Hello Crowd Science, it's Saugat Bolakhe here from Nepal. My question actually revolves around the
most burning issue of this decade that is climate change.
This is Crowd Science from the BBC World Service with me Marnie Chesterton.
We're here for your science questions.
We are under climate crisis
and I am a complete supporter of climate movement but some reports claim even if we stop emitting
these greenhouse gases today the temperature will still rises for maybe 40 years or more.
That means we are eventually destined to an unstable climate and future.
What are our preparation, what kind of climate smart and adaptive technology
have been going on in this world recently?
Saugat's question is timely the UN body for assessing climate science - the IPCC - has released a report
warning that we humans are causing irreversible damage to the planet.
And Saugat should know. He wrote to us from Nepal which has seen an increase in wildfires and drought in recent years.
The monsoon season there has become less and less predictable which makes it harder for farmers to
know when to plant crops or harvest them. Of course it's not just Nepal, here in Europe we're seeing
the effects of climate change on weather patterns too with devastating floods in parts of Germany,
Belgium and the Netherlands.
Meanwhile over in the US, wildfires now seem to be an inevitable part of life.
The IPCC has modelled future scenarios and says that the worst future -
the one with more droughts more floods and millions displaced as their homelands become uninhabitable -
the way to prevent that version is to stop putting more greenhouse gases into the air
and fast. Of course we could all try to not fly, not to drive a gasoline-powered car and not to eat meat
but this is about more than personal responsibility. This needs big changes to the way our societies operate.
We're unlikely to go back to pre-industrial existence. Life without electricity?
How would you listen to Crowdscience? Unthinkable.
Since life is getting more and more digital maybe we could harness some of the potential
of our tech savvy lifestyles to help reduce our emissions.
Ideally without rebuilding the homes and cities we've already constructed,
or causing too much effort to people like me who live in them. Wouldn't that be smart?
Well in today's show we're going to investigate three areas where smart tech might just be able to help.
First though let's look at what's producing most of the greenhouse gases.
Generally speaking the direct emissions come from transport, from buildings, from industry and from agriculture and
forestry.
That's Professor Srinivasan Keshav from Cambridge University
explaining that we humans are responsible for emitting around 40 billion tons of co2 into the atmosphere every single year.
And co2 or carbon dioxide is the most common of the greenhouse gases. It might
surprise you to know that Keshav isn't a climate scientist, he's a data guy. You might be thinking
what does computer science have to do with global warming? Well Keshav's one of a growing number of
people using clever computing to help us cut our carbon emissions in all sorts of ways.
So listener Saugat is right on the money.
A recent report that came out from the World Economic Forum identified digital technology as
being probably the world's most powerful influencer to accelerate action to stabilise global temperatures below two degrees.
And other people identify the digital sector as having the potential to reduce fossil fuel emissions to 15% by 2030.
And it comes from the fact that we can use digital technology to make things more efficient.
This idea of efficiency is key as we'll hear throughout this show it means we don't need to build a new environmentally friendly world
from scratch we just need to use what we have but better. When I say what we have I'm talking about
the infrastructure, the transport network, the power grids, the buildings, all of it can be made to work
much more effectively saving precious energy. So let's start with the sector that actually produces
the energy because currently it's responsible for more than 70% of our greenhouse gas
emissions. That includes the energy that powers big industry, heats and cools our buildings
and fuels our cars. It also powers the tech that aims to radically reduce those emissions.
I mentioned smart technology earlier and you may be wondering what makes any of the new developments
we'll be discussing smart. Keshav says it's a term to be taken with a big dose of cynicism.
Smart is a marketing term you know. It doesn't really mean anything if I say I have a smart
home, that means everybody else has a dumb home, obviously? Right so if anybody says
they have a smart anything I would say you know look twice, they're probably trying to you know.
Whack an extra 50 dollars on the price of your whatever it is?
Exactly. At some level smartness has to do with the incorporation of digital technologies into the
system so it's somehow responsive to your wishes and to your presence. So yes calling something
smart might just be a way of selling us more stuff but it's still useful as a way of describing
how much more reactive things can be to our needs when artificial intelligence is built in.
Keshav uses an example of a home heating system to explain how.
It is on the risk for you to keep changing the temperature when you leave home and you come back home etc
or a smart thermostat. What they do is they observe that you typically leave home around 9.00 am
and you typically come back around 5. All right let's go and change the temperatures
and without you having to do anything it becomes responsive to your occupancy.
