IEA - Queimadas na Amazônia e seus efeitos no ecossistema e na saúde da população
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IEA - Queimadas na Amazônia e seus efeitos no ecossistema e na saúde da população

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Evento organizado pelo IEA polo Ribeirão Preto - USP. ...

Evento organizado pelo IEA polo Ribeirão Preto - USP.

Tema: Queimadas na Amazônia e seus efeitos no ecossistema e na saúde da população

Palestra do Prof. Dr. Paulo Artaxo Netto

Realizada em 26/08/2011

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IEA - Queimadas na Amazônia e seus efeitos no ecossistema e na saúde da população IEA - Queimadas na Amazônia e seus efeitos no ecossistema e na saúde da população Presentation Transcript

  • Instituto de Estudos Avançados, USP Ribeirão Preto 26/Agosto/2011 Prof. Paulo Artaxo Institute of Physics,University of São Paulo, Brazil artaxo@if.usp,br
  • Focus of the Large Scale Biosphere Atmosphere Experiment in AmazoniaSome key issues that are important from the scientific, publicpolicies and conservation in Amazonia:• Carbon cycling and the physiological and climatic controls• Atmospheric chemistry in terms of oxidants and biosphere-atmosphere interactions (O3, VOCs, NOx, etc)• Aerosol-clouds interactions and aerosol radiative forcing• Land Use Change and its effects, including carbon cycling, biomass burning emissions, modeling and social drivers.• Role of disturbances (droughts of 2005 and 2010)• Effects of climate change in Amazonia
  • 26 years ago… View slide
  • Tropical deforestation drivers View slide
  • Net CO2 Emissions from LUC in Tropical Countries 600 2000-2005 RA Houghton 2009, CO2 emissions (TgC y-1) 500 Brazil 60% 400 Indonesia 300 Cameroon Colombia Venezuela 200 Nicaragua Peru Rep.Dem.Congo India 100 Nigeria Philippines Nepal 0 4-2% 2-1% <1%Land use change was responsible for estimated net emissions of 1.5 PgC per year over thelast 15 years.This is 12% of total emissions in 2008, down from 20% in the 1990´s
  • Forest clearing and forest cover in the humid tropical forest biome, 2000–2005Forest loss in Brazil accounts for 48% of total biome clearing, nearly four times thatof the next highest country, Indonesia, which accounts for 13%. Hansen M. C. et.al. PNAS 2008
  • Deforestation was reduced from 27,000 Km² in 2004 to 7,000 Km² in 2010. A very dynamical system, and we need to know what effects on the ecosystem these changes have produced Deforestation in Amazonia 1977-2009 in km² per year 35000 30000 27.000 Km² in 2004Desflorestation (km² per year) 25000 20000 15000 7.000 Km² in 2010 10000 5000 0 88/89 89/90 90/91 91/92 92/94 94/95 95/96 96/97 97/98 98/99 99/00 00/01 01/02 02/03 03/04 04/05 05/06 06/07 07/08 08/09 77/88* * annual average per decade Data from INPE, 2009 What public policies are needed to sustain this reduction?
  • Brazilian Greenhouse Gases Emission Inventory 2005 24 56 12 5 3 Deforestation Agrobusines Energy+Transport Industry Landfills MCT Feb 2010Copenhagen Commitment: Reduction in 80% emissions from deforestationin 2015 from 2004. Same target in the Brazilian law passed in Congress.
