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Motivation Objective Conceptual Framework Methodology Results Conclusions Impact of reducing the pre harvest burning of sugar-cane area on respiratory health in Brazil Alexandre Nicolella Department of Economics University of S ao

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Motivation Objective Conceptual Framework Methodology Results Conclusions

Impact of reducing the pre harvest burning

  • f sugar-cane area on respiratory health in

Brazil

Alexandre Nicolella

Department of Economics University of S˜ ao Paulo, Ribeir˜ ao Preto MGG n.7

University of Kent 2010

Alexandre Nicolella 2010 c

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Motivation Objective Conceptual Framework Methodology Results Conclusions Biofuel: Brazil and World Reasons for Ethanol Demand in Brazil Two System of Production Consequences of Sugar Cane Production Health Consequences of Sugar-Cane Production

Biofuel: Brazil and World

Renewable sources: sugar-cane, corn, cellulose and woody crops etc Projections 5% of the liquid fuels by 2025 Brazil: 34% of the world ethanol production in 2009 Brazil consumption: Ethanol 22, 823 103m3 Gasoline 19, 057 103m3 (2009) Sugar-cane products: 18.1% of the Brazilian energy matrix

Alexandre Nicolella 2010 c

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Motivation Objective Conceptual Framework Methodology Results Conclusions Biofuel: Brazil and World Reasons for Ethanol Demand in Brazil Two System of Production Consequences of Sugar Cane Production Health Consequences of Sugar-Cane Production

Reasons for Ethanol Demand in Brazil

30 years of investment in R&D for industrial and agricultural ethanol sector

Productivity: from 34t.ha−1 in 1960 to 69t.ha−1 in 2006 Ethanol cost: from US$ 980m3 in 1975 to US$ 260-305m3 in 2004

Rise of oil prices and the decline of ethanol prices

Producer price: ethanol US$ 301m3 and gasoline US$ 502m3 (2009)

Flex fuel technology

Flex-fuel light-cars sold: from 39% in 2005 to 87% in 2009

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Motivation Objective Conceptual Framework Methodology Results Conclusions Biofuel: Brazil and World Reasons for Ethanol Demand in Brazil Two System of Production Consequences of Sugar Cane Production Health Consequences of Sugar-Cane Production

Two System of Production

Sugar-cane area: from 4.9 (2000) to 8.2 million ha (2008) = ⇒ g.r. 6.7% a year Sugar-cane is a semi perennial culture Mechanical harvest of the raw sugar-cane Manual harvest with previous burning of sugar-cane State of S˜ ao Paulo: 56% of the sugar-cane area was harvested raw (2009)

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Motivation Objective Conceptual Framework Methodology Results Conclusions Biofuel: Brazil and World Reasons for Ethanol Demand in Brazil Two System of Production Consequences of Sugar Cane Production Health Consequences of Sugar-Cane Production

Consequences of Sugar Cane Production

Labor market Water pollution Green house gases emission Soil degradation Health

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Motivation Objective Conceptual Framework Methodology Results Conclusions Biofuel: Brazil and World Reasons for Ethanol Demand in Brazil Two System of Production Consequences of Sugar Cane Production Health Consequences of Sugar-Cane Production

Health Consequences of Sugar-Cane Production

Sugar-cane on air pollution: Andrade et al. (2010); Lara et al (2005) and Allen et al (2004)

⇑ Fine particulate matter (PM2.5) ⇑ Coarse particulate matter (CPM) ⇑ Black Carbon concentration (BC) ⇑ Nitrite, sulfite, oxide of carbon

Alexandre Nicolella 2010 c

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Motivation Objective Conceptual Framework Methodology Results Conclusions Biofuel: Brazil and World Reasons for Ethanol Demand in Brazil Two System of Production Consequences of Sugar Cane Production Health Consequences of Sugar-Cane Production

Health Consequences of Sugar-Cane Production

Sugar-cane and health

Arbex et al (2000) and Arbex et al (2007)

City of Araraquara (SP) using data from 1995 and 2003 (respectively) found a positive impact of sugar cane on inhalation and asthma admission

Canc ¸ado (2006)

City of Piracicaba (SP) using data from 1997/98 found a positive impact of sugar cane burning and child and elderly admission due to respiratory diseases

Uriarte et al (2009)

State of S˜ ao Paulo using data from 2003 found a positive impact of fire occurrence on child and elderly admission due to respiratory diseases