Smart thermostats like the one Keshav's talking about are common place these days.
Maybe some of you have even got one in which case well done you're almost certainly using less energy to keep warm but don't feel too smug yet
because if that home heating system is powered by fossil fuel - and globally most heating systems are -
then both digging it out of the ground and burning it produce carbon emissions.
To decarbonize to take carbon dioxide out of the equation we need an alternative like wind power.
Here in the UK renewables like wind and solar, even wave power are already providing just under
half our energy needs but they don't always work as efficiently as they could and some companies
are using artificial intelligence to try and change that. Here to explain how is former Crowd
scientist Graihagh Jackson.
Hi Graihagh.
Hi Marnie.
The reason we've asked you to come back is because you've now got your own show, also on the BBC World Service about climate change.
What's that called?
The Climate Question. We basically look at why we find it so hard to save our planet.
Like what's holding us back from taking action.
So you're the perfect person to talk to about a project linking renewable energies to smart tech.
I mean there are really high hopes for renewable energy as one of the big solutions to climate change but there are some problems.
There's always a problem isn't there. And it's something experts call intermittency. I'm gonna let Enass Abo-Hamed explain that.
She's an award-winning scientist originally from Palestine but she now lives in the UK where she co-founded a company called
H2 Go Power.
Renewable energy is intermittent by its nature because we're dependent and relying on
the weather. When the sun shines and when the wind blows. And these by nature are not
24 hour 7 reliable constant.
And that means that demand doesn't always meet supply of renewables?
It can mean that we get blackouts but on the other hand it means that when the sun is up and we were producing all that
power or when the wind is blowing and we're producing power we might not be able to use that energy -
there's no demand for it. And so it's wasted.
That is absolutely true. Demand varies a lot and it varies with all the changes that we have.
When we've had Covid hitting us our behaviour changed which meant our demand for electricity changed
and the grids are not designed to be extremely flexible. But if we had a source of reliable storage that could bridge this gap between supply and demand.
We could achieve better results.
Her team have developed this artificially intelligent algorithm that predicts when there's surplus renewable energy
and when there's high demand. So when there's excess it stores the electricity as hydrogen and when there's
high demand it converts the hydrogen back into electricity. That sounds pretty simple, what makes it smart though?
Well I've made it sound really simple but actually grids are these really big complicated beasts and if you throw in the unpredictability of
weather and then the fluctuating demand for power there's actually quite a lot of data to process
and then act upon, make a decision. So what the artificially intelligent algorithm is doing is
essentially calling the shots, working out when it's best to do what.
And Enass has been trialling this in Orkney this is a little island off the north coast of Scotland, a country close to
your heart Marnie I believe?
Yes a place of weather some of it quite bad.
Orkney is a really interesting test bed because you're talking about a remote island,
not a very good connection and the weather conditions there that you have a lot of variability.
You could have like a week off a lot of wind and then a week of nothing so basically you're talking about prediction software
that allows you to know when the wind turbine is going to generate a lot of wind or not based on the weather
and then the ability to take that data process it and predict well in advance what is the best point to instruct
the system to store and then convert it back to the grid.
And you mentioned that it's stored as hydrogen, why hydrogen and why not just use batteries?
The thing about batteries is they don't hold charge for a long period of time normally people talk about one to four hours.
The 12 plus r1s are just not really that cost effective at the scale we need them to store
all this surplus renewable energy and this is where it makes sense to convert that electricity
into hydrogen because you can store it for much much longer and then convert it back whenever
you need it.
And how do you do that, how do you make the hydrogen?
Split water molecules, H2o, by passing an electric current through that and in this case you create that electric current
with wind so when you want electricity at the other end you simply recombine the oxygen and the hydrogen
to create water and importantly electricity.
Are there other ways people are using computer technology to make wind farms more efficient?
Let's just look at the wind farm for a moment. Before they're even built engineers are using these really sophisticated
computer models to make sure that even the blades are the best shape they possibly can
to harness as much wind as possible. And then if there's going to be more than one turbine software
can make sure that they're placed in the perfect position so one turbine doesn't block another one's bit of wind.
And then even when they're built some engineers use something called a digital twin. This is really
interesting actually this is where lots of sensors are attached to the wind turbine so it can be
modeled on a computer in real time and then using machine learning you can then simulate
what's happening to the wind turbine in specific weather conditions and this is important because
it means they can make sure they're performing at their best. So basically computer modelling,
smart tech can be involved at every single step of the process here.
