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Impact of Transportation Demand Impact of Transportation Demand Management Policies on Green Management Policies on Green
House Gas Emissions: House Gas Emissions: A Modeling ApproachA Modeling Approach
Wu SunWu SunJoaquin OrtegaJoaquin Ortega
Rick CurryRick CurrySan Diego Association of GovernmentsSan Diego Association of Governments
May 18May 18thth, 2009, 20091212thth TRB Transportation Planning Application Conference TRB Transportation Planning Application Conference
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IntroductionIntroductionEnergy and climate change are on top of federal, state and local Energy and climate change are on top of federal, state and local government’s political and economic agendagovernment’s political and economic agenda
California Global Warming Solutions Act of 2006 (AB 32): reduce California Global Warming Solutions Act of 2006 (AB 32): reduce greenhouse gas (GHG) emissions to 1990 levels by 2020.greenhouse gas (GHG) emissions to 1990 levels by 2020.
California Senate Bill 375: Air Resources Board (ARB) will establish California Senate Bill 375: Air Resources Board (ARB) will establish mandatory reduction targets for GHG emissions from passenger cars and mandatory reduction targets for GHG emissions from passenger cars and light-trucks for years 2020 and 2035.light-trucks for years 2020 and 2035.
California Assembly Bill 1493: enforced California vehicle emission California Assembly Bill 1493: enforced California vehicle emission standards, allows California to enact and enforce emission standards to standards, allows California to enact and enforce emission standards to reduce GHG emissions.reduce GHG emissions.
Low Carbon Fuel Standard (LCFS): requires fuel providers to reduce the Low Carbon Fuel Standard (LCFS): requires fuel providers to reduce the carbon intensity of transportation fuels sold in the state by 10% by 2020 carbon intensity of transportation fuels sold in the state by 10% by 2020
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Introduction (Continued)Introduction (Continued)
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Introduction (Continued)Introduction (Continued)
San Diego County emitted 34 MMT of CO2 in San Diego County emitted 34 MMT of CO2 in 2006, compared with 29 MMT in 1990, an 18% 2006, compared with 29 MMT in 1990, an 18% increase over 1990 levelsincrease over 1990 levels
By 2020, under a business-as-usual scenario, By 2020, under a business-as-usual scenario, regional GHG emissions are expected to be 43 regional GHG emissions are expected to be 43 MMT CO2.MMT CO2.
In 2006, emissions from transportation sector In 2006, emissions from transportation sector represented 46% of total GHG emissions in San represented 46% of total GHG emissions in San Diego County.Diego County.
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Introduction (Continued)Introduction (Continued)
.Rail, 1%
Waste, 2%
Off-Road Equipment and Vehicels, 4%
Other Fuels/Other, 4%
Industrial Processes and Products, 5%
Civil Aviation, 5%
Natural Gas End Uses, 9%
Electricity, 25%
On-Road Transportation, 46%
Agriculture/Forestry/Land Use, 2%
Water-Borne Navigation, 0.40%
.
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SANDAG Travel Forecasting ModelSANDAG Travel Forecasting Model
4-step model4-step model 4605 zones4605 zones 3 time of day periods3 time of day periods 10 trip purposes10 trip purposes nested mode choice structurenested mode choice structure trip generation depends on land use inputs trip generation depends on land use inputs TransCAD platformTransCAD platform
Activity-based model (ABM)Activity-based model (ABM) DisaggregateDisaggregate Behaviorally realisticBehaviorally realistic Household socio-demographic attributesHousehold socio-demographic attributes
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Emission Inventories Calculation Emission Inventories Calculation for Vehiclesfor Vehicles
Emfac2007: the latest emission inventory model Emfac2007: the latest emission inventory model developed by the California Air Resources Board developed by the California Air Resources Board (CARB)(CARB)
SANDAG 4-step model produce an input file to SANDAG 4-step model produce an input file to Emfac2007Emfac2007
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Modeled GHG Reduction Modeled GHG Reduction StrategiesStrategies
Low Carbon Land Use GrowthLow Carbon Land Use Growth
Enhanced Transit NetworkEnhanced Transit Network
Transportation Demand ManagementTransportation Demand Management
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Modeled GHG Reduction 2030 Modeled GHG Reduction 2030 ScenariosScenarios
Existing Regional Policy (Baseline)Existing Regional Policy (Baseline)
Low Carbon Land UseLow Carbon Land Use
Enhanced TransitEnhanced Transit
Low Carbon Land Use with Enhanced TransitLow Carbon Land Use with Enhanced Transit
Individually test the 4 separate TDM Individually test the 4 separate TDM componentscomponents
Low Carbon Land Use, Enhanced Transit, and Low Carbon Land Use, Enhanced Transit, and all TDM components combined.all TDM components combined.
