Tidy Tuesday - Carbon Majors Emissions Data

21st May 2024

Author

Arun Koundinya Parasa

Published

June 8, 2024

0. Loading Libraries

This particular visualization is done on R to visualize the data with custom back ground.

Loading Libraries 
library(tidyverse)
library(jpeg)
library(grid)

1. Data Loading

Loading Data 
emissions <- readr::read_csv('https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2024/2024-05-21/emissions.csv')

2. Data Manipulation

Data Manipulation 
# Creating new columns for better visualization
emissions <- 
  emissions |> 
  mutate(
    commodity_updated = case_when(
      commodity %in% c("Oil & NGL") ~ "Oil",
      commodity %in% c("Natural Gas") ~ "Gas",
      commodity %in% c("Cement") ~ "Cement",
      commodity %in% c("Sub-Bituminous Coal","Metallurgical Coal","Bituminous Coal",
                       "Thermal Coal", "Anthracite Coal","Lignite Coal" ) ~ "Coal"
    ),
    parent_updated = case_when(
      parent_type %in% c("Investor-owned Company") ~ "Investor-Owned",
      parent_type %in% c("Nation State") ~ "Countries",
      parent_type %in% c("State-owned Entity") ~ "State-Owned"
    )
  )

# Emissions Summary  Data frame o by commodity and year
emissions_summary <-
  emissions |>
  group_by(year,commodity_updated) |>
  summarise(co2_emissions = sum(total_emissions_MtCO2e),.groups = "drop")

# Emissions Summary  Data frame o by year
emissions_summary_1 <-
  emissions |>
  group_by(year) |>
  summarise(co2_emissions = sum(total_emissions_MtCO2e),.groups = "drop")

# Emissions Summary  Data frame o on commodity
emissions_summary_2 <-
  emissions |>
  group_by(commodity_updated) |>
  summarise(co2_emissions = sum(total_emissions_MtCO2e),.groups = "drop") |>
  mutate(
    perc = round((co2_emissions/ sum(co2_emissions))*100)
  )

# Emissions Summary  Data frame o on entity group and year
emissions_summary_3 <-
  emissions |>
  group_by(year,parent_updated) |>
  summarise(co2_emissions = sum(total_emissions_MtCO2e),.groups = "drop")

# Emissions Summary Data frame on entity group
emissions_summary_4 <-
  emissions |>
  group_by(commodity_updated,parent_updated) |>
  summarise(co2_emissions = sum(total_emissions_MtCO2e),.groups = "drop")

3. Plots

3.1. 1.42 Trillion Tonnes of CO2 Emissions

Plot1 Code 
# Plot1 - Area Chart with background image

# Pie Chart to annote inside Area Chart
emissions_summary_2 |>
  arrange(desc(co2_emissions)) |>
  ggplot(aes(x= "",y = perc , fill = commodity_updated)) + 
  geom_bar(stat = "identity",width = 1) + 
  geom_label(aes( x= 1.1, label = paste(perc,"%",sep = "")), position = position_stack(vjust = .5), color = "white") + 
  coord_polar("y", start = 2.1) + 
  scale_fill_manual(values = c("grey", "black", "#2e7ac5","#efb61b")) +
  theme_void() + 
  theme(
    legend.position = "none"
  ) -> pie_chart

goem_label_repel


bg_image <- readJPEG("background.jpg")
bg_image <- rasterGrob(bg_image, interpolate=TRUE)

