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ZEYNEB MAGAVI: The Session
1 is Framing the Challenge,

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and we're going to go
as high level as we can,

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looking at the whole
world and all of humanity.

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And I couldn't be more excited
about the three speakers.

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I will not do them
justice by introducing,

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so I'm asking each of
them to take a moment

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to introduce themselves.

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And we're going to start
with Jason Jay from here

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at MIT Sloan School, who has--

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I will just add one
piece of introduction.

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He has the incredible
distinction,

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which I don't know if
it's on your LinkedIn,

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but of being a early HEET
volunteer for an energy

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efficiency barn raising.

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JASON JAY: That's right.

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I learned how to use a
caulking gun from Zeyneb.

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[LAUGHTER]

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Good morning, everybody.

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AUDIENCE: Good morning.

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Good morning.

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JASON JAY: Good
morning, everybody!

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AUDIENCE: Good morning.

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JASON JAY: All right.

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So I'm Jason Jay.

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I teach at the MIT Sloan
School of Management.

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I'm the director of the
Sustainability Initiative there.

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I've had the great
pleasure to be

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part of this HEET journey
from the beginning,

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as Zeyneb was saying.

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When I did my PhD here, I
was studying something called

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the Cambridge Energy Alliance.

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And I was looking at the
multi-stakeholder collaborations

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that were occurring here
around our city of Cambridge,

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advancing energy
efficiency topics.

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And part of that
included participating

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in HEET's early barn raisings.

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And I did, in fact, learn to
use a caulking gun from Zeyneb

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as we were weatherizing
people's homes.

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And then, I've gotten to watch
as this whole thing has evolved,

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going to the gas leaks
effort, the collaboration

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with Eversource
and other utility

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companies, the advancement
of the legal policy

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framework around better
measurement of gas leaks,

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and then towards this
transformational idea

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of geothermal energy
networks, where now there's

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enough trust between the
advocates and the utilities

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to actually say, hey, could
we just not have you be a gas

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utility anymore? which
is an audacious thing,

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and is the reason we bring
in Zeyneb as a guest speaker

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into our courses every year.

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What she asked me to
do is to, as she said,

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go to the level of all
of the whole planet

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and all of humanity.

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And the way I'm
going to do that is

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using an interactive
simulation tool called nROADS.

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Just a quick show of hands,
how many of you have seen

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nROADS before?

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OK.

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About half the room.

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So this is the result of a
collaboration between the MIT

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Sloan Sustainability Initiative
and Climate Interactive,

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which is an independent,
nonpartisan, nonprofit made

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of mostly MIT grads,
who do a simulation

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tool that behaves the same
as the big supercomputer

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integrated assessment models
but runs instantly on any laptop

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and is freely available
in open source

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to anybody with a web browser.

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So you can't open it
up on your phones.

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But on any laptop or
iPad, you can pull this up

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and experiment with it yourself.

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And I am not on
the modeling team.

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I'm not a climate scientist.

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I'm not an energy scientist.

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I'm an organizations person.

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But I've been facilitating
probably hundreds of workshops

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at this point using this tool.

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And that means that any of
you can do that as well, which

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I would certainly recommend.

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What I'm going to
try to do is just

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use this to expose a little
bit about the climate challenge

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and how the things that we're
talking about here today

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fit within that bigger
picture and what

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some of the system
interactions are because this

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is a system dynamics model.

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This is the interdependence
of thousands

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of variables to produce the
outcomes that we are facing.

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So here you can see
on the left, this

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is the stack of global energy.

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So she talked about a
ZettaJoule that humanity

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is using about half of a
ZettaJoule, so 500 exajoules.

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You can see that
here on this picture.

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And that is made up of coal,
oil, gas, renewables, biomass,

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and nuclear.

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If we were to invent nuclear
fusion or some other new zero

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carbon, we could
add that to the mix.

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We're not going to
talk about that today.

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On the right, we have the stack
of greenhouse gas emissions

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that are partly related to that.

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So the largest source of human
anthropogenic greenhouse gas

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emissions is CO2 from energy.

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That's about 35 gigatons
a year right now.

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The second highest
source is methane.

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So this is put on 100-year CO2
equivalent units on this graph,

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so 10 gigatons of CO2 equivalent
from methane emissions.

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The third highest
is land use change

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from deforestation and
peatlands and so on.

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And then you have nitrous
oxide and F-gases.

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So this gives you a
picture of the faucet

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into the bathtub of the
atmosphere, how much greenhouse

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gas we are putting into
the atmosphere every year.

