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GHG Inventory hands-on training Workshop of the CGE

GHG Inventory hands-on training Workshop of the CGE. Difficulties in calculating net CO 2 emissions from Brazilian agricultural soils. Panama, October 2004. Ricardo Leonardo Vianna Rodrigues. IPCC: three potential sources of CO 2 emissions from soils.

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GHG Inventory hands-on training Workshop of the CGE

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  1. GHG Inventory hands-on trainingWorkshop of the CGE Difficulties in calculating net CO2 emissions from Brazilian agricultural soils Panama, October 2004 Ricardo Leonardo Vianna Rodrigues

  2. IPCC: three potential sources of CO2 emissions from soils • Net carbon stock changes from mineral soils associated with land use change and management; • Emissions from liming of agricultural soils; • Emissions from cultivated organic soils;

  3. Net carbon stock changes from mineral soils associated with land use change and management

  4. Calculation procedures for mineral soils DATA NEEDED • Soil carbon content from different soil types (top 30 cm depth), • Land use area (grassland, grain etc) in the year t and in the year t-20, for each soil type, • Impact factors according to the use,

  5. LAND USE / MANAGEMENT Agriculture Census Cadastre of rural properties, Remote sensing data SOIL DATA Soil survey data from different sources, Phyto-physiognomic maps Soil distribution maps, Sources of data

  6. ADVANTAGES Available (do not requires much effort to be collected) Systematically collected every 5 or 10 years, Land use type data, DISADVANTAGES Do not cover all land area, Considers only data of properties economically active Data are non geo-referenced, Lack of management data Land use data - Agriculture Census

  7. ADVANTAGES Available Consider properties economically active and inactive, Land use data DISADVANTAGES Not complete, may cover only a short period, Land use is declaratory, Data are not geo-referenced Do not report management Rural properties cadastre data

  8. ADVANTAGES Data are geo-referenced, Land use data may be collected, Multi-temporal data allows estimates of deforestation rate, DISADVANTAGES Very expensive data Land use data not available (have to be collected), Need specialists to analyze RS data, Other management data are unlikely to be collected, Remote sensing data

  9. DATA NEEDED Soil type, Soil analysis (C content) Soil spatial distribution, Vegetation spatial distribution, DIFFICULTIES To gather data from different sources and scales, To integrate Soil and Vegetation maps in one map, according to IPCC soil classes, Soil and C content data

  10. Activity datachoice • Experts in net flux of CO2 from soils chose Brazilian Agricultural Census as the most suitable data; Difficulties: • Brazilian Agricultural Census considers only rural properties that are economically active; • Besides, Census do not take into account agriculture management,

  11. Agricultural Census Data Consequences of excluding rural properties that are economically inactive from Census: • Deforestation rate may have been underestimated in some regions, • Because of that, changes in soil carbon stock may be underestimated;

  12. Consequences of using non geo-referenced data • When data are non geo-referenced, as happens with Agriculture Census, the integration between soil C content and land use is hindered; • Alternative: to assume that each soil class have the same proportion of land use classes for a determined region (high uncertainties);

  13. Difficulties associated to soil carbon contentdata • The soil data base comes from different sources and scales (generally, large scale); • C content was estimated by different methods, and unsuitable methods, increasing uncertainties, • Carbon stock = Bulk Density * Carbon * horizon thickness (top 30 cm) • Lack of bulk density data in most of soil profiles (g dry soil/cm3 - which includes the pore spaces); and the solution was to use of multiple linear regression equations to estimate bulk density;

  14. Impact Factors • Lack of specific data for Brazil (mainly cultivation intensity factor and entrance level factor) may have hindered estimations; • Use of coefficients (EF default) suggested by IPCC for tropical regions, which may not be representative of Brazilian conditions;

  15. Emissions from liming of agricultural soils

  16. Emissions from liming of agricultural soils • Lack of suitable statistics about amount of agricultural lime sold yearly in Brazil; • Data were obtained from the greatest Lime Producers Associations; • Lack of detail about the composition of lime sold in Brazil;

  17. Emissions from cultivated organic soils

  18. Emissions from cultivated organic soils • Lack of cultivated organic soils data; Solutions • Use as proxy agriculture data usually associated to this kind of soil.

  19. Conclusions Estimations of net CO2 emissions from Brazilian agricultural soils may have been hindered by: • Lack of suitable land use and lack of management data; • Different and unsuitable methods to estimate soil carbon content; • Lack of suitable impact factors, • Data are non geo-referenced; • Lack of suitable lime production statistics; • Lack of cultivated organic soils statistics;

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