This document summarizes the Brazilian experience with the EU-FP6 project SENSOR, which aimed to develop ex-ante impact assessment tools to support land use and agricultural policies. It describes how the project was adapted to test the tools in Brazil, focusing on sugarcane expansion policies in Mato Grosso do Sul state. Spatially-explicit land use change models and sustainability impact indicators were used to assess the effects of sugarcane expansion on the environment, economy and society. The results highlighted limitations in approach and data, but demonstrated the potential for participatory impact assessment frameworks to strengthen the analysis where data and modeling capacity are limited.

4. Integrated Sustainability
Assessment Tools
“The Brazilian Experience with
SENSOR”
Heitor L. C. Coutinho
(heitor@cnps.embrapa.br)
II Workshop AISE
São Carlos, 13 de abril de 2010
EESC-USP

5. •SENSOR (EU-FP6): Sustainability Impact Assessment: Tools for
environmental, social and economic effects of multifunctional
land use in European Regions
Coordinator: Leibniz-Centre for Agricultural Landscape
Research (ZALF), Münchberg,Germany
Participants: 33 Institutions from 15 European countries
Project duration: Dec 2004 – Nov 2008
Project demanded by the EC to support SIA of EU policies
(Bioenergy; The Common Agricultural Policy reform; biodiversity
policies; the forest strategy; and European transportation policy).
Objective
Deliver ex-ante Impact Assessment Tools (SIAT) to
support decision making on policies related to multifunctional
land use in Europe

6. Project SENSOR Mercosur
•Baseline project: IAI-CRN II (2006-2010) “Land use change in the
Rio de la Plata Basin: Linking biophysical and human factors to predict
trends, assess impacts, and support viable land-use strategies for the
future”
History: Oct 2005 – visit to ZALF; March 2006 – invitation to join
SENSOR – proposal submitted to FP6-TTC (international cooperation to
adapt the European approach to extra European conditions in Targeted
Third Countries).
Sensor TTC partners: Embrapa and UFSC (Brazil); UBA
(Argentina); UDELAR (Uruguay); IGNSRR and CASS (China)

7. Project SENSOR Mercosur
•Objectives
•Test and critical review of the feasibility of transferability of
SIAT from Europe to extra European regions
•Review on land use related policies
•Test of the SIAT developed in SENSOR in TTC
•Development of a comprehensive scientific data
management infrastructure and an adapted indicator
framework
•Identification of key issues of sustainability in sensitive
areas in selected regions in TTC and identification of so called
“hot-spots” of environmental degradation
•Stakeholder participation and institutional analysis in TTC
•Identification of driving forces in TTC
•End-user identification
•Definition of sustainability thresholds and sustainability
choice spaces in the context of the TTC countries

8. Project SENSOR – Conceptual framework
• Socio economic drivers (demographic change,
Driver world economic growth, world oil price, etc.)
• Policy cases
• Land use change (priority 1: Policy – Land use change – Sustainability)
Pressure
• Direct effect of impact issues (priority 2: Policy – Sustainability)
• Bio-geophysical conditions
State • Socio-economic conditions
• Impact issues
Impact • „impact identification“ and „impact valuation“
• Relation to landscape function;
• Up to decision maker
Response Land Use
Policies
• Not requested from SENSOR

9. Project SENSOR Mercosur
•Policy Cases
•Sugarcane Expansion in Mato Grosso do Sul State
Sugarcane land occupancy in Sugarcane ethanol plants in
Central Brazil (2007/2008) Central Brazil
http://www.dsr.inpe.br/mapds
Martorano et al., 2008 r/index.jsp

10. Project SENSOR Mercosur
•Policy Cases
•Sugarcane Expansion in Mato Grosso do Sul State
Evolution of sugarcane land
2003-2004 occupancy in South Brazil
2007-2008
http://www.dsr.inpe.br/mapd
Martorano et al., 2008 sr/index.jsp

11. Project SENSOR Mercosur
•Policy Cases
•Afforestation in the South of Brazil, Argentina, and Uruguay
Jobaggy et al., 2006

12. Project SENSOR Mercosur
•Policy Cases
•Afforestation in the South of Brazil, Argentina, and Uruguay
Período Cultivos Pastizales Bosques y Cuerpos de Miscelán
foresta agua eas
ciones
1985/1990º ha 4934865 15132028 1503388 738457 129463
% 21.99 67.44 6.70 3.29 0.58
2000/2004º ha 5805757 13781790 1940254 867546 41574
% 25.88 61.42 8.65 3.87 0.19
∆relativo % 17.65 -8.92 29.06 17.48 -67.89
Baldi, 2006