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And the result of
that faucet being

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on stronger and
stronger every year

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as we grow the global
industrial economy,

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is that the concentration of CO2
in the atmosphere is increasing.

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You've heard 350.org wanting
to get that back down to 350,

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closer to preindustrial levels.

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We're now at about 424.

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And that increasing greenhouse
gas, as Zeyneb said,

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creates this thermal
regulation problem,

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which is that we're
heating the planet.

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And so the temperature
is increasing.

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In 2024, the data
is still coming in,

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but we're really pushing
close to that 1.5 mark.

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And you can see in our
business-as-usual projections

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on nROADS, we pass
the 1.5-degree goal.

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We pass the two-degree goal.

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We, at the end of the century,
hit 3.3 degrees Celsius, which

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is what this big number is.

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And unfortunately, the slope
of this line is positive,

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which means that we're
continuing to warm the planet

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into the 22nd century.

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Not everybody has
a visceral sense

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of what 3.3 degrees
Celsius means.

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And so one thing
you can do is you

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can use the impact graphs in
nROADS to explore some of that.

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So for example, we can
think about how much sea

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level rise might we see as
a result of that warming?

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Or we can think about other
graphs like the extinction risk

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from animal species, so the
effects on biodiversity.

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One of the things that-- if
you haven't played with nROADS

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in a little while,
we've now added

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is that we interface
with maps that

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are from the Probable
Futures site, which

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allows you to see
what happens on a more

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regional or geographic basis to
the places that we care about.

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So for example,
this is a picture

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of the number of extreme
humidity and heat days.

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So how many days
per year do we have

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with wet-bulb temperatures
above 26 degrees Celsius, which

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is where you start to
have really serious health

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consequences of outdoor
work, outdoor sports,

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and if you don't have
cooling in your home,

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just even sleeping at night.

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So you can see that the
Southeast of the United States

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starts to have really
dire conditions.

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And you can back this off by
year and see how this evolves.

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So here's where we were in
2000 in terms of the frequency

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of those ultra high heat days.

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And you can see that
that's all increasing

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throughout North America.

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And of course, if we look at
other geographies in the world,

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in sub-Saharan Africa, where
my wife's family is, in India,

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in the Eastern part
in West Bengal,

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you can see that there's
very serious consequences.

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And so what this
means is that we

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have to learn how to cool our
buildings fast and quickly

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and cheaply and low carbon.

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And so that demand
for cooling is

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a big piece of the
puzzle of what we're

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going to be grappling with.

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So that's one thing
just to be oriented to.

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What is the challenge,
and why are we

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trying to solve for more
efficient, low-carbon methods

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for doing heating and cooling?

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Now, a couple other things I
wanted to just illuminate here.

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So one is that the methane
as a significant source

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of greenhouse gases, this lever
here, which is about the waste--

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oops, sorry, I'm
not used to Windows.

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Can I make that go away?

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OK.

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Good.

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This lever over here, which
is about the waste and leakage

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of non-CO2 greenhouse gases,
so if we look at methane

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in particular, what you can see
here is that people talk about

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methane--

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when we talk about
methane, oftentimes we

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talk about cows and
agricultural sources.

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And that is very important.

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You can see that agricultural
methane emissions.

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But what a lot of
people don't think

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about is the fact that a very
significant part of our methane

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emissions, this is depending
on the time horizon,

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50, 60 times stronger
than CO2, do significantly

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come from energy production.

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So when we can move away from
coal, which leaks methane out

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of the mines, gas, which leaks
methane across the value chain,

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and oil, which leaks methane
at the drilling sites

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and in the refineries, we can
work on this chunk, right?

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So if we can decrease methane
leakage from the energy systems,

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which was HEET's first
major effort, yeah, OK.

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So you can see this bent
the curve a little bit here.

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And if I just do a little
replay, you can see the change.

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So that bending of that
curve of energy leakage

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is one opportunity.

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But if we can get off
of those fossil fuels

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entirely, for example, by
pricing CO2 and doing things

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that allow us to decarbonize
energy supply, what you'll see

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is that those methane
emissions from energy

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go down even further.

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So there's a two-prong
approach here,

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which is to reduce the leakage
from the system that we have,

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which is the original
gas leaks idea.

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And then there's
the question of how

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do we transition away from these
high-carbon sources of energy?

