Planning with technologies

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1 Metropolitan Solutions 2016 Savvas Verdis / Katrin Mueller Planning with technologies Unrestricted Answers for infrastructure and cities.

2 Siemens Sustainable Cities Initiative Why the Crystal? A sustainable cities initiative by Siemens. Supporting long term cooperation with cities for infrastructure solutions A platform for global collaboration amongst key players in urban sustainability A centre to discuss and learn about the challenges cities are facing and possible solutions to reduce their environmental impact. Home for thought leadership on urban sustainability providing experts to exchange ideas.

3 Case studies

4 How do the same technologies perform differently from city to city?

5 ISTANBUL BOGOTA

7 Cities are unique and technologies should be tailored

8 Cities are unique in emissions and its root causes

Step 1: Develop a baseline with over 300 data points General 5 data points Population City population, density and growth Emission targets Targets for CO 2, NO x and PM 10 Energy 50+ data points

9 Step 1: Develop a baseline with over 300 data points General 5 data points Population City population, density and growth Emission targets Targets for CO 2, NO x and PM 10 Energy 50+ data points Consumption City`s annual energy consumption from electricity, heating and cooling. Source mix City`s consumption source mix for electricity, heating and cooling. Grid losses City`s transmission and distribution losses per KW generated power. Transport 120+ data points Passenger Annual passenger kilometer travelled inside the city borders and the split between travel modes. Freight Ton kilometers of goods transported within the city borders annually, with split between road and rail. Public transport service Length of network, number of vehicles and capacity utilization for passenger transport modes. Vehicles and fuel source Private vehicles, taxis and trucks fleet distribution. Roads and infrastructure Road network, traffic management and streetlights Buildings 80+* data points Floor space City`s total floor space, per building category. Electricity usage The share of electricity split between lighting, ventilation appliances, per building category. Building envelope The share of losses from heating and cooling building space, per building category. *per building category: Residential, non-residential

10 Step 1: GHG Emissions Baseline of a City

11 Step 2: Choose from over 70 technologies Buildings Building envelope Building automation Monitoring and optimization Public transport Private transport Traffic management Freight Transport 70+ technologies Energy Renewable generation Combined Heat and Power Grid management

12 Step 2: Choose from Building Levers Commercial buildings Residential buildings 17 levers 6 levers Commercial Wall Insulation Commercial Double/Triple Glazing Efficient Motors & Drives Room Automation, HVAC Residential Wall Insulation Residential Double/Triple Glazing Commercial Efficient Lighting Demand Oriented Lighting Building Efficiency Monitoring Room Automation, HVAC & Lighting 80 by 2050 Residential Building Envelope Room Automation, HVAC & Lighting + Blinds Residential Efficient Lighting Building Automation, BACS C Home Energy Monitoring Building Performance Optimization Demand Controlled Ventilation Heat Recovery Commercial Building Envelope Remote Monitoring Building Automation, BACS B Building Automation, BACS A Home Automation

13 Step 2: Choose from Transportation Levers Transport 38 levers Metro: New Vehicles Metro: New Line Freight Tram Freight Rail-Electrification Metro: Reduced Headway BRT Electrification Switch to electric vehicles Metro: Automated Train Operation GNG Bus GNG Car Metro: Regenerative Braking E-Bus E-Car Regional Train: Automated Train Operation Hybrid Electric Bus Hydrogen Car Tram: New Line E-Taxi Plug-in Hybrid Car Tram: New Vehicles E-BRT New Line Hybrid Car Demand Oriented Street Lighting LED Street Lighting Smart Street Lighting 80 by 2050 Intelligent Traffic Light Management Intermodal Traffic Management Low Emission Zone (Truck) Eco Driving Training Urban Bike Sharing Tram: Automated Train Operation E-Ticketing E-Car Sharing Cycling Highway Tram: Regenerative Braking E-Highways Occupancy Dependent Tolling City Tolling

14 Step 2: Choose from Energy Levers Photovoltaic Energy 10 levers Wind Power Generation Combined Cycle Gas Turbine Combined Heat and Power Network Optimization Smart Grid for Monitoring and Automation Power System Automation & Optimized Network Smart Metering On Shore Power Supply in Harbors

15 Impact of replacing 20% of car fleet with electric cars

16 Impact of replacing 20% of car fleet with electric cars [Kg CO 2 e / capita] Kg and % reduction in annual transport emissions 9% 5% City A Munich City B Vienna

17 Modal share City A Walking 3% Bicycle 7% Interregional train 1% Regional train 4% City B Walking 5% Bicylce 3% Interregional Train 4% City Train 1% City train 8% Car 37% Car 59% Metro 11% Metro 28% Taxi 1% Motorcycle 1% Tram 2% Bus 3% Taxi 4% Bus 8% Tram 10%

