General ESPON meeting Espoo, 14-15 november, 2006

Prof. Roberto Camagni – Politecnico di Milano

General ESPON meeting General ESPON meeting Espoo, 14-15 november, 2006Espoo, 14-15 november, 2006

TEQUILA SIP ESPON 3.2Interactive Simulation Package

for Territorial Impact Assessment

Roberto Camagni (Politecnico di Milano)


The team The team

DIG - Department of Management, Economics and Industrial

Engineering – Politecnico di Milano

Roberto CAMAGNI (direction and concept) DIG – Politecnico

Lidia DIAPPI (package supervision) DIAP-Politecnico

Paola BOLCHI (SIP package construction) DIAP-Politecnico

Chiara TRAVISI (data base and calibration) DIG - Politecnico

Paolo SALZANI (data base and simulation) DIG - Politecnico


Content Content

1. The TIA / Territorial Cohesion link

2. An operational definition of Territorial Cohesion

3. Territorial dimensions and assessment criteria

4. The General Assessment Model: the TEQUILA Model

5. The Territorial Assessment Model: TIM

6. TEQUILA SIP: Interactive Simulation Package

7. Application to TENs policies

8. The interactive package

9. Mapping the results


1. The TIA / Territorial Cohesion link

A TIA methodology has necessarily to start by linking up with a sound theoretical and operational definition of Territorial Cohesion

“Territorial cohesion translates the goal of sustainable and balanced development assigned to the Union into territorial terms” (Rotterdam Declaration, Dutch Presidency, 2004)

For us:

Territorial cohesion may be seen as the territorial dimension of sustainability (beyond the technological, the behavioural and the diplomatic dimensions of sustainability) (Camagni, 2004)



The 3 main components of territorial cohesion:

* Territorial Efficiency: resource-efficiency with respect to energy, land and natural resources; competitiveness and attractiveness of the local territory; internal and external accessibility

* Territorial Quality: the quality of the living and working environment; comparable living standards across territories; similar access to services of general interest and to knowledge

* Territorial Identity: presence of “social capital”; landscape and cultural heritage;capability of developing shared visions of the future; creativity;productive “vocations” and competitive advantage of each territory


3. Territorial dimensions and assessment criteria3. Territorial dimensions and assessment criteria

Ec

Soc

Territorial quality

Territorial efficiency

Territorial identity

Env

Quality of life and working conditions; access to services of general interest

Resource -efficiency Competitiveness, attractiveness

Social capital; shared visions

Sustainable transport: s hare of public transport and reduction of congestion on the network

Compact city form; reduction of sprawl

Co -operation between city and countryside

Integrated and balanced territori al system

Efficient and polycentric urban system

Inter -regional integration

Complementarity of knowledge and Know -how

Multiethnic solidarity and integration

Conservation and creative management of cultural resources

Conservation and creative management of natural landscape

Reduction of poverty and exclusion

Economic performance

Employment performance

Accessibility to telecommunication services and to knowledge

Strengthening of gateway cities

Financial costs and benefits of

policies

Conservation of natural resources Conservation of water resources

Accessibility to infrastructure

Reduction of environmental risks

Quality of services

Quality of transport services


4. The General Assessment model: the TEQUILA Model

T erritorial

E fficiency

QU ality

I dentity

L ayered the TEQUILA ModelA ssessment

Model

(Camagni, 2006)



1. TEQUILA is a Multicriteria Model for the Territorial Impact Assessment of EU policies

2. The 3 components of the T.C. concept and their sub-components become the criteria in the Assessment Model

3. The weights of the 3 criteria and sub-criteria are flexible

(sensitivity of results with respect to change in weights is tested interactively)

4. The general impact of EU policies on each criterion is defined using ad hoc studies, in both qualitative and quantitative ways

5. A method for combining quali-quantitative impact indicators inside the multi-criteria analysis is supplied



Alternative scaling of quantitative assessments (e.g.)