00:10:22.180 --> 00:10:24.580 align:middle line:84%
I'm just going to revert
back without those changes

00:10:24.580 --> 00:10:26.420 align:middle line:90%
and just say that--

00:10:26.420 --> 00:10:27.940 align:middle line:84%
so then the question
is, well, how

00:10:27.940 --> 00:10:31.738 align:middle line:84%
might we simulate the effects
of doing district geothermal,

00:10:31.738 --> 00:10:34.280 align:middle line:84%
like we're going to be talking
about the next couple of days?

00:10:34.280 --> 00:10:39.230 align:middle line:84%
And what I'll say is that that's
a blind spot in tools like this

00:10:39.230 --> 00:10:41.980 align:middle line:84%
because, as the first
thing Zeyneb said

00:10:41.980 --> 00:10:44.380 align:middle line:84%
today was that so
much of our attention

00:10:44.380 --> 00:10:46.550 align:middle line:84%
has been on
electricity and light,

00:10:46.550 --> 00:10:48.770 align:middle line:84%
we don't tend to think
about thermal energy.

00:10:48.770 --> 00:10:51.530 align:middle line:84%
And I'll say that that's
also the case for nROADS.

00:10:51.530 --> 00:10:57.580 align:middle line:84%
There is geothermal built into
what we define as renewables so

00:10:57.580 --> 00:11:00.370 align:middle line:84%
that when you're
subsidizing renewables

00:11:00.370 --> 00:11:04.060 align:middle line:84%
or you're doing other moves,
like carbon pricing that

00:11:04.060 --> 00:11:07.970 align:middle line:84%
do transition toward a renewable
world, that does include,

00:11:07.970 --> 00:11:10.070 align:middle line:84%
if you look at the
details, geothermal.

00:11:10.070 --> 00:11:12.760 align:middle line:84%
But it's largely thinking
about that first bucket

00:11:12.760 --> 00:11:19.090 align:middle line:84%
in her graph of using the super
high-temperature geothermal

00:11:19.090 --> 00:11:20.360 align:middle line:90%
to generate electricity.

00:11:20.360 --> 00:11:24.080 align:middle line:84%
We're not really dealing with
it from a heat standpoint.

00:11:24.080 --> 00:11:26.590 align:middle line:84%
The best way for us
to represent that is

00:11:26.590 --> 00:11:29.740 align:middle line:84%
for us to think about
electrifying the building

00:11:29.740 --> 00:11:31.750 align:middle line:84%
and industry space
because what you're doing

00:11:31.750 --> 00:11:34.300 align:middle line:84%
is you're often moving
to some kind of a heat

00:11:34.300 --> 00:11:39.260 align:middle line:84%
pump, a geothermal heat
pump, in lieu of a--

00:11:39.260 --> 00:11:43.000 align:middle line:84%
but you're also doing that in
a far more energy efficient way

00:11:43.000 --> 00:11:46.640 align:middle line:84%
than you'd be doing
otherwise with fossil fuels.

00:11:46.640 --> 00:11:49.870 align:middle line:84%
So this is an energy
efficiency and electrification

00:11:49.870 --> 00:11:53.320 align:middle line:84%
play, which are important
pieces of the puzzle.

00:11:53.320 --> 00:11:56.290 align:middle line:84%
The last thing I'll
just say is that anytime

00:11:56.290 --> 00:12:00.012 align:middle line:84%
you're electrifying something,
of course, you'll have to--

00:12:00.012 --> 00:12:02.470 align:middle line:84%
and you'll notice if you play
with nROADS that electrifying

00:12:02.470 --> 00:12:05.510 align:middle line:84%
transport doesn't have a
huge effect on the climate.

00:12:05.510 --> 00:12:07.420 align:middle line:84%
Electrifying building
an industry by itself

00:12:07.420 --> 00:12:09.170 align:middle line:84%
doesn't have a huge
effect on the climate.

00:12:09.170 --> 00:12:13.020 align:middle line:84%
And part of that is because
you're not decarbonizing

00:12:13.020 --> 00:12:14.160 align:middle line:90%
the electricity supply.

00:12:14.160 --> 00:12:16.868 align:middle line:84%
So you have to make sure that if
you're running those heat pumps,

00:12:16.868 --> 00:12:19.530 align:middle line:84%
you're running them off
of low-carbon electricity.

00:12:19.530 --> 00:12:21.450 align:middle line:84%
And that's another
system interaction.

