Skip to contents

Get air pollutant data

Source: R/airpol_get.R
airpol_get.Rd

Retrieve air emissions accounts by NACE Rev. 2 activity for environmental impact assessments. Currently tested only with product × product tables.

Usage

airpol_get(
  airpol = "GHG",
  geo = "BE",
  year = 2020,
  unit = "THS_T",
  data_directory = NULL,
  force_download = TRUE
)

Source

Eurostat dataset: Air emissions accounts by NACE Rev. 2 activity.

Arguments

airpol

Pollutant code. Defaults to "GHG". Common values include "ACG", "CH4", "CO2", "NH3", "NOX", "PM10", "PM2_5", "SOX_SO2E". See Details for the full list.

geo

Country code. The special value "germany_1995" returns the built-in replication dataset germany_airpol.

year

Reference year (2008 or later for NACE Rev. 2 statistics).

unit

Unit of measure. Defaults to "THS_T" (thousand tons).

data_directory

Optional directory path. If valid, the downloaded and pre-processed data will be saved here.

force_download

Logical, defaults to TRUE. If FALSE, the function reuses an existing file in data_directory or a temporary directory.

Value

A data frame with auxiliary metadata conforming to symmetric input–output tables.

Details

The Eurostat dataset Air emissions accounts by NACE Rev. 2 activity (env_ac_ainah_r2) contains emissions of major pollutants, including: CO2, biomass CO2, N2O, CH4, PFCs, HFCs, SF6 (incl. NF3), NOx, NMVOC, CO, PM10, PM2.5, SO2, and NH3.

For details, see the Eurostat Reference Metadata (SIMS), particularly on aggregated indicators: global warming potential (GHG), acidifying gases (ACG), and tropospheric ozone precursors (O3PR).

See also

Other import functions: employment_get(), iotables_download(), iotables_metadata_get(), iotables_read_tempdir()

Examples

airpol_get(
  airpol = "CO2",
  geo = "germany_1995",
  year = 1995,
  unit = "THS_T"
)
#> # A tibble: 1 × 9
#>   indicator    agriculture_group industry_group construction trade_group
#>   <chr>                    <int>          <int>        <int>       <int>
#> 1 CO2_emission             10448         558327        11194       71269
#> # ℹ 4 more variables: business_services_group <int>,
#> #   other_services_group <int>, final_consumption_households <int>,
#> #   output_bp <int>