ANALYSIS OF LAND USE AND MOBILITY SCENARIOS FOR THE REDUCTION OF TRANSPORT ENERGY IN THE URBAN AREA OF CATANIA

Transcription

1 ANALYSIS OF LAND USE AND MOBILITY SCENARIOS FOR THE REDUCTION OF TRANSPORT ENERGY IN THE URBAN AREA OF CATANIA Giuseppe Inturri*, Matteo Ignaccolo*, Michela Le Pira*, Valentina Mancuso, Salvatore Caprì* University of Catania, Department of Civil Engineering and Architecture *AIIT member Italian Association for Traffic and Transport Engineering

2 Research objectives Highlight the impact of transport on energy sustainability of urban areas Set up a methodology to calculate a transport energy indicator to support the delivery of sustainable land use and delivery of land use and transport urban plans Test the methodology in a case study 3

3 Transport Energy impacts 1/3 of energy 70% of oil 25% of CO2 emissions 2.5% average rate growth EU Energy and Transport in Figures St atistical Pocket book

4 Transport Energy Efficiency 100% Fuel Standby 17 % Engine Engine losses 63% Accessories 2 % 18% Driveline losses 5% 13% Aero 3% Rolling 4% Braking 6% EU Energy and Transport in Figures St atistical Pocket book 2010 INTRINSIC ENERGY INEFFICIENCY OF CARS less than 2% of consumed energy is used by the payload 5

5 Urban Energy Demand ENERGY (KWH/PERSON/YEAR) 2000; HEATING METRO 5% MODAL SHIFT W/C 15% 6083; TRANSPORT 1333; ELECTRICITY LRT 10% BUS 10% CAR 60% km/pers/year 100 kwh/year/mq (including cooling and lighting) Waste management and urban deliveries not included 6

6 How to reduce urban transport energy demand Land Use Efficiency Vehicle Efficiency Land Use E t kwh Persons pax Dis tan ce km Vehicle _ unit _ consumption Vehicle _ capacity kwh / km pax Load _ factor % Spatial Interactions Transportation Network Transport System Efficiency 7

7 Efficienza Energe,ca Globale RIDURRE Efficienza del territorio kwh = veic pax ( pax km) CAMBIARE Efficienza dei traspor, kwh veic km MIGLIORARE Efficienza dei veicoli Integrare uso del territorio traspor, Smart Growth Transit Oriented Development (pax- km) Favorire l uso dei modi di trasporto a basso impabo e consumo unitario (veic/pax) Tecnologie per ridurre l energia per km (TTW) e usare carburan, puli, (WTT) kwh/km Pianificazione territoriale kwh = Pianificazione dei traspor, ineff _ trasporto ( trasporto) ( ) ( consumo_ ) Innovazione tecnologica veic

8 Urban density and transport energy Hong Kong Houston 9

9 Average Density vs Spatial Dynamics Radial monocentric Random polycentric Urban village polycentric Random and radial mono-polycentric 10

10 Land Use- Transport Energy model P L A N N I N G S C E N A R I O -Zoning -Residents by zone -Activities by zone -Demand flows -Road network -Pedestrian netw. -Cycling Network -Transit network -Vehicle by fuel type -Vehicle Energy Eff. LAND USE MODEL TRANSPORT MODEL ENERGY MODEL Land Use Spatial Interactions -Min distance by mode -Transit network density by zone -Travel behaviour criteria TED<TED* NO YES IMPLEMENT SCENARIO MODE CHOICE MODEL Transportation Network OPTIMAL DISTRIBUTION ASSIGNMENT TRANSPORT ENERGY DEPENDENCE (TED) 12

11 Transport mode choice model dod=shortest path dod < dw yes walking distance TRANSIT DENSITY THRESHOLD no dod < dc transit stop density > threshold no yes yes cycling distance transit distance car distance BUS 6.67 Km/km 2 LRT 3.30 Km/km 2 METRO 2.50 Km/km 2 Choice Distance WALKING <500m dod CYCLING <1000m dod BUS < m Stop access/egress LRT < m Stop access/egress METRO < m Stop access/egress 13

12 Optimal demand flows assignment min m Z c ij x n i 1 j 1 ij n xij j 1 s i m xij i 1 d j x ij 0 14

13 Transport Energy Dependence X ij opt c ij TED s = o t od l od d e v c v LF v t od number of trips assigned from zone o to zone d to minimize Z (passengers) l od shortest distance between zone o and zone d (km) e v unit energy consumption of the chosen transport mode (kwh/km) c v capacity of the vehicle (spaces) LF v load factor (passengers/spaces) Mode of transport Unit energy consumption kwh/pax-km Private Car Regular Bus Transit Bus Rapid Transit Metro Transit Kenworthy (2003) 15

14 Optimal demand flows assignment (n zones) dod=shortest path no dod < dw dod < dc yes yes walking distance cycling distance nxn matrices Distance matrix [km] l od Energy matrix [kwh/pax] e v l od c v LF v Flow matrix [pass] [pax]? t od transit stop density > threshold no yes transit distance car distance Total energy [kwh]= flow matrix*energy matrix [pax*kwh/pax] TED s = o t od l od d e v c v LF v min(total energy) 16

15 Case Study - Catania inh. municipality inh. urban area 17

16 population jobs

17 Private transport demand Public transport demand

18 Car per 100 inh. Car ownership rate (cars per 100 inh.) Car ownership tasso di motorizzazione rate of Italian aree metropolitane di areas Italia autovetture per 100 abitanti 75,00 70,00 65,00 60,00 55,00 50,00 Genova Trieste Bologna Firenze Milano Bari Napoli Reggio Calabria Palermo Torino Cagliari Messina Catania Roma Media Italia Europa 45,00 Venezia 40,00

19 Ingoing flows veh/h 50% of internal flow Peak hour traffic flow Road capacity saturation

20 Catania Transport Model Transport demand: commuting flows (5 home-to-work trips/week) Transport supply: - the road network, composed of 516 nodes and 1122 links; - the transit network considers 49 bus lines, 4 BRT lines and 1 metro line. PTV VISUM software package: shortest paths by mode between all origin and destination pairs by all modes of transport (criterion: time) option of transit intermodality Shortest path by car Shortest path by transit 25

21 Scenarios Scenario 0 Scenario 2: Introducing 4 BRT lines and 1 Metro line Transit network Road network Scenario 1: improving PT accessibility Density threshold: 5km/km PT-covered-zones Scenario 3: Transit Oriented Development relocating a fraction (10%) of residents around the stations of the metro line 26

22 kwh/employee/year pax-km per year Milioni Results Transport Energy Dependence Travelled distance by mode 896,13 747,16 679,69 653,23 Sc. 0 Sc. 1 Sc. 2 Sc. 3 Scenarios 100,00 90,00 80,00 70,00 60,00 50,00 40,00 30,00 20,00 10,00 0,00 Sc.0 Sc.1 Sc.2 Sc.3 WALKING AND CYCLING METRO BRT BUS CAR Scenarios 28

23 kwh/pax-km Results 0,90 0,80 0,70 0,60 0,50 0,40 0,30 0,20 0,10 0,00 Transport Energy Efficiency Sc. 0 Sc. 1 Sc. 2 Sc. 3 Mode of transport Unit energy consumption kwh/pax-km Private Car Regular Bus Transit Bus Rapid Transit Metro Transit

24 Transport Energy Dependence by zone TED (kwh/pers/year) JOBS/WORKERS Jobs/Workers balance reduces the Transport Energy dependence 30

25 Conclusions 31

26 ACKNOWLEDGMENTS Contact: 32