TROUPE Final

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					          Uncertainty/Sensitivity analysis of the transport
                        model TREMOVE

                                      Final Meeting
                                                      Charis Kouridis
                                                      Ioannis Kioutsioukis
                                                      Thomas Papageorgiou
                                                      Stephen Mills
                                                      Les White
                                                      Leonidas Ntziachristos


    DG CLIMA, Brussels, 18 Feb 2011

1
    Contents (1/2)
     Objectives of the study
     Uncertainty ranges of input variables and modelling parameters
         Input variables description
         Emission factor modelling
         Input variables and parameters not affected by the study
         Changes over interim report
     Modelling Theory / Approach
         Methods
         Parameterisations of input data
     TREMOVE software modification and update
         Software code modification
         Software code added
         New features
         Guidance to use the software
         Differences between the two steps



2
    Contents (2/2)
    Baseline
        Screening uncertainty and sensitivity analysis
        Variance-based uncertainty and sensitivity analysis
        Discussion
    Scenarios
        Ownership tax increase
        Fuel cost estimation uncertainty
        HDV Euro VI
    Conclusions and recommendations




3
    Objectives of the study


    Identify the variance of the input data to TREMOVE.

    Determine the uncertainty range of the baseline.

    Determine the uncertainty range of three indicative
    scenarios.

    Conduct a sensitivity analysis to identify the most important
    factors in terms of uncertainty.




4
    Variance of input variables

    Input variables found in the model’s input database
       Variables are multidimensional resulting in a significantly large
       number of values
    4 major categories
       Variables influenced
        • road stock module
        • emissions module
       Variables that were not relevant to the UK study (eg 0 values, or
       country related dummy variables)
       Variables that are actually parameters used to facilitate intermediate
       calculations (eg emission factor parameters)
       Variables related to modules other than road stock and emissions



5
    Short input variables description

                        Name             Varied                   Name           Varied
         FUEL_ENERGY_DENSITY               Y      SRESIDUALparaA                   Y
         FUELSPEC                          Y      SRESIDUALparaB                   Y
         LTRIP                             Y      TMAX                             Y
         paraB                             Y      TMIN                             Y
         paraT                             Y      PUBLICVAT                        N
         PUBLICCOSTCOV                     Y      r                                N
         RFACTORUNCONV                     Y      Rairco_maintenancefreq           N
         RFC_REDUC_RESISTANCE              Y      REDUC_NEW_TECH                   N
         RFCairco                          Y      RFACTORACEA                      N
         RFUEL_COMPOSITION                 Y      RFACTORDIE                       N
         RHC                               Y      RFACTORREAL                      N
         RINSCFRACTION                     Y      RFC_ACEA_2002                    N
         RLABOURC                          Y      RFC_REDUC_GSI                    N
         RLABOURTX                         Y      RFCairco_REDUC_SCENARIO          N
         RLOADCAP                          Y      RFCOST_COMP                      N
         RLOGITCNGAVAIL                    Y      RFTAX_COMP                       N
         RLOGITPACC                        Y      RFVAT                            N
         RLPG_FIT_COST                     Y      RINSTXfix                        N
         RMILage                           Y      RINSTXrate                       N
         RMILnew                           Y      RLOGITPGDP                       N
         ROWNTX                            Y      RMILinc                          N
         RPCS_BASE                         Y      RPCS_INCREASE_AIRCO_SCENARIO     N
         RPCS_INCREASE_2009                Y      RPCS_INCREASE_GSI                N
         RPCS_INCREASE_2012                Y      RPCS_INCREASE_TPMS               N
         RREPMAINTC_INCREASE_RTECH_RES     Y      RRegTX                           N
         RREPMAINTCFRACTION                Y      RTECH_GSI_SHARE                  N
         RSHairco                          Y      RTECH_RESISTANCE_MX              N
         RSTNBY                            Y      RVAT                             N
         RVP                               Y      TECHMX                           N



6
    Detailed information on the variables

     UK                                  29               Name: RINSC FRAC TION
     Type:                   -                            units: %
                             Insurance cost as percentage of vehicle purchase resource cost
     Description:
     Sources:                Automobile Association and Road Hauliers Association
                             Notes: Assumptions are in the UK AA report that motorists will benefit
                             from an average 60% discount on the full price of insurance. It is worth
                             noting a considerable variation is possible with different
                             underwriters/providers. One example in 2010 gave a range of between
                             £470 and £750 with a mean of £636. This gave a range of ratio of
     Comments:               between 0.016 - 0.0214. There are a considerable number of variables
                             influencing the price of vehicle insurance: age and experience of driver,
                             male/female, age and value of vehicle, model of vehicle (currently 20
                             categories), security of vehicle, address where it is kept, cost of parts
                             (?imports).


