►
From YouTube: Using Hyperledger Fabric to Track Embedded Carbon in Industrial Supply... - Douglas Johnson-Poensgen
Description
Using Hyperledger Fabric to Track Embedded Carbon in Industrial Supply Chains - Douglas Johnson-Poensgen, Circulor
Circulor has been working in some of the most carbon intensive industrial supply chains since 2018. Sustainability is now a mainstream business issue and there is wide recognition of the carbon intensity of the supply chain in the manufacture of things like electric vehicles.
This talk will present a case study of the dynamic attribution of the embedded carbon in the electric vehicle battery supply chain. The outcome is to enable procurement professionals to buy more sustainably and so make a direct and significant contribution to the organisation's net zero ambitions.
Session Details & Slides (if available)- https://sched.co/jcpw
Access All Sessions: https://events.linuxfoundation.org/hyperledger-global-forum/program/schedule/
----
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A
Right
folks,
we're
we're
about
a
minute,
or
so
after
our
start
time,
so
I
think
we'll
get
going
and
this
is
being
recorded
and
will
therefore
be
available
for
others
to
view
later
as
well.
So
my
name
is
doug
johnson
pensgun,
I'm
the
co-founder
and
chief
exec
of
circular
we've
been
members
of
hyperledger
since
about
2017
contributing
to
a
variety
of
the
hyperledger
projects
and
our
platform,
which
I'm
going
to
tell
you
a
little
bit
more
about
as
we
go
through.
This
uses
hyperledger
fabric.
A
What
I
intend
to
cover
in
the
next
sort
of
25
minutes
or
so
is
an
introduction
to
some
of
the
problems
that
we
solve,
how
we,
how
we
have
implemented
a
platform
to
do
it
and
to
unpack
a
little
bit
some
of
those
lessons
from
the
front
line
of
trying
to
to
deal
with
carbon
emissions.
So
the
title
of
this
presentation
is
tackling
the
supply
chain's
contribution
to
global
carbon
emissions,
and
what
I
want
to
after
giving
a
little
bit
of
an
introduction
to
who
we
are.
A
I
want
to
explain
a
bit
about
why
that
is
a
problem
and
something
that
is
worthy
of
being
solved
or
addressed
and
then
get
into
a
little
bit
more
of
houses
actually
work.
The
reason
you're
seeing
me
like
this
and
I'm
not
actually
putting
my
powerpoint
into
full
screen
is
so
that
I
can
actually
keep
an
eye
on
the
chat
and
also
the
q,
a
which
I
can't
do
if
I
go
into
full
screen
mode.
A
The
reason
why
complex
industrial
supply
chains
is
there
are
some
inherently
critical
challenges
in
those
industrial
supply
chains,
where
materials
change
between
their
origin
and
their
consumption,
which
needs
tackling
both
from
a
responsible
sourcing
perspective,
but
also
from
a
carbon
emissions
perspective.
And
that's
what
I'm
going
to
be
talking
about
today.
A
We've
raised
around
20
million
dollars
so
far,
and
you
know
just
to
give
you
an
idea
of
some
of
the
people
we
work
with
the
customers
shown
on
this
slide
have
gone
public
with
what
we
do,
or
you
know
their
downstream
oems
have
talked
about
what
we
do
with
them.
You'll
see
car
manufacturers
there,
like
volvo
daimler
polestar,
you
know,
manufacturers
of
of
industrial
vehicles
like
cnh,
for
example,
mining
companies
like
bhp
and
a
whole
variety
of
midstream
participants
in
primarily
the
battery
supply
chain,
but
also
hard
to
recycle
plastics.
A
So
why
am
I
focusing
on
this
question
of
carbon
emissions
and
supply
chains?
Here's
a
quote
from
from
the
united
nations
high-level
climate
action
champion
talking
about
the
role
of
of
supply
chains
in
global
carbon
emissions,
I'm
going
to
bring
that
to
life
a
little
bit
for
everybody
in
a
second
but
last
year.
Of
course,
when
we
all
went
into
lockdowns
all
around
the
world.
A
Global
carbon
emissions
fell
by
about
seven
percent,
because
we
weren't
traveling,
and
so
many
of
the
things
that
we
as
consumers
do
stopped,
whether
it's
car
travel
or
air
travel
or
you
know,
etc.
