iinas et al (2016) wp 3 case study report us southeast final · bioenergy trade strategy for 2020...

BioTrade2020plusSupporting a Sustainable European Bioenergy TradeStrategy

IntelligentEnergyEurope

IEE/13/577/SI2.675534

DeliverableWP3

BiomassUseandPotentialforexporttotheEuropeanUnionfrom2015to2030

UnitedStatesSoutheast–CaseStudy

Publicity level: Public

Date: April 2016

DRAFTFORINTERNALBIOTRADE2020+USEONLY

DONOTCITEORDISTRIBUTE–SUBJECTTOCHANGE

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TheBioTrade2020plusProject

Objectives

The main aim of BioTrade2020plus is to provide guidelines for the development of a EuropeanBioenergy Trade Strategy for 2020 and beyond ensuring that imported biomass feedstock issustainably sourced and used in an efficient way, while avoiding distortion of other (non-energy)markets. This will be accomplished by analyzing the potentials (technical, economical andsustainable)andassessingkey sustainability risksof currentand future lignocellulosicbiomassandbioenergy carriers. Focuswill beplacedonwoodchips,pellets, torrefiedbiomassandpyrolysisoilfromcurrentandpotentialfuturemajorsourcingregionsoftheworld(Canada,US,Russia,Ukraine,LatinAmerica,AsiaandSub-SaharanAfrica).

BioTrade2020pluswill thus provide support to the use of stable, sustainable, competitively pricedandresource-efficientflowsofimportedbiomassfeedstocktotheEU–anecessarypre-requisiteforthedevelopmentofthebio-basedeconomyinEurope.

In order to achieve this objective close cooperation will be ensured with current internationalinitiatives such as IEA Bioenergy Task 40 on “Sustainable International Bioenergy Trade - SecuringSupply and Demand” and European projects such as Biomass Policies, S2BIOM, Biomass TradeCenters,DIA-CORE,andPELLCERT.

Activities

ThefollowingmainactivitiesareimplementedintheframeworkoftheBioTrade2020plusproject:

• AssessmentofsustainablepotentialsoflignocellulosicbiomassinthemainsourcingregionsoutsidetheEU

• Definitionandapplicationofsustainabilitycriteriaandindicators• Analysis of themain economic andmarket issues of biomass/bioenergy imports to the EU

fromthetargetregions• Developmentofadedicatedanduserfriendlyweb-basedGIS-toolonlignocellulosicbiomass

resourcesfromtargetregions• Information to European industries to identify, quantify and mobilize sustainable

lignocellulosicbiomassresourcesfromexportregions• Policy advice on long-term strategies to include sustainable biomass imports in European

bioenergymarkets• Involvementofstakeholdersthroughconsultationsanddedicatedworkshops

MoreinformationisavailableattheBioTrade2020pluswebsite:www.biotrade2020plus.eu



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About this documentThisreportisoneofthesixcasestudiesdevelopedunderWP3oftheBioTrade2020+project

Startdateofproject: 01-03-2014Duration: 30monthsDuedateofdeliverable: September2015(draftreport)Actualsubmissiondate: April2016(finalreport)Workpackage WP3Task 3.1-3.3Lead contractor for thisdeliverable

UU

Authors KevinFingerman,LeireIriarte,UweR.Fritsche(IINAS)Gert-JanNabuurs,BerienElbersen,IgorStaritsky(Alterra)LotteVisser,ThuyMai-Moulin,MartinJunginger(UU)

Collaborations IINAS,Alterra

DisseminationLevelPU Public XPP Restrictedtootherprogramparticipants(includingtheCommissionServices) RE Restrictedtoagroupspecifiedbytheconsortium(includingtheCommissionServices): CO Confidential,onlyformembersoftheconsortium(includingtheCommissionServices)

Version Date Reasonformodification Status

0.1 30/09/2015 Draftversionforcommentsintheconsortium Finished

0.2 15/02/2016 Final draft for comments in the consortium and theBioTrade2020advisoryboard Finished

1.0 30/04/2016 Finalreport Finished

This project is co-funded by the European Union within the INTELLIGENT ENERGY - EUROPAProgramme.GrantAgreementn °IEE/13/577/SI2.675534.The sole responsibilityof thispublicationlieswith the author. TheEuropeanUnion is not responsible for anyuse thatmaybemadeof theinformationcontainedtherein.



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ContentsTheBioTrade2020plusProject.........................................................................................................2

Contents..........................................................................................................................................4

ListofTables...................................................................................................................................5

ListofFigures..................................................................................................................................5

ListofAcronyms..............................................................................................................................7

1 Introduction..............................................................................................................................9

1.1 ForestsandforestryintheUSSoutheast....................................................................................10

1.2 USForestproductsmarket..........................................................................................................12

1.3 Pelletsmarketsandtrade............................................................................................................15

1.4 SustainabilityConsiderations.......................................................................................................19

2 Methods..................................................................................................................................21

2.1 Assessmentofbiomasssupply....................................................................................................21

2.1.1 Feedstockandcountyselection................................................................................................21

2.1.2 Technicalpotential....................................................................................................................24

2.1.3 Sustainablepotential................................................................................................................27

2.2 DeterminingpotentialsurplussupplyforexporttotheEU-28...................................................32

2.2.1 USdomesticbiomassdemand.................................................................................................32

2.3 Scenariooverview........................................................................................................................33

2.4 Biomasscostcurvedevelopment................................................................................................34

3 Results....................................................................................................................................36

3.1 TechnicalandSustainablebiomasspotential..............................................................................36

3.2 Biomasssupplycostsandcost-supplycurves..............................................................................40

4 Discussion...............................................................................................................................42

4.1 Technicalbiomasspotential........................................................................................................42

4.2 Sustainablebiomasspotential.....................................................................................................42

4.3 USDomesticDemand..................................................................................................................44

4.4 Methodologicallimitationsandsourcesofuncertainty..............................................................44

5 Outlookonfuturework...........................................................................................................46

References....................................................................................................................................47

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ListofTablesTable1: Summaryofcountriesandfeedstockpotential....................................................................9Table2: ForestryoverviewstatisticsfortheUSSouth.....................................................................11Table3: MaincharacteristicsoftheRPA/SRESscenariosusedinthisanalysis................................26Table4: MainparametersdefiningtheBAUandHighTradescenarios...........................................33

ListofFiguresFigure1: ForesttypesoftheUSSoutheast.......................................................................................10Figure2: Totalprojected forestland in theUSSouthper the threemain2010ResourcePlanningActAssessmentscenariosfortheforestareaintheUSSouth.............................................................12Figure3: UnitedStatesNetimportsofwoodproductsandpulp/paperproductssince1964..........14Figure4: GrowthinpelletproductioncapacitybyUSregionfrom2003through2013....................15Figure5:EU28importsofwoodpellets,2009-2014........................................................................16Figure6:TopfiveimportersofUSpellets(2014)..............................................................................16Figure7: FeedstocksourceforuseinpelletproductionintheUSSouthfor2005–2016................18Figure8: WoodpelletpricesatAmsterdam,Rotterdam,Antwerp(ARA),May2013-March2015..19Figure9: OverallmethodologyoftheBiotrade2020+projectforselectedcountriesandregions..21Figure10: StatesintheUSSEstudyregion.......................................................................................23Figure11: ForestecoregionsoftheSouthernUS.............................................................................24Figure12: USnationalroundwoodremovalsbyclassandregion(1997-2012)................................25Figure13: Highconservationvalue,orotherwiseprotectedareas...................................................28Figure14: Rarity-weighted species richness index aids in identification of diversity "hotspots" toscreenoutinevaluatingsustainablepotential.....................................................................................29Figure15: The 'sustainability constraint factor' or fraction of each county's forest area thatremainsavailableforwoodproductionaftersustainabilitycriteriaareappliedspatially....................30Figure16: Twodifferentapproachestoevaluatingthesustainabilityofdomesticdemand–choiceofapproachgreatlyimpactssustainablepotentialforexport..............................................................31Figure17:AnnualUSpaperandpaperboardconsumption,andprojectionsbyRPAscenario........32Figure18:AnnualUSstructuralpanelconsumption,andprojectionsbyRPAscenario...................32Figure19: Historicalandprojectedfuturetotalbiomassavailability...............................................36Figure20: Projected domestic demand for biomass from the US SE region for key sectorscompetingwiththeexportpelletmarketforbiomassmaterial...........................................................37



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Figure21: ProjectionsoftotaltechnicalproductionpotentialfromtheSEUSAforests,(forallusesofbiomass),andpotentialavailableforexportoncedomesticdemandismet...................................38Figure22: Technical export potential (same as export bars in fig 20) and sustainable exportpotentialwhenallbiomassharvestisconfinedtosustainablesourcing..............................................39Figure23: Spatial distributionof net sustainable potential for roundwood in the 2020 and 2030BAUandHighTradecases.....................................................................................................................40Figure24: Biomasscostcurvesforsustainableexportpotential -2015,2020,and2030,BAUandHighTradescenarios.............................................................................................................................41Figure25: Leakageriskfromonlyapplyingsustainabilityconstraintstoexportedbiomass.............43Figure26: Aggregategreenhousegassupplycurveforpotentialsestimatedinthisanalysis..........53



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ListofAcronymsACB AllBiomassConstrained(implementationscenario)

AEO USDepartmentofEnergy’sAnnualEnergyOutlook

ARA AmsterdamRotterdamAntwerp

BAU BusinessAsUsual(scenario)