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Motivation Objective Conceptual Framework Methodology Results Conclusions Objective

Objective and contribution

Objective Measure the impact of the increasing of raw sugar-cane harvesting area on inpatient and outpatient visits due to respiratory diseases on the state of S˜ ao Paulo” Contribution Raw sugar-cane harvested area Other sources of pollution as car and industries Incorporating socio-economics variables Health system supply Control for health private sector

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Motivation Objective Conceptual Framework Methodology Results Conclusions Conceptual Framework

Human Capital Model - Grossman (1972) and Cropper (1981)

For a municipality the average health capital variation will be: ∆Ht+1 = Ht+1 − Ht = It − δtHt (1) The average rate of decay or depreciation of health capital in a municipality: δt = f(St, Ψt) (2) The municipality per capita investment in health capital: It = f(th

t , Mt, Et, Υ)

(3) The mean marginal cost to invest in health: πt = f(Wt, PM

t )

(4)

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Motivation Objective Conceptual Framework Methodology Results Conclusions Conceptual Framework

Human Capital Model - Results

Model results Individuals in polluted area will choose to keep a lower level of health capital and will present more incidences of illness Model results Individual in long term polluted areas can undertaken some behaviors to minor the effect of this externality. Pollution can be endogenously determined.

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Motivation Objective Conceptual Framework Methodology Results Conclusions Study Region Data Base Econometric Specification

Region: S˜ ao Paulo State

State of S˜ ao Paulo: 60% of total Brazilian sugar-cane production in 2007/2008 More detailed socio-economic data base for municipalities State Law N. 11.241 of 2002 - gradually diminish the sugar cane burning 2007 Protocol that anticipate the abolishment of pre harvest burning of sugar-cane (2014/17)

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Motivation Objective Conceptual Framework Methodology Results Conclusions Study Region Data Base Econometric Specification

Data Base

Ht:

Inpatient visits per 1000 habitants and local of residence due to respiratory diseases; Outpatient visits due to inhalation procedure per 1000 habitants; Length of stay per local of residence due to respiratory diseases.

St

population density; percentage of population above 60 years; weather considered time invariant variable.

Ψo

t

total fleet 1000 units (2002) total industrial energy consumption 1000 MWh (2001)

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Motivation Objective Conceptual Framework Methodology Results Conclusions Study Region Data Base Econometric Specification

Data Base

Ψc

t

Raw sugar cane area in 1000 hectare.

th

t and Υ

Considered time invariant variable.

Mt and PM

t

Health professionals and nurses per 1000 habitants registered in the regional council for the municipalities; Percentage of population that is beneficiaries of private health plans

Et and Wt

Average of real salary for formal workers.

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Motivation Objective Conceptual Framework Methodology Results Conclusions Study Region Data Base Econometric Specification

Panel Model

The impact of increase raw sugar-cane harvested area on population respiratory health can be estimated as follow: hit = β1Ψc

it + β2Ψo it + β3Sit + β4Mit + β5Wit + εit

εit = uit + θi uit ∼ N(0, 1) (5) This model can control for the endogeneity caused by the individual (behavior) and municipality (weather) heterogeneity.

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Motivation Objective Conceptual Framework Methodology Results Conclusions Stability Inpatient visits Outpatient Visits and Length of Stay

Stability and sensibility of the model

Inpatient visits per 1000 habitants due to respiratory diseases Independent Vari- ables St St, Ψ St, Ψ, Mt St, Ψ, Mt , Et, Wt St, Ψ, Mt , Et, Wt FE model FE model FE model FE model FE model -SP Population density 0.00121 0.000615 0.00145 0.00101 0.00118 (0.00122) (0.00124) (0.00120) (0.00123) (0.00118) Population > 60

  • 147.6***
  • 125.4***
  • 75.54**
  • 66.84**
  • 66.36**

(21.37) (23.69) (31.93) (31.72) (31.91) Raw sugar-cane

  • 0.172***
  • 0.140***
  • 0.129***
  • 0.127***

(0.0379) (0.0355) (0.0355) (0.0355) Total fleet 0.00269*** 0.00342*** 0.00267***

  • 0.00246

(0.000949) (0.000893) (0.000955) (0.0154) Industry Energy 0.00128*** 0.00159*** 0.00161*** 0.00168*** (0.000421) (0.000457) (0.000423) (0.000428) Health professionals

