Episode 164

Charting a Hopeful Future with Data Wisdom by Hannah Ritchie

Episode Summary: Olabanji and Jeremy are joined by Hannah Ritchie, a Data Scientist and the Deputy Editor and Lead Researcher from Our World in Data, a non-profit focused on uncovering facts about the world's most pressing issues.

Hannah is also a TED speaker and a writer.

In this episode, we delve into Hannah’s book, "Not the End of the World - How We Can Be the First Generation to Build a Sustainable Planet", a guide for understanding and addressing global environmental challenges.

Hannah shares how she merges her love for science and writing to explore and explain complex issues through data.

We dive into intriguing topics like the true impact of palm oil, the surprising benefits of electric vehicles in cold climates, and how we can address multiple environmental problems with singular solutions.

Her insights provide a deeper understanding of sustainability, debunking myths, and highlighting the importance of a data-driven approach to environmental issues.

So tune in, as Hannah Ritchie helps us navigate through rumors and facts, bringing clarity to our collective mission for a sustainable future.

https://hannahritchie.com/

https://ourworldindata.org/

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Visit thecarbonalmanac.org/podcasts and send us a voice message on this episode or any other climate-related ideas and perspectives.

Don’t Take Our Word For It, Look It Up!

https://thecarbonalmanac.org/

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Featuring Carbon Almanac Contributors Olabanji Stephen and Jeremy Côté.

Olabanji is from Lagos Nigeria. He’s a Creative Director and visual designer that helps brands gain clarity, deliver meaningful experiences and build tribes through Design & Strategy. He founded Jorney - a community designed to help people stay productive, accountable, and do their best work.

Jeremy is a scientist, an athlete, a coach, and a writer from Québec, Canada.

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The CarbonSessions Podcast is produced and edited by Leekei Tang, Steve Heatherington and Rob Slater.

Transcript
Speaker:

Hi, I'm Christina.

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I'm from Prague.

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Hi, I'm Jen, and I'm from Canada.

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Hi, I'm Oladunji, and I'm from Nigeria.

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Hello, I'm Liki, and I live in Paris.

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Hi, I'm Brian, and I'm from New York.

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Welcome to Carbon Sessions, a podcast with

Carbon Conversations for every day, with

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everyone, from everywhere in the world.

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In our conversations, we share ideas.

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perspectives, questions, and things we

can actually do to make a difference.

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So don't be shy and join our Carbon

Sessions because it's not too late.

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Hi, I am Ola Bungie.

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Hey, I'm Jeremy.

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Hi, I'm Hanna.

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All right.

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And this is Carbon Sessions.

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So here at the Carbon Almanac

Network, one of our key ideas.

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Both behind the book and the community

is that to really create change, we

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need to have useful conversations and

useful conversations requires knowing the

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facts of whatever you're talking about.

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So today we have, uh, we have a

guest who thinks, writes about and

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excavates those facts for living.

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So we have Hannah Ritchie here from our

world in data, a nonprofit dedicated

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to publishing research and data to make

progress on the world's greatest problems.

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So.

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Outside of Our World in

Data, Hannah also does a lot.

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She's given a TED talk this summer.

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She, uh, she's been writing

a book, which we'll get into.

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And she's also writing a, uh, weekly

ish newsletter, which is really great.

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I highly recommend it.

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I've Read all of these, uh,

all of these new dispatches.

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So first, Hannah, I want to say

congratulations on the announcement

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last week from Vox for being

part of the future perfect 50.

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It was really cool to see you with all

of the, all of the others in the cohort.

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No, thank you very much.

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Yeah, it was a big surprise to me as well.

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Like they tell you like a day

before, Hey, you're going to be

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announced tomorrow as on this list.

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So yeah, it was a great privilege.

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And there's like other amazing people

on the list, especially on like climate

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stuff, um, that I really admire.

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So it's like a pleasure

to be next to them.

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Yeah, yeah, no, it's like I was just like

reading some of the people on the list.

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And yeah, it was like a really,

really cool, like suite of people

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doing, uh, doing really great stuff.

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Okay.

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So I wanted to start off this conversation

really about the, the book that you've

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been writing and getting ready to

publish, uh, in about a month from now.

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And what I wanted to ask you is this book,

it's called not the end of the world.

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It's a book that you wrote kind of for.

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For others, but also for a younger

version of yourself, you wrote that

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it's like the, it's the book that you

wish you had when you were younger.

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So what I wanted to ask at the

beginning is just when did this

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book start percolating within you?

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Was it something that like, when you

were younger, you're like, okay, I,

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I wanted to write something and then

you didn't really know what shape it

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was going to take, or did it just come

more like within the last few years?

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Yeah, so I think I've always loved books.

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I've always liked reading, I've

always loved writing, and I think

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when I was younger I always saw that

maybe someday I would write a book.

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That was kind of the dream.

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And I think even when I was deciding,

like, when you get to that fork in the

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road, like, after school and going to

university, I think there was two paths.

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One, I could go down a very

scientific path, or the other was

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I was really interested in writing.

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I could see myself maybe being,

like, I don't know, like a

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science journalist or something.

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So, like, I also had this And I tried to

decide, like, should I go for the science

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degree and then do writing on the side?

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Or should I go for the journalism degree

and try to learn science on the side?

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And I decided I should go the science

route and then try to just, um, enhance

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my writing skills along the way.

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So, yeah, I've always

had an interest in this.

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I think that It came down to when was

like the right time to write the book.

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And I think, I think I had this kind

of brewing for maybe a decade or so.

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Um, and I think it was, I, once I started

writing it, I could feel like, I think

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this is like the, the right time where I,

I feel like I've built up enough knowledge

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and, and building the narrative around

it that I can, I can produce like a.

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A good book here, um, whereas I

think if I tried to do it a few years

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earlier, I maybe could have produced

an okay book, but I think it wouldn't

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had, have had like the full, uh, kind

of narrative enveloped around it.

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So I felt like this was like

the right time to go for it.

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Yeah, totally.

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And like one of the, like one of the

things I noticed while reading, reading

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the book is that you aren't just,

you do infuse bits and pieces of your

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own journey within, within the book.

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But really it's a, it's a book

about facts, a book about data,

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a book about long term trends.

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And like you were saying, it's probably

a good Testament that you waited for

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a while before writing this book.

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So you can really amass all of this.

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All of this knowledge because you tackle

like a wide range of topics, right?

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Like you were tackling a lot of the

big problems within sustainability,

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but this like touches on many

different aspects of our world.

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Yeah.