Thank you Graihagh. In return for helping Crowdscience I've helped Graihagh with an episode of
The Climate Question where together we looked in detail at the promise of green hydrogen.
Find it wherever you get your podcasts. In summary I've learned that smart grids don't just transport power
from a source to a plug socket, they're two-way using lots of data to know when conditions
require more electricity and when to save it up for later. Smart grids allow more localised storage
which means more flexibility which we'll need to respond to increasingly noticeable extreme weather events.
And according to Srinivasan Keshev if all of the electric gadgets in our home connect to these smart grids a computer can start
the washing machine when the electricity is cheapest without us having to lift a finger.
It's not going to be possible for humans to deal with the variability and demand. They may not even
be home to deal with this so many people have put together what they call a home energy controller
and that home energy controller has the role of forecasting your occupancy, forecasting the demand
and forecasting the price that they expect to see based on observations of weather, or past history
or using AI techniques, or talking to other home energy controllers and then saying we're going to
take these actions and our goal is to keep you comfortable but also reduce your energy demand.
And do you think in the future as part of this people are going to have batteries in their home
that sort of store up energy so that the grid is much more of a two-way system -
it's not just us taking electricity from the system?
There have been a bunch of technological changes which have been super positive.
One of them is the rise of solar and of wind and the holy grail in some sense is for people to install their own solar panel
on the rooftop and put in a storage battery in the garage and they essentially meet
all of the energy needs themselves. With electric cars coming in there's actually a possibility
that we don't need to buy storage, we can just use our cars.
So I have an electric car at home and it has 50 kilowatt hours of storage. It's a lot of storage
enough for about a week of my electricity consumption so all I need to do would be to store the sunlight by day
and then at night just have my car parked by my house.
This is something that is almost there, we need perhaps a few more years but I fully envisioned that in the five years
from now when you buy an electric car it'll be a bi-directional electric car and so you'll
put your solar panels on the roof and so your car is being run on sunshine from your home and at night your car runs your lights.
This is Crowdscience from the BBC World Service and this week we're looking at some of the clever
ways in which smart tech can help us save and store energy and avoid warming the planet.
We've heard how renewables that help us reduce our reliance on fossil fuels like coal and gas can
be made more effective by digital systems. Whether that's by using artificial intelligence to predict
when the wind will blow harder or by allowing us to program our homes to be clever about when we
use that electricity. In the developing world where national grids may be smaller and less complicated
than the existing ones we have here it may be even easier to introduce this type of smart technology.
Of course electric cars are expensive and while Keshav's dream of vehicle-powered homes might
only be achievable for the most wealthy people on the planet it is still an inspiring idea.
But energy consumption in our homes is a fraction of what we need to power the office
blocks where many of us work or at least where we used to work before the pandemic.
I've come to the brand new offices of the engineering firm Arcadis in the heart of London's financial district
and it quickly becomes apparent that this no ordinary office block.
Welcome your host Matthew has been notified that you're here and will meet you shortly. Take a seat.
Hello hello that's here can I get you a drink or anything?
This is a sumptuous space so I wouldn't be too surprised if they did have an automated cocktail
bar. The whole building has a futuristic feel to it from the wall made of LED screens to the touch
screen coffee hubs. There's also a lot of greenery, plants everywhere and they're not just for show.
Arcadis's head of technology Matthew Martin says there's a lot more to this place than meets the eye.
I think of a smart building as giving you all sorts of outcomes to do with sustainability,
to do with space and for sapiens so that means that the technology uses data and the sorts of
insights to do something that's quite cool for you know how everything operates. Not very articulate that...
No no no I think it's one of those things that you might need to demonstrate in order for me to
to get the gist of it. So where's the first smart thing I'd encounter if I came in?
The first thing that happened when you came through the door was that you went up in a lift
that's got something called destination control and that means by knowing who you are where you're
going to visit it's able to balance and optimise who gets into which lift so that it's able to
firstly reduce the amount of energy consumption and help to make the lift kind of last longer
because it reduces the travel times and distances that it goes by getting folks to group together.
We'll go around into the canteen. So one of the the ways in which we've designed this office
here is all to do with collaboration and in order to deal with a space that's like that
can be quite challenging which is why you need some of the sort of smart building software in
the first place to make that happen. That software is actually a massive computing system designed to
process loads and loads of real-time information about how the building is being used. Everyone who
works here has a smartphone which they use to book meeting rooms, control the temperature in a
specific area, open a locker and even find out where their colleagues are at any given time.
