Top-Down Methods for Estimating the European Carbon Budget: Towards Independent Monitoring and Verification of Carbon Emissions

This thesis investigates advanced methods for improving regional CO₂ flux estimates using atmospheric observations and Δ¹⁴CO₂ measurements. It highlights the role of Δ¹⁴CO₂ in distinguishing fossil fuel emissions from natural CO₂ fluxes, emphasizing the importance of optimized network design and sampling strategies. The findings support better carbon monitoring and climate policy development.

Understanding how much carbon dioxide (CO₂) we emit into the atmosphere is crucial for tackling climate change. CO₂, especially from burning fossil fuels like coal, oil, and gas, is one of the main drivers of global warming. But measuring these emissions accurately is not easy. Some methods rely on reported data from industries and governments, which can have gaps or inaccuracies. Others, called "top-down" methods, use observations of CO₂ in the atmosphere (top) to estimate emissions produced in the terrestrial surface (down). This thesis explores how combining these approaches with advanced techniques and unique tools, like measuring the amount of radiocarbon (∆¹⁴CO₂) in the air, can improve our understanding of where and how much CO₂ is being emitted.
Radiocarbon (∆¹⁴CO₂) is the radioactive form of carbon that is naturally found in the atmosphere but is absent in fossil fuels due to their age. By measuring ∆¹⁴CO₂ in the air, we can separate CO₂ emissions from burning fossil fuels from those naturally released by plants and soils. This research shows that using ∆¹⁴CO₂ measurements significantly improves the accuracy of emission estimates, particularly in regions with dense networks of monitoring stations, like western and central Europe. In areas with fewer stations, such as southern and eastern Europe, the uncertainties are higher, showing the need for better coverage.
Italy was used as a case study because its southern regions have relatively few monitoring stations. By running simulations, this thesis identified specific locations where new stations could make the biggest difference in improving CO₂ estimates. However, the study also found that adding too many stations doesn’t always lead to big improvements, which highlights the importance of smart planning to use resources efficiently.
Another important part of this research focuses on how to choose the best times and places to collect air samples. Prioritizing areas with strong fossil fuel signals and avoiding contamination from other sources, like nuclear power plants, helps make the data more reliable. These strategies are key to improving how we measure emissions.
This work not only advances scientific methods but also helps policymakers and organizations responsible for tracking emissions. By improving how we measure and understand CO₂ emissions, we can make better decisions to meet climate goals, such as those in the Paris Agreement, and ensure a more sustainable future for the planet.