iea - queimadas na amazônia e seus efeitos no ecossistema e na saúde da população
DESCRIPTION
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 26/08/2011TRANSCRIPT
Prof. Paulo Artaxo
Institute of Physics,
University of São Paulo, Brazil
Instituto de Estudos Avançados,
USP Ribeirão Preto 26/Agosto/2011
Focus of the Large Scale Biosphere Atmosphere Experiment 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
Some key issues that are important from the scientific, public
policies and conservation in Amazonia:
26 years ago…
Tropical deforestation drivers
Net CO2 Emissions from LUC in Tropical Countries
2000-2005
0
100
200
300
400
500
600
Brazil
Indonesia
CO
2 em
issi
ons
(TgC
y-1
) RA Houghton 2009,
60%
Venezuela
Rep.Dem.Congo
Nigeria
4-2%
Cameroon
Peru
Philippines
2-1%
Colombia
Nicaragua
Nepal
India
<1%
Land use change was responsible for estimated net emissions of 1.5 PgC per year over the
last 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, 2000–2005
Hansen M. C. et.al. PNAS 2008
Forest loss in Brazil accounts for 48% of total biome clearing, nearly four times that of the next highest country, Indonesia, which accounts for 13%.
0
5000
10000
15000
20000
25000
30000
35000
77/8
8*
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
Desflore
sta
tion (
km
² per
year)
Deforestation in Amazonia 1977-2009 in km² per year
* annual average per decade Data from INPE, 2009
27.000 Km² in 2004
7.000 Km² in 2010
What public policies are needed to sustain this reduction?
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
Copenhagen Commitment: Reduction in 80% emissions from deforestation
in 2015 from 2004. Same target in the Brazilian law passed in Congress.
56
24
12
5
3
Deforestation Agrobusines Energy+Transport
Industry Landfills
Brazilian Greenhouse Gases Emission Inventory 2005
MCT Feb 2010
Current pyrogeography on Earth, illustrated by (A) net primary productivity (NPP, g C m-2 year-1) from 2001 to 2006, and (B) annual average number of fires observed by satellite
Bowman et al., Science, 2009
NPP
Fires
Estimated contribution of fire associated with deforestation to changes in radiative forcing compared to 1750, assuming a steady state for other fire emissions.
Global Deforestation Fires: Responsible for 19% of global radiative forcing
Bowman et al., Science, 2009
Global Distribution of Carbon Monoxide (CO) from MOPPIT
Climatological precipitation (mm mo-1)
Top tower precipitation (mm mo-1)
Climatological temperature (oC)
Top tower temperature (oC)
Jan Mar May Jul Sep Nov
0
100
200
300
(mm)
24
25
26
27
28
(oC)(a) Manaus k34
Jan Mar May Jul Sep Nov
0
100
200
300
(mm)
22
23
24
25
26
27
28
(oC)
(d) Jarú (JRU)
Jan Mar May Jul Sep Nov
0
100
200
300
(mm)
22
23
24
25
26
27
28
(oC)(c) Santarem k83
Jan Mar May Jul Sep Nov
0
100
200
300
(mm)
22
23
24
25
26
27
28
(oC)(b) Santarem k67
Jan Mar May Jul Sep Nov
0
100
200
300
(mm)
24
25
26
27
28
29
(oC)(e) Javaés (JAV)
Jan Mar May Jul Sep Nov
0
100
200
300
(mm)
16
18
20
22
24
26
(oC)(g) Pé deGigante (PEG)Jan Mar May Jul Sep Nov
0
100
200
300
400
(mm)
22
23
24
25
26
27
(oC)(f) Sinop (SIN)
Rocha et al. 2010