BTU BillionTonUpdate

CHP CombinedHeatandPower

CIF Cost,InsuranceandFreight

DECC UKDepartmentofEnergy&ClimateChange

EBC ExportBiomassConstrained(implementationscenario)

EC EuropeanCommission

EIA EnergyInformationAdministration(USDepartmentofEnergy)

EPA USEnvironmentalProtectionAgency

EU EuropeanUnion

FPM ForestProductsModule

FRSC FuelReductionCostSimulator

GDP GrossDomesticProduct

GHG Greenhousegases

ha hectare

HT HighTrade(scenario)

IEA InternationalEnergyAgency

IPCC IntergovernmentalPanelonClimateChange

JRC JointResearchCentre

LCA Life-cycleAssessment

Mt Millionmetrictonnes

OSB Orientedstrandboard

PJ PetaJoules

RPA ResourcePlanningAct

SRTS SubregionalTimberSupply



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SCF SustainabilityConstraintFactor

TPO Timberproductoutput

t Metrictonne(1000kg)

UNECE UnitedNationsEconomicCommissionforEurope

UNFAO FoodandAgricultureOrganizationoftheUnitedNations



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1 IntroductionThemainobjectiveof theBioTrade2020+WorkPackage3 is toanalyze the technicalandsustainable potentials for import of biomass/bioenergy feedstocks from selected sourceindustries and regions. These assessments consider the main economic, biophysical, andmarket drivers affecting biomass availability for the six designated biomass sourcesdescribedinTable1.Theselectionofregionsandfeedstocksforinvestigationwasbasedonliterature review, partners’ previous work in the selected countries and informationprovided by the Advisory Board members. This report focuses on forest biomass fromtheSoutheasternUnitedStates.

Table1: Summaryofcountriesandfeedstockpotential

Country Feedstock

Forestresidues

Agriculturalresidues

Forestplantations

Biomasscrops

New forestplantations

Brazil √ √ √

Colombia √ √

Kenya √ √ √

Indonesia √

UnitedStates √ √ √

Ukraine √ √ √

Source: ownelaboration

Themaindriversofbiomassavailabilityandcostinthesecasestudyregionsare:

• Currentandprojectedfutureproductionofselectedbiomasstypes

• Policy constraints aimed at addressing the environmental and social impacts ofbiomasssourcing

• Industrydynamicsaswellasphysicalandlogisticalconstraintslimitingutilizationofmaterials

• Marketdemandforbiomassforenergyandotherusesbothinthesourcecountryaswellasinthird-countrytradingpartners

These drivers vary strongly between the different case studies, and also data availabilityranges fromverygood topoor.While theapproach to the issuesabovediffers somewhatbetweentheBioTrade2020+WP3casestudies,theyalldetermineanetsustainableexportpotentialofbiomassand related costandGHGsupply curvesaselaborated in theproject(seeMai-Moulinetal.2014).



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1.1 ForestsandforestryintheUSSoutheastThe United States Southeast (US SE) gained a lot of attention from the traditional forestsectorintheUSasofthelate1980sand1990sasbiodiversityconservationeffortsfocusedespeciallyaround theNorthernSpottedOwl (Strixoccidentalis caurina) led toa significantdecline in timber harvest throughout the US Pacific Northwest (Thomas et al. 2006).Production attention shifted strongly to the Southeast, and led to further investments inplantations.Asaconsequence,bothplantationareaaswellasgrowthratesofslashpineandloblollypineincreased.CurrentforesttypesoftheUSSEareillustratedinError!Referencesourcenotfound..

Eventhoughtheplantationsareonlyabout30%ofthetotal forestarea,their(stemwood)volumeincrementismorethan2/3ofthetotalregionalincrement(

Table2).Butabout75%of that increment isalreadyharvested for industryor lostdue tomortality.TheUSSEgenerates60%oftheUSannualtimberharvest(Conradetal.2011).InmostUSSEStates,plantationareahasbeen fairly stable in recentyears (Abt,Abt&Galik2013;Macedo2013).

Figure1: ForesttypesoftheUSSoutheast

Source:USDAForestservicefia.fs.fed.us



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Note: Thetotalforestareaissome100millionha.Brownish/pinkcolorsarethelongleaf-slashpineandloblolly-shortleafpineplantations,coveringcloseto30millionha.Thedarkgreenatthecoastisnativebottomlandhardwoodsofoak-gum-cypress.Moreinlandlightanddarkgreenareoak-hickoryandoakpineforests.

Table2: ForestryoverviewstatisticsfortheUSSouth1

Forestarea,Mha

Netannualstemwoodvolume

increment,Mm3

Fellings(pulplogsandsawlogs),Mm3

Mortality,Mm3

TotalSouth 100 364 224 78

Longleaf and shortleafpineplantations

29 246 148 33

Source:USFS(2012)

Despiteeconomicdevelopmentandgrowingpopulation,thetotalamountofforestedlandintheUShasremainedlargelyunchangedthroughoutthepastcentury.However,increasingdevelopmentandcontinuingpopulationgrowthareexpectedtodriveareductioninforestarea in the near future. The 2010 Resource Planning Act (RPA) Assessment projectedreductionsintotalforestlandwithintheUSsouthrangingfrom3.6to7.2Mha,orabout5-10%by2060(USFS2012).

Upland hardwood forests are expected to decline in particular as population growth andurbanization pressures expand in the area. These projected reductions in forestlandoccurredacrossall scenarios considered in theRPAAssessment. Theprimaryexception intheseprojectedlossesacrosstheUSSEistheareaofpineplantation,whichisexpectedtogrow(USFS2012).Figure2presentstotalforestlandexpectedunderthedifferentscenariosconsidered under the 2010 RPA Assessment. These scenarios vary in their projections ofglobal andUS economic and population growth aswell as the global development of thebioenergyindustry.Thesescenariosaredescribedinsection2.1.2ofthepresentreport(formoredetail,seeUSFS2012andNakicenovic&Swart2000).

1Differentanalysesanddatasetsintheforestryspacecoverdifferentspecificregions.ThenationwideResourcePlanning Act Assessment published every five years by the USFS includes all of TX and OK in the region itdefinesasthe“South.”Thesetwostatesareoutsidetheboundariesofthisanalysis,however,astheyareinadifferent ecoregion than the rest of the Southeast study region (see Figure 11) and have not been amajorsourceofbiomasssupplytotheEUinthepast.



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Figure2: TotalprojectedforestlandintheUSSouthperthethreemain2010ResourcePlanningActAssessmentscenariosfortheforestareaintheUSSouth.

Source: Wear(2011)

1.2 USForestproductsmarketHistorically,theUShasbeenboththelargestproducerandthelargestconsumerofwoodybiomass in theworld. TheUS shareof globalwoodproduct productionpeaked at 28% in1998andhassincefallentobelow20%(Prestemonetal.2015).Theamountofroundwoodrequired for wood and pulp product demand in the US has roughly tracked populationgrowth, (Skogetal. 2012), and the total roundwoodequivalent volume tomeetUSwoodandpapermaterialsdemandwasroughlystablethroughthelatterhalfofthe20thcentury(USFS2012).US importsofsawnwoodproducts rose in theearlypartof thiscentury,asagapbegan to growbetweendomestic production anddemand.However, consumptionoftheseproductshasdropped in recent years. Theprimarydriverof this downturnwas thereduction inhousing starts2 beginning in 2005, exacerbatedby the2008 financial crisis aswellas theshiftaway fromprint towardsdigitalmedia (USFS2012).Figure3presents the

2 A common indicator of economic activity, the “housing start” is defined as the commencement ofconstructiononanewresidenceduringagivenperiod.



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trendsinnetimportlevelsforsolidwoodproductsaswellaspulpandpaperfortheUnitedStatesoverthepast50years.

Timberdemandismostcloselycorrelatedwithhousingstarts,anditisstillover25%lowerintheUS than itwasat itspeakbefore thecollapseof thehousingmarket.While therehasbeensomerecentrecovery,several factorscombinetoreducethetotalwooddemandforUShousing(adaptedfromSkogetal.2012):

1. Much of the recent rise in housing starts has been in multi-unit dwellings, whichrequirelesstotalwoodperunit,astheyaresmalleronaverageandsharestructuralelements.While18%ofhousingstarts from1998-2006weremore than fourunits,thisfigureis32%forstartssince2012.

2. Residencesstartedin2009-2013wereonaverage9%smallerthansimilarstartsfrom1998-2006.

3. Engineering and construction technique have shifted over the past half century,leadingtoa50%reductioninwooduseperft2ofusablespace.

Pulp and paper markets in the US correlate most closely with overall trends inmanufacturing; both peaked in 1998. Paper production has dropped off even moreprecipitously,owingtothecombinationofmacroeconomictrendssuchasthedropinoverallmanufacturing and the ongoing shift towards electronic media (Prestemon at al. 2015).Consumptionofnewsprinthasbeenfallingsincethe1980s,withprintingandwritingpapersjoiningintheearly2000s.Thisdeclineinnewsprintconsumptionhastoalargedegreebeencompensated by a rise in demand for pulp for cardboard packaging.Most recent signalsshow a stable to small increase in overall consumption of pulp and paper again (UNECE2015).



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Figure3: UnitedStatesNetimportsofwoodproductsandpulp/paperproductssince1964

Source:ownelaborationfromUNECE-FAO(2015)database

Note:Muchoftheincreaseinnetpulpandpaperexportthroughrecentyearsisduetoariseinthecollectionandexportof“recovered”paperthroughrecyclingwhichcurrentlystandsatapproximately20milliontonnesexportedannually.

