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Tercer Seminário Regional Agricultura e cambio Climático:Nuevas tecnologias em la mitigacion y adaptation de
La agricultura al cambio climatico
27 y 28 de septembre 2012
Sistemas de informacion para la gestion ambiental em la agricultura
Eduardo Delgado AssadEmbrapa - Brasil
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Una vision integral de la gestion ambiental, la gestion de riesgo y la
adaptation de la agricultura y los cambios climáticos
Eduardo Delgado AssadEmbrapa Informática agropecuária
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EVOLUTION OF BRAZILIAN MITIGATION TARGETS
NATIONAL CLIMATE CHANGE POLICY (PNMC)DECREE 7.390/2010
• Sanctioned right after COP-15, when the Brazilian government announced voluntary GHG emissions reduction targets, later included in the Copenhagen Accord.
• Sets up a reduction target between 36.1 and 38.9% in relation to the baseline projected to 2020.
–The baseline was calculated using data from the Second National Emissions Inventory released in 2010.
• Establishes sectoral mitigation and adaptation plans
• Defines the National Climate Change Fund (Climate Fund) as main financial instrument
• Regulated by Decree no. 7.390/2010.
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EVOLUTION OF BRAZILIAN MITIGATION TARGETS
NATIONAL CLIMATE CHANGE POLICYDECREE 7.390/2010
• According to Decree no. 7.390/2010, the revised National Climate Change Plan will be composed of the following sectoral mitigation plans:
–Action Plan for the Prevention and Control of Deforestation in the Legal Amazon (PPCDAm)
–Action Plan for the Prevention and Control of Deferestation and Wildfires in the Cerrado (PPCerrado)
–Ten Year Energy Plan (PDE, from 2007-2016)
–Low Carbon Agriculture Plan (Plan ABC), and
–Emissions Reduction in the Iron and Steel Industry.
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EVOLUTION OF BRAZILIAN MITIGATION TARGETS
NATIONAL CLIMATE CHANGE POLICYDECREE 7.390/2010
• Emissions projections in 2020: 3.236 millions tCO2-eq
• Reduction target:
–Art. 6: actions will be implemented in order to reduce between 1.168 milhões tCO2-eq and 1.259 milhões tCO2-eq of the total projected emissions
•1.168 millions tCO2-eq – 36,1%
•1.259 millions tCO2-eq – 38,9%
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source: INPE (2010)
Deforestation rate in the Amazon (thousands of Km2/ha)
Lowest deforestation rate since 2005
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Reducing emissions in the Amazon CO2 (million tons per year)
projectedemissionFor 2020
Reduction equivalent to 67% of projected emissions for 2020
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Related issues, but diferent nature
Each four years
Commitment by the UNFCCC(Specific Guidelines)
Estimates
Inventory
commitment made under Decree 7.390/2010 year
Monitoring
Actions associated with the SectorialPlans
?
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Sectoral Plans
In preparation:
- Transportation;- Industry;- Mining;- Health;- Aquaculture & Fisheries
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Monitoring and estimate Coordination
- Embrapa;- Unicamp;-Agriculture clima network.
Monitoring Centers Monitoring Centers
Focused on adaptation
Amazondeforestation
cerrados Energy Transportation
Industry Mining
Health Aquaculture & Fisheries
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Impactos y tendencias
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Tmax (Precis-A2) 2010 – media 1960-1990
8 a 6.5
6 a 5
4.5 a 3
2.5 a 1.5
1 a 0
-0.5 a -2
[⁰C]
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Tmax (Precis-A2) 2020 – media 1960-1990
8 a 6.5
6 a 5
4.5 a 3
2.5 a 1.5
1 a 0
-0.5 a -2
[⁰C]
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Tmax (Precis-A2) 2030 – media 1960-1990
8 a 6.5
6 a 5
4.5 a 3
2.5 a 1.5
1 a 0
-0.5 a -2
[⁰C]
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Tmax (Precis-A2) 2040 – media 1960-1990
8 a 6.5
6 a 5
4.5 a 3
2.5 a 1.5
1 a 0
-0.5 a -2
[⁰C]
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Análisis de riesgos climáticos
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Inicial
Vegetativ
o
Reproduccion Maduracionração
Kc
Zonification de riesgos climáticos
la capacidad de agua del suelo
Evapotranspiracion precipitacion
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Balance Hídrico Secuencial+
Análisis frecuencial de los resultados
Precipitacion
Diária
ETPPromedio decendial
Fecha de siembra
Tipo de suelo
Tamaño del Ciclo
Datos Fijos
Metodologia (1/2)
ISNA = ETR/ETM
Datos Variábles
AnoAno ValorValor
11 ISNA(Ano1ISNA(Ano1))
22 ISNA(Ano2ISNA(Ano2))
...... ......