LBA Flux Towers
0
1
2
3
4
5
6
JEN
-06
CY
B-0
1
JEN
-09
HC
C-2
1
MN
U-0
4
CU
Z-0
4
JAS
-03
YA
N-0
1
CU
Z-0
3
PA
K-0
3
TA
M-0
4
BC
I-50
MN
U-0
3
JAS
-02
LS
L-0
2
SU
C-0
2
ALP
-22
CE
L-15
ELD
-03
TA
M-0
5
MN
U-0
6
TA
M-0
7
LIN
-01
NO
R-0
1
MN
U-0
1
RIO
-01
PA
K-0
2
CR
P-0
1
TA
P-0
2
BN
T-0
7
TIP
-03
BN
T-0
5
TA
M-0
2
TA
P-0
1
BN
T-0
4
TA
P-0
3
JEN
-10
SC
R-0
2
LS
L-0
1
BC
I-01
BD
F-0
1
BD
F-1
0
BD
F-1
4
BD
F-0
9
CA
X-0
2
BD
F-1
3
BD
F-1
2
SC
R-0
1
SC
R-0
3
Gro
wth
Site
Above-Ground Wood Production (t C ha-1 year-1)
Venezuela
Brazil
N PeruS Peru
Bolivia
Guyanas
Ecuador
LBA/RAINFOR - Aboveground
wood production for 97 sites
Malhi et al, 2010
3
3.5
4
4.5
5
5.5
6
6.5
7
7.5
8
0 500 1000 1500 2000 2500
Distance from Andes (km)
So
il p
H
Forest in Amazonia are accumulating carbon at a rate of about 0.7 tC/ha/year from 1998-2010
WP1 Atmospheric
concentrations
WP2 Ecosystem
fluxes
WP3 Biomass
inventories
WP4 EOS
land use
Amazonica project
approach to measure
regional carbon balance
(Humberto Rocha, USP, Emanuel Gloor, Leeds, 2011)
CO2 fluxes: annual sum is prone to uncertainties Miller 2004, Ecol Appl; Goulden 2004 Ecol Appl, 2006 JGR Saleska 2003, Science; Hutyra 2007 JGR
Reco
GPP
Reco ~ Respiration (nighttime flux)
GPP ~ daytime flux – Reco
High numbers are observed in the tropics (Miller 2004, Ecol Appl)
... but leads to a reasonable interpretation of seasonality
Reco u*filtered
Dry season
sink
Wet season
loss
CO2 flux – tropical forest Santarem (k83)
(Humberto Rocha, USP, 2011)
320 meters tall tower in Amazonia for long term monitoring of trace gases and aerosols
Intact forests seem resilient to substantial seasonal drought, but begin to die back after several successive years of drought Nepstad 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), Global Change Biology
Two plots with rain exclusion (drought experiments) in Amazonia
Rio Negro mean water levels (m) at Manaus-AM during drought years
1963
2010
2005
Lowest levels at Manaus
Two strong droughts in 2005 and 2010: Variability of Rio Negro during drought years
Response to interannual drought
1 2 3 4 5 6 7 8
10
20
30
0
100
200
For
est
Phot
osynt
hesis
(Mg
C h
a-1 y
r-1)
El Nino Drought
Hadley modeled GPP & precip in central Amazonia in years relative to El Nino drought
Model-Predicted Response
(Jones et al., 2001)
Years: -3 -2 -1 0 1 2 3 4
Precip
(mm m
o-1)
Empirical Test: the 2005 drought
Tropical Rainfall Measuring Mission (TRMM) satellite precip anomalies in 3rd quarter 2005
(Saleska et al., Science, 2007)
Annual aboveground biomass change during the 2005 interval.
Effect of the 2005
drought in the
carbon balance
in Amazonia
Phillips et al. 2009 Science
Drought sensitivity of the Amazon Rainforest
Spatial patterns of standardized anomalies of normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI).
Drought of 2010 in Amazonia Manaus river level for 2005 and 2010
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 in Amazonia
• Severe health effects on the Amazonian population (about 20 million people)
• Climatic effects, with strong effects on cloud physics and radiation balance.
