2 01 eduardo delgado assad

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

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

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.


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.


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%

source: INPE (2010)

Deforestation rate in the Amazon (thousands of Km2/ha)

Lowest deforestation rate since 2005

Reducing emissions in the Amazon CO2 (million tons per year)

projectedemissionFor 2020

Reduction equivalent to 67% of projected emissions for 2020

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

?

Sectoral Plans

In preparation:

- Transportation;- Industry;- Mining;- Health;- Aquaculture & Fisheries

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

Impactos y tendencias

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]


8 a 6.5

6 a 5

4.5 a 3

2.5 a 1.5

1 a 0

-0.5 a -2

[⁰C]


8 a 6.5

6 a 5

4.5 a 3

2.5 a 1.5

1 a 0

-0.5 a -2

[⁰C]


8 a 6.5

6 a 5

4.5 a 3

2.5 a 1.5

1 a 0

-0.5 a -2

[⁰C]

Análisis de riesgos climáticos

Inicial

Vegetativ

o

Reproduccion Maduracionração

Kc

Zonification de riesgos climáticos

la capacidad de agua del suelo

Evapotranspiracion precipitacion

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

0 1 2 3 4 5 33 34 353ª fase fenológica

dias

ISNA

fISNA(x)

0

1

Isna= 65%

P

“critério”

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

Impactos del cambio climático sobre la agricultura

• simulación de ocho modelos diferentes (tres en downscale)

• cinco culturas• pastos• Período de 2010 a 2030

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

Estrategia de Adaptación

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

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

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

ManzanaManzana

Proyección: El Proyección: El aumento de la aumento de la

temperatura a 2temperatura a 2ooCC

BananaBananaProyección: Proyección:

El aumento de la El aumento de la temperatura a temperatura a

2oC2oC

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

Estrategia de MitigacionEstrategia de Mitigacion

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.

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.

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

N2O fluxes measurement

Fonte :Bruno Alves Embrapa Agrobiologia

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


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.


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


N2O emissions derived from cattle excreta in pastures

IPCC: 2% of N-excreta is lost as N2O


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.


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

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

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

Methane collection from dairy cattle

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

Buenos Pastizales

Son eficientes en lo sequestro

de carbono

recuperación de las pasturas

Degradacion de las pasturas

Recuperacion de 15 millones de hectareas

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

60Fonte :Embrapa agrobiologia

las emisiones de CO2 co aumento de peso

61

62

63

64

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

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

Eduardo Delgado Assad

[email protected]

Documents

2 01 eduardo delgado assad