Avoiding a bigger climate catastrophe should be a concern for everyone, but understanding how to do that could be a challenge for some. The EN Roads simulator is a way for people to easily understand how to end our destructive energy practices. It’s an easy to use interface that has tons of educational resources behind it, and if you like it you can get training on how to use it to train other people on the how we can save the climate.
Developed by Climate Interactive, the MIT Sloan Sustainability Initiative, and Ventana Systems, En-ROADS is a system dynamics model carefully grounded in the best available science, and has been calibrated against a wide range of existing integrated assessment, climate, and energy models. En-ROADS runs on an ordinary laptop in a fraction of a second, is freely available online, offers an intuitive user-friendly interface, and is available in over a dozen languages.
En-ROADS helps people make connections between things they care about and the possibilities available to help ensure a resilient future. Users can quickly see the long-term effects of the global climate policies and actions they imagine. The goal? To break through the noise and equip elected officials, business leaders, and others with the knowledge they need to implement equitable and high-leverage climate solutions. You can learn more about the science behind the simulator here.
When you think about climate change coverage in the Financial Times you may assume that they’re writing about how to profit from it; however, the tides have risen. The market-focused publication recently published a short and sweet game that explores how we can avoid climate catastrophe. Through a series of key decisions players need to figure out how to protect the environment and the wealth of the elite. Ultimately, players need to get the global economy to net zero by 2050. Can you do it?
It’s hard to predict the future, but with enough data we can at least get better at it. That’s exactly what digital twins are all about. By using as much real world data as possible to model out anything from a building, to a person, to a city in a digital space we can run simulations on what can work best for the real world counterpart. Of course, since simulations are only as good as the data source (and how we process the data) there are limits to effectiveness of digital twins; still, the idea that we can effectively model solutions and their potential outcomes in higher fidelity is appealing.
With the rise of the internet of things, sensor technology is increasingly being installed in our homes and workplaces, as well as the physical infrastructure that surrounds us. Meanwhile, cloud computing makes it easier than ever for data to be shared across different devices and networks.
As a result, businesses and other organisations have been able to build up huge volumes of data. Not all of this is private either â€“ online sources such as theLondon Datastoreare making live data readily available to anyone who wants to use it.
“We see digital twins as a way of improving decision making,” Hayes told Dezeen.
“A city is effectively a system of systems â€“ water, electricity, housing, schools, hospitals, prisons, natural environment â€“ it all fits together,” she said. “When you start to connect the datasets from these digital twins, you can build a bird’s eye view of a city, which gives you better information about the consequences of your decisions.”
Sadly there are still incidents of death that are a result of people panicking while evacuating spaces. For decades engineers have looked into ways to make buildings easy to evacuate and have made a lot of headway, unfortunately there are still times when their efforts are for not. Today the work into dealing with evacuating panicky people is being done by more than engineers; psychologist are using computer simulations to investigate new approaches to better building designs.
“One crucial aspect of crowd dynamics lies in the social interactions that take place between individuals,” say the authors. “These interactions create feedback loops and amplification effects and give rise to self-organized macroscopic patterns.”
The simulation was also run without the stressors and this led to some interesting differences. For instance, “In the absence of stress, participants tended to keep reasonably safe distances from their neighbors in order to avoid the collision penalty,” says the report. This means that there were almost zero body contacts. In the regular escape, the participants were prepared to sacrifice points in order to jostle their way to a faster exit.