13. Brazilian Policies related with sugarcane expansion
•The Brazilian Agribusiness Policy Guidelines - 2006/2011 -
Ministry of Agriculture, Livestock, and Food Supply (MAPA)
•twenty-five per cent (25%) of the mandatory amount of
anhydrous ethyl alcohol added to gasoline - CIMA (Conselho
Interministerial do Açúcar e do Álcool )
•The Brazilian Agroenergy Plan - 2006/2011
•Sugarcane Agroecologic Zoning (ZAE CANA)
•Decadal Energy Plan (Plano Decenal de Energia – PDE) - Ministry
of Mines and Energy
•Developed by the Energy Research Company (Empresa de
Pesquisa Energética – EPE) - energy supply and demand
forecast
•Growth Acceleration Plan (PAC)
•Investment on logistics, energy and social/urban
development

14. Policy Scenario - Sugarcane expansion
Área nova projetada MS ( ha)
Área total projetada MS (mil ha)
Área projetada Brasil (mil ha)
8.970
8.431
7.898
7.341
6.765
6.078
5.431
4.849
4.387
3.756
2.965
2.095 2.503
1.416 1.732
908 1.143
346 519 702
186
160 172 183 206 234 274 316 363 408 462
2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017

15. Sugarcane Agroecologic
Zoning (ZAE CANA)
•Based on biophysical
conditionants and legal
restrictions
We know how much land we need, and where it is legally and
biophysically suitable to produce sugarcane. So, where will land
use change take place?

16. •Policy response – Land Use Change Model
•Dyna-CLUE (Conversion of Land Use and its Effects, Verburg et
al., 2002, 2007)
•Simulates the spatial allocation of land use changes
•Uses empirical relationships between land use classes and
LUC driving forces in a dynamic modeling process
•land demand at a regional level (non-spatial
component)
•knowledge rules and logistic regression to estimate
allocation at a local level
•Land use class x driving forces variables
Estimator of land use change
distance to river
Low suitability zone;
distance to ethanol plant
Intermediate suitability zone;
distance to municipality core
High suitability zone
distance to road

17. Land use in 2008, Mato Grosso do Sul state CLUE-S land use simulation for 2018
Ellipses denote hotspot sugarcane growth areas

18. Spatial Regional Reference Framework
1st level: World datasets
Administrative Regions
Biophysical: Socio-economics:
Brazil => micro-regions • Land use • GDP
Argentina => departamentos • Elevation • Population
• Temperature • Roads
Uruguay => unidades censales • Soils
• Ecological zones
Create grids for all these datasets
aggregate regions.

19. Spatial Regional Reference Framework
Turetta et al., 2010

20. Selected Impact Issues for Mercosur
Sustainability Impact
Indicators
Criteria:
•policy relevance
•analytical soundness
•Measurability
•availability (spatial &
temporal)
•simple, concise and easy
to interpret
•Operability

21. Selected Indicators, data sources and availability
INDICATOR SOURCE COVERAGE YEAR
IBGE[1] – Indicators of Sustainable
Consumption of pesticides Brazilian States 2000, 2005
Development
Access to water supply system IBGE – Demographic Census Municipality 2000
Gini Index for the distribution of
Atlas of Human Development - PNUD Municipality 1991, 2000
income
Occupied Persons IBGE - Central Company Register Municipality 1996 - 2006
IBGE – Demographic Census
GDP per capita IBGE – Gross Domestic Product of Municipalities Municipality 2000 - 2006
IBGE – Population Estimate
Ministry of Development, Industry and
Balance of Trade Municipality 2000 - 2006
Foreign Trade, Secex
[1] IBGE – Brazilian Institute of Geography and Statistics.

22. •SIAT (Sustainability Impact Assessment Tool)
•a meta-modelling system
•Requirements of the tool:
•Set of policy options
•Quick SIA response
•Transparency of indicator processing methods
•Effectiveness of indicator results

23. SIAT Sugarcane MS

24. SIAT Sugarcane MS

25. SIAT Sugarcane MS

26. •Lessons learned
•Limitations of approach
•Lack of a reliable SI indicator set (time-series)
•Weakness of available modelling frameworks (too specific)
• Need to develop and apply effective SIA participatory
approaches
FoPIA - Framework for Participatory Impact Assessment (Morris et al., 2008)
•A stand alone, participation-based framework of sequenced methods for
involving national, regional and local stakeholders in assessments of land use
policy impacts
•Participatory SIA can plug some of the gaps caused by limited data
availability / modelling capacity

27. FoPIA - Framework for Participatory Impact Assessment
Morris & Tassone, 2008

28. •Future developments
•Apply FoPIA
•Apply the Sensor approach to a larger spatial scale
•Develop knowledge rules for SI indicators
•Develop a broader set of SI indicators
•Apply the LUF approach

29. Thank You!
(heitor@cnps.embrapa.br)