Thelarge-scaletrendsinthemarketsforUSforestproductshavealsohadanimpactontheregionaldistributionofforestryactivities.Ashiftfromsolidsawnwoodtowardsengineeredwood products has enabled an increase in the proportion of smaller-diameter trees intimberharvest. Thishas led toa shift away from thePacificNorthwest region,whichwasonce the centre of the US forest products industry towards plantation operations in theSoutheast. Inthedecadebetween1986and1996,thefractionofUStimberharvest intheNorthwestregiondroppedfrom26%to15%(Haynes2003).

TheuseofwoodforenergyintheUSwas2,336PJin2014orabout146milliondrytonnesofwood.Thisrepresents2.2%oftotalenergyand23%ofrenewableenergyuse.Whilethiswasa2%increasefrom2013,itisstill18%belowthe1985peak(UNECE-FAO2015).Whilemostofthe increase iscomingfromincreasingpelletizationandgenerationofbioelectricity,themajority of thewood use for energy is still for home heating. Approximately 2.1% of UShouseholds are heated primarily with wood, and another 7.7% use it as a supplementalheatingsource.Mostofthisuseisassplit logs,thoughtheuseofbaggedpelletsforhomeheatingisontherise(UNECE-FAO2015).



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1.3 PelletsmarketsandtradeDuringthepastdecade,pelletproductionhasincreasedthroughouttheUS,andespeciallyintheSoutheastregion(seeError!Referencesourcenotfound.).Thisexpansionhasbeeninlarge part a response to the increasing EU market demand. In 2014, US wood pelletproductionwasestimatedat6.9milliontonnes(Mt)–anincreaseofabout21%from2013(UNECE-FAO2015).Ofthismaterial,about4.7Mtwasexported,98%ofwhichwasfromtheUSSouthregion(Wangetal.2015).Asof2015,9.1Mt/yrofpelletizationcapacityiscurrentlyoperationalinthecountry(UNECE-FAO2015).

Figure4: GrowthinpelletproductioncapacitybyUSregionfrom2003through2013.

Source:ForiskConsulting(2014)in:Abtetal.(2014)

Note:Amountsarepresentedingreenshorttonnes.Pelletproductionwouldberoughlyhalfofthesefigures.

PelletexportsfromtheUStotheEUhaveincreased6-foldsince2008(Wangetal,2015).AsillustratedinError!Referencesourcenotfound.,theUShasbecometheprimarysourceofpelletstoEUmarkets,representingmorethan60percentofthetotalwoodpelletimportstotheEUin2014.TheUKistheprimaryimportmarketforpelletsfromtheUSSE,followedbyBelgiumandtheNetherlands,asshowninError!Referencesourcenotfound.(UNECE-FAO2015).



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Figure5:EU28importsofwoodpellets,2009-2014

Source:UNECE-FAO(2015)

Figure6:TopfiveimportersofUSpellets(2014)

Source:UNECE-FAO(2015)

ThetrendtowardsexpandingwoodybiomassproductionandexportfromtheUSSEregionisexpectedtocontinue.TheforwardprojectionsconductedfortheUSForestService’s2010ResourcePlanningAct(RPA)Assessment(USFS2012),anticipatethattheSouthregionwillcontinue to be the primary timber region in the country. In all of the RPA scenariosconsidered, the region was projected to account for over 50% of total national timberharvest,includingthemajorityofbioenergyfeedstockproduction.

Mostwoodybiomassburnedforenergy,andnearlyallofthatexportedforthispurpose,isin the formof biomasspellets,which are valued for their stability andenergydensity. ByMay2015,installedwoodpelletproductioncapacityreached9.1milliontonnesandbytheendoftheyearwasontracktotop11milliontonnes(COWI2015).ThevastmajorityofUSwoodpelletcapacityisfoundintheSoutheast.SeveralfactorshaveledtotheUSindustrialpellet sector growing mainly in the US SE and making it the most promising region forproductionofpelletsfortheEUmarket.Theseinclude(ForiskConsulting2013;COWI2015):

- TheresponseofinvestorsandprojectdeveloperstocurrentdemandintheEU.

- The perceived availability of low-cost biomass (based on historical and currentmarketdata)especiallygivendeclinesinpapermillingindustry,

- A well-developed forest products industry that could facilitate the acquisition ofmaterialsforpellets,

- Cost-effective transportation networks for both feedstock procurement andmovementoffinishedproducttoexportterminals.

- Attractivenessasaninvestmentduetotherelativelylowlevelsofcapitalinvestmentwhencomparedtoliquidfuelandlarge-scaleelectricityprojects($150millionorlessvs.hundredsofmillionsofdollars).



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Photo:TheEnvivapelletmillinAhoskie,NC.Ontheleft,rawmaterialscanbeseen:low

qualitylogsaswellassawdustandchips.Beinglocatedinaregionwithbothshortrotationindustrialplantationsaswellasnativebottomlandhardwoods.Thesourcingofthisandsimilarfacilitieshascomeunderheavyscrutiny(Hammel&Smith2013)andcouldbeimpactedbyEUbiomasssustainabilitycriteria.

Until 2010,mill residues represented themajor feedstock for pellet production, but since2011bothsoftwoodandhardwoodpulpwoodsarealsobeingused(Abtetal.2014;Iriarte,Fritsche&Pelkmans2014). In2013,about45%of thebiomass forpellets in theUScamefrom softwood pulpwood, about 15% from hardwood pulpwood and the remaining 40%frommillresidues(Abtetal.2014).

It is expected that the share of pulpwood feedstock will continue to increase. All thesefacilitieshave to relyonoutsidesourcesofwood (dealers/loggers,gatewoodorstumpagepurchases directly from landowners, either through spot markets or contracts). Error!Reference source not found. presents recent and projected feedstock use for pelletproductionintheUSSE.



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Figure7: FeedstocksourceforuseinpelletproductionintheUSSouthfor2005–2016

Source:ForiskConsulting(2014)in:Abtetal.(2014)

The economics of wood pellet production are complex, especially where high-qualityfeedstocks such as wood chips and mill residues are used. Pellet manufacturers mustcompete for these feedstocks with manufacturers of paper products and panel productssuchasparticleboardandorientedstrandboard(USFS2012).

While biomass pellets have, up to this point, been made almost exclusively from millresiduesandpulpwood, lowerquality resources suchasharvest residues, areexpected tobecomeimportant,orevendominant, if theuseofwoodforenergy increasessignificantly(USFS2012).

While consumption of wood pellets has risen in the recent past, this has been offset byincreasedavailabilityofwoodpellets,keepingaveragewood-pelletpricesunder$200/tonneas illustrated inError! Reference source not found.. Increased use of biomass for energywould lead to both tightening of biomass markets as well as the increased reliance onresourcessuchasharvestresiduesandthinningsthatarecomparativelycostlyowingtothelogistics associated with their collection and processing. The economic viability of thesefeedstockshingesontheefficiencywithwhichtheycanbeharvested(Grusheckyetal.2007inGalik&Abt2015).



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Figure8: WoodpelletpricesatAmsterdam,Rotterdam,Antwerp(ARA),May2013-March2015

Source: UNECE-FAO(2015)

1.4 SustainabilityConsiderationsManyforestlandsoftheUSSoutheastarebiodiversityhotspots.Theregionhasarelativelyhigh rate (11%) of plant and animal species considered to be at-risk (i.e. vulnerable,imperiled, critically-imperiled, or thought to be extinct) (Wear&Greis 2002; NatureServe2013).SomeforesttypesofhighconservationvalueontheCoastalPlainarebottomlandandfloodplain forests, gum-cypress, elm-ash-cottonwood, as well as some oak/hickory andoak/pinesystems.

As reported in Deliverable 2.1 of the BioTrade2020+ project (Díaz Chavez 2015), speciesrichnessishighest intheMid-SouthandCoastalPlain.Landusechangeshaveoccurredforseveral centuries in the region, and the fracturing of forestland combined with climatechangehaveledtoimportantimpacts.Inthenearfuture,furthershiftsfromnaturalforesttomanagedplantationsmightadverselyaffectendangeredspeciesincertainlocations,butshifts fromagriculturalsystemsto forestsmight improvehabitatconditions (Alavalapatietal.2013).



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Private landowners hold 86%of the forest area in the South,with two-thirds of this areaowned by families or individuals (Butler &Wear 2013). A key point for reflection is thatregulations in the US give significant freedom to landowners to make decisions in theirforestlands.Assuch,ownerbehaviourmight influence landusechangesandmanagementpractices inanydirection(e.g. fromforest landtoagriculture landorviceversa).Landusechanges might significantly impact biodiversity (and other forest features). This studyassumesthatcurrentharvestingstatisticsalreadyreflectthesedynamics,sothisparameterwillnotbefurtherconsideredintheanalysis.

Froma greenhouse gas (GHG) perspective,most life cycle assessment studies show somegains from displacing EU grid electricitywith bioelectricity fromUS pellets. Dwivedi et al.(2014),forexample,foundgenerationofUKbioelectricityfromUSpinepelletstorepresentalifecycleemissionsreductionofbetween50%and68%.Similarly,Wangetal(2015)foundforestbiomasspellets tooffera74% lifecycleGHGemissionreductionwhentheyreplacecoal in UK power generation. These findings are in line with the life cycle emissionscalculated in theEC’sownresearchconductedby its JointResearchCentre (Guintolietal.2015). A critical consideration with the numbers presented here is that this approach tocalculating the life cycle GHG emissions from bioenergy systems considers combustion ofbiogenicfuelstobecarbonneutral3.

