0:03

Hello. Welcome to the climate question

0:05

from the BBC World Service.

0:07

With me, Luke Jones. I'm Miss Sofie store.

0:14

Everywhere in the world, we are talking about

0:16

more floods and we talk about more droughts.

0:19

And so those are caused by

0:21

a combination of changes in temperature and

0:23

changes in

0:23

precipitation patterns. It's hard

0:26

to escape the effect of climate

0:28

change. What it's doing to our weather systems

0:30

touches so many parts of our lives,

0:32

but one of the most vital is

0:34

farming.

0:35

You might have heard about the

0:38

extreme drought in the Horn of

0:40

Africa where we have had four rainy

0:43

seasons that were

0:44

dry. The number of people now being

0:46

affected by the worst drought in forty years

0:48

has more than doubled, but less than half

0:50

the money needed to help them has been

0:52

raised. Climate change and conflict

0:55

have contributed to severe food

0:57

shortages across the horn of

0:59

Africa. So farmers expect

1:01

rain to come. It doesn't come. And

1:03

the impact this is having is

1:05

huge. For the world's food security,

1:07

it's making a bad situation even

1:10

worse. Twenty million children

1:12

at severe risk of

1:15

hunger, food insecurity, lack

1:17

of access to water for drinking, We

1:20

have two million children, you know, that

1:22

are starving. And

1:24

now, this acute level means they

1:27

will die if they don't get immediate

1:29

port or they are dying or half died.

1:32

Farming is under severe pressure from climate

1:34

change, with the world's poorest countries

1:36

worst affected. Yeah. According

1:38

to the World Bank, eighty percent of those

1:41

most at risk of crop failures and hunger

1:43

from climate change are in sub Saharan

1:45

Africa, South and Southeast Asia,

1:47

where farmers tend to be poorer and more vulnerable.

1:50

So humans are struggling to overcome the challenge.

1:52

Could machine learning help?

1:55

Our question this week could artificial

1:58

intelligence help farmers adapt

2:00

to the effects of climate change?

2:05

Doctor Claudia Rengler is from the International

2:08

Food Policy Research Institute. It's a

2:10

think tank which works on food security in

2:12

developing countries and innovation in

2:14

agriculture.

2:15

Basically, what we have seen over

2:18

the last century or so is

2:21

quite substantial increases in average

2:23

global surface air temperature, about

2:25

one point two five degrees Celsius, you

2:27

know, between eighteen fifty and nineteen

2:29

hundred and today, And so

2:31

while it doesn't sound like a lot, these

2:33

hotter temperatures basically affect

2:36

crop yields through plants,

2:38

like the plants that we would like to eat

2:41

through heat stress. And because

2:43

it's hotter, it also means the plants

2:46

need more water for survival.

2:48

And while there is a lot of focus on

2:51

plants and crops, animals, livestock

2:53

is, of course, also affected directly

2:55

by heat stress. This heat stirs

2:57

reduces milk productivity. It

3:00

makes the animals more susceptible

3:03

to diseases, etcetera. And of

3:05

course, laborers, people

3:07

working in the field also experience

3:10

heat

3:10

stress, and as well as reducing

3:13

crop yields.

3:14

Is climate change also affecting the

3:16

quality of crops? It's

3:18

both. It's obviously the quantity,

3:20

as usual, is more easily measurable.

3:23

So we have seen declines of

3:25

one percent to two percent per decades of crop

3:27

yields. We expect about an

3:29

eleven percent decline in

3:31

crop yields out to twenty fifty.

3:34

And again, the numbers might sound small,

3:36

but for poorer food consumers that

3:38

spend forty percent to sixty percent of

3:41

their income on food. When they

3:43

see prices that are twenty percent higher

3:45

or thirty percent higher than they were before,

3:47

it's real food and security. So

3:50

this is the quantity component, but the quality

3:52

is a little bit more challenging to see.