  • 0.492**
  • 0.480**
  • 0.476**

(0.194) (0.191) (0.192) Private beneficiaries

  • 3.860**
  • 3.486*
  • 3.520*

(1.928) (1.904) (1.918) Salary

  • 0.00297**
  • 0.00301**

(0.00134) (0.00136) Constant 27.27*** 25.07*** 22.12*** 24.29*** 24.32*** (2.300) (2.514) (2.864) (2.933) (2.933) R-squared 0.113 0.130 0.145 0.152 0.152 Municipalities 644 643 643 643 642 Robust standard errors in parentheses *** p<0.01, ** p<0.05, * p<0.1 Alexandre Nicolella 2010 c

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Motivation Objective Conceptual Framework Methodology Results Conclusions Stability Inpatient visits Outpatient Visits and Length of Stay

Hospital admission per 1000hab - resp. diseases

Inpatient visits due to respiratory diseases -FE Model Variable Inpatient Inpatient priv. Inpatient < 15 Inpatient > 60 Population Density 0.00101

  • 0.00133

0.00282

  • 0.00229

(0.00123) (0.00215) (0.00214) (0.00360) Population > 60

  • 66.84**
  • 66.94**

(31.72) (33.88) Raw sugar-cane

  • 0.129***
  • 0.148**
  • 0.192**
  • 0.378***

(0.0355) (0.0678) (0.0772) (0.103) Total fleet 0.00267*** 0.00203 0.00271 0.00609*** (0.000955) (0.00349) (0.00283) (0.00233) Industry energy 0.00161*** 0.0168*** 0.00203** 0.00336*** (0.000423) (0.00203) (0.000864) (0.000860) Health professionals

  • 0.480**
  • 0.628***
  • 0.871***
  • 1.737***

(0.191) (0.221) (0.241) (0.429) Private beneficiaries

  • 3.486*

(1.904) Private beneficiaries <15

  • 2.275

(2.560) Private beneficiaries >60

  • 4.507

(8.136) Salary

  • 0.00297**
  • 0.00295*
  • 0.00294
  • 0.00863**

(0.00134) (0.00159) (0.00203) (0.00419) Constant 24.29*** 25.87*** 25.24*** 49.06*** (2.933) (3.236) (2.341) (4.641) Robust standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1 Alexandre Nicolella 2010 c

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Motivation Objective Conceptual Framework Methodology Results Conclusions Stability Inpatient visits Outpatient Visits and Length of Stay

Inhalation and LS - resp. diseases

Outpatient visits for inhalation per 1000hab and Length of Stay Variable Inhalation - FE inhalation - RE Length of stay - FE Population density

  • 0.0315
  • 0.00584

0.000421 (0.0523) (0.00956) (0.000385) Population <15 2,043*** 1,633*** (627.5) (298.7) Population >60

  • 10.59*

(5.470) Raw sugar-cane 0.701

  • 1.770

0.0106 (2.707) (2.327) (0.00996) Total fleet 0.0725

  • 0.0167

0.000690 (0.0882) (0.0418) (0.000657) industry energy

  • 0.122**
  • 0.0434

0.000350 (0.0483) (0.0411) (0.000264) Nurses

  • 6.053
  • 11.17***

(9.986) (4.106) Health professionals 0.0458 (0.0402) Private beneficiaries

  • 12.10

220.6** 0.456 (153.0) (109.0) (0.518) Salary 0.0316

  • 0.0794*
  • 0.000397

(0.0781) (0.0471) (0.000274) Constant

  • 61.17

136.6 6.166*** (222.4) (86.04) (0.554) Robust standard errors in parentheses; *** p<0.01, ** p<0.05, * p<0.1 Alexandre Nicolella 2010 c

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Motivation Objective Conceptual Framework Methodology Results Conclusions Conclusions

Conclusions

Pollution

Raw sugar-cane harvested area decrease the number of inpatient visits Total fleet and industrial energy consumption increases the number of inpatient visits Higher effect for young and elderly No effect on inhalation and length of stay

Environmental factors

Population over 60 decreases the number of inpatient visits Population under 15 years increases of inhalation per 1000 habitants

Alexandre Nicolella 2010 c

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Motivation Objective Conceptual Framework Methodology Results Conclusions Conclusions

Conclusions

Health goods

Health professionals decrease the number of inpatient visits and inhalation Large effect for young and elderly Private health plans beneficiaries decrease the number of inpatient visits

Salary

Salary decrease the number of inpatient visits and inhalation Especially for elderly

Alexandre Nicolella 2010 c

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