Some stakeholders (e.g. environmental NGOs, researchers, etc.) have questioned thisapproach4.However,followingthecurrentapproachoftheEC(seee.g.Giuntolietal.2015),weassumecarbonneutralityforbiomasscombustion inthisreport. It isalsoworthnotingthat the deep emission reductions cited here are not certain: beyond decisions aboutbiogenicCO2 accounting, theydependupon sustainable forest practices aswell as factorssuchaspowerplantcapacity,ageofthesourceforest,andtheapproachusedindryingthebiomass(Iriarteetal.2016).

3Similarly,theUSEPAalsoassumescarbonneutralityforsolidbiomassburntinstationarysources(EPA2014).4 For a critical discussion see e.g., Agostini et al, 2013, Buchholz 2015;Guintoli et al. 2015;Matthews et al.2015;Röder,Whittaker&Thornley2015).



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2 MethodsOncethecasestudiesfortheBioTrade2020+projectwereselected,weappliedacommonmethodologytoeachofthemindeterminingthesustainablepotentialforexporttotheEU(seeError!Referencesourcenotfound.).Wecalculatethetechnicalpotentialaccordingtotheavailabilityoftheselectedfeedstockandtheresidueproductionratioimputedfrompastproductionrates.Thistechnicalpotentialisthenconstrainedtoachievesustainabilitygoalsdependingonregionalconditionsanddataavailability.TheoverallmethodologyisillustratedinError!Referencesourcenotfound.(andinmoredetailinthemethodologyreport).

ThefollowingsectionsdescribehowthisgeneralmethodologyhasbeenappliedtotheUSSEcasestudy.

Figure9: OverallmethodologyoftheBiotrade2020+projectforselectedcountriesandregions.

Source:AdaptedfromMai-Moulinetal.(2015)

The background information for the selected countries (see Deliverable 2.1) helped toidentify the regions in each country that weremore promising for the availability of thefeedstockbutalsothatincludedsomeofthetechnologicalfacilities(includingtransportationandotherlogistics)tobringbiomasstomarket.TheinformationprovidedfromtheBioTrade2020+AdvisoryBoard(AB)alsocontributedtoselectionofthesourceregions.

2.1 Assessmentofbiomasssupply

2.1.1 Feedstockandcountyselection

ThisstudyfocusesonbiomassfromforestryintheSoutheasternUS.Weonlyincludeinouranalysis those classes of biomass for which bioenergy could reasonably competeeconomically.Thismeantexcludingmaterial that issuitable forproductionofhigher-valueproducts,suchassawlogs(tobesawninto lumber)andveneer logs(tobe lathedtomakeplywood).

ThefollowingclassesofmaterialsreportedintheUnitedStatesForestService(USFS)TimberProductsOutput(TPO)databasewereincluded:



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- Bothhardwoodandsoftwoodpulplogs

- “Compositeproducts,”“fuelwood,”and“miscellaneous.5”

- Loggingresidues.Thiscategoryincludesidentifiedvolumeastheresidualportionsoftreescut forroundwoodproducts,excesssmallpoletreesandothertrees felled inthe process of extracting roundwood products that are left on the ground afterroundwoodproductharvests6.

- Sawmillresidues.Thiscategoryincludesidentifiedvolumeaswoodandbarkresiduesgenerated by primary wood-using mills during the processing of roundwood intoprimaryproducts,likesawnwood,veneer,andwoodpulp.

- “Other removals7.”Thiscategory includes identifiedvolumeas treesremovedfromthe timberland inventorydue to landuse change to somenon-forestuse, andanytrees felled in timber stand improvement activities, like pre-commercial thinnings,weedings,etc.,thatarenotdirectlyassociatedwithroundwoodproductharvests.

Forthepurposesofthisstudy,theUSSoutheast(USSE)isdefinedasthestatesofAlabama(AL),Arkansas(AR),Florida(FL),Georgia(GA),Kentucky(KY),Louisiana(LA),Missouri(MO),NorthCarolina(NC),SouthCarolina(SC),Tennessee(TN),andVirginia(VA).

SeeError!Referencesourcenotfound.foramapofthestatesinthestudyregion.

5TheseproductsaredefinedintheTPOdatabaseas:

• Composite products – “Roundwood logs, bolts, and chips used in the manufacture ofreconstitutedwoodproducts.”

• Fuelwood – “Roundwood logs, bolts, and chips used as fuel in industrial, residential, andinstitutionalsituations.”

• Miscellaneous–“Roundwoodlogs,bolts,andchipsprocessedintoavarietyofproductsnotpreviouslylisted.”

6 It shouldbenoted that forest residueshaveahighconcentrationofbark (becauseof theirhighsurface tovolume ratio) as well as soil and other debris. Thesematerials can cause slagging, fouling and corrosion inboilers(Stephenson&MacKay2014),andarethereforenotapreferredfuel.Thereremainssomeuncertaintyastotheextenttowhichthesematerialswillbeabletobemadeusefulasbioenergyfeedstocks.7 The “other removals category in the TPO database is defined as “unutilizedwood volume of trees cut orotherwisekilledbyculturaloperations(e.g.pre-commercialthinnings)orlandclearingstonon-forestuses.”



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Figure10: StatesintheUSSEstudyregion

Source:Ownelaboration

Different analyses and datasets in the forestry space cover different specific regions. Forexample,theUSSEregionintheUSFSTPOdatabasecoverstheabovestatesaswellastheeasternportionsof Texas (TX) andOklahoma (OK). ThenationwideResourcePlanningActAssessmentpublishedeveryfiveyearsbytheUSFSincludesallofTXandOKintheregionitdefinesasthe“South.”

However, the majority of TX, and all of OK are in the “Mid-south” ecoregion (Error!Reference source not found.), and these areas have not been amajor source of biomasssupplytotheEUinthepast.Therefore,thesearenotincludedinthisanalysis.



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Figure11: ForestecoregionsoftheSouthernUS

Source: Wear&Greis(2013)

2.1.2 Technicalpotential

The technical potential is definedhere as all of thebiomass suitable forbioenergy that isavailable in the regionwithoutconsidering sustainabilityor feasibilityof itsdelivery.Next,someverybasicno-gosustainability/feasibilityconstraintsareappliedbynotcountinginthetechnicalpotentialanybiomassderivedfrom:

- Deforestation/landclearingoperations

- Illegalcuttingonprotectedlands,or

- Removalofmorethan67%forestresidues(Perlack2011).

Further, we estimate potential biomass supply here, and therefore do not constrain thesupplytocurrentorprojectedfuturepelletizationcapacityorsupplychainsufficiency.Pelletmillcapacitydevelopmentoverthecoming15yearswillbedrivenbydemand,whichwillinturn be driven by energy and climate policy. Hence, this analysis seeks to project variousscenarios of technically available supply without considering market capacity (e.g.pelletizationandsupplychaincapacity).Giventhis,theestimatespresentedmightinsomecases be higher than those seen in pellet supply projections, and should, therefore, beunderstoodtosetasortofa“ceiling”onactualpelletavailability.

Historicaldataon forestproduct removalsweredrawn fromtheUSForestServiceTimberProductsOutput(TPO)database(USDA-USFS2015).Baseline/historicproductionlevelswerecollectedatacounty-level resolution throughout theUSSE region fromtheTPOdatabase



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for the years 1995-2009. Nationwide data are reported less frequently through the RPAprocess, so these data were extracted for RPA years 1997, 2002, 2007, and 2012. Thesereportscollateandaveragedatacollectedbyregionalofficesacrossthestudyperiod,soarenot necessarily representative of the report year, but they do offer a good first-orderapproximationofdifferenttypesofforestryremovalsacrosstheUS.Error!Referencesourcenotfound.presentsthesebaselinenationwidedata.

Figure12: USnationalroundwoodremovalsbyclassandregion(1997-2012).

Source: OwnelaborationbasedondatafromUSFSTimberProductsOutputdatabase.

As described in Section 2.1.1 above, the following classes of materials and respectiveassumptionswereincluded:

• Bothhardwoodandsoftwoodpulplogs

• “Compositeproducts,”“fuelwood,”and“miscellaneous.”

• Loggingresidueata50%removallevelforBAU(Galik,Abt,&Wu2009)and67%levelforthehightradecase(Perlack2011)8.

• Sawmillresidues.

• “Otherremovals”(ata50%removallevelforbothcases,seeHoefnagels2014).

The “other removals” estimates are derived from average annual removals data for thelatest forest inventoryofeachState.AverageannualremovalsestimatesaremadeforthetimeperiodbetweentwosuccessiveStateforestinventories,usuallyabout10years,andarethereforeshort-termhistoricaveragesandnotestimatesforaspecificyear.Theseaverage

8Seesection2.3foradetaileddescriptionofthedifferingstudyscenarios.



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annual removals estimates are also based on sampling procedures designed to providereasonableestimatesoftotalforestareaandtotaltimberinventoryinaState.

Spatially discrete projections of current-year and future forest product production at acountyscalewerederivedfromtheSubregionalTimberSupply(SRTS)Model(Abt2000).Thebaseline SRTSoutputswereused todescribe thebusiness asusual (BAU)production casewithhigh-biomasssupplycasederivedfromthejointUSandglobalForestProductsModule(FPM)model(Ince2011)runsandscenariosdevelopedforthe2010USFSResourcePlanningAct Assessment9 (USFS 2012). This USFSmodelling effort projected future forest productharvestanddemandunderdifferentSpecialReportonEmissionsScenarios(SRES)developedby the IPCC (Nakicenovic and Swart 2000). Parameters in the FPM relating to global anddomesticpopulationgrowth,GDP, global tradepatterns,bioenergyuse, and climateweretiedtothoseappliedintheSRESscenarios.ThetwoprimaryRPA/SRESscenariosusedinthisanalysis are the RPA A1B and RPA B2 scenarios, the key characteristics of which aredescribedinTable3below.