     Quantification of       The HDV data was from the RHA.     It was possible to prepare a selection
     variability (UK):       of samples for passenger cars.
     Type of distribution:   Normal
     Reasoning:              Typical uncertainty distribution




7
    Emission factor uncertainty modelling
                                                 Name              Name                     Name
                                          A1            D1                         M1
                                          A2            D2                         M2
                                          A3            D3                         M3
                                          A4            E0                         NVFUNC
     Emission and consumption factors     A5            E0c                        R0COLDFAST
     parameters were not influenced       A6
                                          A7
                                                        EFNXPM
                                                        F0
                                                                                   R0COLDSLOW
                                                                                   R0WARMFAST
     directly                             A8            F0c                        R0WARMSLOW
                                          AA0           F1                         R1COLDFAST
     Emission and consumption factors     AA1           F1c                        R1COLDSLOW
                                          AA2           F2                         R1WARMFAST
     were influenced indirectly through   AA3           F2c                        R1WARMSLOW
     4 parameters, EFhot, EFcold,         AA4
                                          AMCEUDC
                                                        FF0
                                                        FF0c
                                                                                   R2COLDFAST
                                                                                   R2COLDSLOW
     EF_FChot and EF_FCcold               AMCUDC        FF1                        R2WARMFAST
                                          AV_TEMP       FF1c                       R2WARMSLOW
     Variance was based on                B0            FF2                        REDUC
                                          B1            FF2c                       REDUC_UNCONV
     experimental data using log-normal   B2            FFF0                       RHFC134a_IRREGairco
     PDFs                                 B3
                                          BETAEST1
                                                        FFF0c
                                                        FFF1
                                                                                   RHFC134a_REGairco
                                                                                   RHFC134a_SALEairco
                                          BETAEST2      FFF1c                      RHFC134a_SCRAPairco
                                          BETAEST3      FFF2                       RHFC134a_SERVICEairco
                                          BETAEST4      FFF2c                      SHC
                                          BETAREV       LC_EMI_FACTOR              SHFI
                                          BMCEUDC       LC_EMI_FACTOR_RFUEL_COMP   SULP_LIM1
                                          BMCUDC        LIM1                       SULP_LIM1c
                                          C0            LIM2                       SULP_LIM2
                                          C1            LIM3                       SULP_LIM2c
                                          C2            LIM4
                                          CCID          LIMTRCH
                                          CMCEUDC       LIMVRCH
                                          CMCUDC        M0




8
    Variables not varied in the study

                Name         Appearance                Name    Appearance                Name       Appearance
    AIR_DETOUR                  Air       TCONSFelec          Train         RLOGITP_FCOSTS      Logit
    AIRCONSFfuelD               Air       TEMIF               Train         RLOGITP_INCLARGE    Logit
    AIRCONSFfuelDsplit_alt      Air       TLOADfDif           Train         RLOGITP_INCSMALL    Logit
    AIREMIFD                    Air       TSTBY               Train         RLOGITP_IVLARGE     Logit
    AIREMIFDsplit_alt           Air       TSTNBY              Train         RLOGITP_IVMEDIUM    Logit
    AIRPOLLCOSTUNIT             Air       TVKMEXTREMIS        Train         RLOGITP_IVSMALL     Logit
    PLANEVAT                    Air       ACCIDENTCOST        Welfare       RLOGITP_OCOSTS      Logit
    NETWORKTAX                Demand      ACCIDENTMARGCOST    Welfare       RMOCdummy           Logit
    IWCONFIG                   IWW        L                   Welfare       SLOGITCONST         Logit
    IWCONSFfuel                IWW        LC_POLLCOSTUNIT     Welfare       SLOGITDBIG          Logit
    IWEMIF                     IWW        NOISECOST           Welfare       SLOGITDCOUNTRY      Logit
    IWENGCOST                  IWW        POLLCOSTUNIT        Welfare       SLOGITDSMA          Logit
    IWEQCOST                   IWW        WEARMARGCOST        Welfare       SLOGITDUMMY         Logit
    IWFCOST                    IWW        RINC_LFC_UNSOLD     Logit         SLOGITPROPACC       Logit
    IWFREDUC                   IWW        RLDVdummy           Logit         SLOGITPURCHASE      Logit
    IWFTAX                     IWW        RLOGITCBUS          Logit         SLOGITREPAIR        Logit
    IWFUELdens                 IWW        RLOGITDUM_B         Logit         SLOGITREPxRES       Logit
    RLDVskale                  Logit      RLOGITDUM_DB        Logit         SLOGITRESIDUAL      Logit
    RMOCskale                  Logit      RLOGITDUM_DM        Logit         GAMMA1              Road Stock
    RREPMAINTC_LINK_RPCS       Logit      RLOGITDUM_DS        Logit         GAMMA2              Road Stock
    Rrepmaintcevol             Logit      RLOGITDUM_NO        Logit         GAMMA3              Road Stock
    Ktoe_per_Pjoule            Report     RLOGITDUM_S         Logit         GAMMA4              Road Stock
    Pjoule_per_GWh             Report     RLOGITDUM_UK        Logit         GAMMA5              Road Stock
    METRAMCONSFelec            Train      RLOGITP_ACC         Logit         RRepMaintCorrF      Vehicle Stock
    SULPHUR_RDIESEL            Train      RLOGITP_ACCNO       Logit         RSHARE_EXOG         Vehicle Stock
    TACTTREXalleng             Train      RLOGITP_ACCUK       Logit
    TCONSFelec                 Train      RLOGITP_DUMMYDB     Logit




9
     Changes over the interim report (1/2)
        Main assumption: in order to reduce the number of variables that were to
        be modified it was decided to influence intermediate calculations
        Cost variables were influenced through the COSTROAD parameter