However,
your
global
supply
chain
still
continues
to
operate,
whether
it
is
shipping
logistics
or
the
processes
that
go
into
the
manufacture
of
goods
that
we
ultimately
consume,
and
so
that's
why
dealing
with
the
supply
chain
challenge
is
such
a
significant
one.
The
start
of
this
year,
the
world
economic
forum
published
a
report
about
the
supply
chain's
contributions
to
global
carbon
emissions.
A
They
identified
eight
supply
chains,
and
you
can
see
them
described
on
this.
Oh
some
of
them
described
on
this
slide.
They
identified
eight
supply
chains
that
between
them
account
for
about
50
of
total
global
carbon
emissions,
and
the
reason
for
that
is
the
enormous
amount
of
energy
that
is
invested
in
the
production
of
various
materials
or
that
those
materials
just
by
their
nature,
produce
carbon
in
their
manufacturer.
An
example
is
cement.
The
production
of
cement
means.
A
You
know
that
the
the
mined
material
goes
to
a
refinery
and
the
process
of
creating
cement
drives
off
co2
in
very,
very
large
quantities.
And,
of
course,
carbon
capture
is
possible
at
those
plants,
but
in
many
cases
isn't
yet
being
used,
and
I
want
to
pick
on
two
of
these
electronics
and
automotive,
which
are
our
principal
target
sectors
at
the
moment,
and
the
reason
why
total
emissions
are
so
high.
A
There
is
because,
obviously
they're
large
consumers
of
materials
like
aluminium
and
steel,
but
also
batteries,
ev
batteries,
consumer
electronics,
batteries,
lithium-ion
batteries,
are
massively
energy
intensive
to
to
manufacture
and
and
subsequently
to
recycle.
And
that's
that
means
that
at
the
point
at
which
you
or
I
might
collect
the
keys
to
a
new
electric
vehicle,
the
inherited
carbon
in
that
vehicle
is
enormous
and,
of
course,
it's
offset
by
lower
carbon
emissions
during
the
lifetime
use
of
that
vehicle.
A
Many
of
them
will
be
net
zero
within
their
own
manufacturing
plants,
probably
by
the
middle
of
the
centur
by
the
middle
of
this
decade,
but
it'll
take
them
potentially
another
15
years
in
order
to
get
to
a
point
where
their
supply
chain
has
also
managed
to
decarbonize
its
operations.
So
the
embedded
carbon
within
the
cars
that
we
buy
has
come
down
to
zero
one
of
the
car
manufacturers
and
you
might
have
seen
their
logo
on
on
the
slide.
I
showed
a
couple
of
minutes
ago.
A
A
They're,
a
direct
competitor
of
tesla-
although
perhaps
not
quite
so
well
known
they've,
just
set
an
audacious
target
to
try
and
create
a
net
zero
car
by
2030,
so
about
10
years
ahead
of
other
car
manufacturers
and
and
have
announced
what
they're
doing
with
us
in
in
an
attempt
to
try
and
get
a
better
grip
on
the
supply
chain
now
to
decarbonize
a
supply
chain.
There
are
a
number
of
challenges.
First
of
all,
you
have
to
understand
who
is
in
your
supply
chain
for
your
most
polluting
components.
A
Secondly,
you
have
to
know
what
level
of
embedded
carbon
is
coming
through.
Each
supply
chains,
of
course,
are
not
linear.
What
level
of
embedded
carbon
is
coming
from
each
participant
in
the
supply
chain
over
time
and
use
that
knowledge
in
order
to
buy
more
sustainably
so
that
you
know,
procurement
professionals,
for
example,
in
car
manufacturers,
now
need
to
be
able
to
marry
data
about
sustainability
alongside
price
and
quality,
which
has
traditionally
been
what
procurement
professionals
are
focused
on
in
order
to
try
and
use
their
buying
power.
A
A
If
you
like,
of
of
the
embedded
carbon,
the
scope
one
and
two
emissions
from
each
participant
over
time,
based
on
how
much
material
from
each
of
those
participants
in
the
supply
chain
aggregates
up
over
time
into
the
things
that
you
buy
month
or
month
and
and
one
of
the
things
we
we
already
see
is-
is
a
significant
monthly
variation
in
embedded
carbon.
Just
for
something
like
an
ev
battery,
and
that's
because
you
know
various
midstream
participants
are
buying
from
different.
You
know
different
suppliers
over
time.
A
Some
are
using
a
combination
of
renewable
and
non-renewable
energy
and
some
of
them
using
no
renewable
energy
at
all
and
not
also
not
offsetting
their
carbon
emissions.
