Consumption CO2 Emissions Per Capita for Advanced Economies and Emerging Market Economies

Analysis of Consumption CO2 Per Capita in Country Groups

Jing Yan

Oct.5, 2022

What is Consumption CO2 Emissions Per Capita

Consumption Emissions is emissions resulting from territorial emissions plus net trade emissions. Therefore, it is national or regional emissions which have been adjusted for trade.The following Consumption CO2 Emissions Per Capita data is caluclated by dividing the consumption carbon emissions figure from OWID by the population data provided by the IMF.

The Trend of Consumption CO2 Emissions Per Capita from 2015 to 2019

#Get subset of dm_em_consumption_co2_per_capita
options(dplyr.summarise.inform = FALSE)
dm_em_consumption_co2_per_capita <- emissions_dataset_full %>%
    left_join(imf_wb_country_groups, by = "iso3c") %>%
    filter(country_group == "Advanced Economies"|country_group == "Emerging Market Economies", year>=2015) %>%
    group_by(country_name.x, year, country_group, gdp_usd_current_prices,debt_usd_per_capita)%>%
    summarize(consumption_co2_per_capita)

#Treating missing data dm_em_consumption_co2_per_capita
dm_em_consumption_co2_per_capita_clean <- dm_em_consumption_co2_per_capita %>% filter(!is.na(consumption_co2_per_capita))

#Group by dm & em
by_dm_em_year <- dm_em_consumption_co2_per_capita_clean %>%
    group_by(country_group, year) %>%
    summarize(consumption_co2_per_capita)

ggplot(by_dm_em_year, aes(x = year, y = consumption_co2_per_capita, color = country_group)) +
  geom_line(size = 1) + 
  scale_color_manual(values = c("#000099", "#99CCFF")) +
  geom_point(shape = 22, size = 3, fill = "white") +
  labs(
    x = "",
    y = "Consumption CO2 Per Capita",
    title = "Consumption CO2 Per Capita in Country Group from 2015 to 2019",
    subtitle = "Different Trends in Advanced Economies and Emerging Market Economies", 
    caption = "Data source: Our World In Data, IMF") +
  theme_grey()

The Relationship between Consumption CO2 Emissions Per Capita and Debt Per Capita

#Select Data From 2019
by_debt_2019 <- dm_em_consumption_co2_per_capita_clean %>%
    filter(year == 2019)

ggplot(by_debt_2019, aes(x = debt_usd_per_capita, y = consumption_co2_per_capita, color = country_group)) +
  geom_point() + 
  scale_color_manual(values = c("#000099", "#99CCFF")) +
  labs(
    x = "Debt Per Capita in USD",
    y = "Consumption CO2 Per Capita",
    title = "Consumption CO2 Per Capita in Country in 2019",
    subtitle = "The Relationship between Consumption CO2 and Debt", 
    caption = "Data source: Our World In Data, IMF") +
  theme_grey()

ggplot(by_debt_2019, aes(x = debt_usd_per_capita, y = consumption_co2_per_capita, color = country_group, size = gdp_usd_current_prices)) +
  geom_point() + 
  scale_color_manual(values = c("#000099", "#99CCFF")) +
  labs(
    x = "Debt Per Capita in USD",
    y = "Consumption CO2 Per Capita",
    title = "Consumption CO2 Per Capita in Country in 2019",
    subtitle = "The Relationship between Consumption CO2 and Debt", 
    caption = "Data source: Our World In Data, IMF") +
    facet_grid(. ~ country_group) +
  theme_grey()