        Key issues related to this assumption
         • Parameters used different aggregation level than input variables (usually lower aggregation
           level)
         • Influencing the COSTROAD parameter would require to recalibrate the demand module each
           time, something that would be impossible




10
     Changes over the interim report (2/2)
        Logit module parameters were not be affected
         • Following discussion of the interim meeting (i.e. elasticity of demand not good
           proxy for logit parameters)


        Final approach: vary only relevant input variables and emission and
        fuel consumption factors




11
     Global uncertainty sensitivity method


     Screening test to identify influential variables (512 runs)
     Uncertainty and sensitivity uncertainty of the baseline (5950
     runs)
        Quantify total uncertainty
        Identify sensitivity of input variables to output

     Repeat for scenarios (512 scenarios due to linearity)
        Quantify total uncertainty
        Identify sensitivity of input variables to output



12
     Parameterisations of input data

      The "total error" of the TREMOVE estimates results from an entire
      "chain of errors". This total error consists of three error contributions:
         εstock denotes the error which comes along with the estimation of the total
         amount of stock
         εcost represents the uncertainty in the parameters related to the cost
         module
         εemissions denotes the uncertainty associated with the road transport
         emissions




13
     Parameterisations of input data - Example εstock




          e ~ N(0,1)




14
      Input variable distribution example
     Parameterisations of input data - Example εstock
                120      RLOGITPACC                         120      RSHairco

                100                                         100


                    80                                          80
        Frequency




                                                    Frequency
                    60                                          60


                    40                                          40


                    20                                          20


                    0                                           0



                                       seconds                                         %

                120      RLOGITCNGAVAIL                     120      RFACTORUNCONV

                100                                         100


                    80                                          80
        Frequency




                                                    Frequency


                    60                                          60


                    40                                          40


                    20                                          20


                    0                                           0



                                      Coefficient                               (kg/km) / (kg/km)

15
     Software code modification
               Input data modification
               Code modification



                                                              Filename
     Vehicle   Stock   Module\Calculate_Transport_Demand.gms       Vehicle   Stock   Module\External_Costs_Accidents.gms
     Vehicle   Stock   Module\Calculate_Transport_Demand_BY.gms    Vehicle   Stock   Module\Fuel_Consumption_Road.gms
     Vehicle   Stock   Module\Calibrate_Base_Case.gms              Vehicle   Stock   Module\Logit_Life_Time_Costs.gms
     Vehicle   Stock   Module\Calibrate_CES_Tree.GMS               Vehicle   Stock   Module\main.gms
     Vehicle   Stock   Module\Calibrate_CES_Tree_BY.gms            Vehicle   Stock   Module\Money_Costs_Road.gms
     Vehicle   Stock   Module\Define_Parameters.gms                Vehicle   Stock   Module\Money_Costs_Road_Private.gms
     Vehicle   Stock   Module\Define_Parameters_Emissions.gms      Vehicle   Stock   Module\Purchase_Cost_Road.gms
     Vehicle   Stock   Module\Define_Parameters_Road.gms           Vehicle   Stock   Module\Purchase_Cost_Road_residual.gms
     Vehicle   Stock   Module\Define_Sets.gms                      Vehicle   Stock   Module\Read_Demand_Module_Output.gms
     Vehicle   Stock   Module\Define_Sets_Road.gms                 Vehicle   Stock   Module\Road_Scrap_Policy.gms
     Vehicle   Stock   Module\Degradation_Mileage.gms              Vehicle   Stock   Module\Run_Simulation.gms
     Vehicle   Stock   Module\Emissions_Road.gms                   Vehicle   Stock   Module\Run_TREMOVE.gms
     Vehicle   Stock   Module\External_Cost_Module.gms             Vehicle   Stock   Module\Sale_Shares_Road.gms




16
     Software code added

                  Filename                                  Filename                         Filename
 ZZZ_cold_emissions.gms                    zz_FUEL_ENERGY_DENSITY.gms             m_RLOGITPACC
 ZZZ_cold_FC.gms                           zz_LTRIP.gms                           m_RPCS_BASE
 ZZZ_hot_emissions_for_HDV_&_Buses.gms     zz_paraBT.gms                          m_RSHairco
 ZZZ_hot_emissions_for_non_HDV_buses.gms   zz_RFACTORUNCONV.gms                   m_ROWNTX
 ZZZ_hot_FC_for_HDV_&_Buses.gms            zz_RFC_REDUC_RESISTANCE.gms            m_RVP
 ZZZ_hot_FC_for_non_HDV_buses.gms          zz_RFCairco.gms                        m_RFACTORUNCONV
 ZZZ_set_year.gms                          zz_RHC.gms                             m_RREPMAINTC_INCREASE_RES
                                           zz_RINSCFRACTION.gms                   m_RHC
                                           zz_RLOADCAP.gms                        m_TMAX
                                           zz_RLPG_FIT_COST.gms                   m_TMIN
                                           zz_RMILage.gms                         m_RINSCFRACTION
                                           zz_RREPMAINTC_INCREASE_RTECH_RES.gms   s_RLOGITPACC
                                           zz_RREPMAINTCFRACTION.gms              s_RPCS_BASE
                                           zz_RVP.gms                             s_RSHairco
                                           zz_SRESIDUALparaA.gms                  s_ROWNTX
                                           zz_SRESIDUALparaB.gms                  s_RVP
                                           zz_TMAX.gms                            s_RFACTORUNCONV
                                           zz_TMIN.gms                            s_RREPMAINTC_INCREASE_RES
                                           zzT_FUELSPEC.gms                       s_RHC
                                           zzT_PUBLICCOSTCOV.gms                  s_TMAX
                                           zzT_RFUEL_COMPOSITION.gms              s_TMIN
                                           zzT_RLABOURC.gms                       s_RINSCFRACTION
                                           zzT_RLABOURTX.gms                      std_V_hdv_hot.inc
                                           zzT_RLOGITCNGAVAIL.gms                 std_V_non_hdv_cold.inc
                                           zzT_RLOGITPACC.gms                     std_V_non_hdv_hot.inc
                                           zzT_ROWNTX.gms
                                           zzT_RPCS_BASE.gms
                                           zzT_RPCS_INCREASE_2009.gms
                                           zzT_RPCS_INCREASE_2012.gms
                                           zzT_RSHairco.gms