Table3: MaincharacteristicsoftheRPA/SRESscenariosusedinthisanalysis

RPAA1B RPAB2

Generalscenariodescription Globalization,economicconvergence

Slowgrowth,localizedaction

GlobalrealGDPgrowth(2010-2060) High(6.2x) Medium(3.5x)

USrealGDPgrowth(2010-2060) Medium(3.3x) Low(2.2x)

Globalexpansionofbiomassenergyuse High Medium

Source:adaptedfrom(USFS2012)

Some relevant data sources, such as the FPM model outputs used for the High Tradescenario,areonlyreportedatthenationalscale.Wherethiswasthecase,historicalpatternsofUS-wideandUSSE regionshareofhardwoodandsoftwoodproduction,aswellasRPAprojections of future yield, were used to determine the US SE region “share” of totalproduction.Wheresomeoftheabovecategoriesofbiomasswerenotreported,theregionalTPOdatasetwasusedtoimputeharvestresidue,millresidue,andotherremovalsfromtheaveragehistoricalrelationshipbetweenthesefactorsandremovalratesofdifferentclassesofroundwood.TheseprojectionsofhardwoodandsoftwoodharvestwerebrokendownbytypeanddistributedspatiallybasedontheSRTSmodeloutputs.

9TheSRTSbaselineestimatesareaBAUcase(they’re inthesamerangeashistoricalyields)wheretheUSFSprojectionsarealloptimistic.



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2.1.3 Sustainablepotential

GiventhespecificUSSEcontext,theconcernsalreadyraisedbydifferentstakeholderswithrespect to pellet production, and the sustainability criteria in the EU Renewable EnergyDirective (EU2009)andotherECcommunications, twomain impact categorieshavebeenconsidered in detail: biodiversity and carbon balances. In 2014, the EC decided not topropose binding sustainability criteria for solid bioenergy (EC 2014), indicating that thosepassed for liquid biofuels might apply to solid bioenergy. This led main pellet-importingcountries to develop specific sustainability schemes for solid bioenergy (see e.g. Iriarte&Fritsche2015).

With respect to carbon balances, this report assumes that annual harvested volumeswillcontinuetoremainlowerthanannualforestincrement.RegardingGHGemissionsofforestbioenergy, we have followed the approach given in BioTrade 2020+ deliverable 2.4 (seeIriarteetal.2016).Weconsiderbiomasscombustiontobecarbonneutral,yieldinginmostcases anetGHGemission savingswhenbiomasspellets displace fossil fuels for electricitygeneration (see e.g. Giuntoli et al. 2014). Other concerns, such as carbon debt, have notbeenconsideredinthisanalysis.Forthisreason,lifecycleGHGintensityisnotconsideredapracticalconstraintonbiomasssourcingfromtheUSSE.

Thekeyconstraintemployedindeterminingsustainablesourcingpotentialforthisanalysisisbiodiversity conservation. Geospatial data allows the exclusion of biomass sourced fromareas andhabitat typesofhighbiodiversity conservation value.We start from the countylevel gross technical potential, limiting these yields by application of the following threelayersofconstraints:

1. Protectedareas,areas identifiedashavingspecialconservationsignificance,privatelands covered by conservation easements, or areas classified aswetlands or otherwaterbodies.Thesesourcingrestrictionsweredevelopedandpresented inGalik&Abt(2015)(Error!Referencesourcenotfound.)

2. Other set-aside areas of special biodiversity concerns as per the rarity weightedrichnessindex(NatureServe2013)(Error!Referencesourcenotfound.)

3. ApartialsetasidebasedonforesttypesoftheUSSE.Inparticular,theexclusionofgum-cypress,anda10%exclusionofoak-pineforesttypes(IINAS,EFI&JR2014).

Thefirst layerofexclusionswasderivedfromananalysissimilartothisonethatsoughttoevaluatethesustainablebiomassresourcebaseforexportfromtheUSSEtotheEU(Galik&Abt 2015). The authors excluded areas that are protected, have particular conservationsignificance, or are covered by conservation easements (see Error! Reference source notfound.).



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Figure13: Highconservationvalue,orotherwiseprotectedareas.

Source: Galik&Abt(2015)

Note: Greenareasareareasofhighconservationvalueorprotectedareas.

WhiletheapproachtakenbyGalik&Abt(2015)providesastrongbasisuponwhichtobuildour sustainability spatial constraints, we take a conservative approach to biodiversityconservation by employing additional spatial masks to further ensure the comprehensiveexclusionofhighbiodiversityvalueareas.

Inaddition to theGalik&Abtconstraints,weemploy the rarity-weightedspecies richnessindex (NatureServe 2013; Albuquerque 2015), which scores locations based on acombinationofspeciesrichnessandtherarityofthespeciespresent(seeError!Referencesourcenotfound.).

Regions scoring high (>1) on this index were considered to be of high biodiversityconservationvalueandwerethereforeexcluded.



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Figure14: Rarity-weightedspeciesrichnessindexaidsinidentificationofdiversity"hotspots"toscreenoutinevaluatingsustainablepotential

Source: NatureServe(2013)

Finally, certain high-conservation-priority forest types (see Error! Reference source notfound. forforesttypemap)wereexcludedorconstrainedfromdirectharvestforbiomass.Forest types excludedwere gum-cypress andelm-ash-cottonwood. Recognizing that someoak/hickory and oak/pine forest areawill also harbor biodiversity conservation value, weexclude10%oftheseforestareas(perIINAS,EFI,&JR2014).

Thethreespatialconstraintsmentionedaboveoverlappedtoasignificantextent,buteachalsocoveredareasthatwerenototherwiseexcluded.Bymergingthesethreelayerswitharastermapofforestedarea,weareabletodeterminethefractionofeachcounty’sforestedareatobeexcludedfromproductiontoensuresustainability.This fractionpercountywasthe ‘sustainability constraint factor’ and was multiplied by the technical potential todeterminethesustainablepotentialpercounty.

Error!Referencesourcenotfound.presentsthespatialdistributionandextentofexclusioncreatedbythese‘sustainabilityconstraintfactors’acrosstheUSSE.



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Figure15: The'sustainabilityconstraintfactor'orfractionofeachcounty'sforestareathatremainsavailableforwoodproductionaftersustainabilitycriteriaareappliedspatially


Note: Whilethesefiguresarepresentedatacounty-levelresolution,theyresultfromahigh-levelanalysisthatisunabletocharacterizeallofthesmaller-scaledynamicsatplayintheforestindustryofagivenlocality.Assuch,theseresultsshouldnotbeconsideredapplicableforcounty-levelanalysisorplanning,whereahigherdegreeoflocalnuanceiswarranted.

As described above, the sustainable potential for a given county is determined using thefollowingequation:

𝑃!" = 𝑃!" ∗ SCF

Where:

Ps = Sustainablepotentialincountyc

Ptc = Technicalpotentialincountyc

SCF = SustainabilityConstraintFactor



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The specifics of the way these sustainability constraints might be implemented has asignificantimpactonthescaleofthesustainableresourcebase.

Weapproachthisanalysisconsideringtwobasicmechanismsforimplementation.

1. Net technical potentials for export (i.e. after sourcing of domestic demand) arespatially constrained to avoid unsustainable impacts. This approach is referred tohereafterasthe“exportbiomassconstrained”(EBC)case.

(technicalpotential–domesticdemand)*SCF

2. Gross technical potentials are constrained to avoid unsustainable impacts, withdomesticdemandthendrawnfromthesustainableresourcebase.Thisapproach isreferredtohereafterasthe“allbiomassconstrained”(ABC)case.

(technicalpotential*SCF)–domesticdemand

Figure16: Twodifferentapproachestoevaluatingthesustainabilityofdomesticdemand–choiceofapproachgreatlyimpactssustainablepotentialforexport

Source:ownelaborationfromMai-Moulinetal.(2015)

Note: ABC=allbiomassconstrained;EBC=exportbiomassconstrained

Thebasicdifferencebetween theseapproaches is that the first (EBC)approachconstrainsonly the biomass being counted for pellet export to those areas not creating risk ofunsustainableimpact.Inthesecond(ABC)approach–theapproachtakenelsewhereintheBioTrade2020+ study– sustainability criteria are applied toall biomassproduction for allapplicationsintheregion.

Thefirstcaseismore“realistic;”whileEUpolicymakersmaywellapplysustainabilitycriteriatoimportedpellets,theycouldnotextendthesecriteriatoallbiomassharvestinexportingcountries.Ontheotherhand,aregulationthatonlycoversasmallpartofthemarketrisksfailingtoinfluenceoverallenvironmentalperformance,creatinga“leakage”effect,whereinsustainablebiomassissoldintoexportmarketswithoutanyactualshiftinharvestpracticesacrossthelandscape.



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GiventherealisticnatureofthefirstapproachintermsofwhattheEUcandemand,butthemoreambitiousapproachtosustainabilityimpliedbythesecond,wediscussbothscenariosinthisanalysis.