NN ISNA(AnoNISNA(AnoN))
N Anos
X estaciones
La cartografiaDe lo ISNAFase III
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0 1 2 3 4 5 33 34 353ª fase fenológica
dias
ISNA
fISNA(x)
0
1
Isna= 65%
P
“critério”
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Resulta
• 44 culturas con zonificación hecha todos los años• Enlace directo con la ciencia , tecnología y las políticas
públicas• Parte de la evaluación de los impactos económicos
hecho con la base de la zonificación climática• 17 años de la política pública y la orientación del
crédito agrícola in ejecución• www.agritempo.gov.br
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Impactos del cambio climático sobre la agricultura
• simulación de ocho modelos diferentes (tres en downscale)
• cinco culturas• pastos• Período de 2010 a 2030
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Brazil Base Year 2010 PESSIMISTIC OPTIMISTICCROP
Planted Area 2009 (ha) 2020 (ha) ∆ (%) 2030 (ha) ∆ (%) 2020 (ha) ∆ (%) 2030 (ha) ∆ (%)
Cotton 814.696 775.508 -4,8 774.457 -4,9 777.019 -4,6 776.974 -4,6
Rice 2.904.702 2.688.658 -7,4 2.617.461 -9,9 2.615.513 -10 2.640.323 -9,1
Sugarcane 8.845.659 17.783.411 101 16.921.749 91 18.305.604 107 18.418.819 108
Bean
Summer season 2.612.240 1.161.420 -55,5 1.121.558 -57,1 1.197.625 -54,2 1.187.576 -54,5Autumn season 1.715.000 542.749 -68,4 519.370 -69,7 622.053 -63,7 586.677 -65,8
Mayze
Summer season 9.463.191 7.619.872 -19 7.376.636 -22 8.360.960 -12 8.226.524 -13
Autumn season 4.799.663 4.175.053 -13 4.063.815 -15 4.507.646 -6 4.455.642 -7
Soybean 21.761.782 16.472.685 -24 15.634.280 -28 18.882.508 -13 18.434.357 -15Rainfed Wheat 2.345.496 1.987.386 -15,3 1.877.438 -20 1.383.302 -41 1.613.835 -31,2
table synthesis
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Estrategia de Adaptación
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BR-16 siensien gene 2.5% Umidad del suelo
P58 (BR-16 concon gene)2.5% Umidad del suelo
Expresión de genes tolerantes a la sequía en soja
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0 1 4 5 7 8 9 10Anos
Cronograma para obtenção de uma variedade de soja
X
AB
Hibridação Avanço Seleção Ensaios Semente Semente Semente Produtorde de de genética básica certificada rural
gerações progênies competição fiscalizada(F2 a F4)* F5
A B
* Duas gerações ao ano
Caderno Caderno Registro Licenciamentode de SNPC
cruzamento avaliação
Tiempo para tener un cultivar adaptado
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CulturesPlant Breeding
Million US$/YEAR
BENEFITCOST
RICE 18.9 8,2
COTTON 21.1 10,7
COFFEE 57.8 15,4
BEAN 28.3 7,1
SOYBEAN 210.0 16,7
CORN 196.7 4,3
Costs/benefits of AdaptationPlant breeding – Year 2020
Total = US$532.8 million/year
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ManzanaManzana
Proyección: El Proyección: El aumento de la aumento de la
temperatura a 2temperatura a 2ooCC
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BananaBananaProyección: Proyección:
El aumento de la El aumento de la temperatura a temperatura a
2oC2oC
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Mes de noviembre Actual Mes de noviembre 2070
Mes de noviembre de 2070 con reducción del consumo de agua en 20%
Estratégia biotecnologica
Mes de noviembre 2070 con Ciclo de 110 dias
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Estrategia de MitigacionEstrategia de Mitigacion
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Emissions of CO2, CH4 and N2O in tonnes of CO2 equivalents by Brazilian agriculture for 1990, 1994, 2000 and 2005, according to the Second Brazilian Inventory of GHG Emissions and Removals (MCTI, 2011).
GrainsArea
Production and planted area with grain crops from 1990 to 2011
Brazilian agriculture has experienced a continuous increase in grain production, but with a limited increase in cropped area, which is attributed to technology adoption. This scenario has resulted in an increase in GHG emissions.