• Changes in carbon uptake and ecosystem functioning
Conditions: surface: forest vegetation AOT (=0.95 at 500nm); 24 hour average 7 years (93-95, 99-02 dry season Aug-Oct)
Top: - 10 w/m²
Atmosphere: + 28 w/m²
Surface: - 38 w/m²
Amazonia - Average aerosol forcing clear sky
Pyrocumulus Clouds
“Green Ocean Clouds“
Hydrological cycle critical for Amazonia. Variety of cloud structure caused by different CCN amounts and other cloud dynamic issues
Cloud Microphysics
PRECIPITATION
CCN Activation
Cloud/Aerosol Radiative Transfer
AEROSOLS
Ice Nuclei Activation
Aerosol Wet Removal
Aerosol-cloud-precipitation feedbacks
Cloud Dynamics
CCN = cloud condensation nuclei and IN = ice nuclei.
Cloud Physics in the Pristine Atmosphere
Suppression of low cloud formation by aerosols in Amazonia
Cloud 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 when OD = 1. (Koren and Kaufman, 2003)
Relationships between cloud properties and aerosol loading in Amazonia
Koren et al., Science 2008
Microphysics absorption effects
Aerosol Optical Thickness
Dust relation to ice-nucleus measurements. Dust concentrations during AMAZE-08. a, GEOS-Chem simulated dust from 2–6 March at 18 UTC. The field site, shown as a black diamond, typically fell near the edge of the plumes. Fine-dust concentrations from PIXE measurements (black rectangles; µg/m³, dp<2µm.
Ice nuclei from biogenic emissions and Sahara dust in Central Amazonia
Precipitação na Amazônia em mm/mês
Satyamurty et al., 2010
Rainfall trends in the Brazilian Amazon 1925-2008: Decreasing at Pará and Amazon states?
Annual
Wet Dry
Satyamurty et al., 2010
Rainfall trends in the Brazilian Amazon 1925-2008: increasing?
Rainfall trends in the Brazilian Amazon 1925-2008: whole region
Satyamurty et al., 2010
No biomass burning smoke Heavy biomass burning smoke
Annual
Wet
Dry
Temperature
CO2 Concentration
Photosynthesis BVOC emissions
Aerosol Concentration
+
+
+
+ +
+?
-
Aerosol effects on the Net Plant Productivity
Kulmala et al., 2004
0.0 0.2 0.4 0.6 0.8 1.0
-30
-20
-10
0Wet Season - NEE increase: 24 %
NE
E (
µm
olm
-2s
-1)
Relative Irradiance
Dry Season - NEE increase: 46 %
Amazonia Rondonia Forest site 2000-2001
Strong aerosol effect on forest photosynthesis diffuse radiation have a large effect on CO2 fluxes
Increase in aerosol loading
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
2008 1665 -8.2 + 15.9
2009 1405 -4.7 + 11.0
Average -10.6 + 4.2
AERONET time series of the aerosol optical depth at
500 nm from 2000 to 2009 over two Amazon sites:
Alta Floresta and Rio Branco.
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.
Large scale radiative forcing in Amazonia from 2000 to 2007
CERES (Clouds and the Earth's Radiant Energy System) and MODIS
Ecosystems of Amazonia - environmental drivers of change
LUCC
Fire Climate Change
Climate Extremes
Complex Earth System Models are needed to study all these interacting and simultaneous drivers
Nobre et al., 2011
Effects of climate change in Amazonia
Total deforested area (clear-cutting) is 730,000 km2 in Brazilian Amazonia (18%) (INPE, 2008)
Anthropogenic and Natural Drivers of Environmental
Change in Amazonia
DROUGHTS FOREST FIRES
DEFORESTATION GLOBAL WARMING
Warming of 0.8°C in Amazonia (Victoria et al., 2004. J Climate); IPCC AR4: 3°C to > 5°C in 2100!
Forest fire frequency ↑ (Nepstad et al., 2006) Droughts (e.g., 2005) can become frequent (Cox et al., 2008 Nature)
What direction the Brazilian agriculture will take? The socio-economic drivers matters a lot!!!