And
so
you
end
up
with
this
very
fluctuating
picture.
The
fundamental
driver,
of
course,
is
you
cannot
manage
something
you
cannot
measure.
A
So
I
mentioned
complex
industrial
supply
chains
and
and
the
challenge
with
complex
industrial
supply
chains
is
the
material
changes
on
its
journey
from
source
to
consumption.
So
the
first
thing
you
obviously
have
to
do
is
reliably
reliably.
Digitize
create
a
digital
identity
for
a
blob
of
material.
It
could
be
a
200
ton,
parcel
of
nickel
from
a
mine
site
in
australia
or
a
30
kilo
bag
of
cobalt
ore
from
an
artisanal
mine
site
in
the
congo.
A
But
you
have
to
be
able
to
give
a
reliable
identity
to
that
blob
of
material.
It
depends
how
you
do
it,
of
course,
depends
on
the
availability
of
technology
in
different
locations.
If
you're
talking
about
the
toughest
use
case
of
all,
which
is
an
artisanal
mine
site
in
the
congo,
you
know
there
is
no
technology.
You
may
have
a
mobile
signal.
You
may
not
have
a
mobile
signal,
and
so
you
need
to
be
able
to
identify
who
the
actors
are
where
you
are
reliably
you.
A
The
input
ingredients
go
through
an
industrial
process,
usually
consuming
a
significant
amount
of
energy,
and
what
comes
out
often
has
a
completely
different
chemical
composition
or
or
or
or
sort
of
it's
a
totally
different
material
that
comes
out
from
that
process
from
the
ingredients
that
went
into
it.
So
you
have
to
be
able
to
reliably
connect
input,
ingredients
through
a
combination
of
process
and
mass
balance
and
elapsed
time
and
other
logical
tests
to
the
output
product
of
that
process.
Doing
it
multiple
times
through
the
supply
chain.
I've
already
mentioned.
A
There
are
many
participants
at
each
tier
of
the
supply
chain
and
over
time
a
car
manufacturer
will
have
perhaps
30
or
40
different
participants
in
its
battery
supply
chain
and
for
each
of
those
we're
looking
to
to
collect
data
about
their
scope,
one
and
two
emissions,
and
for
those
of
you
that
are
not
experts
in
carbon
tracking
scope.
One
emissions
are
your
your
direct
energy
consumption.
If
you
like
in
the
manufacture
of
your
goods,
your
scope,
2
emissions
will
be
your
inputs
from,
for
example,
your
wider
workforce
or
logistics
and
scope.
A
3
is
everything
that
happens
downstream
and
upstream
of
you
and,
if
you're
going
to
achieve,
if
you're
aiming
for
a
net
zero
target,
it's
scope,
3
emissions,
that
you
need
to
try
and
get
a
handle
on,
and
there
are
many
many
different
methodologies
for
the
measurement
of
carbon
emissions
and
that's
part
of
the
challenge
here,
because
every
car
manufacturer
will
take
a
slightly
different
approach.
Every
tier
one
supplier
will
take
a
slightly
different
approach
so
trying
to
make
sure
that
everybody's
talking
about
the
same
things
consistently
is
one
of
the
key
challenges
in
this
space.
A
So,
just
a
little
bit,
then
on
the
architecture
that
makes
this
possible.
You
can
see
here
that
this
is
built
on
built
on
oracle
cloud
infrastructure.
We
we
deliberately
chose
to
build
this
on
oracle
cloud
because
we
were
creating,
which
is
quite
unusual
for
a
startup,
but
we
were
looking
to
create
an
enterprise
class
application
out
of
the
box,
and
I
didn't
want
to
have
to
be
trying
to
explain
to
customers.
You
know
why
we
had.
A
You
know
why
what
we
had
built
it
was
secure
and
scalable,
and
one
of
the
reasons
we
picked
hyperledger
fabric
as
our
blockchain
as
our
blockchain
layer
was
because
I
didn't
want
to
have
to
explain
why
we
had
picked
a
particular
blockchain
technology.
Hyperledger
fabric
has,
you
know,
been
recognized
for
some
time,
as
you
know
pretty
much
the
enterprise
standard
for
for
from
blockchain
technology
layer
and
I'm
sure
we
could
have
a
big
argument
about
whether
or
not
there
are
other
better
or
you
know,
different
blockchain
technologies.
