IMPROVING THE ENERGY EFFICIENCY &ENVIRONMENTAL PERFORMANCE OFGOODS MOVEMENTJames J. Winebrake, PhD., Rochester Institute of TechnologyAsllomar 2009 Conference on Transportation and EnergyAcknowledgementsAlthough I am presenting today, much of thematerial was developed jointly with Dr. James J.Corbett,Universityof Delaware.yI am indebted to the faculty and students in theLaboratoryfor Environmental ComputingandpgDecision Making at RIT, including Bryan Comer, ChrisProkop, Dr. Scott Hawker, and Dr. Karl KorfmacherJ. Winebrake, Asilomar, 2009.MyJob TodayyPresent energyand environmental attributes ofgoodsgmovement from multiple modesDiscuss benefits from shifting from high energy-intensitymodes to low energy-intensity modesAssess overall opportunities for mode-shifting in alarger sstems contextyProvoke policy-focused discussionJ. Winebrake, Asilomar, 2009.WorkingHothesisypWe can solve a large part of the energy andenvironmental problems of freight transportation bymovingoods off trucks and onto trains and ships.g pV.J. Winebrake, Asilomar, 2009.O i f G d MOverviewof GoodsMovementJ. Winebrake, Asilomar, 2009.Goods Movement and GDP4800Ton‐Milesv.GDPfortheU.S.(1987‐2005)440046004800380040004200

i les (Billions)340036003800

Ton

‐ M iFor every trillion dollar increase in GDP, weexpect an additional 242 billion ton-miles.300032006000 7000 8000 9000 10000 11000 12000J. Winebrake, Asilomar, 2009.GDP(Billions,2000$)Source: Corbett and Winebrake, 2009.6,000,000U.S.FreightTransportbyMode,1980‐20305,000,000

s3 000 0004,000,000

Ton

‐ mile s2,000,0003,000,000

M illions of1,000,000

M01980 1985 1990 1995 2000 2005 2010 2015 2020 2025 2030TruckRailDomesticShippingAirSo rceB reaofTransportationStatistics46bDomesticShippingu:uuTransportationStatisticsTable1‐(1980‐2006);AEO2009(derived,2007‐2030).J. Winebrake, Asilomar, 2009.8000.0ProjectedEnergyUseinU.S.FreightTransport,2006‐20306000.07000.04000 05000.0

n BTUAAGR:Freight truck =1 3%3000.04000.0

Trillio n-Freight truck =1.3%-Freight rail = 0.9%-Air (freight carriers) = 2.8%-Domestic shipping = 0.9%1000.02000.00.02005 2010 2015 2020 2025 2030TruckRailDomesticShippingAirSource:AEO2009TableTruckRailDomesticShippingAirSource:45J. Winebrake, Asilomar, 2009.Source: AEO 2009, Table 45.Shipping,RecreationalBoats0.9%Air9.8%MilitaryUse2.8%Lubricants0.3%PercentageofEnergy‐RelatedTransportationCO2EmissionsbyMode,2008Total emissionsfrom transportationShipping,Domestic1 2%pp g,International3.1%from transportation~1.9 GtCO2eq/yrTotal emissionsfrom all energy sectorsRail,Freight2.2%1.2%from all energy sectors~5.9 GtCO2eq/yrRail,Passenger0.3%Light‐DutyVehicles57.8%BT iFreightTrucks18.3%CommercialLightTrucksBusTransportation1.0%Trucks2.1%J. Winebrake, Asilomar, 2009.Source: AEO 2009, Table 19.M d l C iModal ComparisonsJ. Winebrake, Asilomar, 2009.5000EnergyIntensityofUSFreightModes,1980‐200640004500