And dotted all over the ceiling are little sensors that measure all sorts of different things.
We've got around 8,000 sensors across the building generating 1.85 million points of data a day so
that we can balance all of that sort of stuff and some of the things that we're looking for
includes humidity temperature, co2, volatile organic compounds as well as things like pm 2.5 and it's
able to give us a score to reassure folks that we're providing a very healthy space for us to
be in. Actually this is now going down the score because i'm breathing on it exactly
because we are giving it carbon dioxide which will mean that you see the machinery above your head
will start to ramp up to give more pressure into the space to react to what we're doing here.
iI's all sounding smart so far, what else have you got to show me?
We'll take you upstairs now.
We're in the winter garden right now and this is where the lighting strategy you can just about see
it because it's not particularly bright outside in the lighting system that we've provided we're
expecting to save about 60% from a normal system and it works on kind of three ways so firstly
the fact it runs on LEDs rather than anything a bit more traditional. The second is that from the
occupancy sensors that you can see it's able to tune on the basis of who's here and who
isn't and then thirdly it does something called daylight harvesting which means it will only top
up synthetic light in addition to what the sun isn't providing so you can just see around the
edge, feel though it's a bit kind of overcast today that it's definitely dimmer than what it is inside.
So the lights above us are they going to switch off once we've disappeared?
Exactly they will give us a little bit of linger time to make sure it's just not that we're being really still and focused
and then they will wind down.
I think we've got them at the BBC they're just kind of you're working late in the evening
you need to kind of swing your arms about because otherwise you're sitting there in darkness.
Your's sound like they're done on something called passive infrared which means it has to see motion
of some sort whereas ours detects infrared - they can see that we've got a person that's
an alive blob and so that's how it looks.
Because the thing when you're editing late at night is you're not moving you're you're staring
at a computer screen.
And then it gets spooky.
Then it does yeah. Do you know how much energy a building normally takes to run per square meter, per year for a commercial building?
We're looking at about 160 kilowatt hours. The challenge for buildings going forward will be as to how they operate
with net zero because I'd expect that to be more at the kind of 55 mark for something that's achievable
to replace with renewables so we're basically asking quite a lot from our people and the way that buildings operate
to be able to do it. Typically 40% of your energy comes from your heating, ventilation, air conditioning,
5% from your lights and 55% from your plug load so to get to net zero we're basically saying we'll swelter in
the summers and freeze in the winters. We'll have to buy some candles so that we can see what we're
doing and we have to ask everybody to pre-charge their devices before they come to the office.
Which doesn't really solve the issue it just moves it elsewhere.
Right okay are you saying that net zero is not not feasible unless you have a huge amount of solar panels and wind turbines on the
roof and things?
It's absolutely feasible and I think any kind of company that isn't using something like
hvac analytics really needs to open their eyes to the power of what it can do and that's something that we've baked into the
design of this building so collecting the data from those 8,000 plus sensors that we have
we're able to use some proper cloud scale intelligence to look at ways in which we can
reduce our energy consumption. All those things add up to what I would expect to be about a 20% saving
across the entire usage of electricity so it helps us to get down to that key 55 number.
And you said 8,000 sensors, I mean presumably those are all
electricity based and so isn't there a huge cost to using a load of cloud storage and algorithms
and and sensors to monitor the whole situation?
Very minimal and a lot of them are actually battery based. The power requirement is very low
and when you talk about using cloud computing yes there is definitely an energy cost to it but by using that little bit for the sake of a server
versus the 20% we get back for a whole building that definitely adds up.
Net zero means adding no greenhouse gases to the atmosphere. What that means in reality is that you balance what you
put in with what you take out so at the moment some companies claim to be net zero they still
produce carbon dioxide since their buildings use energy which might not all come from renewables
then they offset that by planting trees but Matthew argues the intelligence system he's built
means that you don't have to use as much electricity in the first place.
Many new buildings have some form of renewable energy generator on site but digital technology
isn't just helpful for new buildings. Surrounding Matthew's new office in the city of London is
architecture that dates back hundreds of years and those buildings can be retrofitted with sensors so
they can also optimize the heating and lighting according to which employees aware. Small privacy
point these particular sensors aren't cameras they just detect you as a living blob no offense
and the small changes they make in response to how we humans use a building all add up to
meaningful efficiency savings. I've said in this show we'd look at efficiency in three sectors
we've looked at the energy sector and at buildings and finally we're focusing on something we've been
doing for thousands of years farming. Essential for feeding and clothing the almost eight billion
people on this planet but agriculture is a big contributor to greenhouse gas emissions.