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So every chapter is a different

environmental problem.

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So actually climate surprisingly

is just one, one chapter.

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And then there's air

pollution, deforestation food.

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There's like seven different.

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problems.

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I think the key point is that they

tend to all interweave together.

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So they're, they're not like, it's

not as if we're tackling seven

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completely different problems and

we need 50 different solutions

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for these seven problems.

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I think the, the solutions

often interconnect to one

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another, but yeah, I think.

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I think a key part of this process was I

didn't, when I, when I started researching

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this stuff, like maybe like five, ten

years ago, I never ever came into these

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questions like knowing the answer.

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It's been a journey of, I have this

question, I'm sure other people also have

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this question, what does the data and

research tell us in a pretty objective

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way, like trying to put the kind of

subjective moral lens aside and to

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say, like, what does the data actually

tell us about what's happening to CO2

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emissions or deforestation or plastics?

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And, and that kind of curiosity really

spurred me to, to try and find the

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answers and then try to explain them.

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But I think if I publish it a few

years earlier, I, I don't think I

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would have had the complete package and

probably I would have got stuff wrong.

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Yeah, for sure.

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Uh, this, this makes total sense.

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Can you, do you have like some examples

where you have come across some piece

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of research or some data where like

it really kind of went against what

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you would have guessed going in?

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Yeah.

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I think one of the key examples

there, um, Is palm oil.

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So I did a big project for our

own data looking at deforestation.

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And I think I, I had in my head,

like most people have in their

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heads, is that palm oil is evil.

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If we want to stop deforestation,

we need to stop producing palm oil.

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And that's kind of the, the

framing I had into my head when

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I went into doing the topic.

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And then kind of my perspective

on that was turned a lot just by

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looking at the data and research and

what experts were saying on this.

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I would have thought the solution to

the palm oil problem is just a boycott.

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Boycott palm oil and not use

it entirely, and actually none

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of the experts recommend that.

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And just briefly, the reason

for that is that palm oil is an

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incredibly productive crop, right?

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In terms of producing vegetable oil,

palm oil is how you produce the most

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amount of oil using the least land.

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So palm oil has led to

deforestation, that's irrefutable.

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Um, But the question is, if you

weren't using palm oil to meet that

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demand, what would you use instead?

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So if you were to switch to a different

crop, say, coconut oil, for example,

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you would actually need to use more

land to produce the same amount of oil,

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which would mean you would actually

displace The deforestation elsewhere

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and actually would increase the

amount of deforestation that you had.

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So I think you often, when you

step back to look at the data and

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the research, you often find these

counterintuitive findings, which is

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actually quite a better pill to swallow.

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Cause we always have this preconceptions

and we want to find evidence that, that

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confirms those and exacerbates those.

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Um, but actually in this case,

the data did not tell me what

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I expected it to tell me.

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Yeah.

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Yeah.

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I remember.

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reading this part of the book and yeah,

definitely it's sticking out to me.

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So I guess like one of the, the,

one of the elements here about

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digging into data is also thinking

about these knock on effects, right?

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So like you're talking about palm oil

and saying like, it's not just about

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like how, but, but the oil itself, but

it's about like these knock on effects

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of like how much, how much land do

you need to grow, uh, to grow this

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particular, um, crop and like how, how.

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How does this like affect other

parts of the of like the whole supply

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chain for palm oil, for example,

so I suppose this is also like a

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difficult, um, it's a difficult skill

for many people to, to, to build, or

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rather, it might take a long time.

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I mean, you've been doing this now for

a while, and so you might like come

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across some, some piece of data, and

then you're like, okay, I have this

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piece of data, but what does this

mean for the next like parts in the

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chain here and for for someone that.

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It's just, uh, it's just starting

out or they just might be, um, like

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say seeing a figure in the news or on

television or something like this, it

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might like lack this context, I guess,

for really understanding what's going on.

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Yeah, I think, I think the

key point there is the.

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I try to never just go with my gut or go

with my intuition because even after doing

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this data stuff for a long time on topics

that I know very little about or coming

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new to, I just, I don't have a sense of

intuition for it and I think most people

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don't have a sense of intuition for it.

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I mean, that's fine.

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I mean, the point is you step

back, you take your time, you look

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at the data to try and understand

it before jumping to conclusions.

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I think what's really key, you

highlight a really important point

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that there's often knock on impacts,

positive or negative in various ways.

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I think what's really key for me when

we're talking about solutions in this

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space is that I think We too often

are looking for this perfect solution.

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So we're looking for the energy

technology that has zero impacts,

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that you don't need any land.

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You don't need any materials.

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It has zero carbon emissions.

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I think the reality is that there's

just no perfect solutions in this space.

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And I think we need to

come to terms with that.

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And I think if we don't come to terms

with that, then we really, really slow

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down progress because we, we rule out any

option that has a tiny amount of impact.

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So I think what's important with the

numbers is to try and give a sense of

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perspective of, you need to just say,

it has this impact compared to what?

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So if, um, building a solar panel

maybe emits a bit of carbon because

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you're using energy to do that, the

correct conclusion is not, this is a

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bad option because it emits carbon.

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The question is, how much carbon does

it emit compared to coal or compared

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to gas, which you're replacing it with?

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And the answer is way, way, way, way less.

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So we should be pursuing those solutions

because it just makes a massive

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difference compared to the status quo.

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But if we're expecting that we're going

to find solutions that have zero impacts,

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then we'll just be looking forever and

we actually won't make any progress.

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Yeah, I think that that's incredible.

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I was going to ask a dummy

question, which was, what would

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you say the role of data is?

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But I think that you already

sort of started to outline

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What the role of data is.

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I mean, I wouldn't say ideally, but

I mean, general thinking is that it's

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more like, well, you get the data

and you, um, set a course of action.

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But from what you're saying, it's more

like, well, if you get the data, you

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have to do some thinking, you have to

do some comparison, you have to do some

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interpretation of the data before, um,

getting to, Yeah, I think the role,

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the role of data there is to try to

find some grounding and truth on what's

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going on and what options we have.

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I think, I think what's really cool

for us, uh, our world in data and

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also a bit in my communication on

climate as well, is that I think, I

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think too often it's portrayed as.

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Just follow the science.

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And that's what people

would say with the data.

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Just follow the data.

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But the role of science and data

there is not actually to tell anyone

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what we should do, because that's a

much bigger question that takes into

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consideration what does the science

say, um, what are the political

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considerations around that, what are

the economic considerations around that.

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Just following the data or following

the science won't get you to a concrete

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conclusion of this is what we should do.