Impacto das Queimadas na saúde da população amazônica
Os 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 significativos sobre a saúde humana
Exposição de elevada magnitude
Período chuvoso 8 a 10 µg.m³ 100 a 300 partículas cm³ Periodo seco 100 a 300 µg.m-³ 15.000 a 30.000 partículas cm-³
Brônquios Bronquíolos
Bronquíolos respiratóri
os
Alvéolos
(diâmetros em micrômetros) Areia fina de praia
Cabelo humano
Combustão de partículas, compostos orgânicos, etc
Poeira, pólen, etc
AF
Amazônia Subequatorial
Amazônia Subequatorial apresentou os piores
indicadores de morbidade e mortalidade por doenças
respiratórias no período de 2000 - 2005
Exposição humana não necessariamente ocorre no local da queima. Efeito na área urbana
Alta Floresta Aerosol Mass Concentration 1992-2001
0
100
200
300
400
500
600
23-A
ug-9
2
08-S
ep-9
2
25-S
ep-9
2
31-O
ct-9
2
12-J
an-93
20-A
pr-9
3
13-J
ul-93
31-A
ug-9
3
08-S
ep-9
3
26-N
ov-9
3
23-M
ar-9
4
21-J
un-94
19-A
ug-9
4
15-O
ct-9
4
07-F
eb-9
5
25-M
ay-9
5
05-A
ug-9
5
24-A
ug-9
5
05-N
ov-9
5
12-M
ar-9
6
24-A
ug-9
6
01-S
ep-9
6
09-S
ep-9
6
04-O
ct-9
6
30-M
ar-9
7
28-J
ul-97
16-A
ug-9
7
29-S
ep-9
7
07-N
ov-9
7
03-J
an-98
19-A
pr-9
8
20-J
ul-98
24-A
ug-9
8
03-S
ep-9
8
09-O
ct-9
8
12-N
ov-9
8
28-J
an-99
29-M
ar-9
9
07-J
un-99
14-J
ul-99
19-A
ug-9
9
16-S
ep-9
9
25-O
ct-9
9
02-F
eb-0
0
24-A
pr-0
0
11-J
ul-00
21-O
ct-0
0
22-A
pr-0
1
15-S
ep-0
1
Mass c
on
cen
trati
on
(μ
g/m
³)
Coarse Mode
Fine Mode
n=735
Queimadas e Doenças na Amazonia
Mortalidade
Hospitalização
Visitas de emergência (PS)
Visitas médicas
Redução da atividade física
Uso de medicação
Sintomas respiratórios
Alteração na função pulmonar
Efeitos sub-clínicos
Proporção da população afetada
gravidade do efeito
Poluição do Ar – Efeitos 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
11,2
21,2
82,1
120,4
173,0
265,3
349,7
0,0 50,0 100,0 150,0 200,0 250,0 300,0 350,0 400,0
Tangará da Serra
Cuiabá
Sinop
Sorriso
Juína
Colíder
Alta Floresta
Efeitos das Queimadas na Saúde
Tangará da Serra
média_pneumonia
189,1
189,7
261,5
363,0
736,7
757,0
1578,0
0,0 500,0 1000,0 1500,0 2000,0
Cuiabá
Sorriso
Juína
Sinop
Colíder
Alta Floresta
Tangará da Serra
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
Estudo de Asma and Alergias em escolares (ISAAC – fase I) na região de Alta Floresta
e Tangara da Serra
Maior prevalência de asma na região foi em meninos (6-7 anos) > 20%
6370 estudantes
RESULTADOS DOS ESTUDOS
Estimativas da redução do fluxo expiratorio - peak flow
( l/min) para cada aumento de 10 μg/m3 PM2.5 para todos
os 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 cane biomass burning: Also large atmospheric impacts Significant health impacts Change in nutrient deposition Change in the hydrological cycle.
Obrigado pela atenção!!!
Examples of the spatial distribution of the SWARF at TOA
SWARF (W/m2)
2005
AOD
2005
SWARF (W/m2)
2005
AOD
2005
SWARF (W/m2)
2008
AOD
2008
The higher the AOD the higher is the correlation between SWARF
and 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
Figure 1. Natural vegetation reference map [Salazar, 2009] and actual potential vegetation simulated by CPTEC•-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 Vegetation Simulated by the PVM2.0Reg (50 km)
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
Potential Dominant Biome in Response to ∆T, ∆P and CO2 “fertilization” effect