Urban and regional carbon managementin the context of the global carbon cycle

Michael Raupach, Pep Canadell and Shobhakar Dhakal

Global Carbon Project (IGBP-IHDP-WCRP-Diversitas)

URCM Conference, Mexico City, 5-9 September 2006

Cities are amazing places

Cities and towns are transforming the planetNASA Earthlights composite

Carbon, climate and humans

Carbon cycle ClimateNatural biophysicalfeedbacks

(1) Forcing

Human activities

(3) Impacts(4) Response

(2) Altered biophysicalfeedbacks

Carbon-climate-human system: forcing and response

Records (1850-2005) of:

CO2 emissions from fossil fuels

Changing CO2 concentrations in the atmosphere

Changing global mean temperatures (from instrumental record with effects of urbanisation removed)

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1850 1870 1890 1910 1930 1950 1970 1990 2010

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moa

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O2]

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1850 1870 1890 1910 1930 1950 1970 1990 2010

Tem

pera

ture

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C)

Temperature 0.2 C/decade

FFemission to 2003 Marland, CDIACFFemission 2004-05 Marland PersCommGlobal temperature Jones et al, CRUCO2 1832-1958 LawDome 20yrCO2 1959-now MaunaLoa

Present radiative forcing

IPCC AR4, WG1 SPM, second draft (24-mar-2006)

CO2

Non-CO2GHGs

Non-gaseous radiativeforcing

Global warming

IPCC (2001)

Predicted warming of 1.4 to 5.8 C depends on

(1) uncertainties in climate models (around 1 C)

(2) uncertainties in emissions scenarios (around 2 C)

IPCC (2001) Third Assessment, Summary for PolicyMakers

Lags in the response of climate to emissions

IPCC 2001, SYM, Figure 8.3

Impacts: food

Food supplies in developing nations are more vulnerable to climate change than in developed countries

Impacts: water

Water supplies in many nations are vulnerable to climate change

Climate vulnerability compounds population vulnerability, especially in less developed nations

Vörösmarty et al 2000, Science

Outline

Carbon-climate-human feedbacks in the Earth System

The changing carbon cycle: trends, drivers, vulnerabilities• Land-air and ocean-air CO2 exchanges• CO2 emissions from human activities (I = PAT)

Carbon management• Components of carbon management

(technical, economic, policy, cultural)• Opportunities for urban and regional carbon management

The global carbon cycle

The current carbon cycle (Sabine et al 2004)Field CB, Raupach MR (eds.) (2004) The Global Carbon Cycle: Integrating Humans, Climate and the Natural World. Island Press,Washington D.C. 526 pp.

Global atmospheric CO2 budget

http://lgmacweb.env.uea.ac.uk/e415/co2/carbon_budget.htmlCorinne LeQuere, 4 August 2006

Data Sources:Land Use: Houghton (1999) TellusFossil Fuel: Marland et al (2005) CDIACOcean: Buitenhuiset al (2005) GBCAtmosphere: Keeling and Whorf (2005) CDIACLand: difference

dCA/dt = FEmission + FLandUseChange + FLandAir + FOceanAir

Vulnerability of the earth system to destabilisation of carbon pools

C4MIP = Coupled Climate Carbon Cycle Model Intercomparison Experiment

Intercomparison of 8 coupled climate-carbon cycle models

Uncertainty (range among predictions) is comparable with uncertainty from physical climate models and emission scenarios

Friedlingstein et al. 2006, in press

Atmospheric CO2

Land C uptake

Ocean C uptake

NOWtemperature implication: up to 3 degC

present land sink (2 to 3 GtC/y) becomes a source in some models

Vulnerability to release of frozen carbon

CF0 = 900 PgC (from permafrost area and permafrost soil C data)kFT = 0.001 [y-1 K-1] (Anisimov et al 1999: warming of 2 degC over 100 y decreases permafrost by 25%)Raupach, M.R. and Canadell, J.G. (2006). Observing a vulnerable carbon cycle. In: Observing the Continental Scale Greenhouse Gas Balance of Europe (eds. H. Dolman, R. Valentini, A. Freibauer). (Springer). (In press)

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A1 without frozen-C feedbackA1 with frozen-C feedback