3:55

But we already know that some

3:57

crops under this heat stress,

3:59

they produce lower quality

4:02

micronutrients. So for example,

4:04

sink or iron that are also

4:07

produced by these plants. So

4:09

with this higher temperature stress

4:11

and higher water stress, we

4:13

see that the micronutrient quality

4:16

of crops is also declining.

4:20

So climate change means farmers are

4:22

having less successful harvests,

4:24

which are sometimes less nutritious

4:26

too. So that's low yields, less nutritious

4:29

yields, and food price are

4:31

going up and up as

4:32

well, which is devastating for people already struggling

4:34

with hunger. Yeah. The World Bank

4:36

says that in twenty twenty one, rising

4:38

food prices driven in large part

4:40

by climate change pushed thirty

4:43

million people in lower income countries

4:45

into food insecurity.

4:47

And topping off, the world's population is

4:49

growing rapidly as well. So we need to be

4:51

producing more

4:52

food, not less.

4:53

It's a huge challenge So

4:55

can artificial intelligence help?

4:58

Lots of people seem to think so. Spending

5:00

on AI in agriculture is predicted

5:02

to go to four billion dollars a year by

5:04

twenty twenty

5:05

six. That's four times what it was in twenty

5:07

twenty.

5:08

Wow. When I think of artificial intelligence,

5:10

I think of robots in a kind of human

5:13

form like that film x machina,

5:15

but I'm sure there's lots more to it than

5:17

that. I think you're probably right. Artificial intelligence

5:20

is essentially computer system

5:22

that can simulate human intelligence and

5:25

therefore help you with tasks and

5:27

things like decision making. Okay.

5:29

Let's say from somewhere where this is in action.

5:36

Hello. I'm Suria Nazzi.

5:38

I'm a journalist and based in Central

5:41

India. Where are you, Sheria?

5:43

Right now, I am near a village. It's

5:46

in the Central Indian state of Mahdi Pradesh.

5:48

The Papal is its capital. Right

5:51

now I'm in the field. So actually,

5:53

I can see only these farms

5:55

here.

5:56

And what kind of crops do the farms

5:58

grow? See,

6:00

wheat is the main crop, which they have been

6:02

growing soybean and sugarcane.

6:05

Okay. How's the weather today? Is

6:07

there a beautiful all sunny field in

6:09

front of you. Yeah. Yeah. It's it's

6:11

a really sunny, very hot, very hot.

6:14

Surely I met with some of the local farmers who

6:17

have adopted

6:19

a new technology. Actually,

6:21

these farmers, they're facing climate change

6:23

issues.

6:25

In the last few years. And

6:27

the yield of these farmers, it was going down.

6:29

And many of them were deciding to

6:32

sell their land

6:34

and move to a bigger place or

6:37

to a bigger cities and

6:39

do some other job. My

6:45

name is Narayan Singh Verma. I'm thirty

6:48

three years old. Climate change

6:50

is a very big issue here. Everything has been

6:52

affected by it, including our crops. The

6:55

changes in weather patterns is a serious

6:57

concern for us. We faced drought

6:59

in recent years. Also, untimely

7:01

and unseasonable rains of course, substantial

7:04

damage to the crops. Problems

7:06

with insects and moths increased, and

7:08

crop production was declining. Farming

7:10

for us is like the sole is for the body.

7:12

We can't imagine doing anything else.

7:16

We started getting information and learned

7:18

that all this harm to the crops was due to climate

7:20

change. So we made some arrangements.

7:22

We received necessary information and training

7:25

at different places.

7:26

The farmers joined a project paid for

7:28

by the company that buys their crops. It

7:31

gives them training, better

7:32

seeds, and access to a smartphone app.

7:35

Now this app uses artificial intelligence

7:37

to provide long range climate

7:39

forecasting, which helps the farmers

7:41

make better decisions and plan around

7:43

extreme weather.

7:45

They're getting alerts almost every day

7:47

about the weather conditions, about

7:51

everything they're getting. And in real time,

7:53

if they have any query, they can post

7:55

the picture from their farms. Anything

7:58

if they have any issues, they can consult

8:01

experts about pesticides So

8:04

they're getting all the information through this app.