m ile)250030003500

(BTU/ton

‐ mNote:These represent top-down averages and should150020002500

g y Intensitynot be used for blanket modal comparisons!50010001500

Ener g05001980 1985 1990 1995 2000 2005TruckRailDomesticShippingSource:TransportationEnergyDataBook27J. Winebrake, Asilomar, 2009.Range of typical CO2 efficiencies for various cargo carriersCr deGeneral CargoLNGCrudeNOTEI f fBulkChemicalReefer:Impactsareafunctionofmany factors related to routeand modal characteristics.ProductLPGContainerRoadRailRoRo / Vehicle0 50 100 150 200 250g CO2 / ton*kmSource: Buhaug, et al. 2009J. Winebrake, Asilomar, 2009.S E l U i GIFTSomeExamplesUsingGIFTThG ti l I t d l F i ht T t ti (GIFT)eGeospatial Intermodal Freight Transportation(GIFT)model is a model jointly developed by the RochesterInstitute of Technologyand the Universityof Delaware,y ,with funding support from US DOT/MARAD, Great LakesMaritime Research Institute, ARB, among others.J. Winebrake, Asilomar, 2009.Connect Multiple Transportation Mode Networks atIntermodal Transfer FacilitiesRoad NetworkRail NetworkWaterway NetworkIntermodal Transfer FacilityJ. Winebrake, Asilomar, 2009.Define Economic, Energy, Time and Environmental Costsof Traversing Each Network Segment and TransferTruck Segment“Costs”...NOxCO2EnergyOperatingCostTimeDistanceTruck Segment CostsESRI ArcGISNetwork Analyst findsy“Shortest” (least cost) routes.J. Winebrake, Asilomar, 2009.J. Winebrake, Asilomar, 2009.Montreal to Cleveland (Ship 1) Montreal to Cleveland (Ship 2)Emissions and Time of Delivery TradeoffsMontreal to Cleveland400600

2 (kg)0200T kShi (DR)R ilShi (EJ)

CO 2TruckShip(DR)RailShip(EJ)804060

e -of y (hrs)02040

Tim e D eliverJ. Winebrake, Asilomar, 2009.Truck Ship (DR) Rail Ship (EJ)Mode300400CO2Comparison100200300

CO 2 (kg)0100Truck Only Rail Only Ship-Truck Rail-TruckJ. Winebrake, Asilomar, 2009.2500CO2Comparison100015002000

O 2 (kg)05001000

C OTruck Only Rail Only Truck-RailJ. Winebrake, Asilomar, 2009.O i i f M d Shif iOpportunitiesforModeShiftingJ. Winebrake, Asilomar, 2009.The IF-TOLD Mitigation Framework:A C t t f M d Shifti Di iA Context forModeShiftingDiscussionsThe IF-TOLD “six-legged cow”:Intermodalism/mode-shifting–use of efficient modesFuelsuse of low carbon fuels–Technology– application ofefficient technologiesOperations– best practices inoperator behaviorLogistics– improve supply chainmanagementDemand– reduce how muchSTUFF we consumeEven a six-legged cow can moveall legs – dynamic, balancing!J. Winebrake, Asilomar, 2009.Opportunities for Mode-Shifting()[]∑⋅⋅⋅=ΔEEpfcWE−kjiijkijkijkikijEEpfcWEΔEij= energy savings due to modal shift from i to jWik= work done by mode i for commodity k (ton-miles)c= shipmentcompatibility fractionofito j for k (cargo)ijk=shipmentcompatibilityfractionofitojfork(cargo)fijk= shipmentfeasibility fractionof i to j for k (infrastructure)pijk= shipmentpracticality fractionof i to j for k (economic)Ei= energy intensity factor for i (Btu/ton-mile)Ej= energy intensity factor for j (Btu/ton-mile)J. Winebrake, Asilomar, 2009.Also need to account for intermodal transfer penalties.Insights intocijk–Cargo CharacteristicsPercentageofGoodsMovementinU.S.byCommodity(Sample)andMode(2002CFSData)gijkgNonmetallicmineralproductsElect.andelectricalequip.Misc.manufacturedproducts1.1%1.0%4.3%CoalBasicchemicalsp3.7%21.9%1 8%OtheragriculturalproductsGravelandcrushedstoneNonmetallicminerals1.8%3.4%3.5%LiveanimalsandlivefishCerealgrains8.4%0.1%0% 50% 100%TruckRailWaterOther/UnknownJ. Winebrake, Asilomar, 2009.Source: CFS 2002, Ton-Miles by Commodity and ModeInsights intofijk– U.S. IntermodalInfrastructureJ. Winebrake, Asilomar, 2009.1800AverageMilesperShipmentbyModefortheU.S.(2007)1400160010001200