00:12:21.450 --> 00:12:27.890 align:middle line:84%
So if you can do things like
stop building new coal plants,

00:12:27.890 --> 00:12:31.940 align:middle line:84%
and therefore, work toward
that decarbonization

00:12:31.940 --> 00:12:34.340 align:middle line:84%
of the electricity
system, if you

00:12:34.340 --> 00:12:39.350 align:middle line:84%
do some really heavy reductions,
either technologically

00:12:39.350 --> 00:12:43.680 align:middle line:84%
or through policy, to reduce
natural gas and so on,

00:12:43.680 --> 00:12:46.050 align:middle line:84%
then you're decarbonizing
electricity supply.

00:12:46.050 --> 00:12:48.680 align:middle line:84%
Then the electrification
actually has

00:12:48.680 --> 00:12:50.220 align:middle line:84%
more of an impact
on the climate.

00:12:50.220 --> 00:12:53.130 align:middle line:84%
So just to say that these
systems are interactive,

00:12:53.130 --> 00:12:56.750 align:middle line:84%
and we want to think about
as we are going and trying

00:12:56.750 --> 00:12:58.620 align:middle line:84%
to solve these thermal
heating problems,

00:12:58.620 --> 00:13:01.830 align:middle line:84%
that we do it in as renewably
powered way as possible.

00:13:01.830 --> 00:13:04.610 align:middle line:84%
But also just that there
are blind spots in so many

00:13:04.610 --> 00:13:06.680 align:middle line:84%
of these modeling
tools and so many

00:13:06.680 --> 00:13:08.660 align:middle line:84%
of these policy
discussions, given

00:13:08.660 --> 00:13:15.220 align:middle line:84%
the general tendency to focus
very heavily on electricity.

00:13:15.220 --> 00:13:17.000 align:middle line:84%
Is that what you
wanted me to cover?

00:13:17.000 --> 00:13:18.340 align:middle line:90%
ZEYNEB MAGAVI: [INAUDIBLE]

00:13:18.340 --> 00:13:20.590 align:middle line:84%
JASON JAY: Oh, and I'll just
say one more thing, which

00:13:20.590 --> 00:13:24.490 align:middle line:84%
is that, of course, AI
and data center growth

00:13:24.490 --> 00:13:27.820 align:middle line:84%
is driving increase in all
of these parameters in terms

00:13:27.820 --> 00:13:28.703 align:middle line:90%
of energy usage.

00:13:28.703 --> 00:13:31.120 align:middle line:84%
So we have to do everything
that much harder and that much

00:13:31.120 --> 00:13:32.320 align:middle line:90%
faster.

00:13:32.320 --> 00:13:35.300 align:middle line:84%
Now, hopefully, the AI and the
machine learning can help us.

00:13:35.300 --> 00:13:36.280 align:middle line:84%
And we're going to
talk about the ways

00:13:36.280 --> 00:13:37.755 align:middle line:84%
that advanced
analytics can help us

00:13:37.755 --> 00:13:39.130 align:middle line:84%
identify geothermal
opportunities

00:13:39.130 --> 00:13:40.220 align:middle line:90%
and optimize for them.

00:13:40.220 --> 00:13:42.320 align:middle line:84%
But just notice--
just remembering,

00:13:42.320 --> 00:13:45.260 align:middle line:84%
whenever we talk about those
types of computational things,

00:13:45.260 --> 00:13:48.220 align:middle line:84%
we always want to think about
the handprint and the footprint

00:13:48.220 --> 00:13:49.670 align:middle line:90%
of those technologies.

00:13:49.670 --> 00:13:50.290 align:middle line:90%
OK.

00:13:50.290 --> 00:13:50.970 align:middle line:90%
ZEYNEB MAGAVI: Thank you.

00:13:50.970 --> 00:13:51.590 align:middle line:90%
JASON JAY: That's all I got.

00:13:51.590 --> 00:13:52.210 align:middle line:90%
ZEYNEB MAGAVI: Oh, my gosh.

00:13:52.210 --> 00:13:53.210 align:middle line:90%
That was amazing.

00:13:53.210 --> 00:13:55.720 align:middle line:90%
[APPLAUSE]

00:13:55.720 --> 00:14:00.010 align:middle line:90%


00:14:00.010 --> 00:14:00.830 align:middle line:90%
All right.

00:14:00.830 --> 00:14:02.433 align:middle line:90%
That was amazing.

00:14:02.433 --> 00:14:03.850 align:middle line:84%
And now we have
to talk afterwards

00:14:03.850 --> 00:14:05.423 align:middle line:84%
about getting
geothermal in there

00:14:05.423 --> 00:14:06.590 align:middle line:90%
with a little toggle switch.

00:14:06.590 --> 00:14:07.840 align:middle line:90%
Yeah

00:14:07.840 --> 00:14:13.000 align:middle line:90%