8:06

How much has this app and this

8:08

technology helped the farmers that

8:10

you've met? In this particular area,

8:12

they have been using this technology in three hundred

8:14

villages. In most of the cases,

8:17

the yield has doubled. So it has really

8:19

changed their life.

8:24

My name is Ramdael Bermer. My

8:26

father and grandfather were also farmers

8:28

like me. We were farming according to

8:30

old customs, but then we had to try this

8:32

new method. Now we get all

8:34

the information about the weather, winter,

8:36

so, and winter harvest, which sees to plant,

8:38

which medicines to spray. It's benefiting

8:41

us a lot as the alert has just been issued.

8:43

There's likelihood of rainfall soon. So

8:45

we've started harvesting and can take precautions.

8:48

I'm now earning better through farming and it provides

8:51

a good livelihood for my family. We

8:54

tried the things that we were told. But first,

8:56

we thought we've been farming for so long that

8:58

can't be more informed than us. But

9:00

when we tried these things, they were beneficial.

9:03

It increased our yield. There

9:05

was a time when we felt that there was nothing left

9:07

in farming it wasn't profitable. But

9:09

today, the production has increased, and we

9:11

feel that farming is a good business.

9:17

So quite the impact then, doubling crop

9:19

yield, great for harvest, of course,

9:21

and their food supply

9:22

locally. But also one impact on the families

9:25

as well. Yeah. So in these farms,

9:27

it was a combination of new techniques, better

9:30

seeds and this app, which uses artificial

9:32

intelligence.

9:33

Harnessing data on climate, weather,

9:35

and soil, the app sends farmers

9:37

alert on the best time to plant and to

9:39

harvest. So how exactly does

9:42

that AI work? It's powered

9:44

by a company called climate AI.

9:46

We are the world's first

9:48

climate resilience platform.

9:50

Himanshu Gupta is the CEO

9:53

and co founder. He grew up in

9:55

rural India and saw changes to the

9:57

monsoon patterns

9:58

himself. Now he works

10:00

in Silicon Valley. Climate change

10:02

is introducing a lot of volatility in

10:05

our daily weather. And farmers

10:07

still act out of their memory,

10:09

which is the institution memory that they have

10:12

of farming for the last thirty, forty, fifty

10:14

years. Across their generations and their families.

10:17

Now if you are a wheat farmer or a vegetable

10:19

farmer in the north of India and

10:21

you're preparing to So your

10:23

seeds at the onset of

10:25

spring, you're suddenly realizing that your

10:27

window for planting seeds is getting

10:29

shorter and shorter.

10:30

These differences are because of climate change.

10:33

It used to be two or three weeks or four weeks

10:35

after the onset of spring. Now it

10:37

has reduced to week or two And

10:39

then it's also very uncertain. Or what

10:41

our platform does is it keeps

10:44

actionable insights to farmers

10:46

on when to plan, what to

10:48

plan, and where to plant. But

10:50

then in the back end, there's so

10:52

many big data algorithms that

10:54

are crunching terabytes of

10:56

satellite sensor data radar

10:58

station's data, soil moisture

11:00

data, and then using

11:02

that to predict a risk of

11:04

a heat wave you know, predicting soil

11:07

moisture conditions from two weeks out to

11:09

a month out or three months out, and then

11:11

converting all of that into a very

11:13

simple index that farmers

11:15

can understand and use to

11:18

optimize their planting decisions or their harvesting

11:20

decisions on the

11:21

field. So the app the farmers use

11:23

is all fed by big data, and

11:25

the more data there is, the more precise

11:27

the advice that the algorithms can provide.

11:29

Right. And him and she has big

11:32

ambitions for scaling this up.

11:34

Our platform has been deployed across

11:36

forty countries. We have seen that

11:38

more than two million farmers have been impacted

11:41

already. And we think that in

11:43

the next eight years, close to

11:45

hundred and ten million farmers can

11:47

derive benefit out of this technology. But

11:52

do a hundred and ten million farmers around the world

11:55

have the means to access this technology, plenty

11:57

won't have a smartphone for the

11:59

app, let alone the internet they need to power it.