ggplot() + 
  annotation_custom(
    bg_image, xmin = 1850, xmax = 2022, ymin = 0, ymax = 40000
  ) +
  geom_area(data = emissions_summary, aes(x=year, y=co2_emissions, fill=commodity_updated)) + 
  scale_fill_manual(values = c("grey", "black", "#2e7ac5","#efb61b")) +
  geom_line(data = emissions_summary_1, aes(x=year, y=co2_emissions*1.01)) + 
  theme_minimal() + 
  coord_cartesian(xlim = c(1850,2022), ylim = c(0,40000), expand = FALSE) +
  labs(
    title = "122 Entities Contribute to 1.42 Trillion Tonnes of CO2 Emissions",
    subtitle = "Period: 1854 to 2022",
    caption = "Historical data from 122 entities that produces oil, gas , coal & cement ",
    x = "Year",
    y = "CO2 Emissions in MT"
  ) + 
  theme (
    legend.position = c(0.05,0.9),
    legend.background = element_rect(fill="#2a3f4a"),
    plot.background = element_rect(fill="#2a3f4a"),
    axis.title.x = element_text(colour = "white"),
    axis.title.y = element_text(colour = "white"),
    axis.text.x =  element_text(colour = "white"),
    axis.text.y =  element_text(colour = "white"),
    legend.text = element_text(colour = "white"),
    legend.title = element_blank(),
    plot.title = element_text(hjust = 0.5,colour = "white", size = 16),
    plot.subtitle = element_text(hjust = 0.5,colour = "white", size = 12),
    plot.caption = element_text(colour = "white")
    ) + 
  geom_vline(xintercept = 1945, color = "red", linetype = 2) + 
  geom_rect(
    aes(xmin = 1942, xmax = 1948, ymin = 38000, ymax = 39000 ), 
    fill = "red4"
    ) +
  annotate(
    "text",
    x = 1945,
    y = 38500,
    label = "1945",
    size = 3,
    color = "white"
  ) +
  geom_vline(xintercept = 1993, color = "red", linetype = 2) +
  geom_rect(
    aes(xmin = 1989, xmax = 1996, ymin = 38000, ymax = 39000 ), 
    fill = "red4"
  ) +
  annotate(
    "text",
    x = 1993,
    y = 38500,
    label = "1993",
    size = 3,
    color = "white"
  ) +
  annotation_custom(
    ggplotGrob(pie_chart) , xmin = 1850, xmax = 1900, ymax = 20000
  ) + 
  annotate(
    "text",
    x = 1915,
    y = 35000,
    label = "These Emissions contribute to 72% of Global Fossil Fuel \n Inflection years are observed at 1945 and 1993
    suggesting respective phase of globalization",
    color = "white",
    size = 3
  )

3.2. 0.5 Trillion Tonnes of CO2 Emitted by Each Entity Group

Plot2 Code 
# Plot 2 Line Plot by Entities

# Stacked Bar Chart to annote inside line plot
emissions_summary_4 |>
  ggplot(aes(x = parent_updated,y=co2_emissions, fill = commodity_updated)) + 
  geom_col(position="stack") + 
  scale_fill_manual(values = c("grey", "black", "#2e7ac5","#efb61b")) +
  theme_minimal() +
  labs(
    x = "",
    y = ""
  ) +
  theme(
    legend.position = "none",
    axis.text.x =  element_text(colour = "white"),
    axis.text.y =  element_text(colour = "white"),
    panel.grid.minor.y = element_blank(),
    panel.grid.major.x = element_blank()
  ) + 
  scale_y_continuous(labels = scales::unit_format(unit="M",scale=1e-6)) -> stacked_bar_chart

emissions_summary_3 |>
  ggplot(aes(x = year,y =co2_emissions,color = parent_updated)) + 
  geom_line() + 
  scale_color_manual(values = c("red4", "cornsilk3", "skyblue3"))+
  coord_cartesian(xlim = c(1850,2022), ylim = c(0,15000), expand = FALSE) +
  theme_minimal() +
  labs(
    x = "Year",
    y = "CO2 Emissions in MT",
    title = "0.5 Trillion Tonnes of CO2 by each entity group",
    subtitle = "Period: 1854 to 2022"
  ) +
  theme(
    legend.position = "none",
    plot.title = element_text(hjust = 0.5, size = 16),
    plot.subtitle = element_text(hjust = 0.5, size = 12)
  ) + 
  geom_rect(
    aes(xmin = 1850, xmax = 1950, ymin = 1250, ymax = 12000 ), 
    fill = "#2a3f4a"
  ) +
  annotation_custom(
    ggplotGrob(stacked_bar_chart) , xmin = 1845, xmax = 1950, ymin =500, ymax = 12000
  ) +
  geom_rect(
    aes(xmin = 1972, xmax = 1987, ymin = 9100, ymax = 9900 ), 
    fill = "red4"
  ) +
  annotate(
    "text",
    x = 1980,
    y = 9500,
    label = "Countries",
    size = 3,
    color = "white"
  )+
  geom_rect(
    aes(xmin = 1962, xmax = 1975, ymin = 6400, ymax = 7600 ), 
    fill = "cornsilk3"
  ) +
  annotate(
    "text",
    x = 1969,
    y = 7000,
    label = "Investor\nOwned",
    size = 3,
    color = "black"
  )+
  geom_rect(
    aes(xmin = 1974, xmax = 1985, ymin = 3000, ymax = 4200 ), 
    fill = "skyblue3"
  ) +
  annotate(
    "text",
    x = 1980,
    y = 3600,
    label = "State\nOwned",
    size = 3,
    color = "white"
  )

4. References

  • https://stackoverflow.com/questions/70924495/how-to-add-several-vertical-lines-to-ggplot2-in-r
  • https://r-graph-gallery.com/136-stacked-area-chart.html
  • https://imagecolorpicker.com
  • https://stackoverflow.com/questions/2954005/how-to-move-or-position-a-legend-in-ggplot2
  • https://stackoverflow.com/questions/62173825/ggplot2-geom-text-position-in-pie-chart