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Low Carbon Land Use GrowthLow Carbon Land Use Growth
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San Diego Region Transportation San Diego Region Transportation Emission TargetsEmission Targets
Through the SB 375 process, ARB will establish Through the SB 375 process, ARB will establish mandatory reduction targets for GHG emissions mandatory reduction targets for GHG emissions from passenger cars and light-trucks for years from passenger cars and light-trucks for years 2020 and 2035.2020 and 2035.
Estimated targets for modeling purposes:Estimated targets for modeling purposes: 1990: 12.5 MMT CO21990: 12.5 MMT CO2 2020 Target: 12.5 MMT CO22020 Target: 12.5 MMT CO2 2050 Target: 2.5 MMT CO22050 Target: 2.5 MMT CO2 Interpolated 2030 Target: 9.13 MMT CO2Interpolated 2030 Target: 9.13 MMT CO2 2030 Business-as Usual: 19.9 MMT CO22030 Business-as Usual: 19.9 MMT CO2
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Transportation Demand Transportation Demand Management (TDM) AssumptionsManagement (TDM) AssumptionsTelecommuting Increase Telecommuting Increase
Two rates tested: 20% & 40% rate among telecommutable jobs.Two rates tested: 20% & 40% rate among telecommutable jobs.
Increase Auto Operating Costs (VMT fee)Increase Auto Operating Costs (VMT fee)
Two rates tested: 1.2¢ per mile & 4.72¢ per mileTwo rates tested: 1.2¢ per mile & 4.72¢ per mile
5555MPHMPH Freeway Speed Limit Freeway Speed Limit
Increase In Parking CostsIncrease In Parking Costs
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Modeling ApproachModeling Approach
Objective: modify 4-step model to evaluate impact of Objective: modify 4-step model to evaluate impact of land use, network, and TDM policies. land use, network, and TDM policies. Trip generationTrip generation
Low carbon land use growthLow carbon land use growth TelecommutingTelecommuting
Trip distributionTrip distribution Parking pricing: destination zone parking rateParking pricing: destination zone parking rate Reduced speed limitReduced speed limit
Mode choiceMode choice Goal: shift trips from auto modes to transit modesGoal: shift trips from auto modes to transit modes Mode choice structureMode choice structure Auto mode utility function Auto mode utility function
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Mode Choice StructureMode Choice StructureTotal Trips
AutoNon-
MotorizedTransit
Drive Alone Shared-Ride Bicycle
PedestrianNon-Toll
Toll
2 Person
Non-Toll/Non-HOV
Non-Toll/HOV
Toll/HOV
3+ Person
Non-Toll/Non-HOV
Non-Toll/HOV
Toll/HOV
Walk Drive Drop-OFF
Local Bus
Express Bus
BRT
Local Bus
Express Bus
BRT
Local Bus
Express Bus
BRT
Light Rail
Commuter Rail
Light Rail
Commuter Rail
Light Rail
Commuter Rail
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Auto Mode Utility FunctionAuto Mode Utility Function
where:where: m=modem=mode p=trip purposep=trip purpose i=income groupi=income group t=time periodt=time period auu = auto utility by mode, prupose, and income groupauu = auto utility by mode, prupose, and income group auivt = auto in-vehicle travel time between zones by mode and time periodauivt = auto in-vehicle travel time between zones by mode and time period tcoef = time coefficient by type, purpose and income grouptcoef = time coefficient by type, purpose and income group termp = terminal time at production endtermp = terminal time at production end terma = terminal time at attraction endterma = terminal time at attraction end pcost = parking cost at attraction end by purposepcost = parking cost at attraction end by purpose toll = toll facility cost by mode and time periodtoll = toll facility cost by mode and time period audist = auto distance between zones by mode and time periodaudist = auto distance between zones by mode and time period ccoef= cost coefficient by purpose and income groupccoef= cost coefficient by purpose and income group cpm = cost per mile to operate an automobilecpm = cost per mile to operate an automobile nclow = nesting coefficient at lowest level of nest (0.55)nclow = nesting coefficient at lowest level of nest (0.55) ncmid = nesting coefficient at middle level of nest (0.65)ncmid = nesting coefficient at middle level of nest (0.65) nctop = nesting coefficient at top level of nest (0.85)nctop = nesting coefficient at top level of nest (0.85)
nctopncmidnclowipccoefcpmjziztmaudistjziztmtolljzptp
iptcoefjztermaiztermpiptcoefjziztmauivtipmauu
/)),(**),,,(),,,(),(cos
),,2()()(),,1(),,,((),,(
In vehicle time Terminal timeCost termParking cost Auto operating cost
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Adjustment to Auto Utility FunctionsAdjustment to Auto Utility Functions
Adjust auto operating costs via VMT fee.Adjust auto operating costs via VMT fee.
