By Rachel Fritts
On the last day of MIT Orientation Week, I found myself in a room with about 50 other new MIT students participating in an interactive climate policy game called “SimPlanet.” Over the course of four hours and under the guidance of John Sterman, Jay W. Forrester Professor of Management, our goal was to work together to implement policies that would hold global warming to 1.5 degrees by 2100.
To help inform that goal, we were given the opportunity to beta-test a new climate model called En-ROADS. The first thing I was struck by when I saw the model was that it was the first time I had seen so many potential climate policies in one place. The model takes 18 different variables into account, allowing users to see how different policy decisions impact warming. Crucially, it also takes into account how each policy decision will impact the decisions that follow.
As I looked at the model, I realized that I didn’t actually know how these different policies compared to one another. I had thought a lot about individual climate solutions as a student and as a journalist, but I had rarely thought about all of them at once. Would a carbon tax impact projected warming more than a renewable energy subsidy? How many trees would we have to plant to lower the amount of carbon in the atmosphere in a meaningful way? I was eager to find out, but this simulation was meant to model the real world, so there was a catch.
We couldn’t just toggle all those enticing variables at will. As soon as each student entered the room, we were seated at one of eight tables that represented a different interest group. My tablemates and I were standing up for Land, Agriculture, and Forestry. Others spoke for interests like conventional energy and environmental justice. We were given primers that told us which policies were in our individual interests, and which we should object to. This aspect of the SimPlanet simulation served as an important reminder: the policies that got through were as likely to be determined by political interests as the best available science.
Sterman explained to us how the first round would work. Each table would debate internally and choose a few pet policies they might promote or oppose, and then we would go around the room, one by one, and propose a single policy to implement or block. The model would be updated as we went. Since my table represented agriculture, our primer told us we strongly opposed regulation of methane, while afforestation was something we could get behind.
When I read over the primer, it was difficult for me to see how any progress could be made. As a student sitting in a room playing a game, I just wanted to figure out which single decision could make the biggest impact on warming. As a representative for land and agriculture, I was more interested in making sure no one turned their attention to cows.
Predictably, many tables used their turn to block a solution against their own specific interests rather than propose one, and in the end, we had gone from a “do nothing” scenario of 4.1 degrees of warming to a “do barely anything” scenario of 3.1 degrees of warming. Not an inspiring start. To represent the flooding of coastal cities and general peril we had consigned ourselves to, Sterman went to each table one by one, passing a large blue sheet over our heads.
I had never been chastised by a sheet before, but it was surprisingly effective. As he swept the sheet over us, Sterman told my table about all the crops we had just lost to flooding, drought, and heat waves, and the land we had lost to rising sea levels. Then he showed slide after slide of climate change-related disasters and extreme weather events happening right now—not 80 years in the future. The message was clear: If we couldn’t work together to find policies we agreed on, we would all suffer. Point effectively proven, Sterman gave us a second round to fix our mistakes. This time, though, we would have to talk to each other.
Things went differently. Each table sent out ambassadors to persuade other tables to make compromises or form alliances. Some negotiations took longer than others. When time was called, at least half the room had converged at the Conventional Energy table—a physical reminder of the sway of the fossil fuel industry.
The second vote was noticeably more strategic. My own table whispered about proposing a carbon price but decided against offering up a measure with a good chance of getting nullified by someone else. Instead of going after specific industries, many tables decided to propose investing in new technologies or improving energy efficiency. And almost none of us blocked. A coal tax and carbon price both slipped through, and my table allowed some methane regulation. At the end of the second round we had gotten down to 1.9 degrees of warming—not quite our goal, but much better than we had done before we had reached out beyond our respective silos.
This process was fascinating to me. I was struck by how different the two rounds had felt psychologically. In the first round, we were all playing a game, and everything felt very abstract. I was supposed to stand up for land and agriculture, and that’s what I did. In the second round, after a fresh reminder of the consequences of climate change and an urge to find common ground with other groups, the goal felt different. There would be negative consequences for all of us if the climate warmed to 3.3 degrees. We had to band together and find a solution while we still could.
The event ended on a hopeful note, with Sterman highlighting environmental movements and MIT alumni who were making a difference. I left frustrated that we haven’t already implemented some of these policies that have such a clear effect, and nervous about the monumental effort required to mitigate climate change.
But I also felt strangely empowered by the knowledge provided by the model. Because it put so many potential solutions in one place and took their interactions into account, there was a degree of clarity I had never felt when thinking about climate change, which can feel at times like a distressingly nebulous problem. The model also made one thing very apparent—no single solution can come close to solving the problem. It has to be a team effort on a global scale.
Rachel Fritts is a student in the MIT Graduate Program in Science Writing and the resident science writer at the MIT Environmental Solutions Initiative. SimPlanet was hosted by ESI on September 3, 2019, with the support of Professor John Sterman and Climate Interactive.