Greenhouse Gas Emissions in Australia

Author

Steph

Published

April 2, 2026

National Greenhouse Gas data

Our data comes from the National Inventory by Economic Sector. The values are reported in Mt CO2-e.

Import the data

Let’s import the CSV:

library(tidyverse)
ghg <- read_csv("https://raw.githubusercontent.com/uqlibrary/technology-training/master/R/reports/aus_ghg_2022.csv")

Let’s see the table:

year Agriculture, Forestry and Fishing Forestry - Changes in Inventories Mining Manufacturing Electricity, Gas, Water and Waste Services Services, Construction and Transport Residential
1990 280.27 -19.58 46.25 68.68 154.68 35.93 49.15
1991 261.19 -19.90 46.87 68.53 156.23 33.43 48.64
1992 215.30 -26.24 49.05 68.76 159.32 39.05 49.28
1993 197.36 -30.23 49.80 69.11 158.42 38.72 50.33
1994 177.51 -16.91 48.05 69.25 158.41 36.37 50.69
1995 160.99 -21.08 50.34 69.08 164.54 35.04 52.07
1996 158.99 -23.02 51.84 67.26 167.00 37.43 52.66
1997 158.87 -30.32 55.66 67.95 172.27 33.21 52.67
1998 156.06 -21.42 57.62 68.50 183.98 30.39 52.81
1999 174.01 -25.25 55.63 69.86 189.91 32.41 51.77
2000 172.79 -20.36 59.28 68.95 193.32 42.73 53.10
2001 187.22 -23.36 59.54 68.98 200.87 39.81 53.43
2002 198.92 -34.96 59.81 68.98 202.55 40.66 55.02
2003 195.84 -38.75 57.39 71.94 203.03 44.03 57.03
2004 173.40 -44.85 58.41 73.36 210.91 44.93 58.55
2005 205.96 -44.28 61.65 72.50 212.00 43.00 58.62
2006 228.18 -43.29 62.71 71.60 216.32 49.98 59.43
2007 196.86 -45.84 65.79 73.97 219.38 56.22 59.75
2008 173.34 -42.81 65.62 75.02 221.62 61.58 60.27
2009 152.90 -27.95 71.31 68.48 223.30 59.48 60.35
2010 151.08 -19.33 71.00 70.46 217.99 57.22 60.75
2011 123.47 -23.93 71.66 70.94 210.97 62.65 61.85
2012 114.60 -29.78 74.32 68.66 209.11 55.76 61.98
2013 133.00 -35.92 77.26 67.41 195.43 57.14 62.78
2014 133.84 -47.35 76.41 66.08 188.92 57.54 62.89
2015 118.31 -50.14 82.94 62.10 195.84 60.28 64.37
2016 80.28 -58.61 88.22 59.65 201.23 56.91 63.37
2017 112.77 -55.67 94.36 59.06 196.36 57.91 64.12
2018 95.74 -61.24 100.43 59.47 189.69 52.67 64.92
2019 68.10 -48.74 106.38 58.36 184.98 57.19 64.45
2020 63.74 -40.29 107.25 58.45 174.98 50.35 60.06
2021 39.54 -37.78 101.55 59.70 167.35 51.02 57.36
2022 27.07 -28.29 101.28 58.83 161.43 57.70 54.60

Some stats

The dataset contains GHG emissions for the period 1990 to 2022. The maximum GHG emissions for the mining sector is 107.25 Mt CO2-e. We used the functions max() and min().

Tidy the data

Let’s reshape our table from wide format to long format:

ghg_tidy <- pivot_longer(ghg,
                         -year,
                         names_to = "sector",
                         values_to = "emissions")

Visualise

How did emissions evolve over the years?

ggplot(ghg_tidy,
       aes(x = year,
           y = emissions,
           colour = sector)) +
  geom_line()

Make it interactive:

p <- ggplot(ghg_tidy,
       aes(x = year,
           y = emissions,
           colour = sector)) +
  geom_line()
library(plotly)
ggplotly(p)