Assessment 3 - Storytelling with Open Data

Annual Greenhouse Gas Emissions Including Land Use

Felix George
Student No: s4077399

Welcome

🌍 A Journey Through Global Greenhouse Gas Emissions

In this study, I investigate the global evolution of annual greenhouse gas emissions from 1850 to the present, including emissions resulting from changes in land use.
This trip is motivated by a profound interest in how many nations contribute to the climate crisis and how land use, economic development, and industrialization have influenced the atmosphere of our world.
To make these intricate patterns come to life, I use interactive visualization tools in R like Plotly and gganimate on free datasets that were curated by Jones et al. (2024) and processed by Our World in Data.
We will work together to identify the trends in the data and comprehend Australia’s role in the global emissions narrative, which is essential for developing data-driven policies that aim to create a sustainable future.

Data Source & Methodology

  • Dataset: Annual greenhouse gas emissions including land use

  • Jones et al. (2024) – with major processing by Our World in Data.
    “Annual greenhouse gas emissions including land use” [dataset]. Jones et al., “National contributions to climate change 2024.2” [original data].
    Retrieved June 12, 2025 from Our World in Data

  • Units: Million tonnes of CO₂ equivalent

  • Timeframe: 1850–2024

  • The dataset includes emissions by country, with land-use emissions included in the total.

Global Emissions Trend

  • This plot shows the total global greenhouse gas emissions from 1850 to 2024.
  • Emissions include land-use changes and are measured in million tonnes of CO₂ equivalents.
  • Notice the sharp rise after 1950 — the start of the “Great Acceleration.”

Global Emissions Trend: Interactive Plot

🌟 Emissions Over Time: Animated View

  • This animated plot shows how the top 10 emitting countries changed from 1950 to 2020.
  • Notice the rapid rise of industrial nations and emerging economies.

🌐 Global Emissions by Country

  • 🌍 Cumulative GHG emissions shown from 1850 to present
  • 🔴 Countries shaded from light to dark based on total emissions
  • 🇦🇺 Australia is included and can be directly compared

Australia’s Emissions in Global Context

  • Australia’s emission trend over time
  • Regional emissions heatmap comparison
  • Shows Australia vs continents emissions
  • Interactive hover details for deeper insight

🎯 Australia’s Emissions vs Paris Agreement Target

  • 🇦🇺 Australia aims for net-zero emissions by 2050.
  • 🟢 Dashed line = Paris-aligned pathway.
  • 🔴 Red line = actual emissions since 1850.
  • ❓ Are we on track?

✅ Summary & 📢 Call to Action

Since the 1950s, the world’s greenhouse gas emissions have grown dramatically, mostly as a result of the fast industrialization and economic expansion of high-emitting nations. Significant differences across countries are also shown by the historical emissions data, with certain countries bearing a far higher proportion of the cumulative emissions load. With persistently higher emissions than the world average, Australia in particular continues to rank among the top polluters per capita. Current trends indicate that Australia is not yet on a Paris-aligned path, despite a national pledge to achieve net-zero by 2050.

We must promote honest, evidence-based climate policies in order to address this. Public comprehension and engagement are improved by interactive data visualizations made with programs like Plotly and gganimate. Additionally, encouraging open-source tools like R and R Markdown guarantees the reproducibility of climate research and makes it easier for scientists and decision-makers to work together.

References
Jones, C., Peters, G., Davis, S., & Friedlingstein, P. (2024). National contributions to climate change (Version 2024.2) [Dataset]. Our World in Data. https://ourworldindata.org/grapher/total-ghg-emissions
Wickham, H., & Grolemund, G. (2017). R for data science: Import, tidy, transform, visualize, and model data. O’Reilly Media.
Wickham, H. (2016). ggplot2: Elegant graphics for data analysis (2nd ed.). Springer.
Healy, K. (2018). Data visualization: A practical introduction. Princeton University Press.
Sievert, C. (2020). Interactive web-based data visualization with R, plotly, and shiny. CRC Press.

Thank you for viewing this presentation. Questions and feedback are most welcome—stay curious, stay data-driven.