12:01

It's a very good point. And with the investment,

12:03

AMETEK and the skills needed for

12:06

this, is AI really the

12:08

best solution to help farmers in developing

12:10

countries adapt to the effects of climate

12:12

change. Well,

12:13

Himanshu isn't the only one betting on this. Even

12:15

Microsoft isn't on the act. I'm

12:17

Janeil Chandra. I'm the CTO

12:19

for agriculture and food and the managing director

12:22

for research for industry at Microsoft. Ramsey

12:25

is also a Silicon Valley man

12:27

with rural Indian beginnings. My

12:30

grandparent's performers, I spent about

12:32

four months every year in a small

12:34

farm in Pehar, which is one of the

12:36

states in India, one of the poorest states

12:38

at that time. And, yeah, they used

12:40

to grow sugarcane wheat and

12:42

they did spend a lot of time in these villages.

12:45

And did you make yourself useful on the farm? I

12:47

did. I did the volunteer on the farm.

12:49

I made lots of friends. With the kids

12:51

my age, they taught me how to bike. But there

12:54

was no electricity, no toilets, and

12:56

I wasn't really looking forward to spending

12:58

those months

12:58

there, but I did. And I did learn a lot.

13:01

Did that upbringing influence you

13:03

to get into the line of work you're in now?

13:05

It did because I saw so much poverty

13:08

and so much primitive forms of

13:10

agriculture, like when my mom used to

13:12

do the prayers and lay the offerings outside,

13:14

I used to see crowd of people just hanging

13:17

in line, just trying to get something to eat,

13:19

and that has influenced the

13:21

kind of problems that I work

13:23

on. And those problems are the same as we

13:25

heard in Magi Pradesh earlier, rising

13:27

temperatures, erratic rainfall, unpredictable

13:30

weather, they're all threatening farming around

13:32

the world. Particularly in some of the world's

13:34

poorest regions. Ramvish Chandra

13:36

is leading Microsoft's efforts to develop

13:38

AI tools for farmers. But it's

13:40

early days, firstly, a

13:42

lot more data is needed to help

13:44

farmers make more effective decisions.

13:47

We've just scratched the surface For example,

13:50

let's just talk about soils. When you pick up

13:52

soil, the soil has physical,

13:54

chemical, and biological properties.

13:56

Physical is how it feels when you touch

13:58

it. Chemical is things like potassium,

14:01

nitrogen, phosphorus. These are

14:03

the fertilizers that you add to make the soil

14:06

richer. And biological is

14:08

all the microbes, all the bacteria in

14:10

soil. And when people have

14:12

understood physical we are making progress

14:14

in understanding the chemical properties of soil,

14:17

the biological is not well understood. But

14:19

this is where we are using techniques

14:21

such as artificial intelligence to breach

14:23

the gap, to add more understanding. So

14:26

there are lots of data that need to be

14:28

captured for a

14:29

farm. The main drawback is it's still

14:31

not readily accessible to small farmers,

14:33

and they make up ninety percent of the world's

14:35

farms. The technology is mature

14:37

at a point where it can help farmers that are

14:39

medium to large scale farmers.

14:42

For small wooden farmers, we are still

14:44

actively working on it, but we still

14:46

have long way to go to get it adopted

14:48

by the five hundred million

14:51

plus small holder farmers

14:52

worldwide. But I'm very optimistic

14:55

that it will get there. So

14:57

Microsoft has made some of its

14:59

artificial intelligence algorithms for

15:01

farming available open source

15:03

on the

15:03

internet. Meaning developers anywhere

15:06

can access it for free and create their

15:08

own systems. That sounds positive, but

15:10

even so, you'd still need access to a computer

15:13

and the skills needed to code. And then on

15:15

top of that, the farmers would still use smartphone

15:17

and an internet connection to use whatever

15:20

tool had been

15:20

developed. So there's still going to be barrier for

15:22

many people around the world, something Randvay

15:24

admits. When you talk of small

15:26

holder farmer, we are referring to farmer who

15:29

farms less than one hectare, less

15:31

than two point five acres. So affordability

15:33

is number one. The second problem is that of connectivity.