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A - Methane emissions
B - Nitrous oxide emissions
Nitrous oxide emissions represented about 35 % of the overall emissions from Brazilian agriculture
Brazilian GHG inventory for the agriculture sector (2005)
GHG estimates are based on IPCC 1996 guidelines (Tiers 1 and 2) especially for the N2O inventory.
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Arable crops Cattle ranching Biofuel production
N Fertilizer
Legume species
Grazing animals – excreta deposited on pasture
Vinasse frombioethanol production from sugarcane
Research are under way to develop emission factors for the different cropping environments in Brazil.
Issues under evaluation
IPCC direct EF = 1.25% IPCC direct EF = 2.0%
N2O CH4N2OInvestigated GHGs
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N2O fluxes measurement
Fonte :Bruno Alves Embrapa Agrobiologia
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Static chamber
Top-base typeW-40 x L-60 cm12 cm height8 cm inserted in soil
Rubber – aluminum coated top to improve insulation
The 20 mL glass vials are promptly evacuated (-80 kPa) to receive 25 mL of the chamber headspace sample taken by using polyethylene syringes
Fonte :Bruno Alves Embrapa Agrobiologia
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Sampling procedure
• Gas sampling once a day, always in the morning between 9:00 h and 10:00 h.
• Daily sampling during the first 10 days after fertilizer application.
• Most of the results were obtained from a crop season and not necessarily from a whole year.
Fonte :Bruno Alves Embrapa Agrobiologia
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Land useEvaluation
period1 (dias)
N-Fertilizer(source - kg N
ha-1)Soil type
EF based on reference area
(%)
Londrina, PR Red LatosolMaize, SP rotation (yr 1, 2) 136/141 Urea – 80 0.08/0.04Maize, zero tillage,ZT)(yr 1,
2)136/141 Urea – 80 0.13/0.08
Passo Fundo, RS
Dark Red Latosol
Wheat ZT rotation 137 Urea – 40 0.13Soybean/wheat ZT (yr 1, 2) 1 year Fert+Res –
120/1160.56/0.81
Soybean/wheat PC (yr 1, 2) 1 year Fert+Res – 126/133
0.47/0.52
Maize/wheat ZT 1 year Fert+Res – 162 0.41 Maize/wheat CT 1 year Fert+Res – 141 0.70 Sorghun/wheat ZT 1 year Fert+Res – 193 0.24 Sorghun/wheat CT 1 year Fert+Res – 193 0.29
Santo Antônio de Goiás, GO
Dark Red Latosol
Maize ZT rotation 140 Urea – 80 0.22Highland rice ZT (yr 1, 2) 133/132 Urea – 90 0.13/0.14Irrigated common bean ZT 149 Urea – 80 0.12
Seropédica, RJMaize CT 120 Urea – 50 0.16Maize CT 120 Urea – 100 Red-Yellow
Argisol 0.35
Maize CT 120 Urea – 150 0.33Elephant grass 180 Urea – 40 0.18Elephant grass 180 Urea – 80 0.22Elephant grass 180 Urea – 120 0.22Elephant grass 180 Urea – 160 0.37
Emission factor of N2O from Brazilian
agricultural systems
Emission factor of N2O from Brazilian
agricultural systems
Direct emission factor of N2O obtained in Brazil
General mean and confidence interval
0.30 % (0.20 – 0.47%)
Direct emission factor of N2O obtained in Brazil
General mean and confidence interval
0.30 % (0.20 – 0.47%)
Direct Emission Factor recommended
in the IPCC 2006 guidelines1% (0.3 – 3%)
Direct Emission Factor recommended
in the IPCC 2006 guidelines1% (0.3 – 3%)
Data from Embrapa Agrobiologia, Soybean, Wheat and Rice and Bean Centers
Data from Embrapa Agrobiologia, Soybean, Wheat and Rice and Bean Centers
Fonte :Bruno Alves Embrapa Agrobiologia
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N2O emissions derived from cattle excreta in pastures
IPCC: 2% of N-excreta is lost as N2O
Fonte :Bruno Alves Embrapa Agrobiologia
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Soil N2O emissions from cattle urine and faeces
Preliminary data indicates that the N2O direct emission factor for urine is between 1.2 to 1.4 % and for faeces it is between 0.1 to 0.2 %.
N2O-EF1 from “Tier 1” of IPCC guidelines is 2 % of the total N in cattle excreta .
For the Brazilian savannah region that concentrates about 40 % of cattle herd, the weighed average emission factor would vary from 0.5 to 0.7 %, assuming no more than 60% of excreted N is in the urine form.