2.2 DeterminingpotentialsurplussupplyforexporttotheEU-28

2.2.1 USdomesticbiomassdemand

Domestic demand data were drawn from Howard (2013). These values for roundwoodequivalentproductionofvariouswoodybiomassproductswerethenscaledbasedonFPMmodel projections of change in domestic demand for these materials. Error! Referencesource not found.Error! Reference source not found. and Error! Reference source notfound. present theFPMmodelprojections from the2010RPA (Ince2011;USFS2012) forpaperproductsandstructuralpanels respectively.Amongpanels,onlycomposites suchasparticleboardandorientedstrandboard(OSB)competewithenergyforbiomass.

These materials have risen to about 60 percent of the total US panel market, and areprojectedtooccupy80percentofthemarketby2060(Adair2010).Wethereforeaccountfor60%ofstructuralpaneldemandin2015,65%in2020,and70%in2030.

Figure17:AnnualUSpaperandpaperboardconsumptionandprojectionsbyRPAscenario

Source:USFS(2012)

Figure18:AnnualUSpanelconsumption,andprojectionsbyRPAscenario

Source:USFS(2012)

TheRPAscenariosusedinthisanalysisprojecttotalfuturematerialdemandnationwide.WeallocatetheseprojectionstotheSEregionbasedonthatregion’sshareoftotalnationwideprojectedhardwoodand softwoodproduction. For example, the SE region is projected toproduce53.4%of thenation’ssoftwoodoutput in2030,so it is“assigned”this fractionofthetotaldemandforsoftwoodmaterial.Wenotethatfordemandprojectionsuncertaintycanbehigh.Forexample,in2012theRPA(USFS)projectedcontinuingdeclineinpaperandpaperboard consumption, while most recent trends already show a moderate increase(UNECE-FAO2015).



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Inprojectingdemandforconventionalusesofbiomass,thisstudyusesthelow-growthRPAB2scenariofortheBAUcaseandthemorerobustandrenewableenergyfocusedRPAA1Bscenario for theHighTradecase.Morebiomasscouldtheoreticallybeavailable forexportunderascenariooflessrobustGDPgrowthandbiomassexpansion,asthesewouldreducedemand for biomass for conventional and energy uses. However, such a scenario cannotrealistically be expected to coincidewith high levels of biomass supply, so the high tradecaseusesthehighergrowthscenariotoprojectdomesticdemand.

This study breaks from the strict RPA/SRES scenarios in its treatment of US domesticbioenergydemand,however,because theRPAprojections rangewidely,andaredriven inlargepartby theexogenous factorofdomesticbioenergypolicy.Forexample, thehighestRPAscenarioprojectionshowsalmost2billiontonsofbiomassusedforenergyintheUSin2060.Thiswould requireanoverhaulofUS forestryandenergy sectorsandwouldclearlynotleavematerialforexporttoEuropeanmarkets.

There isnoempiricalbasisuponwhichtovarytheUSbiomassdemandbetweenBAUandHighTradecases.Moreover,whiletheHighTradecasewouldcallforlowdomesticbiomassdemandtoenablehigherexports,itisnotreasonabletoprojectalargeincreaseintheuseofbiomassenergyinEuropewhileholdingUSbioenergyusestatic.Forthisreason,weusedthemoderatedomesticbiomassdemandgrowthprojectionfromtheRPAforboththeBAUandHighExportscenarios.Thedemandfordomesticbiomass forenergypresented in thisscenarioisroughlyconsistentwiththeprojecteddoublingofUSbiomassenergyproductionby2030inthe2010AnnualEnergyOutlookreferencecase(USDOEEIA2010).

2.3 ScenariooverviewThisanalysisconsiderstwomainscenariosthataimtocapturedifferentcircumstancesofthemain parameters affecting the sustainable surplus of biomass for exports. These refer toBAU and the high trade cases. Table 4 summarizes key differences between these twoscenarios.

Table4: MainparametersdefiningtheBAUandHighTradescenarios

Parameter BusinessasUsual HighTrade

Technicalpotential

Harvestresiduesextractionrate 50% 67%

“Otherremovals”extractionrate 50%

SustainablePotential

Biodiversityconservation Spatialexclusionofsourcingasdescribedinsection2.1.3

Domesticdemand

Domestic demand for pulp andpanelfeedstocks RPAProjectionB2 RPAProjectionA1B

Domestic demand for biomassforenergy RPAProjectionB2



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Source:ownelaboration

Complementarytothescenarioapproach,weanalyzetheimportanceofwhereinthesupplychainsustainabilitycriteriaareapplied.Weconsideraconservativemodelwhereallbiomassisrequiredtocomplywiththebiodiversityconstrains(ABCapproach)aswellasoneinwhichonly exported biomass is constrained by the biodiversity criteria (EBC approach). Section2.1.3presentsadetailedexplanationofthesecases.

2.4 BiomasscostcurvedevelopmentInevaluatingthepotentialsupplyofbiomassfromtheUSSoutheasttotheEU,thecostofmobilizingthismaterialandbringingittomarketisakeyconsideration.Whilenotincludingcost or supply chain capacity as constraints, this study does evaluate the overall cost ofdelivering pelletized woody biomass to the Amsterdam-Rotterdam-Antwerp (ARA) portregion.Toestimatethecostofbiomasspelletsasdelivered,thefollowingcostcomponentsareincluded:

C! = C! + C!" + C!"# + C!"# + C!" + C!

Where:

CD= TotalcostofbiomasspelletsdeliveredtoARA

Cf= Costoffeedstockcollection/purchase/chipping

CPt= Costofpre-treatment

CTdf= Costofdomestictransportfromfieldtopelletplant

CTdp= Costofdomestictransportfrompelletplanttoexportlocation

CTi= CostofinternationaltransportfromexportlocationtoARAports

CH= Costofhandling

WeusecostestimatesfromtheBillionTonUpdate(Perlackatal.2011)forbiomasscostatthe roadside. The residue biomass considered here is derived from the logging residues(LOGR) category in the Billion Ton Update. Cost characteristics for the “other removals”category in our analysis were derived from the “simulated thinnings” (LOGT) case.WhilePerlack et al. also report values for what they call “other removal residues” (LOGO), thiscategoryofbiomassisspecifictolandconversionfromforest.WhileboththinningsandlandconversionremovalsareincludedintheTPOdatabaseunderthe“otherremovals”heading,we limit our analysis to only 50% of reported/projected “other removals” in order toconstrain the biomass considered to thinnings and other non-harvest activities whileexcludinglandclearing. Inthecaseofthinningandresidues,thesecosts includehaulingtoroadsideandchipping.

The costs for thepulpwood fractionof thebiomassmaterial arebasedon theBillion TonUpdate projected roadside costs for pulpwood timber. For harvest residues, the BTUassumesthattheresidueisremovedaspartofawhole-treeharvestingsystemwhereinthe



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tree is broken down at the roadside,meaning that the only costs are stumpage and thechipping cost. For thinnings, costs include stumpage, harvest, transport to roadside, andchipping. Costs associated with harvesting the material and extracting it to the roadsidecosts are estimated using the Fuel Reduction Cost Simulator (FRCS)model (Dykstra at al.2009).

For privately-held timberland, the stumpage price assumed for thinnings and residuesreflects the opportunity cost of selling into the biomass energy market. Where totalutilization of these materials is low, a nominal price of $4/dry short ton applies to thematerial. Asmore of the slashmaterial ismobilized, its price rises steadily up to 90% ofpulpwoodcost,asitsdemanddrivesupthepriceandthepelletmarketeventuallybeginstocompetewiththepulpandpanelmarkets.

TheBillionTonUpdatereportsbiomassproductioncostsinincrementsof$10.Thisisinfactthemarginalcostofmobilization(i.e.priceofthelastton)ineach$10incrementratherthantheactualcostofdeliveryofeachtonneofmaterial.WeusethisBTUcostdatatodeterminethefractionofeachcategoryofbiomassabletobedeliveredateach$10 incrementupto$200/short ton (atwhich price it is assumed that all bioenergy feedstockmaterial can bemobilized).

Wecalculate these fractionsat thestatewide leveleven thoughestimatesareavailableatthecountyscalebecausethePerlacketal.studycontainsthecaveatthat“duetosamplingconstraints,forestrydataarenotintendedforuseatthesingle-countylevel.”Weapplythecalculated state-level cost fractions to our own county-level output projections to derivecostcurvesformobilizationofthebiomassmaterialinourprojections.

Pre-treatmentandpelletization,andhandlingcostsarederivedfromEhrigetal.(2014)andPirraglia at al. (2010). These cost calculations take into account amortized capitalexpenditures,financing,handling,energycost,aswellasbothfixedandvariableoperationand maintenance costs. Operational characteristics of the facility and feedstockcharacteristicsarealsotakenintoaccount.

Giventhelargeamountofmaterialconsideredhere,andthelargeinfrastructurethatwouldberequiredtoachievethisscaleofbiomassexport,pelletizationisassumedtooccurinlarge(120,000T/year)facilities.Transportcostsareappliedtoproductsfromeachcountyonthebasisof thedistance travelled fromthatcounty’scentroidpoint to theportofexportandthenshippingcosttotheAmsterdam/Rotterdam/Antwerpportregion.



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3 Results

3.1 TechnicalandSustainablebiomasspotentialThe base projections for this analysis are the technical potentials, or the amount of keybiomass types that could technically be mobilized from the US SE region going forward.Error!Referencesourcenotfound.presentsthehistoricaldataonyieldsofthesetypesofbiomass aswell as the projected 2015 yields and both business as usual (BAU) and “hightrade” scenarios for future technical potential. These projections are broken down bybiomass type into both hardwood and softwood pulplogs andmiscellaneous removals, aswellasthe“otherremovals”biomassclass,loggingresidues,andmillresidue.