17
     GUI for the uncertainty study




            TREMOVE basecase is no longer required to be executed
18
     Differences between the 2 steps

                                                  512    5950                                512    5950
                            Filename                                          Filename
                                                  runs   runs                                runs   runs
        ZZZ_cold_emissions.gms                    YES    YES    zzT_RLOGITPACC.gms           YES
        ZZZ_cold_FC.gms                           YES    YES    zzT_ROWNTX.gms               YES    YES
        ZZZ_hot_emissions_for_HDV_&_Buses.gms     YES    YES    zzT_RPCS_BASE.gms            YES    YES
        ZZZ_hot_emissions_for_non_HDV_buses.gms   YES    YES    zzT_RPCS_INCREASE_2009.gms   YES
        ZZZ_hot_FC_for_HDV_&_Buses.gms            YES    YES    zzT_RPCS_INCREASE_2012.gms   YES
        ZZZ_hot_FC_for_non_HDV_buses.gms          YES    YES    zzT_RSHairco.gms             YES
        ZZZ_set_year.gms                          YES    YES    m_RLOGITPACC                 YES
        zz_FUEL_ENERGY_DENSITY.gms                YES           m_RPCS_BASE                  YES    YES
        zz_LTRIP.gms                              YES    YES    m_RSHairco                   YES
        zz_paraBT.gms                             YES    YES    m_ROWNTX                     YES    YES
        zz_RFACTORUNCONV.gms                      YES           m_RVP                        YES
        zz_RFC_REDUC_RESISTANCE.gms               YES           m_RFACTORUNCONV              YES
        zz_RFCairco.gms                           YES           m_RREPMAINTC_INCREASE_RES    YES
        zz_RHC.gms                                YES           m_RHC                        YES
        zz_RINSCFRACTION.gms                      YES    YES    m_TMAX                       YES
        zz_RLOADCAP.gms                           YES           m_TMIN                       YES
        zz_RLPG_FIT_COST.gms                      YES           m_RINSCFRACTION              YES    YES
        zz_RMILage.gms                            YES           s_RLOGITPACC                 YES
        zz_RREPMAINTC_INCREASE_RTECH_RES.gms      YES           s_RPCS_BASE                  YES    YES
        zz_RREPMAINTCFRACTION.gms                 YES    YES    s_RSHairco                   YES
        zz_RVP.gms                                YES           s_ROWNTX                     YES    YES
        zz_SRESIDUALparaA.gms                     YES    YES    s_RVP                        YES
        zz_SRESIDUALparaB.gms                     YES    YES    s_RFACTORUNCONV              YES
        zz_TMAX.gms                               YES           s_RREPMAINTC_INCREASE_RES    YES
        zz_TMIN.gms                               YES           s_RHC                        YES
        zzT_FUELSPEC.gms                          YES           s_TMAX                       YES
        zzT_PUBLICCOSTCOV.gms                     YES    YES    s_TMIN                       YES
        zzT_RFUEL_COMPOSITION.gms                 YES           s_RINSCFRACTION              YES    YES
        zzT_RLABOURC.gms                          YES    YES    std_V_hdv_hot.inc            YES    YES
        zzT_RLABOURTX.gms                         YES    YES    std_V_non_hdv_cold.inc       YES    YES
        zzT_RLOGITCNGAVAIL.gms                    YES           std_V_non_hdv_hot.inc        YES    YES




19
     Screening uncertainty and sensitivity analysis
      512 simulations : 33 variables  14 influential variables
      5950 simulations : 14 influential variables

         the average trip length (ltrip)
         the hot and cold emission factors (eEF, eEFratio, eEFfc, eEFfcratio)
         the (B,T) - parameter: characteristic service life & faillure steepness (paraB and paraT pairs)
         the road vehicle basic purchase resource cost - EURO 2000 (eRPCSBASE)
         the estimated residual value function as a percentage of purchase cost (usresidualparaAB)
         the repair and maintenance cost excluding taxes as % of purchase resource cost (ex tax)
         (eRREPMAINTCFRACTION)
         the insurance cost as percentage of vehicle purchase resource cost (RINSCFRACTION)
         the labour cost - net wage - for truck drivers - EURO per hour (RLABOURC)
         the labour tax - bruto wage minus netto wage - for truck drivers - EURO per hour (RLABOURTX)
         the annual ownership tax road vehicles - EURO 2005 (ROWNTX)
         the public transport fare cost coverage (PUBLICCOSTCOV)