0.8 degC

Response of CO2

Response of temperature

CO2 emissions from human activities

Emissions, population, GDP

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S$b)

F=EmisP=PopG=GDP

Response (emissions) and drivers (population, GDP)

FormalismBasic variables (extensive: proportional to size of a homogeneous region)• F = fossil-fuel CO2 emission

P = populationG = GDP

Basic (Kaya) identity (Nakicenovic 2004)• [ F = P * (G/P) * (F/G) ]

[Impact = Population * Affluence * Technology]

• or F = Pgh

Normalised (intensive) variables• g = G/P = percapita GDP (Affluence)

h = F/G = FF intensity of GDP (Technology)j = F/P = percapita FF emission = gh

Growth rates• Growth rate for quantity X: r(X) = (1/X) dX/dt• Basic identity implies: r(F) = r(P) + r(g) + r(h)

Growth rates in CO2 emissions, population, GDP

Growth rates (5y smoothed)

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1950 1960 1970 1980 1990 2000 2010

Gro

wth

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/y)

rF=F'/FrP=P'/PrG=G'/G

Intensive variables:Percapita emission and GDP, and FF intensity of GDP

Intensities

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1950 1960 1970 1980 1990 2000 2010

g=G/Ph=F/Gj=F/P

g = G/P = Percapita GDP (k$/y/person)

h = F/G = FF intensity of GDP (100gC/$)

j = F/P = Percapita FF emission (tC/y/person)

Vulnerability of the Earth System to CO2 emissions:Stabilisation scenarios and the emissions gap

Stabilisation scenario: future emissions trajectory needed to stabilise CO2 at a given level(a goal, not a prediction)Over 2000-2005, actual emissions are: close to the A1 scenario

close to the maximum for 650 ppmabove the maximum for 450 ppm

1980 2000 2020

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Historic emissionsProjected emissions (A1)to stabilise at 450 ppmto stabilise at 650 ppmto stabilise at 1000 ppm

emissions gap

Outline

Carbon-climate-human feedbacks in the Earth System

The changing carbon cycle: trends, drivers, vulnerabilities• Land-air and ocean-air CO2 exchanges• CO2 emissions from human activities (I = PAT)

Carbon management• Components of carbon management

(technical, economic, policy, cultural)• Opportunities for urban and regional carbon management

Components of carbon managementTechnical• Broad portfolio of energy technologies: renewables, cleaner FF, conservation ...• Both supply-side and demand-side focus • A workable transition pathway that starts now

Economic• Clever use of market drivers• GH accounting, trading mechanisms

Policy• Carbon price signals: policies to make greenhouse costs visible to the market• Support for innovation (technical, economic, policy, socio-cultural)• Implementing favourable incentives, removing perverse incentives

Cultural• Motivating awareness and action• Decoupling quality of life from continual growth in consumption• Protection of the global commons as a universal ethical imperative

Costs of technologies: centralised electricity generation in Australia

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Browncoal pf

Black coal pf(sub critical)

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Blackcoalultrasupercritical

Blackcoal

IGCC

Natural gascombined cycle

Browncoal

IGCC

GaswithCCS

Wind Browncoal

IGCCwithCCS

Blackcoal

IGCCwithCCS

NuclearBiomass Hotfractured

rocks

Largehydro

Gassimplecycle

SolarThermal

2005 cost estimate

2050 cost estimate from literature

Current baseload average electricity price

Current mid-load average electricity price

Current peak-load average electricity price

Paul Graham (CET) and CSIRO Energy Working Group, 2006

Coal wins without a GH cost signal

Cap and trade:New South Wales

Target: 5% better than Australia's Kyoto commitment

Instruments for carbon management:levels of decision and action

town, statetown, stateMotivating awareness and actionC

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Public, privateState, nation, internatCarbon trading

Internat, town?

