in inventories from location dependence in input bonpaybacktimesdecrease30–50%whencropyieldsreach
data and thelocationdependenceofimpactmetricswateror the90thpercentileinglobalyield,representingcropproduc-
biodiversity (Seager et al. 2009) as well as trade, market tivityincreasesand/orsubstantialmanagementchangesacross
mediated and social impacts,all addressed in other sections. global averages (Gibbs et al. 2008), in effect identifying the
Spatialcharacteristicsofthefeedstockproductionsystemare benefitsofaddressingtheglobalyieldgap.Therearepotential
oftenassessedextraneously ineconomicterms.Scownetal. benefitsinnon-GHGimpactsalso.Forexample,inadvanced
(2013) found that, in their scenario that incorporated corn bioenergy landscapes, it is possible for very small trade-
stover, wheat straw and Miscanthus in the USA, only 80 % offs in the economic balance to have a large favourable
ofavailablebiomasswasgeographicallyconcentratedenough impact on biodiversity under particular land conserva-
to warrant utilization for biofuel production; the remaining tion regimes (Evans et al. 2015). These represent chal-
biomass was too dispersed, resulting in prohibitively high lenging aspects for cross-sector agricultural LCAs to
transportation costs. While highly sensitive to supply chain include. Other complicating factors that are of increas-
characteristics,LCAisstillevolvingtoincorporatetheinter- ing importance include conservation mechanisms which
sectionbetweendevelopinginfrastructureandlogistics,such impact biodiversity (see, e.g. Evans et al. 2015), preci-
as transportation modelling (Strogen and Horvath 2013; sion agriculture where practices vary between or even
StrogenandZilberman2014).Thespatialaspectsofresource with fields (Weekley et al. 2012), alternate cropping
managementwillalsobegintocontributeinbioenergyLCA, systems (Perrin et al. 2014) and land sparing practices
as in critical resource assessment (Sonnemann et al. 2015), (e.g. Cohn et al. 2014) which are often multifunctional.
potentially to pivotal effect, because there are more critical Multifunctional landscapes provide many sustainability
resources than just land in biofuels, and land is a critical re- benefits (Perfecto and Vandermeer 2010) but expand
sourceinmorethanbiofuels.Generally,theseissuesintroduce the system boundaries increasing data requirements
reliance on multi-model, multi-scale systems. Data integra- (Rossing et al. 2007) and uncertainty (Jung et al. 2013).
tion, uncertainty integration,errorpropagation,certaintyand Risk, policy uncertainty, nascent markets, infrastruc-
multi-parameter output representation all become important ture and supply chains threaten adoption, which makes
andaredifficulttoconveysuccinctly. projection of roll-out rate or the extent of production
challenging. This increases reliance on representing sta-
3.2.3Bestpracticeandoptimization—farming tistical projections in data and uncertainty and shifting
policy estimates of expansion (Rajagopal and Plevin
Agricultureandfarminginparticulardeservespecialmention 2013), including how to reflect the ranges in the results,
as competition for land increases. Financial incentives and whether knowledge of the demographics can con-
awarded to the farmer to encourage planting of bioenergy tribute to analyses or types of analyses that are more
crops create an interaction among LCA, policy and farming useful from a policy perspective (Plevin 2010).
IntJLifeCycleAssess
3.2.4Robusthighqualitydataandgaps aremoreexplicitthanothers,forexampleEcoIndicator99and
ReCiPebothshowthreeoptionsrangingfroman‘absolutely
Dataavailability,transparency,curationandsharingarekeyto only proven cause and effect’ to a precautionary approach.