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But what science and data can tell you is,

is we're on this course on climate change.

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Once we start to reach these temperatures,

these are what the impacts are.

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And then it's actually for others

to make the decision of, okay, this

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is bad, what should we do about it?

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It's about the data which will tell

us, um, if we want to reduce carbon

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emissions, these are our options.

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These are the most effective options.

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And then it's about others to, to

figure out, should we implement them?

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What scale should we implement them at?

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So I think that's the role of the

data is to, is to show, show a range

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of options, a range of, Of, of, of

futures and then it's for, and sometimes

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others to then decide we should do this

based on the evidence that we have.

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Yeah, this makes a lot of sense.

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And it's something I, like, I

wouldn't have appreciated as much

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like in my, so I'm, uh, I'm like,

uh, have a scientific background.

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So like me, it's like very, uh, for

like physics and mathematics and like.

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Thinking about these topics and

then like kind of abstracting away.

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It's like, okay, the, the question of

like what you should do is different.

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And then it's like, just look at the

data, but yes, this point of, uh, you

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need to kind of map out the possible

futures, but this doesn't tell you

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anything about which futures you

should be taking or you want to take

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or what most people will want to take.

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So this is also a challenge.

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I want to ask you, um, something I've

been wondering a lot about is how do

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you get people to care about data?

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Versus their own perspective.

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So your colleague, um, Max Roser

has, has, has this essay called like

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the, the value of statistics and the

limits of our personal experience.

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And I thought it was, it was bringing

up a really good point of that.

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We, we can base a lot of our worldviews

on just kind of our own personal

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experience of the people we talk

to, but this doesn't necessarily.

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necessarily represent the whole world

or it doesn't inform us on some of

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these like bigger worldwide questions.

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So do you, do you have any

thoughts on like how we can get

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people to care more about data,

care about digging into the data?

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Yeah, I think, I think, uh, yeah,

Max's article on that was very good.

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One point of his article was

one, if you're basing it on like.

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Personal perceptions around you and your

kind of personal story and maybe your

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personal stories of a few people around

you, you're building like quite a narrow

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base of, of understanding the world.

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But I think he also highlighted that you

get this problem with media where, um,

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if you think of it as little, I think

the way he framed it was like little dots

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on like this black, kind of black sheet.

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And with the, with, uh, kind of

personal experiences, you're building

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lots of dots around your little

circle, like it's people around you.

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What you get from the news media

is maybe little dots, but like

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spread really far out, right?

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So I might get a perspective of one news

story in Thailand, and one news story

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in China, and one news story in the U.

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S.

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But again, these are just really,

really small snapshots that

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don't let us build a complete.

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Vision of the world.

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And the only way to really do that is to,

to look at data because with data, you

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can essentially capture the experiences

of eight billion people, right?

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You can figure out what's going

on with CO2, what's going on with

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poverty, what's going on with hunger.

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So data is really the route into

understanding the bigger picture.

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Um, how to get people to care about it

is, is actually probably with great.

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difficulty.

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I think one way to do it is

I think what I found joy.

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I mean, I didn't start

out as a data scientist.

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I was an environmental scientist.

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I mean, what really sparked interest in

it for me was often these counterintuitive

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findings or actually just the appreciation

that like a lot of my perceptions were

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actually really out of line with the data.

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The way I discovered this was

through Hans Rosling who would do TED

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talks where he would basically show

that all of our like really basic.

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conceptions about the

world were really wrong.

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And for me, that like, that's part of.

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Where the joy in that came from was

an exchange of this joy of finding

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out that I was completely wrong.

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But then this curiosity of going

out to find out, like, what

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does the data actually show?

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So I think to some extent it's playing

on the curiosity to understand the world.

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Okay, I've got a question.

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Um, so I mean, and I know you interact

with people every day in the course of

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the work that you do, but what, what is

a random person's relationship with data?

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Like, like someone that

just comes across data.

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How, I mean, in your experience,

how do they even approach data?

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What is the, what is the most common

relationship that people have with data?

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Because I think it, Yeah.

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And the other part of the question is,

what should our relationship with data be?

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Um, because, I mean, on Carbon Sessions,

we have pretty regular people listening

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to this, and they just need something

that can help them the next time they come

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across something that we've discussed.

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So, the first question is, what's

people's relationship with data like?

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And then, what should it be like?

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Are there a set of questions I

should be asking before, or are

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there, like, very basic tools that

I can use to interpret the data?

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Um, like, what, what, what does

that look like, generally speaking?

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Yeah, I think that's a good question.

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I think Most people's interaction with

data, I would say, comes from the news.

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I think where people most frequently will,

will, uh, be exposed to data is, is a

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statistic in a news article, or on the TV

news, or if you get media, uh, your news

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through Twitter or social media platform.

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It's like within a framing of a story

within the media, I think, is where

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most people are exposed to data.

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Now, I think one of the dangers of, of

data is that as soon as someone uses

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a statistic or a number or a graph,

it takes on this field of authority

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of, of course, this must be correct.

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Um, and I think that is actually a

danger in itself because there are

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ways, I mean, there's loads of books

on how to lie with statistics or how

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to manipulate data, which The number

there might be actually correct, but

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it's actually giving you a different

framing or a different understanding

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of the situation just by leave, what,

basically what's being left out.

338

:

So I think one, like, when, when

you come across a statistic, I think

339

:

some really key questions to ask

are one, who's publishing this data?

340

:

Um, is there, you know, some ulterior

motive behind it where you should

341

:

be a bit more skeptical than normal?

342

:

Is that an impartial source?

343

:

Um, again, framing it in the context.

344

:

So I think if you think about carbon

emissions, for example, just a

345

:

really good barometer is considering.

346

:

Like scale.

347

:

So is it hundreds, thousands,

millions, billions of tons?

348

:

Like globally we emit around 41

billion tons of CO2 every year.

349

:

So if you're thinking about something and

you see thousands of tons of CO2, like

350

:

we automatically think when it comes to

thousands of, wow, that's really big.

351

:

But in the scale of 41 billion tons,

that's really, really not a lot.

352

:

So it's trying to bring context

into, is that a big number?

353

:

And then I think another key thing is

to, it seems really basic to, but to ask.

354

:

What's the, what's actually

being measured here?

355

:

Or like, what's the actual

definition of this metric?

356

:

Because I think this can often trip

people up where, but the metric

357

:

is actually not representing what

they think that it represents.

358

:

So actually a big focus for us,

which seems really stupid, but

359

:

on our world in detail, we spend

a ton of time with our top.