20
     Screening analysis

           Module   Output Variable   Module   Output Variable
           EMISS    FC                COST     TAXfuel
           EMISS    PM exhaust        COST     VATfuel
           EMISS    CO exhaust        COST     COSTrepair
           EMISS    VOC exhaust       COST     VATrepair
           EMISS    NOx exhaust       COST     COSTlabour
           COST     COSTpurchase      COST     COSTlabourtax
           COST     TAXregistration   COST     COSTrest
           COST     VATpurchase       COST     TAXrest
           COST     TAXownership      COST     VATrest
           COST     COSTinsurance     COST     Costs
           COST     TAXinsurance      STOCK    Vehicles
           COST     COSTfuel          STOCK    VehKms



21
     Screening method example




22
     Uncertainty analysis of the baseline
Output Variable    Units    Median   2010
                                            Median   2020
                                                            Median   2030
                                                                            cov   2010
                                                                                         cov   2020
                                                                                                      cov   2030


CO                  Ton        252,000         119,402         119,439        69%          51%          51%
PM                  Ton         10,750           3,400           3,421        25%          27%          27%
VOC                 Ton         46,927          30,279          31,559        37%          26%          24%
TAXrest             M€          -8,454          -8,768          -9,365        21%          22%          22%
NOx                 Ton        331,319         170,500         158,458        19%          17%          17%
COSTinsurance       M€          24,922          38,291          44,671         6%          13%          14%
TAXinsurance        M€           1,260           1,934           2,255         6%          13%          14%
VATfuel             M€           8,041           9,418          11,412        13%          13%          13%
TAXfuel             M€          33,301          41,490          48,064        12%          12%          12%
COSTfuel            M€          30,727          32,106          40,202        11%          11%          12%
TAXownership        M€           6,166          10,810          12,070         8%          11%          12%
FC                  Ton     46,618,917      55,591,702      60,043,602        11%          11%          11%
COSTrepair          M€          59,798          73,706          86,483         3%          10%          10%
VATrepair           M€           7,293           9,090          10,691         3%          10%          10%
COSTlabour          M€          10,869          14,896          16,607         9%           9%           9%
COSTlabourtax       M€          11,634          15,944          17,773         9%           9%           9%
VATpurchase         M€          10,841          11,566          13,107         5%           9%           9%
COSTpurchase        M€          84,178          99,323         114,467         4%           8%           9%
TAXregistration     M€            22.5            24.2            27.4         7%           8%           8%
VATrest             M€           1,252           1,293           1,377         5%           5%           5%
Costs               M€         323,333         396,036         458,228         2%           4%           4%
Vehicles             #      33,652,081      37,918,723      40,997,888         2%           3%           3%
Vehkms            ×106 km      585,653         665,914         720,553         2%           3%           3%
COSTrest            M€          41,193          44,395          47,695         2%           2%           2%


23
     Sensitivity analysis of the baseline
                Output Variable   Most Important Input Variable   ΣSI2010   ΣSI2020   ΣSI2030
                                  eRREPMAINTCFRACTION,
               COSTrepair                                         0.97      0.98      0.99
                                  eRPCSBASE
                                  eRREPMAINTCFRACTION,
               VATrepair                                          0.98      0.99      0.99
                                  eRPCSBASE
               FC                 eEFfc                           0.96      0.97      0.98
               COSTfuel           eEFfc                           0.96      0.97      0.97
               TAXfuel            eEFfc                           0.96      0.97      0.97
               VATfuel            eEFfc                           0.96      0.97      0.97
               COSTlabour         RLABOURC                        0.96      0.96      0.96
               COSTlabourtax RLABOURTX                            0.96      0.96      0.96
               TAXrest            PUBLICCOSTCOV                   0.96      0.96      0.96
               VATrest            PUBLICCOSTCOV                   0.96      0.96      0.96
               PM                 eEF                             0.97      0.96      0.96
               COSTpurchase       eRPCSBASE                       0.97      0.95      0.95
               TAXownership       ROWNTX                          0.96      0.95      0.95
               COSTinsurance RINSCFRACTION                        0.94      0.94      0.95
               TAXinsurance       RINSCFRACTION                   0.94      0.94      0.95
               COSTrest           PUBLICCOSTCOV                   0.97      0.96      0.95
               NOx                eEF                             0.96      0.95      0.95
               VATpurchase        eRPCSBASE                       0.97      0.94      0.94
               TAXregistration uparaBT                            0.89      0.92      0.92
               CO                 eEF                             0.91      0.92      0.91
               VOC                eEF                             0.93      0.91      0.91
               Costs              eRPCSBASE, eEFfc                0.88      0.88      0.88
               Vehicles           eRPCSBASE, eEFfc                0.89      0.88      0.88
               Vehkms             eRPCSBASE, eEFfc                0.89      0.88      0.88


