SEEG

Overview

SEEG (Sistema de Estimativa de Emissões e Remoções de Gases de Efeito Estufa - System of Estimates of Emissions and Removals of Greenhouse Gases) is Brazil’s most comprehensive greenhouse gas emissions database developed by Observatório do Clima (Climate Observatory).

This dataset provides:

SEEG is the primary tool for understanding Brazil’s greenhouse gas emissions profile, tracking progress toward climate goals, identifying emission hotspots, and supporting climate policy.

Data Source and Methodology

SEEG emissions estimates are compiled using: - Government data from multiple agencies (MAPA, IBGE, ANP, etc.) - Satellite monitoring of deforestation and land use - International IPCC methodology standards - Peer-reviewed scientific research - Regular updates as new government data becomes available

For more information, visit SEEG Project and Observatório do Clima.

Available Datasets

1. seeg (All Sectors Combined)

Complete greenhouse gas emissions across all sectors in one dataset.

2. seeg_farming (Agricultural and Livestock Emissions)

Greenhouse gas emissions from agriculture and livestock activities.

3. seeg_energy (Energy Sector Emissions)

Emissions from energy production and consumption.

4. seeg_land (Land Use Change Emissions)

Emissions and removals from changes in forest cover and land use.

5. seeg_industry (Industrial Process Emissions)

Emissions from manufacturing and industrial processes.

6. seeg_residuals (Waste and Residuals Emissions)

Emissions from waste management, landfills, and waste treatment.

Important Data Characteristics

Collection 9 Data

The data provided is from SEEG’s Collection 9: - Time period: 2000-2018 - Methodology: Latest available when data was compiled - Quality: Peer-reviewed and validated - Revisions: May be updated in future SEEG collections as better data becomes available

Emissions Units

Download Considerations

Important: The complete SEEG dataset is quite large. When downloading: - Entire datasets are downloaded as single files; year selection is limited - A stable, high-speed internet connection is recommended - Downloads may take time depending on connection speed - Ensure sufficient disk space for storage

Function Parameters

1. dataset

Selects which emission sector(s) to download.

dataset = "seeg"              # All sectors (raw_data = TRUE only)
dataset = "seeg_farming"      # Agriculture and livestock
dataset = "seeg_energy"       # Energy sector
dataset = "seeg_land"         # Land use changes
dataset = "seeg_industry"     # Industrial processes
dataset = "seeg_residuals"    # Waste and residuals

2. raw_data

Controls whether to download original or processed data.

raw_data = FALSE  # logical

3. geo_level

Specifies geographic aggregation level.

geo_level = "state"  # character string

4. language

Output language for variable names and labels.

language = "eng"  # character string

Note on timing: Downloads may take considerable time due to file size.

Examples

Example 1: All sectors combined (raw data) at the country level

# download raw SEEG data (all sectors) at the country level
# note: dataset = "seeg" only works with raw_data = TRUE
all_emissions <- load_seeg(
  dataset = "seeg",
  raw_data = TRUE,
  geo_level = "country",
  language = "eng"
)

Example 2: Agricultural emissions by state

# download treated agricultural emissions at the state level
farming <- load_seeg(
  dataset = "seeg_farming",
  raw_data = FALSE,
  geo_level = "state",
  language = "eng"
)

Example 3: Land use change emissions by state

# download treated land use change emissions at the state level
land_use <- load_seeg(
  dataset = "seeg_land",
  raw_data = FALSE,
  geo_level = "state",
  language = "eng"
)

Example 4: Energy emissions by municipality

# download treated energy emissions at the municipality level
energy <- load_seeg(
  dataset = "seeg_energy",
  raw_data = FALSE,
  geo_level = "municipality",
  language = "eng"
)

Example 5: Industrial process emissions by state

# download treated industrial process emissions at the state level
industry <- load_seeg(
  dataset = "seeg_industry",
  raw_data = FALSE,
  geo_level = "state",
  language = "eng"
)

Example 6: Waste emissions by state

# download treated waste emissions at the state level
residuals <- load_seeg(
  dataset = "seeg_residuals",
  raw_data = FALSE,
  geo_level = "state",
  language = "eng"
)

Data Notes

Emission Sources Included

SEEG includes all major anthropogenic emission sources: - Agriculture (livestock, crops, soil) - Energy (electricity, transport, heating) - Land use change (deforestation, afforestation) - Industrial processes (cement, chemicals, metals) - Waste (landfills, wastewater)

Methodology

Estimates follow: - IPCC guidelines for national greenhouse gas inventories - Brazilian national inventory standards - International best practices - Transparent, documented assumptions

Data Quality

Limitations

  1. Fixed time period: Collection 9 covers 2000-2018 only
  2. File size: Large downloads; requires good internet
  3. Year aggregation: Cannot select individual years; entire dataset downloaded
  4. Revisions: Methodology may change in future SEEG releases
  5. Sub-national uncertainty: Municipal and state estimates have higher uncertainty than national