15:36

Most of these farms don't have good

15:38

reliable internet access. Around

15:41

over two billion people in the world don't have internet

15:43

access, and it is not because they are not in

15:46

in trade coverage

15:47

change. It's because the internet is

15:49

not affordable for these farmers. The

15:52

third challenge is lack of data. That

15:54

is we don't get good data

15:56

to drive your AI model. And

15:58

the fourth problem is around tech readiness.

16:01

That is the farmers, the small holder farmers,

16:03

are not as tech savvy. We need

16:05

subsidies for data driven agriculture so

16:07

that farmers can then start adopting

16:09

these technologies. If they do, everyone

16:12

is going to benefit. Be as consumers,

16:14

farmers themselves, and everyone in

16:16

the food value

16:17

chain. If this technology is being

16:19

adopted by the bigger richer

16:22

farms and the pace of that is

16:24

marching forward. Is there not

16:26

a risk that these smaller farmers are gonna

16:29

be quite quickly left behind

16:31

and therefore kind of priced out

16:33

in the markets that they're trying to sell

16:35

in. This is a great point and

16:37

we need to act fast. We want

16:39

every farmer in the world to start

16:41

using data NII, whether they're a big farmer

16:44

or a small farmer. A lot of

16:46

this next generation of farmers are

16:48

not farmers anymore. They don't

16:50

see in agriculture. For example,

16:52

the kids I grew up with in bihar.

16:55

None of them are farming anymore. They'll go to

16:57

the city, they'll pull a picture, they'll work in a restaurant,

16:59

they don't want to do farming. One

17:01

of the things I'm excited about is with

17:04

the work around data and AI

17:06

and data driven agriculture. We

17:08

can help make agriculture cool again.

17:15

Getting data in artificial intelligence involved

17:17

might make farming more cool to Anves'

17:19

point But if we're concerned about climate

17:21

change, there is another problem. Go on

17:24

Luke. These AI systems and

17:26

smartphone apps come with a huge

17:29

carbon cost If

17:31

you look at data storage around the world, it

17:33

accounts for two percent of

17:35

global greenhouse gas

17:36

emissions. That might not sound like much.

17:38

That's about the same as the emissions from aviation.

17:41

Whoa. That's really surprising. People

17:44

talk a lot about the guilt of flying,

17:46

but I've never had anyone mention guilt

17:48

about how much data we're storing.

17:50

I know. So could this solution to help farmers

17:53

adapt to climate

17:53

change? Actually make the root problem

17:55

much worse.

17:56

While Ramsey disagrees. Agriculture,

17:58

as you know, is one of the biggest emitters of

18:01

greenhouse gases. And with

18:03

data driven acrylic, farmer can use the

18:05

right practices to reduce the amount

18:07

of emissions. For example, if they use

18:09

precision fertilization, they will only

18:11

put chemicals, for example, nitrogen

18:13

where it is needed. Right now, farmers

18:15

would just use nitrogen and put it uniformly in

18:18

the soil. Putting in more fertilizer leads

18:20

to more nitrous oxide emission which is one

18:22

of the most potent greenhouse gases, not

18:24

just nitrogen, it's also C02, it's also

18:26

methane. This is the tool they need

18:29

to adapt to climate change to meet the right decisions.

18:32

Well, round there would say that,

18:34

Microsoft have invested huge amounts of

18:37

money in this. But on that, he's got a point.

