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BRAZIL
CHINA
EUROPE
INDIA
INDONESIA
UNITED STATES
Estrada da Gávea, 50 – 4o andar
Gávea – Rio de Janeiro – RJ
22451-263
Brazil
climatepolicyinitiative.org
DETERring Deforestation in the Brazilian
Amazon
Juliano Assunção Clarissa Gandour Romero Rocha
Environmental Monitoring and Law
Enforcement
1
Agenda
 Introduction
 Institutional context
 Methodology
 Key findings
 Policy implications
 CPI Rio projects
 Q&A
2
Introduction | The Brazilian Amazon
 The Brazilian Amazon
• 4 million km2
• 80% remains covered by native vegetation
• 20% of planet’s fresh water
• Unique biodiversity
• Carbon sink
… combating illegal deforestation is an immense
challenge !
3
0
5
10
15
20
25
30
deforestationrate(thousandkm2)
Annual Amazon Deforestation Rate
Introduction | The Brazilian Amazon
agricultural output
prices
&
conservation policies
4
Introduction | This Study
 Main question
• What role did monitoring and law enforcement play in
the recent deforestation slowdown?
 Our approach
• Empirical regression-based analysis
• Sample: 526 Amazon municipalities from 2007 through
2011
• Explore policy implementation details to assess policy
effectiveness
• Satellite-based targeting of monitoring and law
enforcement
5
 Main findings
• Large deterrent effect of monitoring and law enforcement
• 2007-2011: preserved over 59,500 km2 of Amazon forest
• Estimated monetary benefits are larger than costs
• Forest preservation occurred at no apparent cost to local
agricultural production
 Monitoring and law enforcement policy
Introduction | This Study
effective
monetary
agricultural
& low-cost
6
Agenda
 Introduction
 Institutional context
 Methodology
 Key findings
 Policy implications
 CPI Rio projects
 Q&A
7
Institutional Context | What is Ibama?
 Brazilian Institute for the Environment and Renewable
Natural Resources [Ibama]
• Environmental monitoring and law enforcement authority
• Police force
• Investigation of environmental infractions
• Sanctioning of environmental crimes
8
Institutional Context | Policy Change
 Pivotal conservation effort of 2000s
• Plan for the Prevention and Control of Deforestation in
the Amazon [PPCDAm]
 Stricter monitoring and law enforcement
• Real-Time System for Detection of Deforestation
[DETER]
• Satellite-based real-time monitoring
9
Institutional Context | How DETER Works
National Institute
for Space Research
Remote Sensing
Center
10
Institutional Context | How DETER Works
before
after
11
Institutional Context | How DETER Works
12
Institutional Context | How DETER Works
National Institute
for Space Research
Remote Censing
Center
13
14
15
16
Institutional Context | How DETER Works
 Targeting before DETER
• Voluntary reports of deforestation activity
 Targeting after DETER
• Satellite imagery: 3-day intervals, year-round
• More timely law enforcement action
… significant improvement in Amazon monitoring and
law enforcement capability
 DETER is incapable of capturing land cover patterns
beneath cloud coverage
17
Institutional Context | How DETER Works
Jan 2011
Jul 2011 Oct 2011
Apr 2011
18
Agenda
 Introduction
 Institutional context
 Methodology
 Key findings
 Policy implications
 CPI Rio projects
 Q&A
19
A Word on Methodology
 Goal: identify causal effect of Ibama’s presence on
deforestation activity
• Environmental fines as measure of Ibama’s presence
 Challenge: address two-way causality
monitoring and
law enforcement
deforestation
20
A Word on Methodology
 Use DETER cloud coverage as source of exogenous
variation in law enforcement
• What does this mean?
• For a given area, systematically:
Greater DETER cloud coverage
Lower chance of DETER issuing alert
Lower chance of Ibama targeting the area
Lower intensity of monitoring and law enforcement
… unrelated to deforestation!
21
Agenda
 Introduction
 Institutional context
 Methodology
 Key findings
 Policy implications
 CPI Rio projects
 Q&A
22
Results | Key Findings
 DETER cloud coverage affects Ibama’s presence
• Lower cloud coverage leads to greater number of fines
 Ibama’s presence affects deforestation activity
• Greater number of fines in current year leads to lower
deforestation in following year
• Deterrent effect dissipates over time
cloud coverage monitoring and law
enforcement
deforestation
less more less
23
41.6
101.1
59.5
0
20
40
60
80
100
120
140
160
180
observed estimated
deforestation(thousandkm2)
Results | What Does This Mean?
 What if Amazon monitoring and law enforcement
capability had not improved starting in 2004?
total deforestation, 2007-
2011
24
41.6
164.3
122.7
0
20
40
60
80
100
120
140
160
180
observed estimated
deforestation(thousandkm2)
Results | What Does This Mean?