24
     Sensitivity analysis (COSTpurchase)



     COSTpurchase          SI 2010   SI 2020   SI 2030   STI 2010   STI 2020   STI 2030
     uparaBT                0.05      0.01      0.01       0.17       0.05       0.05
     eRPCSBASE              0.59      0.85      0.85       0.73       0.91       0.91
     usresidualparaAB       0.16      0.04      0.04       0.28       0.09       0.09
     eEF                    0.01      0.00      0.00       0.13       0.04       0.04
     eEFratio               0.01      0.00      0.00       0.11       0.03       0.03
     ltrip                  0.01      0.00      0.00       0.12       0.04       0.04
     eRREPMAINTCFRACTION    0.01      0.00      0.00       0.11       0.04       0.04
     RINSCFRACTION          0.01      0.00      0.00       0.13       0.04       0.04
     RLABOURC               0.01      0.00      0.00       0.10       0.03       0.03
     RLABOURTX              0.01      0.00      0.00       0.12       0.04       0.04
     ROWNTX                 0.01      0.00      0.00       0.13       0.04       0.04
     PUBLICCOSTCOV          0.01      0.00      0.00       0.11       0.04       0.04
     eEFfc                  0.08      0.02      0.02       0.19       0.06       0.05
     eEFfcratio             0.02      0.00      0.00       0.17       0.05       0.05
     SUM                    0.97      0.95      0.95




25
     Sensitivity analysis (NOx)


     NOx                   SI 2010   SI 2020   SI 2030   STI 2010   STI 2020   STI 2030
     uparaBT                0.00      0.01      0.00       0.02       0.02       0.02
     eRPCSBASE              0.00      0.02      0.01       0.02       0.04       0.03
     usresidualparaAB       0.00      0.00      0.00       0.02       0.02       0.02
     eEF                    0.94      0.91      0.92       0.98       0.96       0.97
     eEFratio               0.01      0.01      0.01       0.04       0.04       0.03
     ltrip                  0.00      0.00      0.00       0.02       0.03       0.03
     eRREPMAINTCFRACTION    0.00      0.00      0.00       0.02       0.03       0.03
     RINSCFRACTION          0.00      0.00      0.00       0.03       0.03       0.03
     RLABOURC               0.00      0.00      0.00       0.02       0.03       0.03
     RLABOURTX              0.00      0.00      0.00       0.02       0.02       0.03
     ROWNTX                 0.00      0.00      0.00       0.03       0.03       0.03
     PUBLICCOSTCOV          0.00      0.00      0.00       0.02       0.03       0.03
     eEFfc                  0.00      0.00      0.00       0.02       0.03       0.03
     eEFfcratio             0.00      0.00      0.00       0.02       0.03       0.03
     SUM                    0.96      0.95      0.95




26
     Sensitivity analysis (Population of vehicles)


     Vehicles              SI 2010   SI 2020   SI 2030   STI 2010   STI 2020   STI 2030
     uparaBT                0.01      0.00      0.00       0.04       0.02       0.02
     eRPCSBASE              0.28      0.65      0.64       0.33       0.69       0.68
     usresidualparaAB       0.05      0.02      0.02       0.11       0.04       0.04
     eEF                    0.00      0.00      0.00       0.03       0.02       0.02
     eEFratio               0.00      0.00      0.00       0.05       0.02       0.02
     ltrip                  0.01      0.00      0.00       0.05       0.02       0.02
     eRREPMAINTCFRACTION    0.04      0.07      0.07       0.10       0.09       0.09
     RINSCFRACTION          0.01      0.01      0.01       0.04       0.03       0.03
     RLABOURC               0.00      0.00      0.00       0.07       0.03       0.03
     RLABOURTX              0.00      0.00      0.00       0.04       0.02       0.02
     ROWNTX                 0.00      0.00      0.00       0.05       0.03       0.03
     PUBLICCOSTCOV          0.00      0.00      0.00       0.05       0.02       0.02
     eEFfc                  0.45      0.12      0.12       0.50       0.14       0.14
     eEFfcratio             0.03      0.01      0.01       0.06       0.02       0.03
     SUM                    0.89      0.88      0.88




27
     Scenario 1 : Ownership tax increase
        Ownership tax (ROWNTX) of passenger cars will triple in the year
        2030
        Linear evolution from 2010 to 2030
        Proportionality in uncertainty ranges

                           600

                                    C ar 1.4-2.0l - Petrol
                           500


                           400
               Euro/Year




                           300


                           200

                                              ROWNTX - Scenario
                           100
                                              ROWNTX - Baseline
                             0
                             2000    2005      2010          2015   2020   2025   2030
                                                             Year




28
     Scenario 1: results

      Variables for which statistically significant differences in the output
         values exist are:
      - TAXownership: all years after 2011
      - PM: all years after 2019
      - Costs: all years after 2020
      - Vehicles, Vehkms: all years after 2022
      - NOx: all years after 2025