Adjust parking costs at attraction endsAdjust parking costs at attraction ends
Rates were increased in CBD, Urban Rates were increased in CBD, Urban Centers, Town Centers, and Community Centers, Town Centers, and Community Centers. Rural and suburban rates were Centers. Rural and suburban rates were unchanged.unchanged.
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Parking PricingParking Pricing
Place TypePlace Type Parking Parking TypeType
Parking Price Increase Parking Price Increase ($/hr)($/hr)
Metropolitan CenterMetropolitan Center 55 22
Urban CenterUrban Center 44 1.51.5
Town CenterTown Center 33 1.51.5
Community CenterCommunity Center 22 11
Rural VillageRural Village 11 00
Special Use CenterSpecial Use Center 33 1.51.5
Mixed-Use Transit Mixed-Use Transit CenterCenter
22 1.51.5
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94
98
102
106
110
Tren
d (bas
eline)
Enha
nced
Trans
it Ne
twor
k
55 M
PH Spe
ed Li
mit
VMT Fe
e (4.72
¢)
Increa
sed Pa
rking Fe
es
Low Carbo
n La
nd U
se G
rowth
Increa
sed Te
leco
mmut
ing (40%
)
LCFS
(10%
)
AB14
93
LCFS
(20%
)15
16
17
18
19
20
Initial ResultsInitial ResultsIndividual Component TestsIndividual Component Tests
Daily VMT(thousands)
Annual CO2Emissions
(MMT)
Network CostsTrip
Generation Post Processes
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Initial ResultsInitial Results
ScenarioScenarioAnnual COAnnual CO2 2
Emissions (MMT)Emissions (MMT)
2030 Estimated Target2030 Estimated Target 9.139.13
2030 Trend (Baseline)2030 Trend (Baseline) 19.8519.85
Low Carbon Land Use withLow Carbon Land Use withEnhanced Transit NetworkEnhanced Transit Network 19.2719.27
Low Carbon Land Use withLow Carbon Land Use withEnhanced Transit Network andEnhanced Transit Network andAll TDM measuresAll TDM measures
18.4818.48
Low Carbon LU, Enhanced Transit, All Low Carbon LU, Enhanced Transit, All TDM measures, with AB1493 and TDM measures, with AB1493 and LCFS 20% post processingLCFS 20% post processing
12.2212.22
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Summary Summary
Energy and climate change are on top of Energy and climate change are on top of federal, state and local government’s political federal, state and local government’s political and economic agendaand economic agendaTransportation sector is the largest source of Transportation sector is the largest source of GHG emissions.GHG emissions.Travel forecasting models play important roles in Travel forecasting models play important roles in forecasting GHG emissions.forecasting GHG emissions.TDMs, smart growth land use, and enhanced TDMs, smart growth land use, and enhanced transit network works together to reduce GHG transit network works together to reduce GHG emissions emissions Use disaggregate models, such as ABMs, for Use disaggregate models, such as ABMs, for similar analysissimilar analysis
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San Diego FactsSan Diego Facts
Jurisdiction FactsJurisdiction Facts 2,727,030 acres2,727,030 acres 4,261.0 square miles4,261.0 square miles
PopulationPopulation 2008: 3,146,2742008: 3,146,274 2030: 3,984,7532030: 3,984,753
Median Household IncomeMedian Household Income 2007: $68,388 (current dollars)2007: $68,388 (current dollars)
Housing CharacteristicsHousing Characteristics Total Housing Units: 1,140,349Total Housing Units: 1,140,349 Occupied Housing Units: 1,089,451Occupied Housing Units: 1,089,451
2030 Regional Growth Forecast2030 Regional Growth Forecast Total Population: 3,984,753Total Population: 3,984,753 Housing Units: 1,383,803Housing Units: 1,383,803 Civilian Employment: 1,828,612Civilian Employment: 1,828,612