Seite - 17 - in options, Band winter 2021

MODEL ROLES The institute’s mathematical arsenal includes optimization models, agent-based models, statistical models, game-theoretic models, and many other model types used in various combinations to deal with climate, energy, and pollution; food and water; natural disasters; economy and demography. Where several different goals compete, optimization models can help to find a balance. A highly successful example is the IIASA air pollution model, originally known as the Regional Air Pollution Information and Simulation Model (RAINS). In the 1990s, RAINS helped to guide Europe’s policy on six pollutants, including particulates and sulphur dioxide (the chief cause of acid rain), calculating costs and health effects of various policies. RAINS results in Europe and India have shown the power of cooperative action on air pollution, which is much more effective than efforts by any single state, and therefore more politically attractive. Now extended to include greenhouse gases, the Greenhouse Gas and Air Pollution Interactions and Synergies (GAINS) Model reveals how clean-air policies can have co-benefits, improving the health of people and ecosystems while also curbing climate change. The mathematics behind these models is constantly being developed to deal with new situations and complexities. New sources of data, such as crowdsourcing and novel sensors, are feeding in, and models in different areas are being linked together, to reflect real-world links between systems such as climate and the biosphere. HUMAN VALUES The aim of all this analysis is to steer systems in the right direction. But what is the right direction? Right for whom? On top of that, the shape of social systems is constantly changing, making them hard to navigate. To provide both a moral compass and societal map, systems analysis takes a human-centered approach, engaging with diverse viewpoints. The soft systems methodology provides one way to do this. It is a formal process with several stages, but the essence is to bring people together to sketch out a system, identify goals and possible actions, and then model the system to find out what each action would do. That may involve a causal loop diagram, laying out how the system’s components are connected to reveal critical feedbacks. The whole process is often iterative, with one round of analysis producing insights to inform the next round. Sometimes this can lead to a consensus that satisfies everyone. It can help solutions to stick, because people that have participated in a process are much more likely to trust its outcomes and support action. Other times, people are implacably opposed, but even then, developments in systems analysis are making progress possible. By acknowledging that even diametrically opposed worldviews can be equally valid, it can turn a stalemate into a compromise. In Nocera Inferiore in Southern Italy, conflicting views on how to deal with the risk of landslides had stymied any action. One group favored natural solutions such as tree planting; the other favored artificial barriers. From 2010 to 2013, IIASA led a participatory process with experts and participants working together to generate solutions for each opposing view, rather than imposing an expert-preferred solution. The groups eventually negotiated a mixed approach. So systems analysis is an infinitely adaptable multi- tool, transforming to fit the particular complexity of each subject. It can shift perspectives: embracing different physical systems, disciplines, scales, and viewpoints – giving it a unique ability to grapple with the fiendishly difficult problems posed by today’s fast- changing and increasingly interconnected world. Further info: pure.iiasa.ac.at/16385 pure.iiasa.ac.at/16707 JoAnne Linnerooth-Bayer bayer@iiasa.ac.at Elena Rovenskaya rovenska@iiasa.ac.at Fabian Wagner wagnerf@iiasa.ac.at By Stephen Battersby 17OptionsWinter 2021www.iiasa.ac.at