meanAnnualPerCapTerr = mean(`Annual CO2 emissions (per capita)`, na.rm = TRUE),
meanAnnualPerCapCons = mean(`Annual consumption-based CO2 emissions (per capita)`,na.rm = TRUE),
meanAnnualGDPperCap = mean(`GDP per capita, PPP (constant 2017 international $)`,na.rm = TRUE)), keyby = .(Entity)]
```
# Absolute GDP & emissions
First we'll try production emissions.
## Absolute production emissions
First we'll try production ('territorial') emissions. We are not controlling for population size so countries with large populations will visually dominate.
```{r}
#| label: fig-SelectedProdPlot
...
...
@@ -61,18 +85,18 @@ First we'll try production emissions.
ggplot2::ggplot(plotDT, aes(y = as.numeric(`GDP, PPP (constant 2017 international $)`)/1000000000,
x = as.numeric(`Annual CO2 emissions`)/1000000,
ggplot2::ggplot(plotDT, aes(x = as.numeric(`GDP, PPP (constant 2017 international $)`)/1000000000,
y = as.numeric(`Annual CO2 emissions`)/1000000,
colour = Entity,
alpha = Year)) +
geom_point() +
labs(x = "Annual CO2 emissions (production-based, gT)",
y = "GDP $bn (constant 2017 $)")
labs(y = "Annual CO2 emissions (production-based, gT)",
x = "GDP $bn (constant 2017 $)")
```
Next we'll try consumption emissions.
## Absolute consumption emissions
Note that 2020 consumption-based emissions data is missing so you don't see the downtick
Note that 2020 consumption-based emissions data is missing so you don't see the 2020 COVID-19 downtick. Absolute emissions are falling in some places even as GDP is still increasing...
```{r}
#| label: fig-SelectedConsPlot
...
...
@@ -80,18 +104,20 @@ Note that 2020 consumption-based emissions data is missing so you don't see the
ggplot2::ggplot(plotDT, aes(y = as.numeric(`GDP, PPP (constant 2017 international $)`)/1000000000,
x = as.numeric(`Annual consumption-based CO2 emissions`)/1000000,
ggplot2::ggplot(plotDT, aes(x = as.numeric(`GDP, PPP (constant 2017 international $)`)/1000000000,
y = as.numeric(`Annual consumption-based CO2 emissions`)/1000000,
colour = Entity,
alpha = Year)) +
geom_point() +
labs(x = "Annual CO2 emissions (consumption-based, gT)",
y = "GDP $bn (constant 2017 $)")
labs(y = "Annual CO2 emissions (consumption-based, gT)",
x = "GDP $bn (constant 2017 $)")
```
# Per capita GDP & emissions
Since we'll be dividing everything pairwise by the same denominator, nothing much should change... but the plots should be much clearer as we've removed the affect of population size
Since we'll be dividing everything pairwise by the same denominator, nothing much about the shapes should change... but the plots should be much clearer as we've removed the affect of population size. Countries with large populations will no longer visually dominate...