A
But
it's
still
a
reasonable
assumption
and
what
you
see
here
is
the
ability
to
combine
blockchain
alongside
other
technologies,
so
obviously
whether
it
is
for
the
inputting
of
information
which
can
be
done
I'll
show
you
some
screenshots
in
a
second
through
a
mobile,
app
or
through
a
desktop
application,
or
we
also
take
data,
certainly
from
the
midstream
onwards,
directly
over
api
from
production
management
systems
in
large
industrial
plants,
but
also
the
ability
to
to
check
data
that
is
provided
by
supply
chain
self-reported
by
supply
chain.
Participants
for,
for
you
know,
veracity.
A
You
know
machine
learning,
various
analytics
tools
as
well
as,
of
course
a
blockchain,
and
it's
the
combination
of
all
of
these
technologies
together,
applied
to
a
very
specific
use
case.
That's
allowed
us
to
get
to
a
point
where
we
are
working
on
your
three
or
five
year
contracts
with
all
those
car
manufacturers
that
I
mentioned
earlier
across
a
variety
of
commodities,
but
primarily
in
batteries.
I
can
come
back
to
this
in
questions.
If
people
have
questions
about,
you
know
how
we've
done
it
and
what
we
do
so.
A
Forgive
me
for
this
slide
being
quite
busy
I've.
I
put
it
all
up
here,
so
you
know,
if
you
want
to,
you,
can
see
it
in
the
recording
and
studying
a
little
bit
more
detail,
but
essentially
what
we're
trying
to
do,
based
on
that
flow
of
materials
through
a
supply
chain,
is
attribute
a
slice
of
the
scope,
one
and
two
emissions
from
each
participant
in
the
supply
chain,
based
on
the
flow
of
materials,
so
at
a
tier
two
supplier
they
might
over
tier
two
in
the
supply
chain.
A
There
might
be
three
four
five
six
different
participants
over
time:
each
will
have
a
different
scope,
one
and
two
emission
factors
data,
and
so
what
we're
taking
is
an
attribute,
an
attributable
slice
of
that
based
on
who
got
involved
in
the
supply
of
material.
In
a
given
month
and
how
that
aggregates
up
over
time-
because
you
know
where
you
have
lower
months-
the
question
then
for
the
oem
is:
how
do
I
replicate
more
of
those
low
months,
essentially
using
buying
smarter
as
a
tool
to
drive
greater
sustainability.
A
A
So
you
don't
you
know
you
don't
want
your
immediate
customer
to
be
able
to
to
do
to
work
out
what
proportion
of
your
total
production
is
finding
its
way
to
them.
That's
something
that
you
know
most
companies
will
jealously
guard.
However,
I
need
to
know
that
you
know
what
proportion
of
scope
one
and
two
emissions
in
a
particular
month.
A
I
attribute
ultimately
to
a
battery
that
goes
into
a
mercedes
as
opposed
to
a
battery
that
goes
into
a
volvo
and
so
we've
we've
developed
a
whole
selection
of
you
know:
privacy,
preserving
technologies
in
order
to
allow
the
the
input
by
a
participant
in
the
supply
chain
of
some
of
that
commercially
sensitive
information.
What
proportion
of
production
in
a
given
period
of
time
is
finding
its
way
to
a
particular
set
of
customers,
but
without
that
being
disclosed
further
on
down
through
the
supply
chain.
A
So
what
does
that?
Look
like
to
a
user?
Well,
I
mentioned
a
mobile
app
there's
a
couple
of
screenshots
on
the
left
hand,
side
of
this
slide
of
our
mobile
app.
You
know
being
used
in
the
field
for
recording
you
know
or
creating
that
first
digital
twin
for
a
commodity,
that's
the
most
difficult
use
case,
because
you
know,
if
you're
going
to
an
industrial
mine,
for
example
in
canada
or
finland
or
australia,
or
places
that
we
currently
work.
A
They
already
have
quite
sophisticated
technology
platforms
that
manage
you,
know,
production
and
and
allow
you
to
essentially
draw
data
directly
from
those
systems.
It's
where
you
know
in
the
the
smaller
scale
and
more
artisanal
end
of
this
of
the
mining
world
and
a
significant
proportion
of
some
of
these
materials
are
artisanally
produced
that
you
need
to
be
able
to
provide
technologies
that
are
very,
very
easy
and
intuitive
to
use
in
order
to
be
able
to
reliably
digitize
that
commodity.