360

:

Our titles and subtitles because

people will look at the chart and they

361

:

read the title and the subtitle and

that's how they perceive the data.

362

:

So it's really core for us that when

people are looking at a graph on our own

363

:

data, they can immediately understand

this is what this metric captures

364

:

and this is what has been measured.

365

:

And I think when you just see a

number, a news article, you often

366

:

really don't have that perspective.

367

:

Yeah.

368

:

And what's.

369

:

Turns out to me right now is

putting context to the data.

370

:

I think that is very, very critical

because otherwise then we risk

371

:

misinterpreting the data just

with the example that she gave.

372

:

So thank you.

373

:

Thank you so much.

374

:

Yeah.

375

:

And this idea of not having numbers in

isolation or data points in isolation,

376

:

this can be very, very, very tricky

to understand what's going on.

377

:

If you just have one number

and no context around it.

378

:

I think with this one, there's

something, there's one is.

379

:

more thing on that is to also rather

than just always look at like one

380

:

snapshot is to look at the trend.

381

:

Um, cause I think that also really shapes,

um, your understanding of this issue.

382

:

So, um, like one example I might

use there is, um, which is not

383

:

related to climate, but we cover

global health is child mortality.

384

:

Right.

385

:

So.

386

:

The number of children that die

every year is around 5 million.

387

:

Right?

388

:

So that's horrendous, and most

of those deaths are preventable.

389

:

But, just looking at that number, 5

million, that gives you no perspective

390

:

as to, like, going up or down, or

things getting better or worse.

391

:

You might look at that 5 million and

assume, well, this is just the highest

392

:

that child mortality has ever been.

393

:

Like, the world's just getting

worse and worse and worse.

394

:

But actually, when you look at

the trends, like Chill mortality

395

:

is falling very quickly, so a few

decades ago that was 12 million.

396

:

Um, and go back further in history

and it was, it was even higher.

397

:

So I think it's important to

understand the trend and the

398

:

direction of travel so that you can

frame that number within context.

399

:

Is it going up or down?

400

:

Are things getting better or worse?

401

:

And that's not to course, that's not to

dismiss that 5 million doesn't matter

402

:

or that we're in a fine position.

403

:

But I think actually looking historically

and seeing that we have made progress,

404

:

that number is going down, should give

us a drive to say, well, we, we won't

405

:

accept that 5 million children are

dying and we can drive that down lower.

406

:

So I think looking at the

trend is also important.

407

:

Yeah, that's, that's right.

408

:

I wanted to, I wanted to pivot a little

bit and, and talk about, um, Talk about

409

:

sustainability because this is like

one of the core themes in your book.

410

:

I mean, okay, we were touching on this

already, but, um, one of the first things

411

:

that I, that I learned, um, while reading

your book was just this, uh, this very old

412

:

definition of sustainability and how it

like has, uh, has multiple parts to it.

413

:

Can you speak a little bit about

this for, uh, for, for our audience?

414

:

Yeah.

415

:

So, I mean, I think there are just

multiple definitions of sustainability

416

:

and I think like, it's very.

417

:

It's totally fine to debate those.

418

:

I think as an environmentalist,

my, and my, coming at that from

419

:

my background, I would often frame

just sustainability as having a low

420

:

environmental impact so we don't ruin

the planet for future generations and

421

:

other species on the planet as well.

422

:

But I think to me that that's

a bit of a limiting definition.

423

:

And the reason I say that is because it's

not just about having a low environmental

424

:

impact for future generations.

425

:

I also care about the

current generation, right?

426

:

I care about human suffering.

427

:

I think everyone alive today

should have access to like a

428

:

good high standard of living.

429

:

And actually that comes to the definition

that's like a bit more like a conventional

430

:

sustainable development definition, which

has two halves and one half is meeting

431

:

the needs of the current generation.

432

:

So ensuring that eight billion people

have a good life and, um, not sacrificing

433

:

opportunities for future generations.

434

:

So that's about having a

low environmental impact.

435

:

So basically provide a good

life for everyone without having

436

:

a high environmental impact.

437

:

I think the argument I put forth in

the book is that historically We've

438

:

actually never really achieved both

of those halves at the same time.

439

:

I think we have this notion that

we've only become unsustainable

440

:

in the very recent past, and I

actually don't really think that's

441

:

true based on this definition.

442

:

And the reason is our ancestors might

have had a low environmental impact,

443

:

but they did not have high standards

of living, at least not by our

444

:

kind of modern definitions of that.

445

:

And the example I use in the book

is, is child mortality, where for

446

:

most of human history, between a

third and a half of children were

447

:

dying before reaching puberty, right?

448

:

That's like unimaginable levels to, like,

we could never imagine those levels today,

449

:

that half of children would, would die.

450

:

But that was like, the reality

for most of human history.

451

:

What we've had over the last few centuries

is almost like a tipping where human

452

:

living standards have improved a lot

and they've improved across the world.

453

:

This is not just like, uh, elites

have, have, um, living conditions

454

:

for the elites have improved.

455

:

Like child mortality has

fallen across the world.

456

:

Extreme poverty has

fallen across the world.

457

:

We have education, vaccines, like

we've made amazing human progress

458

:

over the last few centuries, but it's

came at the cost of the environment.

459

:

So we are now face all of

these environmental crises.

460

:

And the argument I put forth in the

book is that I think we could be

461

:

the first generation that does both

of these things at the same time.

462

:

I think it is possible to

continue human progress with

463

:

a lower environmental impact.

464

:

And I think that we would

be, in some sense, the first

465

:

generation to achieve Yeah.

466

:

And I mean, part of, part of this in

your book is you have this, uh, like this

467

:

concept, I'm calling it like decoupling

where it was like these standards of

468

:

living keep going up, but we can decouple

these from kind of the, uh, you can call

469

:

it like extraction of resources or like

negative impacts to the environment.

470

:

And I thought this was, this was

quite a, quite a, quite a neat idea.

471

:

Like I hadn't really.

472

:

seen these, these, uh,

charts before showing this.

473

:

So I thought this was quite eyeopening.

474

:

So I mean, if you take the example of,

of CO2 there, um, we've seen historically

475

:

this really tight relationship that as,

uh, GDP, so as goes up, so as people

476

:

get richer, they tend to just lead more

energy intensive and carbon intensive

477

:

lifestyles, and that's completely true.

478

:

And that's what the data says.

479

:

But what we are also seeing is that it

is possible to decouple these impacts.