29
     Scenario 1: results


       TAXownership                            NOx
                      2020       2030                     2020          2030
           [M€]                               [Ton]
     Baseline          11,345     12,513    Baseline        204,279       179,722
     Scenario 1        14,093     22,374    Scenario 1      204,028       178,827
     % diff              24.2       78.8    % diff              -0.1          -0.5
           Costs                             Vehicles
                      2020       2030                     2020          2030
           [M€]                                [#]
     Baseline         375,041    434,464    Baseline     37,434,661    40,543,655
     Scenario 1       377,300    440,861    Scenario 1   37,304,467    40,174,123
     % diff               0.6        1.5    % diff              -0.3          -0.9
            PM                              Vehicle km
                      2020       2030                     2020          2030
           [Ton]                            [×106 km]
     Baseline           4,128      4,068    Baseline        657,732       712,662
     Scenario 1         4,118      4,038    Scenario 1      655,415       706,393
     % diff               -0.2       -0.8   % diff              -0.4          -0.9




30
     Scenario 1: results

                        650                CAR                                                        7,0                2W
                        625                                                                           6,8
                                                                                                      6,6
                        600
                                                                                                      6,4
                        575                                                                           6,2




                                                                                      VKM (Billion)
       VKM (Billion)




                        550                                                                           6,0
                        525                                                                           5,8
                        500                                                                           5,6
                                                                                                      5,4
                        475
                                                                                                      5,2
                        450                                                                           5,0
                          2005   2010   2015    2020   2025   2030                                      2005   2010   2015     2020   2025   2030
                                               Year                                                                          Year

                        39 000             C AR                                               1       350,0           2W
                        37 000                                                                1       300,0
                                                                                              1       250,0
                        35 000
                                                                                              1       200,0
       POP (Thousand)




                                                                     POP (Thousand)

                        33 000                                                                1       150,0
                        31 000                                                                1 100,0
                                                                                              1 050,0
                        29 000
                                                                                              1 000,0
                        27 000
                                                                                                950,0
                        25 000                                                                  900,0
                             2005 2010 2015 2020 2025 2030                                          2005 2010 2015 2020 2025 2030
                                                Year                                                              Year



31
     Scenario 1: conclusions
     Marginal impact to the output variables with the exception of the
     ownership cost
     Median values between the baseline and the scenario differ maximum
     by 1.5% in 2030 in the case of total road transport costs. All other
     activity and emission data differ by less than 1%.
     the sensitivity analysis results to identical effect of each input variable
     uncertainty to the output variables.
     Activity shifts within the road sector, i.e. shift of the passenger transport
     to either busses or power two wheelers could not be observed.
     Overall, increasing the cost of passenger car ownership leads only to a
     marginal (1%) decrease of activity in the road transport sector which
     comes solely from an identical decrease in the passenger car activity.




32
     Scenario 2 : Fuel cost estimation uncertainty
                     • Uncertainty of the fuel price (barrel) is assumed to be significantly higher after
                       the historic years (3s=+-30% of the default value)

                    0,7   UK prices                                            0,9   UK prices
                    0,6                                                        0,8
                                                                               0,7
                    0,5
                                                                               0,6
       Euro/Litre




                                                                  Euro/Litre
                    0,4                                                        0,5
                    0,3                                                        0,4
                                                       Gasoline                0,3                                Diesel
                    0,2
                                                       +3s Gas                 0,2                                +3s Dies
                    0,1                                                        0,1
                                                       -3s Gas                                                    -3s Dies
                    0,0                                                        0,0
                      1995        2005          2015     2025                    1995        2005          2015     2025
                    0,0 UK prices            Year                              0,3 UK prices            Year
                    0,0
                    0,0                                                        0,2
                    0,0
       Euro/Litre




                                                                  Euro/Litre
                                                                               0,2
                    0,0
                    0,0
                                                                               0,1
                    0,0                                CNG                                                        LPG
                    0,0                                +3s CNG                 0,1                                +3s LPG
                    0,0                                -3s CNG                                                    -3s LPG
                    0,0                                                        0,0
                      1995            2005      2015     2025                    1995            2005      2015     2025
                                             Year                                                       Year




33
     Scenario 2: results

      Variables for which statistically significant differences in the output
         values exist are:

      –   COSTfuel: all years after 2010
      –   TAXfuel: all years after 2010
      –   VATfuel: all years after 2010
      –   PM: all years after 2019
      –   NOx: all years after 2027




34
     Scenario 2: confidence intervals


        COSTfuel                           NOx
                   2020      2030                     2020        2030
          [M€]                            [Ton]
      Baseline      12,602    15,889   Baseline       120,351      93,729
      Scenario 2    21,330    26,646   Scenario 2     118,573      94,836
           PM                            Vehicles
                   2020      2030                     2020        2030
          [Ton]                            [#]
      Baseline       4,264     4,175   Baseline      3,581,258   3,989,700
      Scenario 2     4,260     4,175   Scenario 2    3,642,697   4,077,402
          Costs                         Vehicle km
                   2020      2030                     2020        2030
          [M€]                          [×106 km]
      Baseline      53,492    61,795   Baseline        61,183      68,251
      Scenario 2    55,881    65,938   Scenario 2      62,117      69,646




35
               Scenario 2: effect on non road (pkm)



                   140 000         M E D_BC
                                                AIR                               90 000      TRAIN
                                   P E RC _05
                   135 000         P E RC _95                                     85 000
                                   M E D_S 2
                   130 000
                                   P E RC _05
     Million pkm




