Thank you, Dave! Really appreciate you following along. That's very generous. Yes, Our World in Data is a non-profit, and donations really mean a lot. I am biased, but my teammates really do great work, and I learn a lot from them. That also supports my writing elsewhere.

As of today, there are more electric cars than diesel cars in Norway.

In high school, only 2 other girls in my year chose physics as their science subject. Most girls chose chem or biology. Climate obv involves chem, but probably more physics. In uni, there were very few other women in engineering courses. Chem eng was more popular, but not many in civil, electrical

Thank you! Less sure about climate science (probably because it’s quite physics-based, and of the 3 sciences that skews more male?) The energy field has a strong focus on engineering and construction, which again, are more male-dominated. I think this has been slowly changing.

When people see me working with headphones on, they probably assume I'm listening to calming classical or focus music. In reality, I'm blaring rap and grime.

At a few book events, I've been asked why individuals should care much about their own personal actions on climate when Taylor Swift flies around in her private jet all the time (this was at the height of her tour). Funnily enough, she is the most-listened to artist among my audiobook listeners 😄

I remember looking at demographic data of my followers on Twitter/X a few years ago, and it was very male-skewed (80/20, if I remember rightly). Interesting to see the differences for my audiobooks.

Just discovered that Spotify does a "Wrapped for Authors" on their audiobook demographics for the year. Fun! In my experience, climate/energy stuff is usually quite male-skewed, but I was pleasantly surprised to see that my book listeners weren't skewed *that* much!

This is a legitimate scientific revolution in meteorology. Also, to be clear, these models are not the AI LLMs that most people are familiar with. They are machine learning algorithms trained on observations (actually reanalysis).

In the last decades, the world has made fantastic progress against extreme poverty. In 1990, 2.3 billion people lived in extreme poverty. Since then, the number of extremely poor people has declined by 1.5 *billion* people. 🧵

How are you not laughing the entire way?

Still I think the next first year of falling emissions outside of some crisis (e.g. COVID) is important to wave as a flag of “emissions are down, we can’t let them go back up again. Let‘s get a move on”

The first year of falling global emissions after the peak (whenever that is) will probably also be fairly small, and within the bounds of uncertainty in emission estimates. So you‘d probably want multiple years of data to be confident.