480

:

So you can increase GDP or increase other

metrics, which would be, represent human

481

:

standards of living with CO2 emissions.

482

:

And the reason for that is you can

replace the coal or the gas or the petrol

483

:

car with Uh, solar or wind or electric

vehicles so that your CO2 emissions come

484

:

down, but actually you're not impacting

the standards of living in that country.

485

:

So it is possible with technology

combined with economic and political

486

:

solutions that you can bend that curve

and actually decouple these two things.

487

:

So, so then I guess my.

488

:

My, my like follow up question to this

is that this, this idea of like, we have

489

:

these sustain sustainability with these

two parts and this idea of decoupling

490

:

means that we can keep improving the, um,

the, the lives of people today without,

491

:

uh, sacrificing those in the future.

492

:

I wondered for you, this

is not, this is not.

493

:

As much of a data question, or

maybe it is, you can tell me if

494

:

it is more of a data question,

but how do you balance these two?

495

:

So like now it was like, okay,

sustainability has these two

496

:

parts, but how do we actually

think about balancing them?

497

:

Because, okay, we could like prioritize

the needs of people today, which

498

:

is kind of, I guess what we did

historically, because you can't really

499

:

think about people in the future when

you need to like survive yourself.

500

:

And now we have an opportunity to

kind of like make it more balanced.

501

:

Should we be shifting this

more one way or the other?

502

:

Like how, how could we.

503

:

Start thinking about this.

504

:

I think there the trap you're

falling into is that you're

505

:

assuming that there's a trade off.

506

:

And I think what I'm arguing is

that there isn't a trade off.

507

:

I think if you take the example

of energy as an example.

508

:

The reason that we were never able to

do this in the past is our options for

509

:

energy were either you burned wood.

510

:

Which we did for most of human history.

511

:

And then we discovered fossil fuels.

512

:

So you burn fossil fuels that

were your only, those were

513

:

your only options for energy.

514

:

We're now in the position where we

have solar, we have wind, we have other

515

:

alternative technologies and the issue

we were having say a decade ago, even.

516

:

is that these energy sources

were too expensive, right?

517

:

So you would have actually came to the

conclusion that there was this trade off

518

:

because if someone's living in energy

poverty, um, they're having to decide do

519

:

they go for the expensive solar and wind

to help the environment or do they just

520

:

increase their energy consumption which

would be like higher standards of living.

521

:

We're now in the position where solar

and wind are the cheapest energy sources.

522

:

So actually, they are, they are, in some

sense, that's no longer incompatible.

523

:

You can relieve energy poverty

using really, really cheap,

524

:

low carbon energy sources.

525

:

Now the question there is, is

different levels of income.

526

:

I think we're, for high income

countries, there's really no reason

527

:

at all why we can't just quickly

deploy these technologies and

528

:

massively reduce our footprint.

529

:

Um, I think the key for lower

income countries is because they

530

:

are more finance constrained

is how can rich countries help?

531

:

And there's two ways.

532

:

One, they can directly finance

those energy technologies.

533

:

And the other one is, um, by innovating

and driving these technologies

534

:

themselves, you push down the

cost for lower income countries.

535

:

So they don't face this trade off

between do they have low carbon

536

:

emissions or do they alleviate poverty?

537

:

Because solar, wind or other

technologies will just be the cheapest.

538

:

Yeah, this, this, this, this was a

good point you made to in the book,

539

:

basically like these decoupling curves,

you can kind of shortcut for these,

540

:

uh, lower income countries where, for,

by, for, for higher income countries or

541

:

yeah, for countries with higher income,

they can go and kind of subsidize

542

:

or like make it easier to deploy

these, um, technologies, uh, quickly.

543

:

So, yeah, thanks.

544

:

Uh, thanks.

545

:

Thanks for this perspective.

546

:

What, one of the, one of the other

parts in the book that you, that.

547

:

That you, you get at with

sustainability is that we have like

548

:

all of these different problems.

549

:

You have, I think, seven in the book,

um, seven, like different issues

550

:

that, uh, that you tackle and that

there's a lot of overlap between them.

551

:

So can you talk about how, like,

what, like, uh, helping, helping, for

552

:

example, air pollution can affect these

other, um, problem topics as well?

553

:

Sure.

554

:

Yeah.

555

:

I think this is, um, Also a bit of a

trap we fall into where we just see

556

:

environmental problem after environmental

problem after environmental problem.

557

:

And I think we, we often are worried

that if I make this choice for

558

:

climate change, am I going to make

another problem much, much worse?

559

:

So we can end up feeling pretty

paralyzed about our solutions

560

:

because we automatically assume that

there's just like no, no solutions

561

:

that cover all of our bases.

562

:

And there are, I think there are

just like a core, like five to 10

563

:

different solutions that really

cut across most of these problems.

564

:

If you take the example of.

565

:

of air pollution.

566

:

The problem with air pollution

is burning stuff, right?

567

:

You burn stuff and you produce

particulates, which is air pollution,

568

:

which is bad for our health.

569

:

If you produce energy without burning

stuff, then you don't have air pollution.

570

:

So basically, the core to that is that

if you stop burning wood, which for some

571

:

people in the world is still their core

energy source, is like wood and biomass,

572

:

but for most people it's fossil fuels.

573

:

So if you stop burning woods and you stop

burning fossil fuels, which is, we can

574

:

do, we have alternative technologies,

then you address air pollution, right?

575

:

You massively reduce air pollution, but

you also have the same solution to address

576

:

climate change, like stop burning fossil

fuels and you tackle climate change and

577

:

air pollution at exactly the same time.

578

:

If you take another example, eating meat.

579

:

So a big environmental impact is

global meat production, and in

580

:

particular beef tends to be the

worst in terms of its impact.

581

:

Um, you reduce your beef or meat

consumption, you help climate change, to

582

:

some extent you also help air pollution,

you help deforestation because that's the

583

:

leading driver of deforestation, you help

global food systems and food production,

584

:

you also address biodiversity loss.

585

:

So there you're hitting.

586

:

Well, one solution, you're hitting five

different problems at the same time.

587

:

So I think these are the just core set

of solutions that really cross cut many

588

:

of our, uh, environmental problems.

589

:

Yeah, this is, this is

a really good point.

590

:

Plus it comes back to what you

were saying earlier that you don't

591

:

have to, like, we can do a lot

without having a perfect solution.

592

:

So for example, with this, uh, with

the, the point about eating, uh, eating

593

:

less meat, uh, I think this is a really

good point is just like, okay, if

594

:

you eat less meat, uh, we can make.