18:39

Agriculture accounts for nearly a fifth of

18:41

global C02 emissions, and it needs to

18:43

become more efficient. So you'd need

18:45

to balance the carbon cost of AI against

18:47

the carbon savings that it could help farms

18:50

make. Right. But when it comes to helping

18:52

the average farmer with new technology

18:54

and infrastructure, In countries that

18:56

are worst hit by climate change,

18:59

Claudia Rengler from the International Food

19:01

Policy Research

19:02

Institute, says there are more pressing

19:04

priorities, in particular, water.

19:07

Let's again use the case of the Horn

19:10

of Africa. So there's

19:12

not enough food in the region.

19:14

There's also not enough water

19:16

developed in the region. So

19:18

many of these countries actually have substantial

19:21

groundwater resources. But there

19:23

is no investment to develop these water

19:25

resources. And every time there's a

19:27

drought, the livestock dies. Life

19:29

of dies because of a lack of water

19:31

access point. So solutions have already

19:33

been thought through in terms

19:35

of having more sustainable water

19:38

excess point in terms of

19:40

irrigated, fodder, irrigated pasture.

19:43

Of course, it has to be done carefully to be

19:45

sustainable, but it can be done. But,

19:47

you know, there's just no investment in

19:50

these kind of interventions developing

19:52

drought resistant, drought tolerant

19:54

crops, heat stress,

19:57

like water stress type crops.

20:00

So these varieties can

20:03

be developed. You actually need

20:05

investments to develop these varieties.

20:07

They don't develop, you know, out of thin air.

20:10

And again, investment in agricultural

20:12

research has unfortunately stagnated

20:14

for

20:15

decades. So

20:15

what does clearly make of AI's potential

20:17

to help farmers adapt to climate change?

20:20

It's certainly never useless because anyone

20:22

who can produce more food given

20:25

that we have this eleven percent

20:28

yield decline That's helpful.

20:30

With the question, what we want, of course,

20:32

is equitable access to

20:35

modern technologies and including

20:38

artificial intelligence. I think every

20:40

farmer in the world is interested

20:43

to learn about new technologies, technologies

20:45

that they can afford, technologies that

20:47

they can access But what we

20:50

see is that lot of the technologies

20:53

and practices that are out there end

20:55

up with larger farmers you

20:57

know, farmers that own large amount of land

21:00

or farmers who have already are well

21:02

connected to markets. But at

21:04

some point, we have to find this low cost

21:07

alternatives

21:08

or some means to reach poor farmers.

21:10

And think that's where we still see

21:12

some challenges. So

21:16

billions of dollars are being spent on

21:18

artificial intelligence tools, which

21:20

will largely at least for now

21:23

help

21:23

bigger, richer farms the most. But

21:25

as we've heard, simple smartphone apps driven

21:27

by AI are helping small holder farmers

21:30

in areas like magic potash in India

21:32

adapt to some of this changing

21:33

weather, but it's going to take time for this to

21:35

reach the majority of farmers. Yeah.

21:38

It's clearly not a silver bullet

21:40

for the Av rich pharma in lower income

21:42

countries. And for the region's

21:44

most vulnerable to climate change, food

21:46

shortages, and hunger, a whole

21:48

lot more investment in basic infrastructures

21:51

needed to help farms be more resilient.

21:56

Let

21:56

us know what you think of this Maybe it's something you've

21:58

experienced, working, where you are,

22:00

or not working. And anything else you think

22:02

we should be looking at, please get in touch.

22:04

You can email us at the climate question

22:07

at BBC dot com. Right.

22:16

Before we go, let's have a look at some climate

22:18

news from this week. And there's a big

22:21

story that's really caught people's attention.

