Get top-down projections of Kaya variables for one or more countries or regions

Get top-down projections of Kaya variables for one or more countries or regions

get_top_down_values(region_name, quiet = FALSE, region_code = NULL)

Arguments

region_name

The name of a country or region to look up

quiet

Suppress warnings if there is no data for that country or region.

region_code

Optional three-letter country or region code to look up instead of the region_name

Value

a tibble of values for P, G, E, F, g, e, f, and ef for each country or region:

region

The name of the country or region

P

Population, in billions

G

Gross domestic product, in trillions of constant 2015 U.S. dollars.

E

Total primary energy consumption, in quads

F

CO2 emissions from fossil fuel consumption, in millions of metric tons

g

Per-capita GDP, in thousands of constant 2015 U.S. dollars per person.

e

Energy intensity of the economy, in quads per trillion dollars.

f

Emissions intensity of the energy supply, in million metric tons per quad.

ef

Emissions intensity of the economy, in metric tons per million dollars of GDP.

See also

regions

Examples

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 0.747  34.7  4.73  46.4  219.
#>  2 New Zealand  2011 0.00438 0.162  37.0 0.787  33.8  4.85  42.9  208.
#>  3 New Zealand  2012 0.00445 0.168  37.8 0.798  34.2  4.74  42.9  203.
#>  4 New Zealand  2013 0.00452 0.172  38.0 0.799  33.6  4.65  42.0  195.
#>  5 New Zealand  2014 0.00458 0.177  38.5 0.805  33.7  4.56  41.9  191.
#>  6 New Zealand  2015 0.00465 0.181  38.9 0.811  34.1  4.48  42.0  188.
#>  7 New Zealand  2016 0.00473 0.187  39.4 0.838  35.0  4.49  41.8  188.
#>  8 New Zealand  2017 0.00481 0.191  39.7 0.887  36.7  4.64  41.4  192.
#>  9 New Zealand  2018 0.00489 0.197  40.2 0.913  37.1  4.64  40.6  188.
#> 10 New Zealand  2019 0.00496 0.202  40.7 0.935  37.2  4.63  39.8  184.
#> # 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  43.2  33.5  221. 13047.  5.10  59.2  302.
#>  2 OECD    2011  1.30  44.1  34.0  219. 12932.  4.96  59.1  293.
#>  3 OECD    2012  1.30  44.7  34.3  216. 12756.  4.84  58.9  285.
#>  4 OECD    2013  1.31  45.4  34.6  219. 12869.  4.82  58.8  284.
#>  5 OECD    2014  1.32  46.4  35.1  218. 12735.  4.69  58.5  274.
#>  6 OECD    2015  1.33  47.6  35.7  218. 12635.  4.58  58.0  266.
#>  7 OECD    2016  1.34  48.4  36.2  219. 12578.  4.53  57.4  260.
#>  8 OECD    2017  1.35  49.7  36.9  225. 12438.  4.53  55.3  250.
#>  9 OECD    2018  1.35  50.8  37.5  227. 12384.  4.48  54.5  244.
#> 10 OECD    2019  1.36  51.8  38.0  228. 12197.  4.40  53.6  236.
#> # 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 0.197 0.242  1.23  2.58  151. 10.7   58.5  623.
#>  2 Pakistan  2011 0.200 0.253  1.27  2.61  153. 10.3   58.6  604.
#>  3 Pakistan  2012 0.203 0.266  1.31  2.69  156. 10.1   58.2  587.
#>  4 Pakistan  2013 0.206 0.279  1.36  2.75  166.  9.87  60.4  597.
#>  5 Pakistan  2014 0.208 0.291  1.40  2.84  172.  9.75  60.7  592.
#>  6 Pakistan  2015 0.211 0.304  1.44  2.91  178.  9.59  61.1  586.
#>  7 Pakistan  2016 0.214 0.318  1.49  3.06  185.  9.63  60.6  583.
#>  8 Pakistan  2017 0.216 0.334  1.54  3.21  189.  9.62  58.8  565.
#>  9 Pakistan  2018 0.219 0.351  1.60  3.31  195.  9.43  58.9  555.
#> 10 Pakistan  2019 0.222 0.367  1.66  3.37  199.  9.18  59.0  541.
#> # ℹ 31 more rows