State, nation

Private, public

Public, private

town

State, town

State, town

State, town

State

Level of action

InternatInternational consistency

State, nationIncentives for investment

State, nation, internatEmissions caps (leading to carbon price)

State, nation, internatCarbon accounting, verification

townUrban design: buildings, roads, vegetation

State, nationEnd use efficiency, demand limitation

State, nationBetter storage and distribution

State, nationCleaner transport energy

State, nationCleaner stationary energy

Level of decisionInstrument

Populations of largest urban regions and cities

100 largest urban regions1: Tokyo (35.2M)2: Mexico City (19.4M)100: Casablanca (3.1M)Total: 693M (10.7% of global)

60 largest cities1: Mumbai (12.78M)9: Mexico City (8.5M)60: Pune (3.06M)Total: 351M (5.4% of global)

We are talking about urban settlements of all sizes!

http://en.wikipedia.org/wiki/List_of_metropolitan_areas_by_populationAugust 2006

Populations of largest urban regions and cities (2005)

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Urban RegionsCities

Tokyo region(35M)

Global trends in urbanisation 1950-2015World

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More Developed

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UN Development Program data (August 2006)http://esa.un.org/unup/index.asp?panel=3

Urban and rural incomes: China

Per capita income of urban and rural households in China, 1978 - 1997

Heilig, G.K. (1999) Can China feed itself? A system for evaluation of policy options. IIASA. (http://www.iiasa.ac.at/Research/LUC/ChinaFood/index_h.htm)

Caption: This chart partly explains the attraction of cities and towns for China's rural population. Whereas average household income has risen significantly in rural areas, incomes in urban areas have increased even more. The gap between urban and rural income has remained almost unchanged.

Source: China Statistical Yearbook, Beijing, 1998 (p.325)

Note: Constant prices.

Growth rates in CO2 emissions, population, GDP

Growth rates (5y smoothed)

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1950 1960 1970 1980 1990 2000 2010

Gro

wth

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rF=F'/FrP=P'/PrG=G'/G

SummaryCarbon-climate-human feedbacks in the Earth System• Cities are amazing places• Cities are also growing to be destabilisers of the earth system

The changing carbon cycle: trends, drivers, vulnerabilities• Land and ocean sinks take up ~half of current anthropogenic CO2 emissions• The signature of CO2 emissions is changing:

• growth rate of emissions has accelerated since Y2000• fossil-fuel intensity of GDP has increased since Y2000 (after falling for 30 y)

Carbon management• Technical, economic, policy, and cultural dimensions: all four are critical• Opportunities for urban and regional carbon management:

• Understanding what are the carbon dynamics of urban regions, and how they interact with the global C cycle and earth system

• Understanding the opportunities for urban and regional carbon management , and who controls them

• As a research community, engaging to turn possibilities into realities

Cities are amazing places

Indices of El Nino-Southern Oscillation (ENSO)SOI = P(Tahiti) - P(Darwin)

Nino3.4 = central equatorial Pacific sea surface temperature

MEI = Multivariate ENSO Index • (from first PC of 6 variables: sea surface temp, air temp, atmospheric pressure, zonal

and meridional winds, cloudiness: Wolter and Timlin 1993, 1998)

ENSO indices (standardised, 11-mth smoothed)

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1950 1955 1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015

-SOIm/10Nino3.4MEI

Land-air and ocean-air CO2 exchanges:ENSO as a driver on interannual variability

Atmospheric CO2 budget: dCA/dt = FEmis + FLUC + FLandAir + FOceanAir

Non-fossil-fuel fluxes: (dCA/dt − FEmis) = (FLUC + FLandAir + FOceanAir)

Main influences of ENSO:• on land-air CO2 flux (drought, heat, wildfire)• on LUC flux (humans have coopted ENSO as a helper for land clearing)

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FemisdCa/dtdCadt-FemSOI(tY-1)

FEmis

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SOI(y-1)

dCa/dt − FEmisPinatubo

Conequences of urbanisation for CO2 emissions:a statistical approach

Basic identity:

Let U = population of an individual urban unit (town or city)Umin = population of smallest townUmax = population of largest city

Consider ρ(U), the probability density function of U• Definition: ρ(U) dU is the fraction of the total population living in towns with

populations between U and U + dU

We expect the affluence or percapita GDP (g = G/P) and the fossil-fuel intensity of GDP (h = F/G) to depend on the size of the urban unit: g = g(U), h = h(U)

Then for a region with total population P, distributed among towns of size U with probability density function ρ(U), the total fossil fuel emission F is

( ) ( )F P G P F G Pgh= =

( ) ( ) ( )max

min

U

U

F P g U h U U dU= ρ∫