595

:

quite a big dent in our impact, even

if you don't have to make the, you

596

:

know, the, the full, you go the full

way of like, just stopping eating meat.

597

:

And like, I know you've, you mentioned,

um, like some, some estimates in

598

:

the book that, that get at this,

whereas like you have crazy amount

599

:

of reduction by just having just a

little bit less meat per week, but you

600

:

still end up, you can still eat meat.

601

:

Like there's no issue with this.

602

:

You don't have to like, you know,

Shift your whole personal identity,

603

:

which can be very difficult.

604

:

Um, and you still get

this, uh, massive impact.

605

:

So I think this is also a good point

is like, just, we can tackle all

606

:

of these problems at the same time.

607

:

And we also don't have to, we

don't have to settle for, you

608

:

know, perfect solutions first.

609

:

Yeah, I think it's, like, it's often

about, um, people starting down a

610

:

particular journey or route, like, I

think, like, I, I've never advocated that

611

:

everyone should go vegan, because I think

for most people, actually, that's, that's

612

:

a massive step, and it's like, actually a

barrier, because they think, oh, there's

613

:

no way I could be vegan, but for many

people in the world, they could go vegan.

614

:

have a meatless one or two days a week.

615

:

Um, and that would probably

quite achievable for them.

616

:

Um, and then actually from there,

I think then it starts to build.

617

:

So like you go meatless for a

day, you realize, Oh, there's

618

:

actually like really good vegan

products, um, that I really enjoy.

619

:

So you make it two days.

620

:

And I think from there, there's

a gradual process, but I think.

621

:

Like assuming that everyone's

going to jump in and go straight to

622

:

vegan is just really unrealistic.

623

:

Yeah.

624

:

And I don't think that should stop people

from taking action because sometimes,

625

:

I mean, we feel like the action we need

to take is huge, especially when we

626

:

look at the magnitude of the problem.

627

:

And it's like, well, there

really is nothing I can do.

628

:

So let me do nothing then.

629

:

Um, but yeah, based off of what you said,

it's really important that we do the

630

:

much we can, um, have a quote that says

do what you can until you can do more.

631

:

And when you can do more, then do more.

632

:

And keep doing more until you can do more.

633

:

Uh, so that's, that's pretty good.

634

:

I think there's also just really strong,

like, peer effects of, like, doing the

635

:

action and then to some extent, like,

talking a little bit about the action.

636

:

Like, the, the, the example I use

there is, um, like, electric vehicles.

637

:

I think a decade ago, everyone was

really sceptical to buy an electric car

638

:

because they didn't know anyone with an

electric car, they had no idea, like,

639

:

is it hard to charge, like, do you

just, like, break down on the motorway?

640

:

I mean, there's loads of these barriers.

641

:

That they actually need to, need

to see other people buying them,

642

:

having positive experiences, um,

talking to the friend that has got

643

:

one and actually really enjoys it.

644

:

I think we're now in the position

where a lot of those barriers have

645

:

been lowered, um, because people

have actually just adopted it and,

646

:

and, um, are chatting about it.

647

:

Yeah, and, and just, just to add to that,

I think the other thing is if you find

648

:

a cause or something you can do, even

though you're, you're an early adopter,

649

:

it's okay to be an early adopter, because

then it takes a lot of early adopters for.

650

:

Everyone to now adopt the solution.

651

:

So it's, it's perfectly

okay to be an early adopter.

652

:

I think it's like really

crucial to be an early adopter.

653

:

Like earlier, we were talking about this,

this, uh, like trade off discussion.

654

:

I think the question often, especially

for, I mean, I don't know what the

655

:

demographic of the audience is,

but I think especially for rich

656

:

countries, there's this question of.

657

:

I'm sitting in the UK right now

and there's always the argument

658

:

of the UK only emits 1 percent

of the world's carbon emissions.

659

:

Like what we do doesn't matter,

but I think there, there's

660

:

like another impact there.

661

:

One is just the UK needs to get its

emissions as close to zero as possible,

662

:

especially as a rich country with

a large historical responsibility.

663

:

But the other role that rich countries

can do is to be the early adopters, right?

664

:

When these technologies start out,

they tend to be pretty expensive and

665

:

we want to get those costs low for.

666

:

Middle and low income

countries to implement them.

667

:

So the role of rich countries or rich

consumers is to be the early adopters

668

:

and really force that curve downwards.

669

:

Yeah, that's profound.

670

:

And I guess like here, part of, part

of the issue sometimes, or maybe not an

671

:

issue, but something to, to think about

is that to get say, um, richer countries

672

:

to, to help, um, these lower income

countries, we have to have a sense.

673

:

At least in my mind, that's where

like, you know, a global species

674

:

is like, it's not just us in our

country that we need to care about.

675

:

It's like, there's other people

that it's really helped to,

676

:

to, to help them as well.

677

:

Yeah, totally.

678

:

I mean, yeah, one is just working

on global problems and caring

679

:

about other people in the world.

680

:

Um, but I think that gets like even more.

681

:

difficult when you're talking

about other species, right?

682

:

Like if we can't even get people to

care about someone like a human on the

683

:

other side of the world, how do we get

them to care about biodiversity loss?

684

:

Um, so it's like, it's, it's,

it's just very difficult.

685

:

I think one thing I'd say on

that is that, uh, climate change

686

:

is often framed as this like.

687

:

Collective action problem where

like it's never in like exactly in

688

:

one single country's interest to

act on it because it also depends

689

:

on what other countries are doing.

690

:

I think I think to some extent that's

true, but I think we also need just need

691

:

to really highlight like some of the like.

692

:

Selfish, and I say selfish

in inverted commas, reasons

693

:

for, for countries to do that.

694

:

And I think that comes back to, there's

loads of local benefits to implementing

695

:

the solutions that address climate change.

696

:

So if you take electric cars, for

example, or like electric vehicles,

697

:

or investing in public transport.

698

:

Like it's not just about climate.

699

:

One, you reduce local air pollution.

700

:

If you invest in public transport,

you have like Productivity

701

:

gains, you lower congestion.

702

:

If you implement renewables, you get lower

energy costs and higher energy security.

703

:

So there's lots of like

localized benefits.

704

:

I think we also should really

emphasize because there is this

705

:

like collective action problem on

climate, um, on climate change.

706

:

That's profound.

707

:

So Liki has got a question here.

708

:

She says, um, she'd like to get

your perspective on helping a

709

:

grandma understand the difference

between data and rumors or what

710

:

her friends could have told her.

711

:

So, um, uh, yeah, that's that.