Fonte :Bruno Alves Embrapa Agrobiologia
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0-50-5
30-4030-4020-3020-3010-2010-205-105-10
60-8060-80
40-5040-5050-6050-60
80-100 cm80-100 cm
Quantification of soil C stocks “Shovelometrics”
Trenches 120 cm depth
The soil density must be measured accurately to correct for differential compaction
Fonte : Robert Boddey Embrapa Agrobiologia
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Region Veg. Nativa
Pastura degradad
os
Pastura
recuperada
ILP ILPF
.........................C (t ha-1) ............Sur 59 22 73 50 69
Sudeste 86 49 60 91 95Centro Oeste
60 42 52 79 53
Las reservas de carbono en suelos de diferentes sistemas agrícolas en el sur, sureste y Midwest (0-30 cm). Brasil
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Coordination: Embrapa Southeast Cattle – São Carlos, SP
Participant institutions: Animal Sciences Institute – Nova Odessa, SPEmbrapa Environment – Jaguariúna, SP
PA 4.1. Evaluation of methane emission from ruminants
4.1.1. Evaluation of methane emission from the rumen of dairy cattle
4.1.2. Evaluation of methane emission from the rumen of beef cattle in the Southeast region
4.1.3. Evaluation of methane emission from the rumen of crossbreed dairy cattle with controled ingestion of forage
4.1.4. Evaluation of methane emission from the rumen of beef cattle in the Pantanal region
4.1.4. Methane analysis and sulfur hexafluoride by gas chromatography
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Methane collection from dairy cattle
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Methane emission factors for beef cattle (Nelore) in the
Southeast of Brazil (tropical climate) CH4 g/d*
Category Weight % of total herd
Winter Spring Summer Fall CH4 kg/animal
year
Bulls 500 > 1.4 131 192 274 168 69.7 Cows 350-450 36.6 116 150 198 161 57.0 Heifers (7 months to 2 years)
180-250 11.4 95 99 159 159 46.7
Heifers (2-3 years) 250-351 7.5 103 114 194 130 49.3 Males (7 months to 2 years)
180-250 9.6 95 99 159 159 46.7
Males (2-3 years) 250-351 5.0 103 114 194 130 49.3 Males (3-4 years) 350-450 1.6 116 150 198 161 57.0 Males (4 years ) 450> 0.4 131 192 274 161 69.1
Mean - - 111 139 206 154 53.0
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Buenos Pastizales
Son eficientes en lo sequestro
de carbono
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recuperación de las pasturas
Degradacion de las pasturas
Recuperacion de 15 millones de hectareas
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Rotação lavoura-pasto
Anos
75 76 78 82 86 87 88 89 90 91 92
Mat
éria
org
ânic
a (%
)
0
2
3
4
5Rotação contínua de soja/milhoPasto depois de lavouraLavoura depois de pasto
Sousa, et al., 1997Sousa, et al., 1997
Sucessão soja/milho
Pasto depois de lavoura
Lavoura depois de pasto
Teores de matéria orgânica do solo
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60Fonte :Embrapa agrobiologia
las emisiones de CO2 co aumento de peso
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61
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62
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63
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PASTAGEMPERDA DE PRODUÇÃO (%)
Escenario pesimista Escenário optimista
PA 27 28 29 25 25 25TO 39 40 42 37 37 38MA 46 46 47 45 45 45PI 61 61 63 59 60 60CE 67 68 68 66 67 67RN 66 67 67 65 65 66PB 64 65 66 63 64 64PE 57 58 58 56 56 57AL 51 52 52 51 51 51SE 48 48 49 47 47 47BA 55 55 56 53 54 54MG 45 45 46 42 42 43ES 38 39 40 36 36 37RJ 30 31 31 28 28 28SP 27 28 29 23 23 24PR 11 12 14 7 6 8SC 0 0 0 0 0 0RS 4 4 5 0 0 0MS 31 31 33 27 26 27MT 37 37 39 34 34 35GO 40 40 42 37 37 38
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Agricultural Management
AreaMillion
ha
Mitigation
MTCO²eq
CostBillion US$
Years
Recovery of Degradeted Pastures
15.0 101.7 10.9 10
Crop Livestock Integration
4,0 27.1 19.0 10
No Tillage 8,0 14.6 1.3 10
Biological Fixation of Nitrogen
11.0 20.0 0.2 10
Reforestation 1.5 3.0 8.8 10
Total 39.5 166.4 40.2 10
Reduction of CO² emission, area considered and cost of mitigation activities until 2020
Adapted fromASSAD, E. D. & BARIONI, L. G.
Embrapa Informática