 What if Amazon monitoring and law enforcement had
been entirely inactive?
total deforestation, 2007-
2011
25
 Simulation 1: 59,500 km2
• ≈ 2/3 area of Portugal
 Simulation 2: 122,000 km2
• ≈ area of Nicaragua
• Avoided emissions equivalency: 900 million tCO2 per
year
• ½ US 2011 transport sector emissions
• 2.5–3 times average annual emissions savings from
European renewables sector
Results | What Does This Mean?
26
Results | Worth It?
 Cost-benefit analysis
24,500 km2
average forest area
preserved per year
900 million
tCO2
avoided emissions
per year
560 million
USD
125 million
USD
annual budgets for
Ibama and INPE
685 million USD
annual budget for Amazon
monitoring and law
enforcement
benefit
cost
0.76 USD/tCO2
break-even price of carbon
low monetary
cost
5 USD/tCO2
common current
price of carbon
>>
27
Results | Key Findings
 Tradeoff between economic growth and preservation?
 Ibama’s presence does not affect local agricultural
production
• Greater number of fines has no impact on local
agricultural GDP or crop production
low agricultural cost
28
Agenda
 Introduction
 Institutional context
 Methodology
 Key findings
 Policy implications
 CPI Rio projects
 Q&A
29
Policy Implications
 Maintain Amazon monitoring and law enforcement
efforts
• Strong deterrent effect at relatively low cost
• Need for continuous policy action
• Complementary nature of other conservation policies
 Promote strategic use of technology and information
• Improve monitoring technology
• Further enhance law enforcement capability
30
Agenda
 Introduction
 Institutional context
 Methodology
 Key findings
 Policy implications
 CPI Rio projects
 Q&A
31
CPI Rio Projects | Land Use
 Deforestation
• Prices or policies?
• Conditional rural credit
• Monitoring and law enforcement
• Net impact of protected areas
• Socioeconomic impact of conservation policies
• Forest clearing behavior
 Agriculture
• Enhanced productivity
• Technological adoption
• Insurance for rural producers
32
BRAZIL
CHINA
EUROPE
INDIA
INDONESIA
UNITED STATES
Estrada da Gávea, 50 – 4o andar
Gávea – Rio de Janeiro – RJ
22451-263
Brazil
climatepolicyinitiative.org
Questions?
for full paper and executive summary, click
here
clarissa@cpirio.o
rg

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CPI Webinar: Deterring Deforestation in the Brazilian Amazon

  • 1. 0 BRAZIL CHINA EUROPE INDIA INDONESIA UNITED STATES Estrada da Gávea, 50 – 4o andar Gávea – Rio de Janeiro – RJ 22451-263 Brazil climatepolicyinitiative.org DETERring Deforestation in the Brazilian Amazon Juliano Assunção Clarissa Gandour Romero Rocha Environmental Monitoring and Law Enforcement
  • 2. 1 Agenda  Introduction  Institutional context  Methodology  Key findings  Policy implications  CPI Rio projects  Q&A
  • 3. 2 Introduction | The Brazilian Amazon  The Brazilian Amazon • 4 million km2 • 80% remains covered by native vegetation • 20% of planet’s fresh water • Unique biodiversity • Carbon sink … combating illegal deforestation is an immense challenge !
  • 4. 3 0 5 10 15 20 25 30 deforestationrate(thousandkm2) Annual Amazon Deforestation Rate Introduction | The Brazilian Amazon agricultural output prices & conservation policies
  • 5. 4 Introduction | This Study  Main question • What role did monitoring and law enforcement play in the recent deforestation slowdown?  Our approach • Empirical regression-based analysis • Sample: 526 Amazon municipalities from 2007 through 2011 • Explore policy implementation details to assess policy effectiveness • Satellite-based targeting of monitoring and law enforcement
  • 6. 5  Main findings • Large deterrent effect of monitoring and law enforcement • 2007-2011: preserved over 59,500 km2 of Amazon forest • Estimated monetary benefits are larger than costs • Forest preservation occurred at no apparent cost to local agricultural production  Monitoring and law enforcement policy Introduction | This Study effective monetary agricultural & low-cost
  • 7. 6 Agenda  Introduction  Institutional context  Methodology  Key findings  Policy implications  CPI Rio projects  Q&A
  • 8. 7 Institutional Context | What is Ibama?  Brazilian Institute for the Environment and Renewable Natural Resources [Ibama] • Environmental monitoring and law enforcement authority • Police force • Investigation of environmental infractions • Sanctioning of environmental crimes
  • 9. 8 Institutional Context | Policy Change  Pivotal conservation effort of 2000s • Plan for the Prevention and Control of Deforestation in the Amazon [PPCDAm]  Stricter monitoring and law enforcement • Real-Time System for Detection of Deforestation [DETER] • Satellite-based real-time monitoring