22:23

And that's US president Joe Biden's

22:26

approval of new oil drilling

22:28

in Alaska. It's called the Willow

22:30

Project Luke, you've been looking

22:33

at this. So what exactly has

22:35

Biden given the green light

22:36

to? This is a huge project,

22:38

so eight billion dollars worth the Willow

22:41

Project. And if you can picture Alaska,

22:43

so it's in the very, very northwest of

22:45

the United States, and this is on the remote

22:48

north slope of the country. So the northern edge,

22:50

which leans onto the Arctic Sea. And this

22:52

is gonna be the largest oil development in

22:54

the region for decades. There's

22:57

six hundred million barrels of oil down

22:59

there. They're gonna try and get out a hundred and eighty

23:01

thousand barrels a day. And if you think

23:03

about the impact of the climate, this could have the US

23:05

bureau of land management estimates that the project

23:08

would produce two hundred and seventy

23:10

eight million metric tons of CO2

23:12

over the thirty years that they will be getting oil

23:14

out of it that's the equivalent

23:16

of adding two million more

23:19

cars to the roads in the US.

23:21

That's an enormous impact.

23:23

And it kind of

23:25

seems to go against everything Biden

23:28

said before. I mean, he he's been

23:30

billed as the United States first

23:32

climate president. Yeah.

23:33

And actually in the announcement for this decision,

23:36

they said that this is him continuing to

23:38

deliver one of the most aggressive climate agendas

23:41

in American history, which is a slightly

23:43

strange spin on it, especially as you say when you

23:45

think back to what he said as a candidate in twenty

23:47

twenty. And we know the International Energy Agency

23:49

has said that all he developed countries have to

23:51

stop developing more oil and

23:53

gas if they want to reach net zero by twenty

23:56

fifty. He has imposed some limits on it, so it's

23:58

not likely just giving the complete green light to it.

24:00

They announced that of this twenty

24:02

three million acre reserve, there

24:04

were gonna be quite strict limits on sixteen

24:06

million acres of it. And only

24:09

three sites of the five that this

24:11

oil company wanted to do are actually

24:13

being granted. However, with

24:15

just these three sites, they can still access

24:17

ninety percent of the ore that they wanted in the first place.

24:20

Right. So there's kind of some protections

24:22

to cushion the blow, but it's not

24:25

good news for the

24:26

climate. And what's the

24:28

reaction been? Well, if anyone's on TikTok, you

24:30

might have seen the hashtag stop willow, where lots of

24:32

people have been getting very angry about this. Eboth

24:34

bin more than one million letters of protest

24:37

written to the White House. There's a petition

24:39

online calling for all of this to be halted

24:41

three million people have signed that.

24:43

There's one environmental group who said that these

24:46

new limits that have been put in place don't

24:48

go far enough Kristen Montel, who's a senior

24:50

lawyer at the center for biological diversity, say

24:52

that protecting one area of the Arctic so

24:54

you can destroy another doesn't make sense.

24:57

So why do you think he's done this?

24:59

It seems like a contradictory move

25:01

after that huge law he passed last

25:03

year. The Inflation Reduction Act,

25:05

which of course included billions of

25:08

dollars of investment for climate

25:09

action. Well, some of it could be down to the fact

25:12

that his hands are partially tied on this.

25:14

Licenses, which meant that this company

25:16

could drill in these parts of Alaska, were awarded

25:19

about two decades ago. So if

25:21

Biden did block them, they could take

25:23

US government's court and argue their case.

25:25

But also, politically, it makes sense somewhat

25:27

for Joe Biden. Yes. When he was

25:29

a candidate, he was trying to get the

25:32

more progressive climate conscious

25:34

part of his party on side.

25:36

Mhmm. But now he's facing potential

25:38

reelection in twenty twenty four. He's thinking about

25:40

voters right around the US who are worried about

25:42

the price of gas that goes into their car,

25:44

the price of fuel, which heats their home,

25:47

and Alaska is a huge

25:49

reserve for that kind of

25:50

thing. And even just for the state itself, eighty

25:52

five percent of the state's budget is supplied

25:54

by oil revenues. That is interesting.

25:56

Okay. One to watch. Thanks,

25:58

Luke. That's

26:07

all from us. Thanks for listening. This

26:09

episode was produced by Ben Cooper.

26:12

Matt Dawson and Laura Kane were on

26:14

research. The

26:15

series producer was Alex Lewis. Richard

26:17

Fenton Smith was the editor, and James

26:19

Beard makes the program. Goodbye. Bye.

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