712

:

Oh, I mean, I mean, I, I still

have that problem with my

713

:

grandma, so I haven't solved it.

714

:

Um, I think, I think to some

extent it's, it's very variable

715

:

depending on like how people get

news and where they get news from.

716

:

I think there are some demographics

where like the truth is just

717

:

what their friend told them or

like what the latest rumor is.

718

:

Um, I think, but I think

there are others where, um.

719

:

Most of our, um, news

consumption is online.

720

:

We have specific sources that we go to,

um, I think they are, even when you're

721

:

talking about online media, there's

often a slant one way or the other.

722

:

So like, I'm also still skeptical of

going to a media article and seeing

723

:

data as we discussed earlier, seeing

data there and taking that as the truth.

724

:

Um, I think you can also frame

like some of the data on some

725

:

media articles is also a rumor.

726

:

Um, so I think, I think it comes back

a little bit back to what we discussed

727

:

earlier of, how to approach statistics,

like what you should have in your mind

728

:

when you're encountering statistics.

729

:

Um, yeah, and I, like I'm, in terms of

like rumor of what our friends could

730

:

have told her, I think in general

I'm just like, try to stay away from

731

:

building a worldview on anecdotes.

732

:

Like I think there are, I think stories

are important and like they, they give

733

:

you like interesting perspectives, but

I, I try not to extrapolate and assume

734

:

that You know, what one person has

told me is true at a broader level.

735

:

Yeah.

736

:

I mean, the word, the world's big.

737

:

So like to really build a world view, it's

very difficult on a personal anecdote.

738

:

I wanted to ask you,

Hannah, for like the last.

739

:

So a few minutes we have here,

um, about your newsletter.

740

:

So you started it about a year ago.

741

:

Uh, can you talk a little bit

about the motivations behind this?

742

:

Like why you're having kind of just

like, uh, this like more personal

743

:

project outside of your work?

744

:

Yeah, no, I, uh, a year and a bit

ago I started this newsletter.

745

:

I mean, it's, you said earlier

that it's a weekly, like I've

746

:

tried, really try to like keep it

as close to weekly as possible.

747

:

Um, but yeah, like I do this kind of like

in my free time where I explore like.

748

:

Sustainability issues like

through the lens of numbers.

749

:

So like a lot of this stems from, I,

again, like I have a question on this and

750

:

I want to look at the data to find out and

rather than me just doing that in private,

751

:

maybe I should just put it online so

that others can learn from what I found.

752

:

So yeah, I tried to tackle like really

core questions that people have, like

753

:

I think the latest ones were like,

are we going to run out of minerals?

754

:

Um, for moving to renewable energy.

755

:

And the answer to that is no, but

like looking at the data to find out,

756

:

like, what do the numbers look like?

757

:

What does that tell us?

758

:

Rather than just jumping to a

conclusion one way or the other.

759

:

Um, I, one of the reasons that I have

this kind of personal project and not

760

:

all of it goes on our own data is that

I want it to be like a little bit more.

761

:

Exploratory, where I'm exploring

a, a question kind of on my blog,

762

:

like people's comments and inputs.

763

:

I think like one of the great things

about our own data, but also one of

764

:

the stresses of it is that people

go to our own data and take like,

765

:

this is like the final say on this.

766

:

Topic.

767

:

And this is like the ground truth,

which like puts a lot of pressure on.

768

:

Cause we, we take that very seriously

and want to get everything correct.

769

:

So the blog is like a little bit more

exploratory for me where I'm under like

770

:

a little bit less pressure of like,

this has to be like the absolute stellar

771

:

standard and I can, I can discuss

issues on a, on a different level, but

772

:

it all comes back down to the numbers.

773

:

Like, Oh, I, I, I ground all of this.

774

:

And what does the data tell us on

these really common questions that

775

:

people have about sustainability?

776

:

Yeah.

777

:

And I, I remember like one.

778

:

One of your newsletters in particular,

once I think it was a few posts

779

:

you had, which were about electric

vehicles in, um, in colder countries.

780

:

So like I'm, I'm from Canada.

781

:

Uh, it is very cold even right now.

782

:

And, uh, yeah, like one of the main

questions, whenever I talk to anybody

783

:

about electric vehicles here, it's like,

it is not going to work in the winter.

784

:

And I I've had like horror

stories about people losing

785

:

like half their batteries, like.

786

:

Capacity, uh, in the winter, like having

the car not start or like all of these

787

:

now granted, it does get cold here.

788

:

Like it gets very cold.

789

:

So like, I, I, I can believe that

there are definitely issues versus

790

:

like in warmer, um, in warmer places.

791

:

But you had this series of posts where

you were looking at the performance of,

792

:

uh, electric vehicles in colder countries,

Nordic countries, if I remember correctly.

793

:

And even there, I was

quite impressed by how.

794

:

Like how little the, the, the degradation

of in performance was like, okay, it's

795

:

not quite as cold as here some days,

but like it was still pretty cold, the,

796

:

in the, the, the regions you looked at.

797

:

So I thought this was quite, yeah.

798

:

And I think part of the motivation

for, for doing the blog is that I

799

:

think to people, there are loads of

these like really common questions

800

:

and like going into that, I had no

idea how much the range dropped in a.

801

:

Electric car battery in the cold, but

I, I wanted to know the answer and I,

802

:

I tried to find the answer in the data.

803

:

I think what I've also seen recently is

I think there's been like a significant

804

:

uptick in the media and, and like

disinformation on, on like renewables

805

:

on electric cars on the latest one is

like heat pumps where like a lot of

806

:

these claims are trotted out and Loads

of people believe them, but actually

807

:

that's just not what the data says.

808

:

So I tried to like build a base

where if people want like fact based,

809

:

um, answers to these questions,

they can come, come and find it.

810

:

Now I was just going to say like another

reason to like also bring in the context

811

:

bit that we discussed earlier is that

like petrol cars also suffer in the cold.

812

:

Isn't they, their, um,

performance also drops.

813

:

So it's like, it's, uh, again,

the incorrect framing of.

814

:

Um, assuming that, okay, electric

car battery is suffering,

815

:

but a petrol car is fine.

816

:

And that's, that's not true.

817

:

Yeah.

818

:

Uh, as someone who has recently

had car troubles, I can attest

819

:

to this, it's not been great.

820

:

Uh, but, but yeah, like, uh, what, what

I also really like, uh, about your,

821

:

your, your blog is just, you have.

822

:

Well, I mean, again, you're presenting

the, this data, these numbers, but

823

:

it's not just like you saying like,

there's this statistic or whatever.