18 Passenger Transportation Annual passenger kilometer travelled inside the city borders Km travelled per day City A 18 City B [km]

19 Car fleet Composition of vehicle fleets by fuel source. 100% 80% 60% 40% 20% 0% Diesel Petrol City A Diesel Petrol City B

20 Electricity mix (powering the electrical car) Heavy fuel oil 3% Photovoltaic 5% Other 4% Waste 1% Wind 7% City A Biomass 6% Hardcoal 19% Other 1% City B Wind 5% Biomass 4% Nuclear 16% Natural gas 41% Hydro 49% Natural gas 11% Lignite 26% Hydro 3%

21 Step 3: Results: Technology impacts Implementation rates Emissions savings Cost efficiency Job creation

22 Step 3: Results: Technology impacts (example) Implementation rates Emissions savings Cost efficiency Job creation e-mobility 20% 4% Building Retrofit 30% 6% 0.5 2,500 Renew able Energy 20% 12% 1.3 1,200

23 Planning through KPIs rather than solutions

24 In order to improve a city s KPIs

25 Cities are unique in targets Europe Americas Asia GHG emissions reduction targets GHG emissions reduction targets GHG emissions reduction targets Copenhagen 100% by 2025 Seattle 100% by 2050 Seoul 40% by 2030 Stockholm 100% by 2050 Portland 80% by 2050 Tokyo 25% by 2020 Oslo 95% by 2030 Washington DC 80% by 2050 Wuhan 20% by 2015 Helsinki 92% by 2050 Houston 36% by 2016 London 60% by 2025 Los Angeles 35% by 2030 Australia Berlin 40% by 2020 Vancouver 33% by 2020 GHG emissions reduction targets Amsterdam 40% by 2025 Buenos Aires 33% by 2030 Melbourne 100% by 2020 São Paulo 30% by 2012 Adelaide 100% by 2020 New York 30% by 2030 Sydney 70% by 2030 San Francisco 25% by 2017 Africa Boston 25% by 2020 GHG emissions reduction targets Santiago de Chile 20% by 2020 Johannesburg 30% by 2025

26 Case study: Copenhagen Copenhagen 2,500 2,000 observed How can the city incentivise their private sector? 1,500 1, target % gap

27 Case study: Copenhagen 40 building owners own 20% 6 technologies 10% reductions 5 mill. EUR investment per year jobs to the local economy

28 Case study: Mapping Vienna s scenarios Vienna First Vienna Accelerated Vienna Experimental Technologies implemented Technologies fit to Vienna s strategy Additional technologies to be implemented Increased CHP contribution Photovoltaic power generation Residential home automation Residential wall insulation Residential double/triple glazing Commercial wall insulation Commercial double/triple glazing Residential efficient lighting Residential home energy monitoring Commercial efficient lighting Commercial demand oriented lighting Commercial heat recovery Hybrid electric bus Train - ATO Electric cars LED street lighting Metro ATO Commercial building efficiency monitoring Electric taxis Commercial building performance optimization Demand oriented street lighting CNG cars Hybrid electric vehicles Intermodal traffic management Demand controlled ventilation Metro new line Urban bike sharing Plug in hybrid electric car Electric bus Intelligent traffic light management Electric car sharing

29 Case study: Mapping Vienna s cost efficiencies Comparisons per scenario Vienna First Vienna Accelerated Vienna Experimental 80,000 FTE 40,000 FTE 20,000 FTE Jobs creation

30 Planning through KPIs rather than solutions based on the city s individual baseline

31 The CyPT path Build emissions baseline The CyPT builds a unique city baseline based on your city data.

32 The CyPT path Build emissions baseline Technologies The CyPT builds a unique city baseline based on your city data. Team of city experts collaborate to determine the most appropriate technologies for achieving targets.

33 The CyPT path Build emissions baseline Technologies Results The CyPT builds a unique city baseline based on your city data. Team of city experts collaborate to determine the most appropriate technologies for achieving targets. Results calculate a cost-benefit analysis of the environmental and economic impact of technologies.

34 The CyPT outcomes (KPIs) GHG Air quality Economy CO 2 PM10 NO x Jobs

35 Contact information Katrin Müller Siemens AG Siemensdamm Berlin, Germany Tel.: Fax: Mobil: Savvas Verdis Siemens plc CD SO CY-UD 1 Siemens Brothers Way London E16 1GB Tel.: Mobil: katrin.km.mueller@siemens.com savvas.verdis@siemens.com

Tailoring transport choices

Tailoring transport choices ACCELERATE, 2014 Dr Savvas Verdis, Infrastructure Economist Answers for infrastructure and cities. cities have different demand characteristics Page 2 Page 3 Page 4 Page 5 culture