                                                                                  80 000




                                                                    Million pkm
                   125 000         P E RC _95

                   120 000                                                        75 000
                   115 000
                                                                                  70 000
                   110 000
                                                                                  65 000
                   105 000
                   100 000                                                        60 000
                         2005   2010   2015 2020      2025   2030                      2005    2010   2015 2020   2025   2030
                                          Year                                                           Year




36
     Scenario 2: conclusions

     Impacts only the relevant cost output variables and PM and NOx in a statistically
     significant manner
     Confidence intervals for the output significantly increase only for the fuel
     components and for total cost. The confidence intervals for all other variables
     were only marginally affected
     Due to the small relative effect, the sensitivity analysis produces identical results
     between the baseline and the scenario, i.e. the output depends on the
     uncertainty of the input variables in the same fashion as in the baseline.
     Even such a large uncertainty for the road fuel cost, does not drive more activity
     to other modes of transport (1.5% max change in CI for aviation and rail)




37
     Scenario 3: HDV Euro VI
        • New technology (EURO VI) introduced in 2013 for HDVs and Buses
        • Additional purchase cost (Euro/veh)
                                Vehicle class           Min            Max
                                <7,5 t                  2.855,0        3.553,0
                                7,5 - 16 t              3.287,0        4.084,0
                                16 - 32 t               4.185,0        5.198,0
                                >32 t                   4.651,0        5.780,0
                                Diesel busses           4.185,0        5.198,0

        • Additional maintenance cost (urea cost-Euro/km)
                      AdBlue cost        HTD1          HTD2           HTD3       HTD4            BUS
                       euro /litre       0,009         0,0075        0,00675     0,006          0,006


        • Emission limits (HC, NOx, PM)
                          Limit values           CO          HC            NOx            PM
                        Euro V                   1,5        0,46            2            0,02
                        Euro VI                  1,5        0,13           0,4           0,01
                        % Reduction              0              72         80            50


        • Small increase in fuel consumption (0.5-2% relative to EURO V)




38
     Scenario 3: results


      Variables for which statistically significant differences in the
        output values exist are:
      – PM: all years after 2016
      – NOx: all years after 2016




39
     Scenario 3: results
           COSTpurchase                            VOC
                          2020       2030                     2020         2030
              [M€]                                [Ton]
         Baseline         105,591    121,983   Baseline         29,874       31,501
         Scenario 3       105,722    122,287   Scenario 3       29,821       31,508
         % diff               0.1        0.2   % diff             -0.2          0.0
             COSTrepair                         Fuel cons.
                          2020       2030                     2020         2030
                [M€]                              [Ton]
         Baseline          77,360     90,137   Baseline         52,179       56,217
         Scenario 3        77,449     90,317   Scenario 3       52,221       56,229
         % diff               0.1        0.2   % diff              0.1          0.0
                Costs                            Vehicles
                          2020       2030                     2020         2030
              [milEuro]                            [#]
         Baseline         375,041    434,465   Baseline      37,434,661   40,543,655
         Scenario 3       375,216    434,914   Scenario 3    37,433,657   40,541,438
         % diff               0.0        0.1   % diff               0.0          0.0
                  PM                            Vehicle km
                          2020       2030                     2020         2030
                [Ton]                           [×106 km]
         Baseline           4,128      4,068   Baseline       657,732.0     712,663
         Scenario 3         3,594      3,364   Scenario 3     657,673.0     712,541
         % diff             -12.9      -17.3   % diff               0.0         0.0
                 NOx
                          2020       2030
                [Ton]
         Baseline         204,280    179,722
         Scenario 3       189,119    160,714
         % diff               -7.4     -10.6




40
     Scenario 3: results




                           Red: baseline
                           Blue: scenario




41
     Scenario 3: conclusions


     The effect of the introduction was only shown for PM and
     NOx and for no other output variable

     The contribution of input variables to the uncertainty of the
     scenario is identical to the baseline as the relative variance
     of the Euro VI emission factors has been assumed the same
     as Euro V.




42
     Recommendations (1/2)
      The total uncertainty of the projection, taking into account
      macroeconomic and demographic factors may be realistically assessed
      by introducing alternative basecases in the model. This can be a useful
      future activity.

      A limited number of input variables (14) seems to drive the total model
      uncertainty. In addition, several output variables can be approached as
      linear combinations of input variables with a small loss of precision.
      These effects are driven by the rather limited elasticity in shifts
      between different modes of transport and vehicle types offered by the
      demand module. If this limited flexibility is validated, then it can be
      suggested that several model operations can be simplified with a
      benefit in model transparency and processing time.




43
     Recommendations (2/2)
      Our analysis only took into account the variables and parameters
      inclusive in the model. Expanding the model to cover additional vehicle
      types, such as alternative fuel vehicles, hybrids, plug in hybrids, and
      electric vehicles may increase uncertainty of the estimates but is
      rendered necessary to cover future applications of the model.

      The fact that a rather limited number of variables is important for most
      of the model output uncertainty means that better quality / more
      precision in the estimates of these variables will reduce the uncertainty
      of the output. Of particular importance appear to be the emission
      factors, the purchase cost of vehicles, the parameters defining the
      scrappage probability, the parameters used to estimate the residual
      cost when a vehicle is scrapped and cost-related parameters
      (maintenance, insurance, ownership, labour).



44
     Thank you!




45

				
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