  • Current pyrogeography on Earth, illustrated by (A) net primary productivity (NPP, g C NPP m-2 year-1) from 2001 to 2006, and (B) annual average number of fires observed by satellite FiresBowman et al., Science, 2009
  • Global Deforestation Fires: Responsible for 19% of global radiative forcing Estimated contribution of fire associated with deforestation to changes in radiative forcing compared to 1750, assuming a steady state for other fire emissions.Bowman et al., Science, 2009
  • Global Distribution of Carbon Monoxide (CO) from MOPPIT
  • (mm) (b) Santarem k67 (oC) (mm) (a) Manaus k34 (oC) 28 28 300 27 300 26 27 200 25 200 26 24 100 100 23 25 0 22 Jan Mar May Jul Sep Nov 0 24 Jan Mar May Jul Sep Nov (mm) (c) Santarem k83 (oC) 28 300 27 26 200 25 (d) Jarú (JRU)(mm) (oC) 24 100 28 23300 27 0 22 Jan Mar May Jul Sep Nov 26200 25 24100 23 0 22 (mm) (e) Javaés (JAV) (oC) Jan Mar May Jul Sep Nov 29 300 28 200 27 (mm) (f) Sinop (SIN) (oC) 400 27 26 LBA Flux Towers 100 26 25 300 0 24 25 Jan Mar May Jul Sep Nov 200 24 100 23 Climatological 0 22 (mm) (g) Pé deGigante (oC) precipitation (mm mo-1) Jan Mar May Jul Sep Nov (PEG) 26 Top tower 300 24 precipitation (mm mo-1) 200 22 Climatological temperature (oC) 20 100 Top tower 18 temperature (oC) 0 16 Jan Mar May Jul Sep Nov Rocha et al. 2010
  • 8 7.5 7 6.5 LBA/RAINFOR - Aboveground 6 Soil pH 5.5 5 wood production for 97 sites 4.5 4 3.5 3 0 500 1000 1500 2000 2500 Malhi et al, 2010 Distance from Andes (km) Above-Ground Wood Production (t C ha-1 year-1) 6 Ecuador 5 S Peru 4 N Peru Growth Bolivia Venezuela 3 Guyanas Brazil 2 1 0 PAK-03 PAK-02 BNT-07 BNT-04 BDF-01 BDF-10 BDF-14 BDF-09 BDF-13 BDF-12 BNT-05 HCC-21 RIO-01 LSL-02 LSL-01 TAP-02 TAP-01 TAP-03 TIP-03 CEL-15 ELD-03 TAM-04 SUC-02 TAM-05 TAM-07 LIN-01 CRP-01 TAM-02 SCR-02 SCR-01 SCR-03 MNU-04 MNU-03 MNU-06 MNU-01 JEN-06 JEN-09 ALP-22 JEN-10 CYB-01 YAN-01 CAX-02 CUZ-04 CUZ-03 BCI-50 NOR-01 BCI-01 JAS-03 JAS-02 SiteForest in Amazonia are accumulating carbon at a rate of about 0.7 tC/ha/year from 1998-2010
  • WP4 EOS projectAmazonicaWP3 BiomassWP2 EcosystemWP1 Atmosphericapproach touse fluxesmeasure inventories land concentrationsregional carbon balance
  • CO2 flux – tropical forest Santarem (k83)CO2 fluxes: annual sum is prone to Reco ~ Respiration uncertainties (nighttime flux) Miller 2004, Ecol Appl; Goulden 2004 Ecol Appl, 2006 JGR Saleska 2003, Science; Hutyra 2007 JGR GPP ~ daytime flux – Reco High numbers are observed in the tropics (Miller 2004, Ecol Appl) Reco u*filtered Reco Dry season Wet season GPP sink loss... but leads to a reasonable (Humberto Rocha, USP, 2011) interpretation of seasonality
  • 320 meters tall tower in Amazonia for long term monitoring of trace gases and aerosols
  • Two plots with rain exclusion (drought experiments) in AmazoniaIntact forests seem resilient to substantialseasonal drought, but begin to die back afterseveral successive years of droughtNepstad et al (2007), Ecology, Fisher et al. (2007), Global Change Biology, Brando et al(2008), Philosophical Transactions of the Royal Society B, Sotta et al. (2008), GlobalChange Biology
  • Two strong droughts in 2005 and 2010: Variability of Rio Negro during drought years Rio Negro mean water levels (m) at Manaus-AM during drought years 1963 2005 2010 Lowest levels at Manaus
  • Response to interannual drought Model-Predicted Response Empirical Test: the 2005 drought Hadley modeled GPP & precip in central Tropical Rainfall Measuring Mission (TRMM) Amazonia in years relative to El Nino drought satellite precip anomalies in 3rd quarter 2005Forest Photosynthesis 30 (Mg C ha-1 yr-1) 20 El Nino Drought 10 Precip (mm mo-1) (Jones et al., 2001) 200 100 0 1 2 3 4 5 6 7 8 Years: -3 -2 -1 0 1 2 3 4 (Saleska et al., Science, 2007)
  • Drought sensitivity of the Amazon RainforestAnnual aboveground biomass changeduring the 2005 interval. Effect of the 2005 drought in the carbon balance in Amazonia Phillips et al. 2009 Science
  • Drought of 2010 in AmazoniaManaus river level for 2005 and 2010Spatial patterns of standardized anomalies ofnormalized difference vegetation index (NDVI)and enhanced vegetation index (EVI). Xu et al., GRL 2011
  • Aerosol-clouds interactions and aerosol radiative forcing• Optical, physical properties and chemical composition of biomass burning aerosols• Properties of natural biogenic aerosols• Cloud Condensation Nuclei (CCN) properties• Long term measurements of ground, vertical distribution and column integrated optical properties• Clouds physical properties and distribution coupled with cloud droplets microphysical properties.
