Decision-making models for decarbonization

In recent years, countries have committed to reducing greenhouse gas emissions to curb the negative effects of climate change. Burning fossil fuels for energy such as electricity, heat, and transportation fuel is a major contributor to greenhouse gas emissions. In 2019, the global energy system contributed 34% to overall global greenhouse gas emissions. In combination with other energy-intensive sectors such as transportation, industry, and buildings, energy use makes up 80% of emissions. Many countries recognize the need to convert to cleaner forms of energy to reduce emissions, but transforming the global energy system is far from simple.

As policymakers start to plan out these transitions it is helpful for them to consider scenarios of potential outcomes. In response to this demand Tufts PhD student Jacob Wessel and Associate Professor Jonathan Lamontagne have been working with researchers from the Pacific Northwest National Laboratory, Peking University, and the Korea Advanced Institute of Science and Technology to model future scenarios that consider multiple factors. Their work, “Large Ensemble Exploration of Global Energy Transitions Under National Emissions Pledges,” was recently published in Earth’s Future.

The research explores how different countries may meet emissions reduction goals and how impacts vary regionally. They factor in eleven sources of uncertainty from different sectors including socioeconomics, technology, institutions, demand patterns, and more. The ensemble can be expanded or narrowed to focus on individual regions or consider additional uncertain factors which will give flexibility to analyze different types of scenarios. The resulting simulations identify challenges and opportunities associated with different action plans and provide insight into how they can be distributed across regions.

Previous research in this space has typically focused on a select few future scenarios to explore, which limit the range and diversity of outcomes. Rather than focusing on specific isolated scenarios, the group generated and analyzed over 5,000 future scenario pathways. They combined their framework to model updated national emissions pledges set in the Paris Agreement, along with countries’ long-term strategies to reach net-zero. These considerations give their project real-world relevance and are designed to make the results as useful as possible to decision-makers.

Across the simulations, the researchers noticed the importance of regional difference, with larger economies and developing regions experiencing the most severe economic outcomes across a range of inputs. The results speak to the importance of including such regional differences regarding institutional quality and investment costs in multi-region studies. These findings could be helpful for decision-makers as countries design international climate strategies to meet their goals.

At Tufts, Lamontagne’s research group aims to improve decision making for multisector systems confronting uncertainty, including climate change, population growth, and technological innovation. Other recent projects include analyzing potential nonlinear risks of negative outcomes due to joint population and economic growth uncertainty and developing a novel method for projecting future drought and flood risk under climate change.

Learn more about the Lamontagne Lab.