A
A
I've
talked
quite
a
lot
about
the
attributable
co2
footprint,
those
yellow
bars.
I
know
this
is
a
very
small
image,
but
bottom
left
of
that
second
circle,
the
one
in
the
middle.
You
can
see
so
those
yellow
bars
wildly
different
month
on
month,
and
that
is
largely
due
to
uncontrolled,
buying
behavior
by
the
midstream
within
that
supply
chain.
A
So
a
tier
2
supplier
buying
from
different
tier
3
suppliers-
some
you
know
with
with
lower
emissions
than
than
others
and
that's,
and
what
this
is
doing
is
highlighting
that
for
the
downstream
that
has
the
net
zero
target.
You
can't
manage
something
you
can't
measure
so
this.
The
first
point
is
understand
why
your
carbon
footprint
is
higher
in
some
months
than
in
others
and
start
buying
smarter.
A
Obviously,
when
you
know
the
participants
within
your
supply
chain,
you
can
also
collect
other
information
from
them,
such
as
you
know
the
fair
pay,
gender
balance.
You
know
the
whole
variety
of
esg
metrics,
environmental,
social
and
governance
metrics,
which
are
increasingly
important
to
downstream
brands
in
their
own
reporting
of
doing
responsible
business.
A
So
you
know,
if
you
know
who
the
actors
are
and
you're
collecting
information
from
them.
You
can
not
only
produce
supply
chain
maps
but
also
help
create
heat
maps,
to
manage
risk
in
your
supply
chain
and
then
finally,
on
the
right
hand,
side,
obviously
a
whole
suite
of
tools
for
being
able
to
visualize
and
report
data
on
this.
A
Clearly
it's
early
days,
but
the
reason
we
wanted
to
share
this
presentation
today
was
because
this
is,
you
know
some
some
good
work
being
done
by
car
manufacturers
like
volvo
and
polstar
and
daimler
on
this,
which
actually
deserves
to
be
amplified
because
we
as
new
citizens
of
the
earth,
all
need
carbon
emissions
to
fall
and
supply
chains.
Contributions
are
very,
very
high.
Thank
you
for
your
attention.
We
only
have
a
relatively
short
period
of
time,
but
I'd
be
very
happy
to
answer
any
questions
very
happy
to
answer
any
questions.
A
A
I
don't
know
if
you
can
right.
I've
just
got
a
question
from
your
kim
in
chat.
What
kind
of
machine
learning
approach
are
you
using
in
your
architecture?
How
is
it
integrated
into
your
architecture
and
how
the
models
are
validated,
how
to
detect
suspects
activities?
Right?
That's
quite
a
rich
question,
so
we're
using
machine
learning
in
a
number
of
different
contexts.
So,
first
of
all
imagine
you're
standing
in
a
muddy
puddle
in
a
mine
site
in
the
congo.
A
We
use
facial
recognition
as
a
way
of
knowing
the
identity
of
the
individual,
knowing
that
the
individuals
involved
in
a
transaction
at
the
start
are
registered
minors
or
registered
employees,
we're
also
using
machine
learning
as
a
basis
for
anomaly
detection.
So,
for
example,
where
the
chain
of
custody
data
that
is
provided
by
participants
in
the
supply
chain,
don't
add
up
so
material
being
introduced
from
an
unknown
origin
at
various
points
in
the
supply
chain.
A
We're
also
comparing
third-party
data
that
is
available,
whether
it's
emissions
factors,
data
or
you
know
imagery
analysis,
for
example,
from
from
particularly
polluting
sites
where
you
can,
for
example,
find
fugitive
emissions
of
methane
gas,
for
example,
in
the
oil
and
gas
space
and
augmenting
the
self-reported
data
with
that
to
essentially
test
the
the
degree
to
which
you
can
trust
the
self-reported
data
by
the
supply
chain.
Participants
themselves.
I'm
sorry,
that's
such
a
short
answer
to
such
a
complex
question.
A
A
A
Well,
I
think
we're
pretty
much
out
of
time
so
I'll
I'll
stay
in
the
room
for
for
a
little
bit
longer.
If
there
are
any
questions,
if
not
I'm
very
grateful
for
all
of
your
time.
I
appreciate
you
joining
and
I
know
recordings
recordings
will
be
available
for
people,
and
so
thank
you
very
much
indeed
for
your
attention.
Much
appreciated.
Thank
you.