S hipment600800

Miles per S2004000Truck Rail ShallowdraftGreatLakes Deepdraft Air(includedtruckandParcel,U.S.P.S.orOtherandunknownJ. Winebrake, Asilomar, 2009.air)couriermodesSource: CFS 2007.EstimatingMode ShiftingPotentialg()[]∑−⋅⋅⋅=ΔkjiijkijkijkikijEEpfcWETruckRailWaterIntermodalUSPS/ParcelOtherModalShiftConsider total ton-miles as agridded box, where each cell isJ. Winebrake, Asilomar, 2009.equivalent to 1%.EstimatingMode ShiftingPotentialg()[]∑−⋅⋅⋅=ΔkjiijkijkijkikijEEpfcWETruckRailWaterIntermodalUSPS/ParcelOtherModalShiftAssume that about 50% of the cargo currently movedby truck is compatible with rail or ship due to physicalti f t l di l i ti t [0 50]J. Winebrake, Asilomar, 2009.properties,safety,loadinglogistics,etc.[cijk~0.50]EstimatingMode ShiftingPotentialg()[]∑−⋅⋅⋅=ΔkjiijkijkijkikijEEpfcWETruckRailWaterIntermodalUSPS/ParcelOtherModalShiftAssume that of the cargo that is compatible,infrastructure can only serve 70% of the ton-miles inJ. Winebrake, Asilomar, 2009.the short term [fijk~0.70]EstimatingMode ShiftingPotentialg()[]∑−⋅⋅⋅=ΔkjiijkijkijkikijEEpfcWEUnder these assumptions,there is potential to move ~5% of the total ton-miles(~12% of truck ton-miles)from truck to rail/ship. Iftruck is ~5 times moreenergy intense thanil/ hi h hi i lirail/ship,thenthisimplies~8% reduction in energyconsumption.Average distance by truck is 200 miles. Assume that~50% of the ton-miles shipped > 200 miles and 25% are>500 miles. Assume economic possibility exists for modeJ. Winebrake, Asilomar, 2009.shifting for 35% of total truck trips. [pijk~ 0.35].P li i f P i Effi iPoliciesforPromotingEfficiencyJ. Winebrake, Asilomar, 2009.PolicyOptions d alism ogy o ns sy p

Intermo d Fuel Technol o O p erati o Lo g istic s DemandPolicy OptionsI F TOLDEfficiency standards●●●Taxes●●●●●●Subsidies●●●Technologymandates●Infrastructure investment● ●R&D investment● ●/AlternativeLC fuels● ●Size/weight restrictions● ●●Demand management●J. Winebrake, Asilomar, 2009.C lioncusionJ. Winebrake, Asilomar, 2009.ConclusionModal shifts offer large side-by-side benefitsModal shifts offer large sideSystem benefits vary depending on vessel, vehicle,locomotive, and route characteristics and areconstrained by compatibility, feasibility, andpracticality–research needed hereySuite of policy options should be consideredrecognizing freight sector as a systemWedge analysis needed for freight sector that looksat potential for the IF-TOLD set of elementsJ. Winebrake, Asilomar, 2009.CitationsCorbett, J. J.; Winebrake, J.J.; “The impact of globalisation on internationaliti t t ti it P t t d d f t ti ” imaritimetransportactivity:Past trendsand futureperspectives,” inGlobalisation, Transport, and Environment, edited by N. A. Braathen,Organisation for Economic Cooperation and Development (OECD), Paris,forthcoming.Buhaug, Ø.; Corbett, J. J.; Endresen, Ø.; Eyring, V.; Faber, J.; Hanayama, S.;Lee, D. S.; Lee, D.; Lindstad, H.; Mjelde, A.; Pålsson, C.; Wanquing, W.;Winebrake, J. J.; Yoshida, K.Updated Study on Greenhouse Gas Emissionsfrom Ships; International Maritime Organization(IMOLondon, UK, 2009.)Energy Information Administration (2009).Annual Energy Outlook 2009.Washington, DC; available athttp://www.eia.doe.gov/oiaf/aeo/index.htmlB f T t ti St ti ti C dit Fl S (2002 dBureauof TransportationStatistics,CommodityFlowSurvey(2002and2007), available athttp://www.bts.gov/programs/commodity_flow_survey/J. Winebrake, Asilomar, 2009.