Determinants of cities’ emissions: a comparison of seven global cities

1. Determinants of cities’ emissions:a comparison of seven global cities 3rd International Scientific Conference on “Energy and Climate Change” Athens 7th-8th October 2010 Edoardo Croci

2. Context • Significant contribution of major cities to global GHG emissions, in particular of carbon dioxide • (UNEP, UNHabitat, 2005: urban activities responsible for 80% of global CO2) • Differences in urban absolute/per capita emissions among cities from industrialized and developing countries (and within each “category”) • Increasing voluntary commitment of city governments to emissions reduction targets

3. Research questions • - Whichbasicfactorsunderlieurbanemissions? • - Whichurbanfeaturesinteract in influencingthesefactors… • …and can beconsideredas ultimate determinantsofemissions?

4. Choice of case studies • Criteria: • focus on global cities (at leastpopulation > 1 million) • availabilityofdetailedemissionsinventories • availabilityof data on selectedurbanindicators • representitivenessofdifferent world areas (climate; economic performance) • -> Bangkok, Chicago, London, Madrid, Mexico City, Milan, New York City Main bias: consistency of urban data used (methodology; territorial coverage) • -> definitions of urban areas may differ among countries and accordingly to criteria used

5. Methodology • -> Focus on residentialemissions and groundtransport • Data availability • Twomainsectors in mostofurbaninventories Steps: 1) Disaggregationofemissionsintomainfactors (emissionsfactors; activity data) 2) Analysisofemissionsdeterminants • qualitative comparison + quantitative indicators on urbanfeaturessuchas: climate, morphology, infrastructure, technology, economicactivities in place, income, prices, culture…

6. Main factors: Built sector Eb = emissions from energy used in buildings Qi = quantity of “i” fuel consumed directly for various purposes (i.e. heating, water heating, cooking...) for unit of built surface (kWh/m2) EFi = emission factor of “i” fuel (CO2/kWh) Si = floor space consuming “i” fuel (m2) f = 1, … 8 1 = natural gas 2 = oil 3 = LPG (Liquefied Petroleum Gas) 4 = coal 5 = waste used as fuel 6 = biomass 7 = energy from renewable sources 8 = other Qe = quantity of electricity consumed for various purposes (i.e. heating, water heating, cooking, air conditioning, use of electric appliances...) for unit of built surface (kWhe/m2) EFe = emission factor of electricity purchased in the city (CO2/kWhe) Se = floor space consuming electricity (m2)

7. Main factors: Built sector • Residentialsector: • - significantdifferences in fuel and electricityconsumption per housingunit (e.g. Chicago, highestvalues; Bangkok, Mexico City, lowestvalues) • emissionsfactorshavesecondaryrelevance (apartfromE.F.ofelectricity) Qi = fuelconsumption (kWh/housingunit) Qe=electricityconsumption (kWh/ housingunit)

8. Main factors: Ground transport • Where: • Tj = number of passengers’ trips with “j” mode • Lj = average length of a single trip with “j” mode (passengers km) • lf = load factor of “j” mode (n. passengers/vehicle) • EFji = emission factors of “i” fuel with “j” mode (gCO2/vehicle km) • f = 1, … 6 • 1 = gasoline • 2 = diesel • 3 = LPG • 4 = electricity • 5= other • 6 = no fuel VKTzi = kilometres travelled by freight vehicles of “i” fuel and of “z” mode (vehicle km/inhabitants) EFzi = emission factors of “i” fuel with “z” mode (gCO2/vehicle km) z = 1,…3 1 = light duty vehicles (and sub-categories) 2 = heavy duty vehicles (and sub-categories) 3 = rail m = 1, … 6 1 = foot 2 = bicycle 3 = subway/rail 4 = bus 5 = passenger car 6 = motorcycle

9. Main factors: Ground transport • Ground transport: • relevantroleof private cars (Chicago) and freight (Chicago; Bangkok) in citieswithhigheremissions • relevantroleofnon-motorizedmodes (New York City) and public transport (London; Madrid; Mexico City) in containingemissions *For Mexico City data on foot/bicycle trips are notavailable

10. Main factors: Ground transport • significant differences in the carbon intensity of the private and commercial vehicle stock • e.g. Bangkok: very inefficient public and commercial fleet • Chicago: carbon-intensive stock of passenger cars • London, Milan: very low carbon intensity for passenger cars

11. Main determinants Built sector • Residentialemissions: • climate, primary determinant: entails more relevant energy consumption levels for those cities having higher heating needs (e.g. Chicago, London, New York City) or cooling needs (Bangkok, as emerges from electricity consumption levels). Qi = fuelconsumption (kWh/housingunit) HDD=HeatingDegreeDays

12. Main determinants: Built sector • - features of the residential stock: • cities with a dense built environment consume lower energy quantities per housing unit • better energy efficiency relevant in explaining lower energy consumption level • - level of economic welfare: determinant for electricity use

13. Main determinants: Ground transport • Ground transport emissions: • form and density, primary determinant shaping modes in use and emissions: • high density: relevant quota of passenger demand satisfied through non-motorized transport (New York City) and public transit (New York; London; Mexico City; Milan) • lower density: significant use of private cars and higher emissions (e.g. Chicago)

14. Main determinants: Ground transport Ground transport emissions: - technology and features of vehicle stock: determinant for cities where the stock is very inefficient (e.g. Bangkok) or very efficient (e.g. Milan).

15. Future research • needtocollect more specific data at city level in ordertosupportobservations • e.g. builtsector: • - typologiesofhousingunits and commercial buildings • - heating/coolingsystems in operationwithin the city • diffusionofelectricappliances in households/offices and averageenergyefficiency • e.g. groundtransport: • more detailedinsightinto the vehicle stock (private, public, commercial) • data collection on specificurbanfeatures, in ordertoverifytheir link with the degreeofuse private cars/public transit (i.a.urbanwalkability; accessibility; integrationof the public transport network) • identifylinkagesbetweenurbandeterminantsofemissions and policies/measures • evaluatetrendsofurbanemissionsthroughcities’ updatesofemissionsinventories