Figure19: Historicalandprojectedfuturetotalbiomassavailability


Note: PertheTPOdatabaseconvention,thepulpwood,compositeproducts,fuelwood,andmiscellaneouscategoriesaregroupedtogether,andareherereferredtosimplyas“biomass.”

Thetechnicalpotentialsreportedabovearetotalyieldsperyearofthetypesofmaterialthatcould be suitable for pelletization and export. Excluded from these values are harvestvolumeofsawlogsandveneerlogs,asthesehigher-valuematerialsareunlikelytobeutilizedasbioenergyfeedstock.Furtherexcludedarethe33-50%ofharvestresiduethatisleftinthefieldinthetechnicalpotentialcaseaswellasthe50%ofthe“otherremovals”categoryof



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biomassthatisheldbackinordertoavoidcountingmaterialremovedthroughlandclearingoperations.

Furthermore, the biomass harvest potentials presented in Error! Reference source notfound. are gross availability without accounting for domestic demand. Error! Referencesourcenot found.presentsdomesticdemand for thecategoriesofbiomassutilized in thepelletmarket.Thisanalysisassumesthatthesedomesticdemandsformaterialaresatisfiedbeforebiomasscanbemadeavailableforpelletizationandexport.

Figure20: ProjecteddomesticdemandforbiomassfromtheUSSEregionforkeysectorscompetingwiththeexportpelletmarketforbiomassmaterial.

Source:ownelaborationdrawingonForestProductsModuleoutputs(Ince2011)

Note: Woodenergydemandconsideredhereincludestraditionalwoodenergyuseforheataswellas“modern”bioenergy.

Combining projected production potential with projected domestic demand, we arrive atestimates of technical export potential. Error! Reference source not found. presents thetechnical potential projected for the cases under investigation as well as the materialtheoreticallyavailableforexportafterdomesticdemandhasbeenmet. Itshouldbenotedthat these are theoretical export values, unconstrained by pelletization capacity or cost.



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Furthermore, theseareexportcapacities, ratherthanEU importcapacities. If thismaterialweremobilized andmade available for export, EU importswould be in competitionwithdemand for biomass for various uses in third countries. The global market for theseresourcesisnotevaluatedhere;allexportpotentialfromtheUSSEisconsideredavailabletoEUmarkets.

Figure21: ProjectionsoftotaltechnicalproductionpotentialfromtheSEUSAforests,(forallusesofbiomass),andpotentialavailableforexportoncedomesticdemandismet.


In order to determine the sustainable potential for export, we constrain the technicalpotentialsreportedinError!Referencesourcenotfound.basedonspatiallydiscreteimpactandforesttypedata.Error!Referencesourcenotfound.belowdisplaysbothtechnicalandsustainablepotentialofbiomassforexport.Presentedhereareourconservativesustainablepotentialvalues–derivedfromthe“allbiomassconstrained”approach.Insomeprojections,thesustainableexportpotentialinthiscaseisfoundtobenegative,implyingthatdomesticdemand for biomass from the region is expected to be greater than total sustainablebiomassproduction.



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Figure22: Technicalexportpotential(sameasexportbarsinfig20)andsustainableexportpotentialwhenallbiomassharvestisconfinedtosustainablesourcing


TheUSSEisaverylargegeographicalarea,andthisanalysisprojectsmaterialavailabilityatacounty-levelspatialresolutioninordertoderivemoreaccuratecostestimatesaswellastoenable the sustainability constraintanalysis,which is inherently spatial innature in that itseekstoexcludecertaincategoriesofforest.Error!Referencesourcenotfound.showstheprojectedbiomassavailabilityinthe2030hightradecaseatthecounty-levelresolution.



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Figure23: Spatialdistributionofnetsustainablepotentialforroundwoodinthe2020and2030BAUandHighTradecases

Source:Biotrade2020+project(http://s2biom-test.alterra.wur.nl/web/guest/usa)

Note: Whilethesefiguresarepresentedatacounty-levelresolution,theyresultfromahigh-levelanalysisthatisunabletocharacterizeallofthesmaller-scaledynamicsofvariationsatplayintheforestindustryofagivenlocality.Assuch,theseresultsshouldnotbeconsideredapplicableforcounty-levelanalysisorplanning,whereahigherdegreeoflocalnuanceiswarranted.

3.2 Biomasssupplycostsandcost-supplycurvesMobilisationofbiomassfromthefieldcanbeacostlyproposition,andthecostofproducingthismaterialisperhapsthemostcriticalcomponentofthefeasibilityofbiomassenergyasameaningful component of a low-GHG energy future. Error! Reference source notfound.Error! Reference source not found. presents cost curves for delivery of technicallyavailable biomass (i.e. the technical potential) as biomass pellets to the Amsterdam-Rotterdam-Antwerp port region. The steepness of these curves is attributable to the



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modeled cost of the biomass feedstock drawn from Perlack et al (2011). Most of thematerialpresentinthesesustainableexportcurvesisloggingresidueandthinningsthattheUSFS considers to be low cost/value materials for the most part, with a limited amountharder-to-accessmaterialbecomeavailableathighermobilizationcosts.Asdescribedinthemethods section, the transport costs are averages on a state level. To determine moreaccurate cost of supply would require detailed analysis of the situation in each countyincludingpossiblelocationsofpelletmillsandlocallogistics,whichwouldhavegonebeyondtheframeofthiswork.Thecostlevelsshouldthereforebeconsideredasindicative.

Figure24: Biomasscostcurvesforsustainableexportpotential-2015,2020,and2030,BAUandHighTradescenarios.


Note: The2030BAUcurveisnotvisibleasthereisnoexcessmaterialavailableforexportinthatprojection.Forcomparison,in2015,pricesCIFARArangedbetween160-180Euro/tonne.Presentedherearecostcurvesandsodonotincludeprofittakingatvariouspointsinthesupplychainthatwouldbereflectedinthesemarketprices.



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4 Discussion

4.1 TechnicalbiomasspotentialThis analysismakes it clear that there are significant quantities of biomass that could bemobilizedfromtheSoutheasternUSforuse inthebioenergymarketsoftheEU.However,thefeedstockquantitiesindicatedforsomecasesintheresultsabovearesignificantlyhigherthanthe6.9milliontonnesofpelletsthatareestimatedtohavebeenproducednationwidein2014 (UNECE-FAO2015).This isdue to the fact that theseare totalbiomasspotentials,unconstrained by pelletization or supply chain capacity. It is worth noting that a pelletindustrycanonlyflourish if thetraditional (especiallysawmilling) industryflourishes,giventhe interlinkages between these industries (Wear and Greis 2013). The pellet industry isexpectedtoexpandsignificantlyifthesetraditionalusesofbiomassflourish,sincethiswouldlead to lowquality logsand residuesbecomingavailable.Again,however, thesedynamicsarenotexplicitlyaccountedforinthepresentanalysis.

OtherstudieshaveanalyzedtheamountofforestbiomassforbioenergyinNorthAmericanforests.Forexample,a reportproduced forDECC in theUKestimatedthatby2020, therecould be up to 47 million oven dry tonnes (odt) per year of US forest harvest residuesavailable, thatwouldotherwisebeburnedat theroadside,aswellasanother17.5millionodt/year of residues from fire treatment of US forests (Stephenson & MacKay 2014). Itshouldbenotedthattheirestimatesareinovendrytonnes,wheretheestimatescontainedinthisreportareingreentonnes,whichareassumedtobeabout50%water.

4.2 SustainablebiomasspotentialAs described above, the sustainable potentials presented in Error! Reference source notfound.assumethatallbiomassharvestingintheUSSEisconfinedtothoseareasdeemedtomeet the sustainability criteria considered here. For this reason, these are conservativeestimatesofavailability,and insomecasesthesustainableexportvaluesareverysmalloreven negative.Negative export potential implies that domestic demand for biomass fromthe region isexpected tobegreater than total sustainablebiomassavailability. This couldthereforerequirenetimportofbiomass,shiftingofproductionoutoftheSoutheastregion,greaterharvestlevelinsustainableregions,orsomeunsustainableharvestinordertomeetdomesticdemand.

Thebiodiversityconservationschemeconsideredhereisambitious,andifappliedacrossallforestry activities would leave very little remaining scope for export. However, theseestimatesaredrawn fromactualharvestprojections,which inmost casesare significantlylowerthanthetotalnetannualincrementofbiomassgrowthintheforest(USFS,2012).Thismeansthatthereisoftensomeadditionalbiomassthatcouldbeharvestedfromsustainablymanagedforestsifdemandweresufficient.

It should be noted that any sustainability criteria the EC (or EUmember countries) couldimposeontheuseofbiomassunderitsRenewableEnergyDirectiveandrelatedregulations



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wouldonlyapplytothematerialactuallyusedinMemberStates.Thismeansthatwhiletheapproach presented here gives our best estimate of the amount of actually sustainablematerialthatcouldbeavailableforexportfromtheUSSE,itdoesnotreflecttherealitiesofthe policy frameworks that might cause that material to be used. A much more likelyframeworkwouldconstrainsourcing in theUSSoutheastonly for thebioenergy feedstockmaterialdestinedforuse intheEU.Thisapproachcreatestheriskof leakage,whereintheproductsofunsustainableactivitiesaresimplyshiftedfromtheexportbiomassmarketintoothersectorsratherthanbeingpreventedaltogether.

Bycomparingthesustainablepotentialunderthe“allbiomassconstrained”caseagainstthenominally sustainable potential if only export biomass were constrained we are able toestimatethescaleofthepotentialleakagethatcouldbedrivenbysuchanapproach.Error!Reference source not found. presents the scale of this leakage risk for each of our studycases.