+5

0

180 250 180 250 Impact on regional employment Impact on regional employment

+3

+2

a) “local scaling” b) “ad hoc scaling”

Qualitative impact scores are attributed on a +5 to -5 scale: 5= very high advantage for all; -5= very high disadvantage for all4= high advantage for all; -4= high disadvantage for all3= high advantage for some, medium adv. for all; -3= high dis. for some, medium dis. for all2= medium advantage; -2= medium disadvantage1= low advantage; -1= low disadvantage 0= nil impact;


4. The General Assessment model

The 2 layers

1st layer: General Assessment of the impact of EU policies on the overall European territory: to be intended as a “potential impact” on an abstract territory (PIM)

2nd layer: “Territorial Assessment” on each region. Necessary as:

- the intensity of the policy application may be different on different regions

- the relevance of the different “criteria” is likely to be different for different regions, according to their utility function

- the vulnerability and the receptivity of the different regions to similar “potential” impacts is likely to be different

- a region may not be subject to a specific policy


5. The Territorial Assessment Model: TIM5. The Territorial Assessment Model: TIM

TIMr = Σc θc . (PIMc . PIr ) . Sr,c . PAr

TIM = territorial impactc = criterion of the multi-criteria methodr = regionθc = weight of the c criterionPIM = potential impact of policy (abstract)PI = policy intensity (in region r)Sr,c = sensitivity of region r to criterion cPA = policy applicability (a 0/1 variable)

Sr,c = Dr,c . Vr,cDr,c = desirability of criterion c for region r (territorial “utility function”)Vr,c = vulnerability of region c to impact PIMc (receptivity for positive

impacts): a vector of regional characteristics


6. TEQUILA SIP: an Interactive Simulation Package6. TEQUILA SIP: an Interactive Simulation Package

The TEQUILA model is operated through an interactive simulation device, specifically built by the research team for Espon:

TEQUILA SIP- interactive- easy to build and operate- working on different layers (particularly: Europe 29 and NUTS 3)

As a pioneering and prototype experiment, TEQUILA SIP is applied to the assessment of the Territorial Impact of EU transport policy (TEN-TINA), using existing quantitative ESPON assessments and data base

Territorial level : NUTS 3 (1329 regions) Collaboration of ESPON teams in data supply is gratefully acknowledged


7. Application to TENs policies7. Application to TENs policies

3 criteria Variables 9 sub-criteria

PIM_E1 Internal connectivity

Territorial Efficiency PIM_E2 External Accessibility

PIM_E3 Economic Growth

PIM_Q1 Congestion

Territorial Quality PIM_Q2 Emissions

PIM_Q3 Transport sustainability

PIM_I1 Creativity

Territorial Identity PIM_I2 Cultural heritage

PIM_I3 Landscape resources


7. Application to TENs policies 7. Application to TENs policies : Potential Impact: Potential Impact

PIM Sub-criteria Indicator Unit of measure Dir. Variation Wgt. Source of data

PIM_E1InternalConnectivity

Dif transport endowment (road + rail)/GDP

Km / GDP + 0 to 4 0,333ESPON 3.2Mcrit

PIM_E2ExternalAccessibility

Dif accessibility (road/rail passenger travel), scenario B1 (only priority projects)

Number of people + 2 to 5 0,333ESPON 1,2,1 SASI; Mcrit

PIM_E3 GrowthDif GDP per capita, scenario B1 –

Difference to reference scenario 2000 – 2021

Dif % GDP/inhabitant + 2 to 4 0,333ESPON 2,1,1, SASI Model

PIM_Q1 Congestion Dif-flows, baseline scenario 2015 Million Vehicles/Km - 2 to -5 0,333ESPON 3.2Mcrit

PIM_Q2 Emissions Dif CO2 emissions baseline Million Tons CO2 / Year - 2 to -5 0,333ESPON 3.2Mcrit