From the methane belching livestock to the gases produced from using fertiliser
which are also often made from fossil fuels like natural gas from deforestation to biomass burning.
So I asked Keshav is farming a place where data can help?
If you are able to measure the soil properties on each part of your farm in a fine grained way that means every square meter perhaps
then you wouldn't use the same amount of fertilizer everywhere. You know you use a
fertilizer in those parts of the farm you need it and less otherwise. I mean the farmers have
incentive from the perspective of their costs to do this.
What he's talking about is precision farming. It's becoming more and more common in the west where it's saving large farms a lot of money.
Not only are they using less water, fertilizer and pesticides but the huge amount of information
generated by satellites and soil sensors can help farmers identify the best time to plant
and harvest crops. It means less wastage and oh look there's a theme developing here that
reduces their overall carbon footprint. The World Economic Forum reckons that if these techniques
were employed by just a quarter of farms globally greenhouse gas emissions could be reduced by 10%
in this sector over the next decade. So let's look at India where agriculture is big business and to
find out more i spoke to crowd science correspondent and determined city girl
Chhavi Sachdev.
70% of India lives outside the cities, unlike me and most of those folks are involved in agriculture and growing food for us and a lot of the world. It's what their parents
and grandparents and great great grandparents have always done and that's how their knowledge
has also been transferred. For instance I spoke to Manju Badekar. Her family
owns a quarter of an acre of land about six hours away from Mumbai in Kashegaon village.
I have 10 guntas or a quarter of an acre of land. We grow sugarcane and peanuts we also have brown
gram or chickpeas. We sometimes grow wheat but no rice. It works the way it's always worked
so for instance every year in this season which is the monsoon season we know we should grow peanuts.
Then after that sugarcane then in the festival of diwali or Dussehra we go back to peanuts.
How do we check whether to add fertilizers or when to water? We can see the insects. They're generally
white and we can see when we should water the crops or not. My in-laws do this and they taught us.
We go by the time and season around here, it's always been like that.
So it's not a sector that I can immediately see there being scope for a digital innovation but then again India has a
lot of smartphones.
Yes but there is lots of scope. It's not like it's not possible and that's what we're going to get into and to understand
a little more i spoke to Dr Madhurama Sethi, the Indian Council of Agricultural Research.
We must understand that 80% of farm holdings
in India are fragmented and belong to marginal and small farmers and these farmers have been farming
their small land holdings for centuries. They have been familiar with tilling cropping harvesting and
understand their water and soil requirements very well. In recent times even though their reach to
information has increased with the use of mobile phones and they have access to weather reports on
soil health including sowing advice, that's all they will look at. They will not read subsequent
messages sent to them about irrigation practices or what they need to do for
water application etc because functional literacy is low. Besides that if you send them precision
farming data by way of maps etc they are unable to understand them or interpret them in any way.
This is the biggest factor holding back adoption of precision farming.
I'm getting this picture of there's traditional farming where people just do what they've always done and then there are
these academics and scientists who are saying look there are loads of really cool bits of tech that
can make you do it better is that what precision farming is?
So precision farming as opposed to traditional farming is when you're using really targeted data and information to make decisions
about farming. In India you know technology is what it is and there are lots of companies that
have stepped up because they realise it's a big market gap and they're using digital technology
and data to try and improve this situation. One of them is a company called Cropin which has an app
in particular called Smart Farm that aims to be a complete farm management system. So what they do
is they use AI and machine learning for everything from geotagging the land to sending weather alerts
and prompts and monitoring the process of growing the crops. So if a farmer needs certification it's
all logged and this is the CTO Rajesh Jalan.
Through our application the farmers typically either the farmer or someone whom we call as field officer
captures all the details about that farm starting with the geolocation, the soil quality.
Based on that an agronomist can really get data on each and every part of the land and how to
deal them differently. For example the agronomist could say that in Gujarat this is the time to
sow and at the same time it can say Himachal wait for couple of weeks.
Because our product will enable them to see the weather conditions are different in both of them.
Chhavi, I'm really interested to know more about how this app links up to farmers like Manju who we just heard from
at the beginning who doesn't even have a smartphone?
