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:

  • Greenhouse gas emissions: estimates covering emissions and removals across all major sectors
  • Multi-sector coverage: agriculture, energy, land use change, industrial processes, waste
  • Municipality, state, and country levels: geographic disaggregation for regional analysis
  • Time series: 1970-2024

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

Data Version

The package reads SEEG’s v13.0 municipal summary workbook (seeg.eco.br). Categories are organized as Setor de emissão / Categoria emissora / Sub-categoria emissora / Recorte / Atividade geral. There is no time_period argument – every call returns the full series.

Detail not included

A few dimensions are not available in the current data:

  • No gas/produto breakdown – emissions are not split by individual gas.
  • seeg_farming: no species/crop-level detail.
  • seeg_industry: no input/technology-level detail (partly offset by an actual/potential emission split and a finer end-use breakdown).
  • seeg_energy: no fuel-type breakdown (gasoline, diesel, LPG, etc.).
  • seeg_land: no biome dimension and no origin-to-destination land-cover transition matrix – only four coarser categorical fields.

Available Datasets

1. seeg (All Sectors Combined)

Complete greenhouse gas emissions across all sectors in one dataset. Only available with raw_data = TRUE – it cannot be requested treated (raw_data = FALSE).

  • Coverage: all sectors, 1970-2024
  • Geographic levels: country, state, municipality
  • Format: the cleaned source sheet – one row per municipality x category path, with one numeric column per year (x1970…x2024)

2. seeg_farming (Agricultural and Livestock Emissions)

Sector: Agropecuaria. Only available with raw_data = FALSE.

3. seeg_energy (Energy Sector Emissions)

Sector: Energia. Only available with raw_data = FALSE. No fuel-type breakdown (see “Detail not included” above).

4. seeg_land (Land Use Change Emissions)

Sector: Mudanca de Uso da Terra e Floresta. Only available with raw_data = FALSE. No biome dimension and no land-cover transition matrix (see “Detail not included” above).

5. seeg_industry (Industrial Process Emissions)

Sector: Processos Industriais. Only available with raw_data = FALSE.

6. seeg_residuals (Waste and Residuals Emissions)

Sector: Residuos. Only available with raw_data = FALSE.

Output Columns (raw_data = FALSE)

Every seeg_* sector dataset returns long-format data, one row per category combination and year, with a single value (eng) / Valor (pt) column. The columns available depend on geo_level and on which 4th categorical dimension that sector carries:

geo_level eng columns pt columns
municipality year, city, state, ibge, sector, emission_category, emission_subcategory, <4th dim>, general_activity, emission_type, value Ano, municipio, estado, ibge, setor, categoria_emissao, subcategoria_emissao, <4th dim>, atividade_geral, tipo_emissao, Valor
state (drops city, ibge) (drops municipio, ibge)
country (also drops state) (also drops estado)

The 4th dimension’s name (and whether it is translated in pt) differs by sector:

Dataset eng name pt name pt renamed?
seeg_residuals waste_stream tipo_residuo yes
seeg_farming emission_pathway via_emissao yes
seeg_industry emission_scope recorte no – stays recorte
seeg_energy emission_scope recorte no – stays recorte
seeg_land emission_scope recorte no – stays recorte

language = "pt" output is never value-translated – only language = "eng" runs SEEG’s PT->EN value dictionaries (SEEG_SECTOR_EN, SEEG_EMISSION_TYPE_EN, and one category/subcategory/dimension/activity dictionary per sector, in R/seeg.R). A PT call returns the source’s own Portuguese values as-is.

Function Parameters

1. dataset

Selects which emission sector to download.

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

2. raw_data

Controls whether to download the original or the treated data. Each dataset only works with one value (see above): "seeg" requires TRUE; every seeg_* sector requires FALSE.

3. geo_level

Specifies geographic aggregation level.

  • "country": national total
  • "state": state-level emissions (27 units)
  • "municipality": all 5,570+ municipalities

4. language

Output language for column names and, for eng only, translated values.

  • "pt": Portuguese column names, source’s own Portuguese values (untranslated)
  • "eng": English column names and translated values

Note on timing: the source workbook is 250MB+; downloads may take time. A session-scoped download+parse cache (R/download.R) avoids re-downloading it if you load more than one SEEG dataset in the same session.

Examples

Example 1: All sectors combined (raw data) 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

farming <- load_seeg(
  dataset = "seeg_farming",
  raw_data = FALSE,
  geo_level = "state",
  language = "eng"
)

Example 3: Land use change emissions by state

land_use <- load_seeg(
  dataset = "seeg_land",
  raw_data = FALSE,
  geo_level = "state",
  language = "eng"
)

Example 4: Energy emissions by municipality

energy <- load_seeg(
  dataset = "seeg_energy",
  raw_data = FALSE,
  geo_level = "municipality",
  language = "eng"
)

Example 5: Industrial process emissions by state

industry <- load_seeg(
  dataset = "seeg_industry",
  raw_data = FALSE,
  geo_level = "state",
  language = "eng"
)

Example 6: Waste emissions by state

residuals <- load_seeg(
  dataset = "seeg_residuals",
  raw_data = FALSE,
  geo_level = "state",
  language = "eng"
)

Limitations

  1. No year selection: entire series (1970-2024) is downloaded; there is no time_period argument.
  2. File size: the source workbook is 250MB+; a stable connection is recommended.
  3. Missing detail: see “Detail not included” above – fuel type, species/crop detail, biome, and the land-cover transition matrix are not available in the current data.
  4. pt output is untranslated: only language = "eng" runs SEEG’s value dictionaries.