  • Aerosol Particles: Coupling of Terrestrial Ecosystems and the Hydrologic Cycle Energy and Water Exchange and Processing
  • Large scale aerosol distribution inAmazonia• Severe health effects on the Amazonianpopulation (about 20 million people)• Climatic effects, with strong effects oncloud physics and radiation balance.• Changes in carbon uptake andecosystem functioning
  • Amazonia - Average aerosol forcing clear sky Top: - 10 w/m² Atmosphere: + 28 w/m² Surface: - 38 w/m²Conditions: surface: forest vegetation AOT (=0.95 at 500nm); 24 hour average 7 years (93-95, 99-02 dry season Aug-Oct)
  • Hydrological cycle critical for Amazonia.Variety of cloud structure causedby different CCN amounts andother cloud dynamic issues Pyrocumulus Clouds “Green Ocean Clouds“
  • Aerosol-cloud-precipitation feedbacks CCN = cloud condensation nuclei and IN = ice nuclei. AEROSOLS CCN Activation Ice Nuclei ActivationCloud/Aerosol Cloud Microphysics Radiative TransferCloud Dynamics PRECIPITATION Aerosol Wet Removal
  • Cloud Physics in the Pristine Atmosphere
  • Suppression of low cloud formation by aerosols in AmazoniaCloud fraction as function of aerosol optical depth (OD)..On average, the cloud fraction decreases to less than 1/8 of the cloud fraction in clean conditions whenOD = 1. (Koren and Kaufman, 2003)
  • Relationships between cloud properties and aerosol loading in Amazonia Microphysics absorption effects Aerosol Optical ThicknessKoren et al., Science 2008
  • Ice nuclei from biogenicemissions and Sahara dust inCentral AmazoniaDust relation to ice-nucleus measurements. Dustconcentrations during AMAZE-08. a, GEOS-Chemsimulated dust from 2–6 March at 18 UTC. The fieldsite, shown as a black diamond, typically fell near theedge of the plumes. Fine-dust concentrations fromPIXE measurements (black rectangles; µg/m³,dp<2µm.
  • Precipitação na Amazônia em mm/mês
  • Rainfall trends in the Brazilian Amazon 1925-2008: Decreasing at Pará and Amazon states? Annual Wet DrySatyamurty et al., 2010
  • Rainfall trends in the Brazilian Amazon 1925-2008: increasing?Satyamurty et al., 2010
  • Rainfall trends in the Brazilian Amazon 1925-2008: whole region No biomass burning smoke Heavy biomass burning smoke Annual Wet DrySatyamurty et al., 2010
  • Aerosol effects on the Net Plant ProductivityCO2 Concentration Aerosol Concentration + - + Temperature + + + Photosynthesis +? BVOC emissionsKulmala et al., 2004
  • Strong aerosol effect on forest photosynthesis diffuse radiation have a large effect on CO2 fluxes Amazonia Rondonia Forest site 2000-2001 Dry Season - NEE increase: 46 % 0 Wet Season - NEE increase: 24 % NEE (µmolm s ) -2 -1 -10 -20 -30 Increase in aerosol loading 0.0 0.2 0.4 0.6 0.8 1.0 Relative Irradiance
  • Amazon shortwave aerosol radiative forcing (SWARF) at the top of the atmosphere (TOA) from 2000 to 2009 using shortwave (SW) flux at the TOA from the CERES sensor and AOD from MODIS. Table 1 – Shortwave aerosol radiative forcing for Amazon region during the biomass burning season of the years 2000 to 2009. Year Valid Cells SWARF (W/m2) 2000 1163 -12.3 + 12.5 2001 1492 -8.1 + 13.3 2002 1447 -12.8 + 11.8 2003 1392 -12.0 + 12.5 2004 185 -13.4 + 17.6 2005 1799 -15.0 + 13.4 2006 1654 -9.5 + 12.9 2007 1731 -13.9 + 17.1 AERONET time series of the aerosol optical depth at 2008 1665 -8.2 + 15.9 500 nm from 2000 to 2009 over two Amazon sites: 2009 1405 -4.7 + 11.0 Alta Floresta and Rio Branco. Average -10.6 + 4.2
