 The effects of climate change are already being felt today, particularly by the world's most vulnerable populations. And these impacts threaten to intensify over time, causing widespread global unrest, human suffering, and irreversible changes to our planet. To address these risks, we estimate that we need to flatten emissions and begin to reduce them within the next two decades. But meanwhile, trends in greenhouse gas emissions continue in the opposite direction, with ever-increasing fossil fuel energy consumption with each passing year. So it seems pretty clear that we're losing the fight against climate change. Well, actually, development trends in energy technologies tell a different story, with some low-carbon energy technologies improving at unprecedented rates. So how close are we really to a clean energy transition? You'll hear many well-formulated arguments at both extremes, that a transition is either inevitable or impossible. But to understand what's really going on, we need to take a deeper and more quantitative look, and we need to ask how evolving technologies measure up to people's needs and to climate targets, and what advances are still needed. This is what my research does, and I'll share a few results with you now. In the case of cars, for example, electric vehicles are the only powertrain technology available today that can meet long-term emissions targets, and they can reduce emissions substantially already today. But many people are deterred by range anxiety, which is the fear that your car will run out of juice without the potential to charge. Is this fear justified? Well, as I'll show you now, on most days it is not. When we set out to answer this question, the data did not exist at the level of detail needed to estimate the energy consumption required on a trip-by-trip basis across the entire U.S. So we developed a mathematical model that combines information in different kinds of data to develop the most expansive data set, the largest existing data set on personal vehicle travel in the United States. And when we do this, we see something interesting. Here we have data on the second-by-second travel behavior of millions of drivers in the U.S. We see that 87% of cars on the road daily could be replaced by a low-cost electric vehicle that saves consumers money, even if they can only recharge overnight. And this number is remarkably similar across different cities, from sprawling to dense urban areas. The reason is that there is a certain similarity in how people drive. Even though they consume different amounts of energy per capita, when they do drive in personal vehicles, there is a similarity in how they behave. Using this model, we can also quantify how improving battery technology can allow us to displace more and more gasoline with electric vehicles. As you'll see here, there are diminishing returns to battery improvement, although battery improvement will help, we're likely to need other long-range alternatives for quite some time going forward. And we're taking this model and its predictive power and developing an app that consumers can use to conveniently and reliably estimate on which days they'll need to turn to another kind of vehicle. What's still missing is a business model that allows consumers to order a long-range vehicle as conveniently as they order an Uber today. Cost is also important to consumers, and this year we released an app that allows you to see how your car compares to other models available on the market and to climate targets. What you'll see is that the lowest emission vehicles can actually save consumers money today. So how close are we to a transition and transportation? The technologies are there to allow this transition to begin, but it is far from a done deal. Less than 1% of cars sold in the U.S. today are electric vehicles, and the average car sold emits more than 50% of the 2030 emissions target. Individuals can make a difference. That's the point that we're at now, where individuals can make a difference. And we see this in other areas as well, in areas like stationary energy storage and solar energy. And we're using these results to inform the decisions by policymakers, technology developers, private citizens, as well as business leaders. This research is really about empowering people to make decisions that are within their reach as individuals but can bring about system-wide change. A clean energy transition is neither inevitable nor impossible, but the truth is that we've approached a tipping point where small actions by individuals can have large impacts. What I'd like to discuss with you is how we can use data-informed models to make those efforts as impactful as they can be, to move from adjectives to key informative numbers. Let's have a discussion about how we can enable individuals together to bring about the rapid energy transformation that's needed to address climate change. Thank you.