R/kaya.R
get_top_down_values.RdGet top-down projections of Kaya variables for one or more countries or regions
get_top_down_values(region_name, quiet = FALSE, region_code = NULL)The name of a country or region to look up
Suppress warnings if there is no data for that country or region.
Optional three-letter country or region code to look up
instead of the region_name
a tibble of values for P, G, E, F, g, e, f, and ef
for each country or region:
The name of the country or region
Population, in billions
Gross domestic product, in trillions of constant 2015 U.S. dollars.
Total primary energy consumption, in quads
CO2 emissions from fossil fuel consumption, in millions of metric tons
Per-capita GDP, in thousands of constant 2015 U.S. dollars per person.
Energy intensity of the economy, in quads per trillion dollars.
Emissions intensity of the energy supply, in million metric tons per quad.
Emissions intensity of the economy, in metric tons per million dollars of GDP.
get_top_down_values("New Zealand")
#> # A tibble: 41 × 10
#> region year P G g E F e f ef
#> <chr> <int> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 New Zealand 2010 0.00432 0.158 36.6 0.746 35.5 4.71 47.7 224.
#> 2 New Zealand 2011 0.00438 0.163 37.1 0.786 34.6 4.83 44.0 213.
#> 3 New Zealand 2012 0.00445 0.169 37.9 0.797 35.0 4.73 44.0 208.
#> 4 New Zealand 2013 0.00452 0.172 38.1 0.797 34.4 4.63 43.2 200.
#> 5 New Zealand 2014 0.00458 0.177 38.6 0.804 34.6 4.55 43.0 195.
#> 6 New Zealand 2015 0.00465 0.182 39.0 0.810 34.9 4.46 43.2 192.
#> 7 New Zealand 2016 0.00473 0.187 39.5 0.836 35.9 4.48 42.9 192.
#> 8 New Zealand 2017 0.00481 0.191 39.8 0.885 37.6 4.63 42.4 196.
#> 9 New Zealand 2018 0.00489 0.197 40.3 0.912 38.0 4.63 41.7 193.
#> 10 New Zealand 2019 0.00496 0.202 40.7 0.933 38.1 4.61 40.9 188.
#> # ℹ 31 more rows
get_top_down_values("OECD")
#> # A tibble: 41 × 10
#> region year P G g E F e f ef
#> <chr> <int> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 OECD 2010 1.29 43.1 33.3 219. 12951. 5.09 59.0 301.
#> 2 OECD 2011 1.30 44.0 33.8 218. 12836. 4.95 59.0 292.
#> 3 OECD 2012 1.31 44.6 34.1 215. 12662. 4.83 58.8 284.
#> 4 OECD 2013 1.32 45.2 34.4 218. 12774. 4.81 58.7 282.
#> 5 OECD 2014 1.33 46.2 34.9 217. 12641. 4.68 58.4 273.
#> 6 OECD 2015 1.33 47.4 35.5 217. 12541. 4.57 57.8 265.
#> 7 OECD 2016 1.34 48.3 35.9 218. 12485. 4.52 57.3 259.
#> 8 OECD 2017 1.35 49.5 36.7 224. 12347. 4.52 55.2 249.
#> 9 OECD 2018 1.36 50.6 37.3 226. 12293. 4.47 54.4 243.
#> 10 OECD 2019 1.37 51.6 37.8 226. 12107. 4.39 53.5 235.
#> # ℹ 31 more rows
get_top_down_values(region_code = "PAK")
#> # A tibble: 41 × 10
#> region year P G g E F e f ef
#> <chr> <int> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 Pakistan 2010 0.189 0.216 1.14 2.58 151. 11.9 58.4 697.
#> 2 Pakistan 2011 0.192 0.226 1.18 2.61 153. 11.5 58.6 677.
#> 3 Pakistan 2012 0.195 0.238 1.22 2.69 156. 11.3 58.1 657.
#> 4 Pakistan 2013 0.197 0.249 1.26 2.75 166. 11.1 60.4 668.
#> 5 Pakistan 2014 0.200 0.260 1.30 2.84 172. 10.9 60.6 663.
#> 6 Pakistan 2015 0.203 0.271 1.34 2.92 178. 10.7 61.1 656.
#> 7 Pakistan 2016 0.205 0.284 1.38 3.06 185. 10.8 60.5 653.
#> 8 Pakistan 2017 0.208 0.298 1.43 3.21 189. 10.8 58.7 633.
#> 9 Pakistan 2018 0.210 0.313 1.49 3.31 195. 10.6 58.8 621.
#> 10 Pakistan 2019 0.213 0.328 1.54 3.37 199. 10.3 58.9 606.
#> # ℹ 31 more rows