Figure25: Leakageriskfromonlyapplyingsustainabilityconstraintstoexportedbiomass


AsismadeclearinError!Referencesourcenotfound.,thereisrealriskof leakagefromapolicy constrainingonly exportedpellets for sustainability. This shouldnotbe takenas anargumentagainstapplyingsustainabilitycriteriatoEUpelletimports,butasindicationofthelimited efficacy of such a policy alone. The US SE is a key producer of pulp& paper andtimberproducts,forwhichnoexportcriteriaotherthantheEUTimberRegulationapply.

A more comprehensive strategy, applying sustainability criteria to all imported biomassproductsaswellasadvocatingforstrongerprotectionswithintheUnitedStates,wouldgofartherthanabioenergy-onlypolicytowardsmeaningfulbiodiversityprotections.



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4.3 USDomesticDemandThebasecaseintheUSDepartmentofEnergy’s2014AnnualEnergyOutlook(AEO)projectsa10%increase inwoodenergyuseby2030–asignificantdownwardrevisionfromayearearlierwhentheAEOprojectedanincreaseof47%by2030(USDOE2015).Thebioelectricityindustry is very reliant on policies such as technology-specific carve-outs in RenewablePortfolio Standards. Thesepolicies are in flux at present, in part owing to theuncertaintysurrounding accounting for biogenic carbon emissions. This policy uncertainty has beencombined in recent years with low natural gas prices due to the advent of hydraulicfracturing and the current shale gas boom in the US. Together, these factors have had achilling effect on the recent growth of the bioelectricity industry andmake its large-scalegrowthintheimmediatefutureunlikely.

It couldbe argued that this slowing indemand forbiomassenergy in theUS is apositivedevelopmentfromtheperspectiveoftheavailabilityofthatbiomassforexporttoEurope.However,thepelletizationcapacityneedstobebuilt,andarobustdomesticdemandaswellas active incentives from the US government would stimulate the necessary investment.Also, the lackof robustdemandgrowth in theUS stemsat least inpart from factors thatwouldbeequallytruefortheEUexportmarket.Thisincludestheeconomicandengineeringchallenges of utilizing biomass residue for energy and themixed reputation of bioenergyamong environmental NGOs. The latter of these issues is being felt acutely in Europealready.

Also,demandintheEUremainsuncertain.TheDutchParliamentrecentlyvotedtosuspendan on-going biomass support scheme aimed at increasing the co-firing ofwood pellets inexistingcoalpowerplantsto3.5milliontonnesperyearby2020(Upton2016).Evenbeforethisaction,however,useofpelletsinthecountryhaddroppedtonearzero,dueinparttouncertainties surrounding the sustainability of the fuel and howany EUpolicy tomanagesustainabilitywillbeimplemented(UNECE-FAO2015).

4.4 MethodologicallimitationsandsourcesofuncertaintyThe key primary uncertainty surrounding this and any projection analysis is the fact thatsubjective methodological decisions can have a large impact on the ultimate result. Aninvestigation of the sensitivities in this work shows that choice of RPA scenario, residueremoval level, ABC vs EBC policy framework, andmixed oakwoodland utilization rate forsustainabilitymaskingarethefourlargestvariablesindrivingourresults.

Furthermore,manyof thedriversof thismodelarethemselvessensitivetobothdomesticandglobalpolicyandeconomiccircumstances,whichareprone tounanticipatedchanges.Factors such as the composition of housing stock into the coming decades, the forwardtrendsinpulpandpaperuse,andthehard-to-predicteffectofinsectinfestationscanhavealargeimpactontheavailabilityofbiomassforpelletizationandexport.Furthermore,thereisuncertaintyastotheextenttowhichnon-industrialprivateforestownerswillbewillingtoharvest biomass for bioenergy on their property (e.g. Aguilar, Cai & D'Amato 2014; Galik



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2015).Thescenarioapproachdescribedhereaimstomanagethisvariabilityanduncertaintybypresentingabroadrangeofoutcomesacrossmanypossiblefutures.

Theglobalmarket forpelletsorotherproductsdemanding thesamebiomass resources isnotconsideredhere.IftheresourcebasedescribedinthisreportweremobilizedfromtheUSSEregionandwereavailableforexport,theEUwouldbecompetingeconomicallyforthismaterial. It is possible that EU member states would be the primary importers of thisbiomass,but thepotentials reportedhere shouldbeconsideredasexportpotentials fromtheUSSEandnotnecessarilyasimportpotentialsfortheEU.However,giventhattheonlyothermajormarket for importedwoodpellets is inEastAsia (Koreaand Japan,whicharesuppliedbyexportsfromothercountriesintheregionandWesternCanada),itislikelythatEUmemberstateswillremainthelargestimportmarketforUSbiomassinthecomingyears.

Our results, and most other ambitious projections of the availability of biomass forbioenergy,viewharvestresiduesandthinningsasaparticularlylarge,andlargelyuntapped,resourcebase.However,forestresidueshaveahighconcentrationofbark(becauseoftheirhigh surface to volume ratio) as well as soil and other debris. Thesematerials can causeslagging, fouling and corrosion in boilers (Stephenson&MacKay 2014), and are thereforenot a preferred fuel. There remains some uncertainty as to the extent to which thesematerialswillbeabletobemadeusefulasbioenergyfeedstocks.



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5 OutlookonfutureworkThe results presented in this report raise new and important questions that will requirefurtherresearch.

1. As discussed above, this analysis evaluates the amount of biomass material availableunderseveralscenariosbutdoesnotconsiderthesupplychain(includingpelletization)capacityconsiderationsthatcouldconstrainitsavailabilitytoenergymarkets.Combiningthese estimates with supply chain capacity projections would enable more completetechno-economicprojectionsofpelletavailability.

2. Further research is needed to determine the extent to which the quality of someresidues(e.g.loggingresiduesandthinningswithhighcontentofbark)willconstrainthemobilization and use of the harvest and thinning residue materials that this analysisshowsarecriticaltosustainableexportofbiomassforenergyfromtheUSSE.Researchisalsoneededtodevelopharvestandpost-harvesttreatmentpracticestoenablefurtherutilizationofthesematerialtypes.

3. This type of availability analysis will need to be merged with a sophisticatedunderstandingofglobalbiomassmarketsinordertobetterunderstandtheroleofotherplayers in the global market, both in the pellet sector as well as in other sectorsdemanding the same feedstocks. This will help determine the extent to which thesustainableexportpotentialsdescribedherewillbeavailableforimporttotheEU.

4. A better understanding of non-industrial private forest owner´s willingness to harvestbiomassforbioenergyisneededtoestimate“mobilizable”sustainablepotentials.

5. Further investigation could create a better understanding of the interplay betweencompositionofhousingstock intothecomingdecades, the forwardtrends inpulpandpaperuse,andthehard-to-predicteffectofinsectinfestationsaswellasthesensitivityoftheoutcomestoeachfactor.

6. IfsustainabilitycriteriaweretobeappliedtoEUimportsofbiomasspellets,thiswouldbe unlikely to significantly impact activities on the ground in the US SE region unlessthesecriteriawereappliedacrossthewholeoftheUSforestindustry(anoutcomethatthe EC could not control). A better understanding of the dynamics of this so-called“leakage” in the forest industry could help the EC determine the best framework forensuringthesustainabilityofitsimportsinaneffectivemanner.



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6 AppendixA–GreenhousegassupplycurvesAsdescribedinsection1.4themainbodyofthisreport,mostlifecycleassessmentstudiesshowsomegreenhousegasreductionsfromdisplacingEUgridelectricitywithbioelectricityfromUSpellets.ThesefindingsareinlinewiththelifecycleemissionscalculatedintheEC’sownresearchconductedby its JointResearchCentre(Guintolietal.2015).Theseanalysestypicallyconsidercombustionofbiogenicfuelstobecarbonneutral–anapproachthathasbeencontroversialinsomequarters.However,followingthecurrentapproachoftheEC,weassumecarbonneutralityforbiomasscombustioninthisreport.Wealsoassumethatannualharvested volumes will continue to remain lower than annual forest increment. Otherconcerns,suchascarbondebt,havenotbeenconsideredinthisanalysis.

For the reasonsdescribedabove,wehavenot considered life cycleGHG intensity tobeameaningful sustainability constraint from an EU policy perspective. However, becausecarbonintensityremainsanimportantenvironmentalcharacteristicofenergysystems,andinkeepingwiththeotherBioTrade2020+casestudies,wehaveevaluatedthelifecycleGHGfootprint of the biomass pellets considered in this analysis. GHG emissions are calculatedacrosstheentiresupplychain,takingintoaccountallofthefollowingemissionsources:

• Cultivationandharvestingactivities

• Fertilizerproductiontoreplacenutrientswithdrawnbyresiduesremoval

• Pre-treatmentandpelletizationfacilityoperations

• Domesticandintercontinentaltransport

Greenhouse gas emissions are calculated based on the same characteristics of the pelletproduction cost. GHG emissions of transport are, just as the cost, taken from the BIT-UUmodel.EUdefaultvaluesareusedfortheemissionsassociatedwithcultivation,harvestingandpre-treatment.Furtherdetailon theLifeCycleGHG intensityanalysiscanbe found inBioTrade 2020+ deliverable 2.4 (Iriarte et al. 2016). Figure 26, below, presents the GHGintensitycurvesforthepotentialsupplyestimatedinthisanalysis.



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Figure26: Aggregate greenhouse gas supply curve for potentials estimated in thisanalysis