  • Large scale radiative forcing in Amazonia from 2000 to 2007 CERES (Clouds and the Earths Radiant Energy System) and MODIS
  • Effects of climate change in Amazonia Complex Earth System Models are needed to study all these interacting and simultaneous drivers LUCC Climate Fire Change Climate Nobre et al., 2011 ExtremesEcosystems of Amazonia - environmental drivers of change
  • Warming of 0.8°C in Amazonia (Victoria et al., Total deforested area (clear-cutting) is 730,000 km22004. J Climate); IPCC AR4: 3°C to > 5°C in 2100! in Brazilian Amazonia (18%) (INPE, 2008) GLOBAL WARMING DEFORESTATION Anthropogenic and Natural Drivers of Environmental Change in Amazonia DROUGHTS FOREST FIRES Droughts (e.g., 2005) can become frequent (Cox et al., 2008 Nature) Forest fire frequency ↑ (Nepstad et al., 2006)
  • What direction the Brazilian agriculture will take?The socio-economic drivers matters a lot!!!
  • Impacto das Queimadas na saúde da população amazônicaOs primeiros estudos tiveram início em 1992 com medidas de material particulado e Hg gasoso com o objetivo de identificar a composição físico química, concentrações, tamanho da partícula e as propriedades toxicológicas da fumaça.
  • Quais os riscos da exposição humana à fumaça? Quais poluentes ?Qual a magnitude da exposição?O risco é o mesmo para todos ? Qual o custo-benefício do controle?
  • Efeitos significativosPeríodo chuvoso sobre a saúde humana8 a 10 µg.m³ Exposição de elevada100 a 300 partículas cm³ magnitudePeriodo seco100 a 300 µg.m-³15.000 a 30.000partículas cm-³ Combustão de partículas, Brônquio s Cabelo humano compostos orgânicos, etc Bronquíolos Bronquíolos respiratóri Poeira, pólen, etc os Alvéolos Areia fina de praia
  • Mass concentration (μg/m³) 23 -A 100 200 300 400 500 600 0 08 ug -S -9 25 ep 2 -S -9 31 ep 2 -O -9 12 ct- 2 -J 9 urbana 20 a n 2 -A -9 p 3 13 r-9 n=735 31 -Ju 3 -A l-9 08 ug 3 -S -9 26 ep 3 -N -9 23 ov 3 -M -9 21 ar 3 - -9 19 Ju n 4 -A -9 15 ug - 4 -O 9 07 ct 4 -F -9 25 eb 4 -M -9 05 ay 5 -A -9 24 ug 5 -A -9 05 ug 5 -N -9 12 ov 5 -M -9 24 ar 5 -A -9 01 ug 6 -S -9 09 ep 6 -S -9 04 ep 6 -O -9 30 ct 6 -M -96 28 ar- 9 16 -Ju 7 -A l-9 29 ug 7 -S -97 07 ep -N -9 03 ov 7 -J -9 19 a n 7 -A -9 p 8 20 r-9 24 -Ju 8 -A l-9 03 ug 8 -S -98 09 ep - -9 12 Oct 8 -N -9 28 ov 8 -J -9 29 a n 8 -M -9 Amazônia Subequatorial 07 ar 9 -J -99 u 14 n-9 19 -Ju 9 -A l-9 16 ug 9 Alta Floresta Aerosol Mass Concentration 1992-2001 -S -99 25 ep -O -9 Exposição humana não necessariamente ocorre no local da queima. Efeito na área 02 ct 9 -F -9 24 eb 9 -A -00 p 11 r-0 - 0 Fine Mode 21 Ju l -O -00 22 ct -A -0 Coarse Mode 15 pr- 0 -S 01 ep -0 1 Queimadas e Doenças na Amazonia AF 2000 - 2005 apresentou os piores mortalidade por doenças Amazônia Subequatorial respiratórias no período deindicadores de morbidade e