PIM_Q3Transport sustainability

Dif rail - Dif road, baseline scenario 2000-2015

Km - Km + -3 to 3 0,333ESPON 3.2Mcrit

PIM_I1 CreativityDif accessibility*[knowledge and

creative services](# people)*( # libraries +

theatres)+ 1 to 4 0,333

ESPON 2,1,1, SASI Model

PIM_I2 Cultural heritageDif accessibility*[ # monuments +

museums ](# people)*( # monuments-

museums)+ 1 to 4 0,333

ESPON 2,1,1, SASI Model

PIM_I3 LandscapeDif. Transport endowment

(road+rail) / GDP Km / GDP - 0 to -4 0,333

ESPON 3.2Mcrit


7. Application to TENs policies 7. Application to TENs policies : Sensitivity: Sensitivity

Sensitivity Sensitivity parameters Unit of measure Variation Functional shape

Source of data

S_E1

D = LOG of current density of transport endowment [density=(road+rail)/GDP]

R = 1S = D norm

LOG[km road+rail] / GDP 0,8 to 1,2 Linear ESPON 3.2McritESPON 3.1

S_E2D = LOG [current accessibility]R = 1S = D norm

LOG [# of people daily accessible by car]

0,8 to 1,2 Non Linear ESPON 2,1,1 – SASI Model

S_E3D = GDP 2000 PPP per inhabitantR = 1S = D norm

GDP 2000 PPP per inhabitant] 0,9 to 1,2 Linear ESPON 3.1, Eurostat Regio

S_Q1D=Present congestion V=Share of natural areasS= mean of normalised D and V

D= Million Vehicles / network KmV= share of natural areas (Km2)

0,8 to 1,2 D = Non Linear ESPON 3.2 –Mcrit; BBR Corine Landcover

S_Q2D=Present emissionsV=Share of natural areas S= mean of normalised D and V

Present emissions CO2 year 2000 [million tons]

V= share of natural areas (Km2)

0,8 to 1,20,9 to 1,2

D = Non LinearV = Linear

ESPON 3.2 -McritBBR Corine Landcover

S_Q3D=Present share of railways on total tran. ntw.R = 1S = D norm

Km / Km (%) 0,8 to 1,2 D = Non Linear ESPON 3.2Mcrit

S_I1D=GDP 2000 PPP per inhabitantR = 1S = D norm

GDP 2000 PPP per inhabitant 0,9 to 1,2 Linear ESPON 3.1, Eurostat Regio

S_I2D=GDP 2000 PPP per inhabitantR = 1S = D norm

GDP 2000 PPP per inhabitant 0,9 to 1,2 Linear ESPON 3.1, Eurostat Regio

S_I3

D=1V = Natural vulnerability (natural area

fragmentation)S= V norm

Natural area fragmentation indicator 1-5: 1= very low; 5 = max fragmentation

1,2 to 0,9 LinearESPON 1,3,1; GTK


8. The interactive package8. The interactive package


8. The interactive package: Impact on Efficiency8. The interactive package: Impact on Efficiency


8. The interactive package: Potential Impact 8. The interactive package: Potential Impact


9. Mapping results: impact on Territorial Efficiency 9. Mapping results: impact on Territorial Efficiency

Politecnico di Milano – TEQUILA SIP – June 2006

Mean Value = 2.1773


9. Mapping results: impact on Territorial Quality9. Mapping results: impact on Territorial Quality


Mean Value = -1.19


9. Mapping results: impact on Territorial Identity 9. Mapping results: impact on Territorial Identity


Mean Value = 0.714


8. Mapping results: General Impact (a)8. Mapping results: General Impact (a)


Mean Value = 0.5492


8. Mapping results: General Impact (b)8. Mapping results: General Impact (b)


Mean Values = 0.5173


Thanks!Thanks!

Thanks for your attention!

Roberto CamagniDepartment of Management, Economics and Industrial EngineeringPolitecnico di MilanoPiazza Leonardo da Vinci 32 - 20133 MILANOtel: +39 02 2399.2744 - 2750 secr.fax: +39 02 [email protected]://econreg.altervista.org

http://econreg.altervista.org/

http://econreg.altervista.org/

General ESPON meeting Espoo, 14-15 november, 2006

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