824

:

I mean, like you're, you're, you're

reading a bunch of papers and different

825

:

people that have already worked on this.

826

:

It's like, it's not you.

827

:

I think you probably mentioned

this in your newsletter.

828

:

It's like, it's not you

doing the research here.

829

:

It's more of the synthesis, like taking

all of these different, uh, like estimates

830

:

and, uh, different just case studies and

kind of putting them together to try to

831

:

answer maybe a slightly more, uh, Like

regular question that someone might have,

832

:

like, how is the, how is my Evie going?

833

:

My electric vehicle going to work?

834

:

I should say that like, I

don't do any of the hard work.

835

:

There's like researchers that like

properly do the hard work of like

836

:

doing the research and the data.

837

:

Actually, it's also true

for on our own data.

838

:

Like we rely really heavily on,

on amazing people doing the work

839

:

of providing the data, doing the

research where we see ourselves.

840

:

Um, and where I see my blog is like,

we almost see ourselves as like

841

:

translators, like this bridge between

the research and then the general

842

:

public or policy makers or journalists.

843

:

I think we have a, an issue in science

where there's loads of people doing

844

:

amazing work, but like the results never

get into the world where they can be used.

845

:

So a core part of our work is to

be this like bridge in this gap in

846

:

the middle where we, we bring the,

the important results to people

847

:

who can then put that into action.

848

:

Yeah.

849

:

And I suppose probably over like the last,

uh, like decade or so you've been doing

850

:

this, you've probably gotten a better

sense of what, what makes say a good

851

:

study, what makes a good research paper.

852

:

Cause I mean, okay, there's

a lot of science out there.

853

:

There's a lot of stuff that people

do, and you kind of have to like sort

854

:

through it and say like, okay, even.

855

:

Again, this idea of just because there's

a number that's out there doesn't mean

856

:

it's authoritative, even within science

itself, like, unfortunately, but it's

857

:

the case, because we're all human.

858

:

Um, so, so like, even sorting

through this is also, also an

859

:

important skill that I guess you've.

860

:

Yeah, I think being like really

highly engaged with the public has

861

:

been really useful in one shaping

like what are the core questions

862

:

that people have, like we can, we can

understand what do people misunderstand?

863

:

What are they curious about?

864

:

Um, and even once we've published an

article, like, Looking at the, the

865

:

comments and feedback, like it's not,

it's not always like that pleasurable,

866

:

but like understanding what are

the main pushbacks against this?

867

:

What are people like misunderstanding?

868

:

Have we not been clear enough in some way?

869

:

So I think like, yeah, doing this

really close public engagement

870

:

is really important for us.

871

:

Okay.

872

:

So I see where we're running,

uh, almost out of time.

873

:

So I want to ask you like one last

question, which is amongst your friends.

874

:

Are you the person they run to when they

have any like data science questions?

875

:

Like, are they like, Hannah,

I have this question.

876

:

I don't know how to answer it.

877

:

Can you please help me out?

878

:

Yeah, I can still, I can, I can, uh,

associate with often, like someone

879

:

will say a fact or what they think is

a fact or a number and then they'll

880

:

kind of give me a side eye of like,

is she going to support this or

881

:

is she like raising her eyebrows?

882

:

So yeah, I think they, they wait for my

level of skepticism about whether that.

883

:

that fact is actually correct.

884

:

Um, yeah.

885

:

Right.

886

:

Awesome.

887

:

So, so yeah, so thank you.

888

:

Thank you very much, Hannah,

for taking the time, um, for

889

:

coming on Carbon Sessions today.

890

:

Again, uh, your, your book's

coming out in January.

891

:

It's on January what?

892

:

Uh, the US is January 9th

and the UK is the 11th.

893

:

All right, awesome.

894

:

So yes, check out, check out her new book.

895

:

It's really good.

896

:

Uh, and also check out, check out

Hannah's newsletter, which, uh, which,

897

:

uh, comes out again, weekly ish.

898

:

It's, uh, it gives you a nice, uh, data

driven way of, uh, seeing the world and

899

:

just answering a bunch of questions.

900

:

So.

901

:

Again, thanks Hannah for being

on the podcast and, uh, do you

902

:

have any, any, uh, thing you want

to say as, uh, as closing out?

903

:

No, just thanks very much for having

me and keep working on the solutions.

904

:

Thank you so much.

905

:

All right.

906

:

Awesome.

907

:

You've been listening to carbon

sessions, a podcast with carbon

908

:

conversations for every day with

everyone from everywhere in the world.

909

:

We'd love you to join the Carbon

Sessions so you too can share your

910

:

perspectives from wherever you are.

911

:

This is a great way for our community

to learn from your ideas and

912

:

experiences, connect, and take action.

913

:

If you want to add your voice to the

conversation, go to thecarbonalmanac.

914

:

org slash podcast.

915

:

And sign up to be part

of a future episode.

916

:

This podcast is also part of

the Carbon Almanac Network.

917

:

For more information, to sign up for

the emails, to join the movement,

918

:

and to order your copy of the Carbon

Almanac, go to thecarbonalmanac.

919

:

org.

920

:

Be sure to subscribe and join

us here again, as together

921

:

we can change the world.

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Carbon Almanac

When it comes to the climate, we don’t need more marketing or anxiety. We need established facts and a plan for collective action.

The climate is the fundamental issue of our time, and now we face a critical decision. Whether to be optimistic or fatalistic, whether to profess skepticism or to take action. Yet it seems we can barely agree on what is really going on, let alone what needs to be done. We urgently need facts, not opinions. Insights, not statistics. And a shift from thinking about climate change as a “me” problem to a “we” problem.

The Carbon Almanac is a once-in-a-lifetime collaboration between hundreds of writers, researchers, thinkers, and illustrators that focuses on what we know, what has come before, and what might happen next. Drawing on over 1,000 data points, the book uses cartoons, quotes, illustrations, tables, histories, and articles to lay out carbon’s impact on our food system, ocean acidity, agriculture, energy, biodiversity, extreme weather events, the economy, human health, and best and worst-case scenarios. Visually engaging and built to share, The Carbon Almanac is the definitive source for facts and the basis for a global movement to fight climate change.

This isn’t what the oil companies, marketers, activists, or politicians want you to believe. This is what’s really happening, right now. Our planet is in trouble, and no one concerned group, corporation, country, or hemisphere can address this on its own. Self-interest only increases the problem. We are in this together. And it’s not too late to for concerted, collective action for change.