thelong-termsuccessofLCAbothgenerallyandforcompar- Pragmatically,thesedatabasesandsoftwarepackagesarefre-
isons used in bioenergy planning. Reliability of the results quentlythemostaccessiblesolutionforthepractitionersince
from LCA studies strongly depends on the extent to which primary data is either unavailable or too time consuming to
data quality requirements are met, where common problems gather(Hetheringtonetal.2014).Thisisreflectedintheliter-
includelackoftransparencyanddatavariationandgaps.For ature,whereuptakeofthesedatabasesisrapid;studiesciting
lignocellulosicethanol,forexample,datainconsistenciescon- the widely used ECOINVENT database launched in 2000
tribute to conflicts in published LCA results of GHG emis- (Frischknecht et al. 2004) had reached 2240 by mid-2014
sions (e.g. Wiloso et al. 2012), ranging from −1.25 to (scopus search, 18th July 2014). However, these proprietary
0.84 kg CO eq/km travelled when using E100 (Borrion databasesandsoftwaretoolscanlimittransparency,indepen-
2
etal. 2012).Thereare specificcases where there isminimal dentreproducibilityandtransferabilityastheunderlyingdata
data,forexample,enzymeproduction(Spatarietal.2010),or cannotbesharedinpublications.Thehigh-costsettingupand
where data is outdated, for example, pesticide production maintaining the quality of database impedes open access
(Audsleyetal.2009).Primarydatasets,despitetheiroverall (HellwegandCanals2014).Anumberofopendatasetsand
strength, also sometimes have errors (see, e.g. Cooper et al. standardization efforts seek to address this, in particular the
2012).Datasetcompositionsvaryregionally,andsometimes EuropeanPlatformonLCA’sEuropeanreferenceLifeCycle
sectorally, inthe completenessoftheirdataonwhich GHGs DatabaseandtheInternationalReferenceLifeCycleDatasys-
areincluded(AnsemsandLigthart2002).Reusabilityofdata temcommondataformatstandard,aswellasandtheUSDA
is highly dependent on sufficient data documentation, and LCA Commons and NREL US Life Cycle Inventory
standards are emerging (see, e.g. Sonnemann et al. 2013) to Database.1
addressthis,forexample,intheareaofLCAsusedforEnvi- Becauseawiderangeofstakeholdersusetheresults,indi-
ronmental Product Declaration (EPDs) (Ingwersen et al. cationsofdataqualityareincreasinglyimportant.Qualitative
2012). indicators can be used along with their quantitative counter-
While transferability is a common approach to supply partstoaddressdatatransparencyissuessuchasdata source
missingdata,usingthevaluefromanotherregionforamiss- andtoaddresstheconfidenceanduncertaintyofdata(seefor
ing parameter, the approach frequently fails for bioenergy. example,AnsemsandLigthart2002)underparticularcircum-
Data for non-global environmental impact categories fre- stances,suchasintheelectricitysector(see,e.g.Garraínetal.
quentlyvarybyregion,oftenforcategoriestowhichagricul- 2015). Qualitative indicators help to contextualize the rele-
turalassessmentsarehighlysensitive(e.g.ecotoxicity).Some vanceofthedatasothatpolicymakersareabletomakemore
impact categories, such as water quality and use impacts in informeddecisionsaboutthecircumstancestowhichthedata
bioenergy,canbelocal,regionalorboth(Daleetal.2010)and apply,thusmakingpolicyjudgementsbasedontheavailable
are further complicated bythe importanceofthe local water data more reliable. Such indicators are sometimes contained
context (e.g. drought to excess).Waterconsumption, for ex- within commercial software packages (for example
ample, may range from 5 to 2138 L per litre of ethanol de- SimaPro—PreConsultants(2014)andGaBi-PEInternation-
pending on regional irrigation practices in the USA (Chiu al (2014)). While these packages can aid very quick and ef-
etal.2009)).Region-specificdataarealsooftennotavailable fective calculations, it is also very easy for general users to
(for example land use and biodiversity (Dale et al. 2010)). employthemanddefaultdatabaseswithoutanunderstanding
Industrial data for emerging processes and technologies is oftheuncertaintyorqualityofthedatacontainedwithinthem.
frequentlylimitedduetocommercialconfidentialityandalso
as the data for such systems and an understanding of their
impact is nascent. New scientific understanding of various 3.3Uptake
impacts,suchastheimpactofairpollutantsonhumanhealth
(see,e.g.Hajatetal.2015;Nováketal.2014),ornewerissues Uptake of LCA results has been primarily driven by policy
such as ‘black carbon’ (see, e.g. Cai and Wang 2014; Otto settinginrecentyears,achangefromitspriorregulatoryuse
etal.2014),alsointroducedataormethodlimitations. (McManusandTaylor2015).Threemainareasareassociated
Undersomeconditions,datasets/databasesusedinaLCA with uptake: communication and complexity, policy and
reflectexternalvaluejudgments,ofwhichusersmayormay
notbeawareortaketimetodiscover.Forexample,thereare
1EPLCA: http://eplca.jrc.ec.europa.eu/; ELCD:http://eplca.jrc.ec.
levelsofdetailwithinandbetweendatasets,somewithwider
europa.eu/ELCD3/;ILCDStandard:http://eplca.jrc.ec.europa.eu/?page_
boundaries than others. There are also value judgments em-
id=86;NRELUSLCID:http://www.nrel.gov/lci/;LCACommons:http://
bedded in ‘off the shelf’ impact assessment methods. Some www.lcacommons.gov/