  • Poluição do Ar – Efeitos na Saúde Mortalidade Hospitalização Visitas de emergência (PS) gravidade do Visitas médicas efeito Redução da atividade física Uso de medicação Sintomas respiratórios Alteração na função pulmonar Efeitos sub-clínicos Proporção da população afetada
  • Efeitos das Queimadas na Saúde Média das taxas de internação por asma em menores de cinco anos (por 10.000) dos municípios maiores de 25 mil habitantes do estado de Mato Grosso: 2000 - 2005 média asma 2000-2005 Alta Floresta 349,7 Colíder 265,3 Juína 173,0 Sorriso 120,4 Sinop 82,1 Cuiabá 21,2Tangará da Serra 11,2 0,0 50,0 100,0 150,0 200,0 250,0 300,0 350,0 400,0
  • Média das taxas de internação por pneumonia em menores de cinco anos (por 10.000) dos municípios < de 25 mil habitantes em MT 2000 - 2005 média_pneumoniaTangará da Serra 1578,0 Tangará da Serra Alta Floresta 757,0 Colíder 736,7 Sinop 363,0 Juína 261,5 Sorriso 189,7 Cuiabá 189,1 0,0 500,0 1000,0 1500,0 2000,0
  • RESULTADOS DOS ESTUDOSEstudo de Asma and Alergias em escolares(ISAAC – fase I) na região de Alta Floresta e Tangara da Serra 6370 estudantes Maior prevalência de asma na região foi em meninos (6-7 anos) > 20%
  • Estimativas da redução do fluxo expiratorio - peak flow( l/min) para cada aumento de 10 μg/m3 PM2.5 para todosos estudantes Redução do fluxo de 0.31 and 0.34 l/min para a exposição ao PM2.5 no mesmo dia e de 0.18 - 0.21 l/min para efeitos acumulados de dois dias.
  • São Paulo State sugar canebiomass burning:Also large atmospheric impactsSignificant health impactsChange in nutrient depositionChange in the hydrological cycle.
  • Obrigado pela atenção!!!
  • Examples of the spatial distribution of the SWARF at TOA 2005 2005 SWARF (W/m2) AOD 2008 2008 SWARF (W/m2) AODThe higher the AOD the higher is the correlation between SWARFand AOD. For lower AOD values the influence of other parameters such as the surface reflectance also become important.
  • Impact of Manaus City on the Amazon Green Ocean atmosphere: aerosol and ozone production, precursor sensitivity and transport Kuhn et al., ACPD 2010
  • Potential Vegetation Simulated by the PVM2.0Reg (50 km)Figure 1. Natural vegetation reference map [Salazar, 2009] and actual potential vegetation simulated byCPTEC•PVM2.0Reg model under the 1961–1990 mean climate. The division of the Amazon domain is -indicated by the continuous box in the natural vegetation map. Region 1: Southeast (5.25°S–13.75°S;50.75°W–63.75°W); Region 2: Northeast (4.75°N–5.25°S; 50.75°W–63.75°W); Region 3: Northwest(4.75°N–5.25°S; 63.75°W; 75.25°W); Region 4: Southwest (5.25°S–13.75°S; 63.75°W–75.25°W). Salazar and Nobre, 2010 GRL
  • Potential Dominant Biome in Response to ∆T, ∆P and CO2 “fertilization” effect Figure 2. Potential dominant biome simulated by CPTEC• - PVM2.0Reg for different temperature anomalies, precipitation changes, and fertilization effects (0%, 25% and 100%) for SRES A2 climate scenario for the period 2070– 2099, and for the regions of Amazonia (indicated in Figure 1): (a–c) southeast, (d–f) northeast, (g–i) northwest and (j–l) southwest Amazonia. The climate anomalies projected by regional (ETA CCS, RegCM3 and HadRM3P) and selected global (GISS• ]ER, ECHAM5, HadCM3 and M: average of fifteen global models from IPCC) models plotted for each region. Salazar and Nobre, 2010 GRL