  • 10. 9 Institutional Context | How DETER Works National Institute for Space Research Remote Sensing Center
  • 11. 10 Institutional Context | How DETER Works before after
  • 12. 11 Institutional Context | How DETER Works
  • 13. 12 Institutional Context | How DETER Works National Institute for Space Research Remote Censing Center
  • 14. 13
  • 15. 14
  • 16. 15
  • 17. 16 Institutional Context | How DETER Works  Targeting before DETER • Voluntary reports of deforestation activity  Targeting after DETER • Satellite imagery: 3-day intervals, year-round • More timely law enforcement action … significant improvement in Amazon monitoring and law enforcement capability  DETER is incapable of capturing land cover patterns beneath cloud coverage
  • 18. 17 Institutional Context | How DETER Works Jan 2011 Jul 2011 Oct 2011 Apr 2011
  • 19. 18 Agenda  Introduction  Institutional context  Methodology  Key findings  Policy implications  CPI Rio projects  Q&A
  • 20. 19 A Word on Methodology  Goal: identify causal effect of Ibama’s presence on deforestation activity • Environmental fines as measure of Ibama’s presence  Challenge: address two-way causality monitoring and law enforcement deforestation
  • 21. 20 A Word on Methodology  Use DETER cloud coverage as source of exogenous variation in law enforcement • What does this mean? • For a given area, systematically: Greater DETER cloud coverage Lower chance of DETER issuing alert Lower chance of Ibama targeting the area Lower intensity of monitoring and law enforcement … unrelated to deforestation!
  • 22. 21 Agenda  Introduction  Institutional context  Methodology  Key findings  Policy implications  CPI Rio projects  Q&A
  • 23. 22 Results | Key Findings  DETER cloud coverage affects Ibama’s presence • Lower cloud coverage leads to greater number of fines  Ibama’s presence affects deforestation activity • Greater number of fines in current year leads to lower deforestation in following year • Deterrent effect dissipates over time cloud coverage monitoring and law enforcement deforestation less more less
  • 24. 23 41.6 101.1 59.5 0 20 40 60 80 100 120 140 160 180 observed estimated deforestation(thousandkm2) Results | What Does This Mean?  What if Amazon monitoring and law enforcement capability had not improved starting in 2004? total deforestation, 2007- 2011
  • 25. 24 41.6 164.3 122.7 0 20 40 60 80 100 120 140 160 180 observed estimated deforestation(thousandkm2) Results | What Does This Mean?  What if Amazon monitoring and law enforcement had been entirely inactive? total deforestation, 2007- 2011
  • 26. 25  Simulation 1: 59,500 km2 • ≈ 2/3 area of Portugal  Simulation 2: 122,000 km2 • ≈ area of Nicaragua • Avoided emissions equivalency: 900 million tCO2 per year • ½ US 2011 transport sector emissions • 2.5–3 times average annual emissions savings from European renewables sector Results | What Does This Mean?
  • 27. 26 Results | Worth It?  Cost-benefit analysis 24,500 km2 average forest area preserved per year 900 million tCO2 avoided emissions per year 560 million USD 125 million USD annual budgets for Ibama and INPE 685 million USD annual budget for Amazon monitoring and law enforcement benefit cost 0.76 USD/tCO2 break-even price of carbon low monetary cost 5 USD/tCO2 common current price of carbon >>
  • 28. 27 Results | Key Findings  Tradeoff between economic growth and preservation?  Ibama’s presence does not affect local agricultural production • Greater number of fines has no impact on local agricultural GDP or crop production low agricultural cost
  • 29. 28 Agenda  Introduction  Institutional context  Methodology  Key findings  Policy implications  CPI Rio projects  Q&A
  • 30. 29 Policy Implications  Maintain Amazon monitoring and law enforcement efforts • Strong deterrent effect at relatively low cost • Need for continuous policy action • Complementary nature of other conservation policies  Promote strategic use of technology and information • Improve monitoring technology • Further enhance law enforcement capability
  • 31. 30 Agenda  Introduction  Institutional context  Methodology  Key findings  Policy implications  CPI Rio projects  Q&A
  • 32. 31 CPI Rio Projects | Land Use  Deforestation • Prices or policies? • Conditional rural credit • Monitoring and law enforcement • Net impact of protected areas • Socioeconomic impact of conservation policies • Forest clearing behavior  Agriculture • Enhanced productivity • Technological adoption • Insurance for rural producers
  • 33. 32 BRAZIL CHINA EUROPE INDIA INDONESIA UNITED STATES Estrada da Gávea, 50 – 4o andar Gávea – Rio de Janeiro – RJ 22451-263 Brazil climatepolicyinitiative.org Questions? for full paper and executive summary, click here clarissa@cpirio.o rg