Yeah that's definitely a challenge and Crop In knows that literacy and access to smartphones and
data is the issue and they've put in a secondary system where field officers are trained in the
community to spread the alerts like a human alert system.
If precision farming were to expand what kind of effect would this app have on climate change or emissions from farming in India?
Well according to Crop In the results are astounding. So Jalen says they have 16 million digitised acres
with 2 million Indian farmers. Already the farmers are reaping 30 to 40 percent more yield in a
sustainable way and so working with data about soil about wind and weather patterns means they're
using less water less pesticides and this also means reduced emissions from overuse of chemicals.
30 to 40% that's quite impressive and I'm just wondering is Crop In the only company doing
this or is this the sort of thing that's becoming really widespread in India?
Oh it's definitely growing. So this kind of smart technology in the sector is called agrotech. I found all sorts of
other examples when I was doing my research from mobile phone technology to run irrigation systems
or a robot based seed sowing program that's connected to the internet of things.
Yhe only thing to remember is that all of this relies on farmers having access to smartphones,
data networks and of course the ability to read.
It's not just illiteracy that's the problem here. I can see how someone like Manju the farmer that Chhavi spoke with might not be convinced that an
app's going to do a better job of telling her when to add pesticides than just using her own eyes to
check for bugs on leaves. And with just a quarter of an acre to farm it may not seem worth it to
invest in the tech. Then you've got to consider that smartphones require data networks which are
notoriously patchy the more remote you get so is this kind of upgrade to traditional farming
really just a rich country thing? Well Keshav says that the technology doesn't actually need
to be that expensive or complicated to have a big impact.
Being a farmer in a developing region is one of the most risky businesses you could ever
get into. Choosing what crop varieties to plant, when to plant it, how much to water it,
when should you harvest it, what to do when you have pests coming in, what kind of fertilizer inputs to use,
when to put it in. I mean really there's thousands of things you need to take into account and if you mess up
on any one of them you lose your crop. The main thing we can do to help them is to improve the state of their knowledge even as something
as simple as being able to listen to a radio program that says okay farmers in your region have
experienced these kinds of conditions and this is what they're doing is actually very valuable
feedback to them. Another technology that's very useful and it's getting cheaper all the time is
just regular mobile phones where you can call up a toll-free number and listen to targeted feedback
from agricultural experts about situations in that neighbourhood.
Maybe using words like digital and tech are misleading here ultimately this comes down to gathering information that helps people
make better decisions. That information can be fed into sophisticated algorithms attached to an
app or it can be stored in a database that's sent out on local radio or via text messages.
The world wide web is only 32 years old but analog life already has an impressive digital carapace a
sort of technological second skin we're monitoring and connecting life on earth as never before
and if you think all that data might be creating a carbon footprint of its own well good news because
the total amount of energy spent on powering all of the digital technology in the world that's all
of the computers mobile phones cell towers data centers only comes to about 2% of total
emissions. How do we know this? Well it's thanks to data of course. In connecting everything digitally
with all this extra information, privacy and security is vital. What happens if digital networks
get hacked or data falls into the wrong hands? We didn't have time to get into cyber security
but it is worth at least a whole episode on its own and crowd science will come back to it later.
As the latest IPCC report lays out a red warning for humanity I take some comfort in all the people
out there using this information to be cleverer, more efficient about the lives we lead.
We've shown it can make a difference to the buildings in which we live and work the electricity grids
that power them or the farming that feeds the planet all have scope to do the same job cleaner,
greener and therefore better. Call me an optimist but I find that encouraging.
Perhaps unsurprisingly so does Keshav.
Each of these underlying systems is a traditional system. These are actually not high-tech systems.
By adding to them the ability to analyse data, to do this what-if analysis, what if you did this, what would happen,
these oil systems get transformed. So these kinds of digital technologies which are getting unleashed upon the world when used the right way.
But the appropriate policies and regulations I think will make it possible for us to move to a world where we're
not going to be in a situation as absolutely terrible climate change you know. We are heading
with the business as usual scenario to some pretty terrible consequences and luckily we do have at
our disposal some very very powerful tools. And now it's a matter of getting the tools and the tool
builders and the policy makers to get together and use these tools for the benefit of humanity.
Thanks for listening to Crowdscience from the BBC World Service.
Today's question was from me, Saugat Bolakhe in Nepal, the presenter was Marnie Chesterton and the producer was Marik Peters.
If you want to write to them with your own question you can email crowd science at bbc dot co dot uk.