The rapid development of digital tools and technologies in the world today enables us to analyze environmental and societal challenges on a deeper level and devise better fitting solutions. In 2021, researchers at IIASA made several pioneering applications of digital technologies to work on pressing global issues.

In collaboration with the University of Tokyo, Advancing Systems Analysis Program researcher Sebastian Poledna contributed to the development of the first-ever implementation of a macroeconomic agent-based model (ABM) on supercomputers. The ABM approach allows for creating a high-resolution model of a large economy like the Eurozone by explicitly representing the behavior of each individual and each firm in a region. The agent-based model was implemented on Fugaku, the fastest computer system in the world.

The Biodiversity and Natural Resources Program used machine learning to help policymakers adapt to agricultural climate vulnerability. For the first time, researchers combined crop model simulations, machine learning, and a large climate model to estimate the likelihood of soybean failures in the US Corn Belt under climate change. The model was successful at selecting the most relevant meteorological variables for crop failures, outperforming the two benchmark models that are in use today. The same technique has since been applied to modeling afforestation options in Southern and Northern Korea, resulting in several influential studies.

By combining machine learning and geographic information system (GIS) based mapping methods with a high spatial-temporal resolution, the IIASA Energy, Climate, and Environment Program has developed digital tools offering a novel perspective to data analyses. The methods were used to assess new global potentials for rooftop solar panels to generate electricity under different socioeconomic pathways.

The IIASA Population and Just Societies Program also used a new statistical model and machine learning tools to monitor and project food insecurity into the future for countries and regions. The researchers examined global temporal trends while accounting for the effects of the COVID-19 pandemic and found that while the rates of severe food insecurity are declining, the total number of moderately food insecure people has been increasing. By considering climatic and socioeconomic trends for the first time, the study presents a realistic picture of future food security, which has implications for the achievement of UN Sustainable Development Goal 2: ending hunger.